# Interactive platforms for solar energy planning in smart cities: A state-of-the-art review of solar cadasters

M. Giorio, M. Manni, N.I. Köker, C. Bertolin, Martin Thebault, G. Lobaccaro

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M. Giorio, M. Manni, N.I. Köker, C. Bertolin, Martin Thebault, et al.. Interactive platforms for solar energy planning in smart cities: A state-of-the-art review of solar cadasters. Solar Energy, 2025, 287, pp.113227. 10.1016/j.solener.2024.113227. hal-04913403

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# Interactive platforms for solar energy planning in smart cities: A state-of-the-art review of solar cadasters

M. Giorio<sup>a, *</sup>, M. Manni<sup>a, †</sup>, N.I. Köker<sup>a</sup>, C. Bertolin<sup>b, †</sup>, M. Thebault<sup>c, †</sup>, G. Lobaccaro<sup>a, ‡</sup>

## ARTICLE INFO

**Keywords:**

Solar web platforms

Solar cadasters

Solar energy potential

Users' interaction

Sustainable Development Goal

## ABSTRACT

The deployment of solar energy is among the key strategies to counterbalance the increasing energy consumption and greenhouse gas emissions in urban areas, contributing to a sustainable built environment. In this context, interactive platforms such as solar atlas, mapping, and cadasters play a primary role by enabling the evaluation of urban solar energy potential. Solar cadasters, in particular, facilitate user interaction for early exploration and pre-design of solar installations. This study presents a comprehensive – non-exhaustive – database of solar cadasters, focusing on interaction, accuracy, and degree of customization of solar data. The scale and level of detail of the geometry model, as well as the visualization of solar metrics on analyzed surfaces, are investigated. Solar cadasters mostly investigate the urban scale, with a medium–high level of detail of the geometry models and a gradient visualization of the solar data. Additionally, the functionality of solar cadasters is examined, identifying design input parameters and the estimated energy, technical, economic, and environmental metrics. Based on the results, future solar cadasters should enhance the calculation of the building solar potential, with a specific focus on facades, taking into account inter-building reflections and material properties. Additionally, user experience, data visualization, accessibility, and interoperability of solar cadasters with urban planning tools should be improved. This research is relevant for developing informed decision-making to accelerate urban clean-energy transitions, support innovation, increase public and private stakeholder engagement on solar energy systems adoption, and contribute to achieve targeted Sustainable Development Goals in high- and low-income countries.

## 1. Introduction

The integration of solar energy systems within urban environments is fundamental to untap the potential of renewable energy sources (RES) and counterbalance both rising urban energy demand and greenhouse gas emissions (GHG) from cities [1]. The achievement of optimal levels of integration of solar systems into the built environment, however, requires coordinated efforts across multiple sectors and stakeholders [2,3]. Effective collaboration between public authorities, private investors, and community representatives – referred to as the

public–private-people (PPP) model – remains important to fully realizing this potential. The PPP model emphasizes inclusivity and aims to balance technical feasibility, regulatory standards, economic considerations, and social acceptance. Such a need for collaborative and integrated approaches aligns with the United Nations Sustainable Development Goals (SDGs), which provide a framework for transforming cities into sustainable and smart systems. The SDG 7 – *Affordable and clean energy*, which seeks to ensure access to affordable, reliable, and sustainable energy for all, highlights the importance of scaling RES, particularly in densely populated urban environments. While achieving

**Abbreviations:** API, Application Programming Interface; B, Building stock; BIM, Building Information Modelling; BIPV, Building Integrated Photovoltaics; CI, Territorial cadastral information; DSM, Digital Surface Model; DTM, Digital Terrain Model; GAN, Generative Adversarial Network; GDP, Gross domestic product; GHG, Greenhouse gas emissions; GIS, Geographical Information System; GUI, Graphical user interface; HIC, High-income countries; IEA, International Energy Agency; LIC, Low-income countries; LOD, Level of detail; LOV, Level of visualization; NGO, Non-governmental organization; PPP, Public private people; PV, Photovoltaic; RES, Renewable energy sources; SDG, Sustainable Development Goal; SHC, Solar Heating and Cooling; 3D, Three-dimensional; 2D, Two-dimensional; UI, User interaction; UN, United Nations; VR, Virtual Reality; KPI, Key performance indicator.

* Corresponding author.

E-mail address: martina.giorio@ntnu.no (M. Giorio).

<footnote><sup>a</sup> Department of Civil and Environmental Engineering, Faculty of Engineering, Norwegian University of Science and Technology (NTNU), Trondheim, Norway</footnote>

<footnote><sup>b</sup> Department of Mechanical and Industrial Engineering, Faculty of Engineering, Norwegian University of Science and Technology (NTNU) Trondheim, Norway</footnote>

<footnote><sup>c</sup> LOCIE UMR CNRS 5271, Polytech'Annecy-Chambéry, France</footnote>
this goal is complex, its – hence RES – implementation is essential for
advancing other interconnected goals, such as reducing inequalities
(SDG 10), fostering sustainable urban communities (SDG 11), driving
climate action (SDG 13), and promoting resource conservation (SDG
15). Nonetheless, RES projects in cities often face barriers related to
social acceptance, energy policies, subsidies, and cross-sectoral coordi-
nation, with isolated innovations – both spatially and temporally
disconnected – that fail to generate the impact needed for systemic
transformation. To support these collaborative efforts, various digital
tools have been developed to facilitate communication and data ex-
change. Among these, solar web platforms stand out by integrating
meteorological, geographical, and city geometry data to enable accurate
estimations of solar potential and other energy-related metrics [4]. By
communicating and visualizing outputs on two-dimensional (2D) or
three-dimensional (3D) city models, these platforms assist the users in
identifying suitable and usable areas for the installation of solar systems
[5–8]. Knowing the potential for solar energy generation since the initial
urban planning stages is, indeed, essential to take informed decisions
[9,10]. In that regard, solar web platforms can provide PPP with a more
in-depth understanding on installation, operation, maintenance, finan-
cial subsidies, payback time, and savings in bills of solar active systems.
Solar web platforms further facilitate PPP engagement through intuitive
graphical user interfaces (GUI) that allow interaction with solar data and
simulation outputs, aiding in the exploration of project impacts [11].
This interactivity encourages both technical and public communities to
actively participate and influence decision-making process, supporting
sustainable energy solutions that align with a city’s needs and SDGs
priorities. Despite these benefits, the landscape of solar web platforms is
still heterogeneous, with a lack of unified taxonomy and considerable
variation in the interactivity of solar cadasters (i.e., customization of
input parameters and output metrics). Additionally, few studies [12–15]
have systematically analyzed the capabilities and limitations of these
platforms, leaving critical gaps in understanding how they can best
support PPP efforts to achieve effective integration of solar systems in
cities. This study aims to address this gap by reviewing the current
landscape of solar web platforms, providing insights into their role in
supporting collaborative data-informed solar exploitation aligned with
the SDGs.

1.1. *Aims and structure of the study*

The present state-of-the-art review focuses on solar cadasters,
analyzing their progress over the last years and highlighting their po-
tential in advancing SDGs. The main objectives of the study are (i) to
harmonize the taxonomy applied to solar web platforms, (ii) to create
and share a database of exemplary solar cadasters, (iii) to analyze the
level of standardization achieved in these digital tools, and (iv) to
explore the role of the solar cadasters in advancing SDGs within the
context of smart and sustainable cities, both in high-income and low-
income countries.

For the first time, a definition of solar cadasters is provided. In fact,
the terms “solar atlas”, “solar map”, and “solar cadaster” are often used
interchangeably, resulting in growing confusion among users. More-
over, the features of solar atlas, maps, and cadasters are outlined, thus
identifying a framework for the classification of solar web platforms.

A database of solar cadasters is produced as a result of this work. The
aim is to provide a list of platforms that is not exhaustive and continu-
ously updatable, as it includes examples from all around the world.
Furthermore, this database serves as a tool for categorizing solar
cadasters based on functionalities and characteristics, such as data
visualization, geometry complexity, and customizability. In this study,
the landscape of solar cadasters is mapped with the objective of evalu-
ating the degree of uniformity across platforms. Both the information
provided (e.g., metric outputs) and the methods of delivering (e.g., 3D
visualization) in various case studies are assessed to establish guidelines
and best practices for the future development of solar cadasters.

Particular attention is also given to how the PPP engagement is facili-
tated within the solar cadaster interface.

Finally, potential contributions of solar cadasters to smart and sus-
tainable cities are investigated with a specific focus on advancing the
SDGs. The analysis of existing solar cadasters allows to determine how
these digital tools can help define transformation pathways in technol-
ogies, policies, and behaviors, supporting multi-level governance in
implementing energy incentives, standards, and infrastructure to facil-
itate solar energy integration in cities.

## 2. Methodology

The methodology developed in this review paper involved three
main steps (Fig. 1): *Step 1 – Document collection*, which implied the
collection of relevant documents (e.g., journal articles, conference pro-
ceedings, technical reports, websites) on solar web platforms; *Step 2 –
Screening*, which focused on mapping solar web platforms and classi-
fying them according to the proposed categories (i.e., solar mapping,
solar cadasters and solar atlas); and *Step 3 – Solar cadaster analysis*,
functional for the identification of the research gaps and further
developments.

2.1. *Step 1 – Document collection*

The Step 1 was organized around three stages: *Stage a – Preliminary literature research*, which focused on the analysis of academic databases; *Stage b – Detailed (multi-source) research*, during which the search was refined and expanded to include non-academic databases; and *Stage c – Contributions from international experts*, in which the results were enriched by external inputs from international experts.

In *Stage a*, a preliminary investigation was performed with a specific
focus on scholar (e.g., Scopus, Web of Science) and specialized (e.g.,
IEEE Xplore, ScienceDirect) databases. The aim of this stage was to
retrieve journal articles, book chapters, and conference proceedings that
presented solar web platforms and the implemented calculation
methods. The research was conducted in May 2024. The following
search terms were used in Scopus: "TITLE-ABS-KEY (solar PRE/2 ((map* OR cadast*) OR ((urban OR district OR neighb*) PRE/3 planning)))". The
Scopus database returned up to 775 documents. In Web of Science, the
search query was: "TI = (solar NEAR/2 ((map* OR cadast*) OR ((urban OR district OR neighb*) NEAR/3 planning))) OR AB = (solar NEAR/2 ((map* OR cadast*) OR ((urban OR district OR neighb*) NEAR/3 plan- ning)))". The total number of documents found in the Web of Science
database was 1,535. Most of the documents (more than 1,000) regarded
analyses and computational methods developed for limited spatial do-
mains (i.e., from a single building to a neighborhood) that rarely
resulted in web platforms. Among the documents retrieved from Scopus
and Web of Science, only 13 studies – 10 journal articles and 3 con-
ference proceedings – considered the integration of solar resource data
into web platforms. In addition to these, 11 studies – 8 journal articles
and 3 conference proceedings consider approaches, workflows, and
tools for solar analyses at diverse spatial scales (from urban to national
scale), providing also lists of existing solar web platforms.

In the *Stage b – Detailed (multi-source) research*, the search queries
used in *Stage a* were refined, while the research methodology was
expanded to include both academic and non-academic databases. These
actions were necessary due to (i) the non-scientific nature of the review
object (i.e., websites permitting to access solar web platforms) and (ii)
the low number of solar web platforms that were found in the *Stage a*.
The search queries used in the academic databases were modified to
include additional terms such as “GIS-based web solar tools” and “urban
solar availability”. In Scopus, the research was formulated as follows:
“TITLE-ABS-KEY (solar PRE/2 ((map* OR cadast* OR tool*) OR ((urban OR district OR neighb*) PRE/3 planning) OR (gis OR urban)))”. Similarly,
the search query in Web of Science was changed into “TI = (solar NEAR/2 ((map* OR cadast* OR tool*) OR ((urban OR district OR neighb*) NEAR/
<figure><img src="image_4.png" /><figcaption>Fig. 1. Workflow of the sequential steps of the methodology for the solar web platforms review.</figcaption></figure>

3 planning) OR (gis OR urban))) OR AB = (solar NEAR/2 ((map* OR cadast* OR tool*) OR ((urban OR district OR neighb*) NEAR/3 planning) OR (gis OR urban)))". The documents tracked in Scopus and Web of Science were respectively 1,363 and 2,571, but only a few were related to solar web platforms. In fact, despite the outcomes from the academic databases were doubled compared to Stage a, only 2 new relevant documents were found. In parallel, the non-academic databases were searched for (i) technical reports from governments, cross-country organizations, platforms developer, research institutions, and (ii) web pages to access solar platforms. The query entered in the academic databases was rewritten according to the Google syntax for searching in the non-academic sources. The resulting searching string was the following: ""solar" AND ("map" OR "cadaster" OR "cadastre" OR "tool" OR ("urban planning" OR "district planning" OR "neighborhood planning") OR "GIS" OR "urban")". Whenever a solar web platform was found in the non-academic databases, new research was performed in the academic databases by adding the names of the solar web platforms, cities, and developers to the search terms, using both English and the original language of the solar web platforms. For example, in the cases of the solar web platforms of Grand Annecy [16], the search terms were made in English "Solar cadaster of Grand Annecy" and in French "Cadastre solaire du Grand Annecy". This searching process was highly effective and enabled the identification of 4 journal articles, 13 technical reports, and 79 web pages.

Finally, in the *Stage c*, the contributions from international experts in solar energy, especially those engaged in the Solar Heating and Cooling (SHC) Programme by the International Energy Agency (IEA) Task 63 "Solar Neighborhood Planning" [17], provided valuable insights. Such international experts shared new case studies based on their personal knowledge and experience. Some of these platforms were not found during the previous stages due to barriers such as language differences and confidentiality (i.e., access restricted to developers). To ensure the accuracy and reliability of the international experts' inputs, these were validated through cross-referencing scientific documents and web pages (i.e., for each input, a multi-source research, as in *Stage b*, was conducted through academic and non-academic databases). Some of inputs from the international experts have been also collected in one of reports of the subtask C - Solar planning tools - within IEA SHC Task 63, focusing on improved workflows and development needs of solar planning tools [18]. The interaction with the international experts permitted to identify additional 7 websites and 2 technical reports. In total, the *Step 1* led to the acquisition of 131 documents, consisting of 24 journal articles, 6 conference proceedings, 15 technical reports, and 86 web pages.

## 2.2. Step 2 – screening

The documents retrieved in the *Step 1* were screened in the *Step 2* to identify the linked solar web platforms and additional relevant sources through a snowballing process (also known as the citation chaining process). This process permitted to pinpoint 173 solar web platforms from the journal articles (24), 45 from the conference proceedings (6), 86 from the websites (86), and 123 from the technical reports (15). In

total, 427 solar web platforms were preliminary identified. Afterwards, duplicates (i.e., same solar web platforms retrieved from two or more diverse sources) were removed from the list, resulting in the elimination of 318 items. The remaining 109 solar web platforms were further reduced to 94 due to the exclusion of 15 solar web platforms that were no longer available (i.e., server not found).

### 2.2.1. Definition of the solar web platforms

The review process highlighted the lack of a univocal taxonomy applied to online platforms, based on the Geographical Information System (GIS), for sharing solar resource data, namely solar web platforms. Researchers indistinctively referred to solar web platforms as solar map, solar cadaster, solar chart, and solar atlas, regardless of their characteristics and functioning. For example, among the "solar maps" listed in the report of the EUKI project from Solar Adria [11], some platforms allow only for visualizing the solar energy potential (e.g., the *Potencial Solar de Lisboa* [19]), while others are more interactive, enabling the design and simulation of a PV plant (e.g., the *Auckland Rooftop Solar Energy Potential* [20]). Hence, this review study aims to develop a classification of solar web platforms, contributing to a shared and clear definition of solar atlas, solar map, and solar cadaster (Table 1). A first distinction was made between solar web platforms that consider both the terrain and the presence of buildings and those that only consider the orography of the terrain. The latter were labelled as "solar atlases", and they consist of solar web platforms that permit to visualize the solar energy potential of the terrain by solely considering its orography (Table 1). The effects of the built environment such as

<table><caption>**Table 1**

Definition and comparison among the diverse solar web platforms. The comparison has been done on the following features: the platforms have the presence (full dots) of building stocks (B), the territorial cadastral information (CI), the graphical user interface (GUI), the possibility to have user interaction (UI), key performance indicators (KPI).</caption><thead><tr><th>Solar platforms</th><th>B</th><th>CI</th><th>GUI</th><th>UI</th><th>KPI</th></tr></thead><tbody><tr><td>Atlases</td><td>o</td><td>o</td><td>●</td><td>●</td><td>●</td></tr><tr><td>Mapping</td><td>●</td><td>●</td><td>●</td><td>o</td><td>●</td></tr><tr><td>Cadasters</td><td>●</td><td>●</td><td>●</td><td>●</td><td>●</td></tr></tbody></table>

<figure><img src="image_5.png" /></figure>

<figure><img src="image_6.png" /></figure>

<figure><img src="image_7.png" /></figure>
shadows and buildings' reflections are neglected. In the most advanced solar atlases (e.g., PVGIS [21]), the estimated solar energy potential at the ground level can be used as input to quantify the PV power output. In these cases, a GUI allows customizing the geometry and technical properties of the PV system. When it comes to solar web platforms that process buildings, it is possible to distinguish between static solar web platforms, defined as "solar maps", and dynamic platforms, which are hereby regarded as "solar cadasters". The solar maps provide users with access to GIS-based maps – two-dimensional (2D) or 3D – displaying solar metrics (e.g., solar irradiance, PV potential); however, their interfaces limit user interaction with the database, restricting them to passive observation (i.e., visualization of solar metrics on buildings' envelopes). Users cannot design or customize solar systems by defining variables such as geometry or the technical specifications of PV products. An increased level of interaction between users and the online database is among the main characteristics of the solar cadasters. A solar cadaster can be considered as a simplified simulation tool that permits to conduct solar analysis at a preliminary phase and at multiple spatial scales, ranging from single building to the urban scale. Differently from the solar maps, the GUIs of solar cadasters allow the customization of various input variables related to solar analysis and system design. The geometry of the analyzed surface (e.g., area, orientation, tilt angle), the time interval (e.g., monthly, annually), the financial (e.g., electricity prices, intervention costs, economic availability) and environmental (e. g., CO₂ emissions per kWh) variables can be modified to quantify different metrics (e.g., PV energy production, PV payback time, avoided GHG). Moreover, the solar cadasters can include territorial cadastral information (e.g., destination use, surface area, volume, energy consumption, legislative constraints), expanding their range of applicability.

The 100 solar web platforms reviewed in this study were classified according to these definitions, resulting in 5 solar atlases, 42 solar maps, and 53 solar cadasters. It is worth reporting that 2 of the 53 solar cadasters are exclusively available through subscriptions (i.e. no open-access); hence, they were excluded from the following analyses. Although the solar maps and atlases were excluded from the scope of the research, a complete list of them is included in the Section a.10 in the Appendix. The analysis of the 51 solar cadasters aimed at outlining the state of art of these digital tools, providing insights into their functioning and potential applications.

## 2.3. PRISMA method for systematic review

The outcomes from the Step 1 and the Step 2 of the workflow described in Section 2.1 can be summarized following the PRISMA method for systematic review [22]. This approach incorporates a set of evidence-based guidelines to conduct systematic reviews and meta-analyses that are characterized by various data sources [23,24], ensuring that the selected studies are thorough, accessible, and well-documented. The PRISMA approach (see Fig. 2) follows three key stages: identification, screening, and inclusion. In this way, different sources such as journal articles, conference proceedings, reports, and websites can be documented. Their analysis permitted to identify the existing solar web platforms, and specifically the solar cadasters, which were further investigated in this study.

## 2.4. Step 3 – solar cadaster analysis

This section describes the key attributes that were analyzed in the reviewed solar cadasters (Table 2). The analysis of the solar cadasters aimed at outlining their features and limitations, facilitating the identification of research gaps and areas for further developments.

The most relevant analyzed key attributes and levels of information refer to the geographical distribution and coverage, geometry model, solar data visualization, regulations, user interaction, and metrics.

**Geographical distribution and coverage.** The solar cadasters were

## Identification of new studies via databases and registers

<figure><img src="image_8.png" /><figcaption>Fig. 2. The screening process followed in this review paper according to the PRISMA method [22].</figcaption></figure>
<table><caption>**Table 2**
Key attributes and levels of information for the solar cadasters analysis.</caption><thead><tr><th colspan="2">Geographical distribution and coverage</th></tr></thead><tbody><tr><td>1. Localization</td><td>[Continent/Nation/Region/ City]</td></tr><tr><td>2. Climate zone</td><td>[Köppen climate zone]</td></tr><tr><td>3. Spatial scale</td><td>[Urban/Regional/National]</td></tr><tr><td>4. Extension</td><td>[Covered area in km²]</td></tr></tbody><thead><tr><th colspan="2">Geometry model</th></tr></thead><tbody><tr><td>1. Level of detail</td><td>[LOD0 - LOD4]</td></tr><tr><td>2. Presence of vegetation elements</td><td>[Yes/No]</td></tr></tbody><thead><tr><th colspan="2">Solar data visualization</th></tr></thead><tbody><tr><td>1. Level of visualization</td><td>[LOV1 - LOV3]</td></tr><tr><td>2. Analyzed geometry</td><td>[Roof/Facades/Ground]</td></tr><tr><td>3. Model</td><td>[2D/3D]</td></tr></tbody><thead><tr><th colspan="2">Regulations</th></tr></thead><tbody><tr><td>1. Cadastral information</td><td>[Yes/No]</td></tr><tr><td>2. Heritage constrains</td><td>[Yes/No]</td></tr></tbody><thead><tr><th colspan="2">User interaction</th></tr></thead><tbody><tr><td>1. Building features and function</td><td>[Yes/No]</td></tr><tr><td>2. Solar system specifications</td><td>[Yes/No]</td></tr><tr><td>3. Number (or area) of PV panels</td><td>[Yes/No]</td></tr><tr><td>4. Drawing of PV panels</td><td>[Yes/No]</td></tr><tr><td>5. Investment and costs</td><td>[Yes/No]</td></tr><tr><td>6. Energy demand</td><td>[Yes/No]</td></tr><tr><td>7. Combination of PV with other energy systems</td><td>[Yes/No]</td></tr><tr><td>8. System installer</td><td>[Yes/No]</td></tr><tr><td>9. Environmental impact</td><td>[Yes/No]</td></tr><tr><td>10. Tax deduction</td><td>[Yes/No]</td></tr></tbody><thead><tr><th colspan="2">Metrics</th></tr></thead><tbody><tr><td>1. Energy metrics</td><td></td></tr><tr><td>- Irradiance</td><td>[Yes/No]</td></tr><tr><td>- Daylight</td><td>[Yes/No]</td></tr><tr><td>- PV potential production</td><td>[Yes/No]</td></tr><tr><td>- Thermal potential production</td><td>[Yes/No]</td></tr><tr><td>- Energy self-sufficiency</td><td>[Yes/No]</td></tr><tr><td>- Energy storage</td><td>[Yes/No]</td></tr><tr><td>2. Technical metrics</td><td></td></tr><tr><td>- Optimal area for PV</td><td>[Yes/No]</td></tr><tr><td>- Optimal size of solar thermal</td><td>[Yes/No]</td></tr><tr><td>3. Economic metrics</td><td></td></tr><tr><td>- Payback</td><td>[Yes/No]</td></tr><tr><td>- Investment cost</td><td>[Yes/No]</td></tr><tr><td>- Operational cost and savings</td><td>[Yes/No]</td></tr><tr><td>- Subsidies</td><td>[Yes/No]</td></tr><tr><td>4. Environmental metrics</td><td></td></tr><tr><td>- Avoided emissions</td><td>[Yes/No]</td></tr><tr><td>- Relative indicators</td><td>[Yes/No]</td></tr></tbody></table>

geographically categorized by location (continent, nation, region and city), and the corresponding Köppen climate zone [25]. More than one location could be assigned to a single solar cadaster since the same solar web platform can enable the exploration of solar resource data from multiple cities, as in the case of IRENA [26]. Additionally, the geographical coverage was estimated by means of features like the spatial scale (urban, regional, national, global) and the extension

(surface area in km²) of the investigated area. The urban scale regards the analysis of a spatial extension ranging from groups of buildings to a city; the regional scale refers to the study of multiple urban agglomerations, extending up to an entire region; and the national scale includes more than one region, potentially covering the whole nation.

**Geometry model.** The features of the geometry model were evaluated by means of the level of detail (LOD) of the analyzed geometry (see Fig. 3). The LOD can vary between the LOD0, which corresponds to 2D building footprints, and the LOD4, which consists of a highly detailed 3D model including accurate features for both outdoor and indoor environments [27]. Intermediate levels exist, as illustrated in Fig. 3. Beside the LOD, the presence of vegetation elements was also assessed in this group of key attributes and levels of information.

**Solar data visualization.** A preliminary classification of the solar cadasters was conducted based on whether solar resource data were visualized on 2D or 3D geometries. Additionally, the surfaces for which the solar potential is calculated were analyzed, including roofs, facades, and ground, either individually or in combination. The level of visualization (LOV) was introduced to assess the detail of solar data representation. The LOV was defined similarly to the LOD: the lower the value, the less accurate is the visualization of the solar irradiation data. The LOV ranged from LOV1, where a single, uniform color is used in each surface according to the average value of solar irradiation, to LOV2, where gradients are applied to visualize the spatial distribution of the solar irradiation on the urban surfaces. A LOV2 allowed the visualization of shadows projected on the analyzed surface depending on the LOD of the geometry model. Finally, a LOV3 visualization consists in a series of gradients in which each gradient corresponds to a specific time (Fig. 4).

**Regulations.** The integration of territorial cadastral data and information about the local building regulations represented a key feature to evaluate in solar cadasters. Cadastral data (e.g., urban plans, landscape constraints, proximity of watercourses, ownership, boundaries, land use, etc.) may be included in specific layers of the solar cadaster, constraining the design of solar systems by users. Among the various cadastral data, this study specifically focused on cultural heritage protection acts and laws. These are crucial for developing appropriate mechanisms to protect the peculiar materials and geometric features of cultural heritage, as well as for determining obligations and rights of property owners. Indeed, heritage constraints often represent the primary reason for denying solar system installations in historic centers, where building facades – and rooftops in some cases – cannot be altered.

**User interaction.** This level of information addresses the user interaction and engagement features offered by solar cadasters. Indeed, their GUIs allow users to modify different variables, which can enhance the accuracy of the calculations in relation to actual conditions. These variables include: (a) building features and function (e.g., building typology, number of floors, primary function); (b) solar system specifications (e.g., technology, efficiency, solar panel tilt); (c) number (or area) of PV panels; (d) drawing of PV panels (e.g., manual delimitation of the PV area); (e) investment and costs (e.g., payback time); (f) energy demand (e.g., number of building occupants, number of electric vehicles to charge); (g) combination of PV with other energy systems (e.g., heat pump); (h) system installer (e.g., possibility to select the installer from a

<figure><img src="image_9.png" /><figcaption>**Fig. 3.** Illustration of different levels of detail (LOD) for the same building, ranging from a basic representation without height information (LOD0) to highly detailed models with intricate architectural features (LOD4). Redrawn from [28].</figcaption></figure>
<figure><img src="image_10.png" /><figcaption>**Fig. 4.** Illustration of different levels of visualization (LOV) for the same building, ranging from a basic representation with a single and uniform color (LOV1) to highly detailed representations with series of gradients over specific times (LOV3).</figcaption></figure>

list); (i) environmental impact (e.g., carbon dioxide emissions factor per kWh of electricity generated from combustion systems); and (l) tax deduction (e.g., governmental subsidies, tax deduction policies). Some solar cadasters may be integrated with external platforms to calculate additional metrics and enhance the user experience by expanding the functionalities of the solar cadaster. In such cases, some or all these variables may be managed by the external platform. Following this, our analysis distinguished between variables customized within the solar cadaster and those modified externally.

**Metrics.** As a final step, the metrics provided by the solar cadasters were reviewed and analyzed. The metrics are relevant information for PPP users especially for the decision-making process. In total, 14 metrics were identified and grouped into four main categories, namely the energy, technical, economic, and environmental metrics. Each category is composed of sub-categories:

*   **Energy metrics** are calculated from weather data and technical specifications of the PV panels. The solar *irradiance* metrics indicate the amount of solar irradiation received by any surface and it is often expressed either on yearly or monthly basis. These quantities can also be expressed in terms of *daylight*. The *PV potential production* and the *thermal potential production* address, respectively, the energy generation from PV and from solar thermal systems. These metrics are calculated considering either the user-defined dimensions of the solar system or the system's optimal area identified by the technical metrics. Finally, metrics about *energy self-sufficiency* and *energy storage* are estimated when building's energy demand is also known.

*   **Technical metrics** are based on the geometric characteristics of the solar system to design. These metrics regard the *optimal area for PV* and the *optimal size of solar thermal*. The former indicates the optimal dimensions of the PV system to install on the selected surface. Depending on the solar cadaster, this metric is expressed either in terms of area, capacity, or the number of PV modules. The latter consists in the optimal area of the thermal solar system. Their calculation strongly depends on the LOD of the geometry model, as the presence of superstructure elements (e.g., chimneys, windows, and heating, ventilation, and air conditioning systems) can reduce the available and usable areas for solar system installations.

*   **Economic metrics** can be quantified from the energy metrics and local economic variables (e.g., energy price). These metrics are site-specific and account for the price (retail and wholesale) of electricity, potential subsidies or incentives, and the local cost of a PV installation. Among economic metrics, one of the most used is the *payback* period, which provides the time period to cover the costs of the PV systems. Other economic metrics are related to the *investment cost* of the designed solar system (e.g., PV module, thermal solar collectors, energy storage elements) as well as the *operational cost and savings* (e.g., maintenance expenses, savings in energy bills). Finally, the most recent solar cadasters provide information about *subsidies* for the installation of solar systems. Similar to the energy metrics, the

economic metrics are sensitive to assumptions and the quality of input parameters (e.g., available area, irradiance, self-consumption rate).

*   **Environmental metrics** concern the *avoided emissions* and the *relative indicators*. The former measures the environmental impacts of the designed solar system, often expressed as offset carbon emissions or PM 2.5 savings. The latter provides the same information by means of equivalent representations, such as the number of trees grown or compensated passenger cars.

### 3. Results

This multi-faceted approach of data collection and analysis allowed for a comprehensive exploration of the existing solar cadasters by providing insights on the state of the art and identifying research gaps for further developments. The framework is based on the key attributes analysis described in Section 2.4.

#### 3.1. Geographical distribution and coverage

The Fig. 5 shows a global map describing the geographical distribution and coverage of the investigated solar cadasters (Table 3). The solar cadasters were divided into national (6), regional (18), and urban (27) depending on the scale of the analyzed area (Fig. 5, Fig. 6a).

As some solar web platforms, like IRENA [26] and MyHEATSolar [29], considered multiple cities, the totality of the cities highlighted in the global map 61 is greater than the number of urban solar cadasters (27, Fig. 6b). Indeed, IRENA [26] developed a unique solar web platform to support the energy transition in diverse developing countries such as Africa, Asia, and Central America. Up to 31 exemplary cities can be accessed from the IRENA's solar cadaster. On the other hand, MyHEATSolar [29] developed the solar cadasters for five (5) cities in Canada.

The investigated solar cadasters are mostly concentrated in Europe (80 %) (Fig. 6b), particularly in the West and Continental Europe (Fig. 5). These results are not just influenced by the cultural proximity of the authors and experts' contamination, which are coming mostly from European countries, but also from the lack of homogeneous building stock at the EU and continental level and within cities. The variability in available datasets, with each city with different characteristics [77], is a crucial point for decision-makers who require uniform data for efficient energy planning. For the following analyses we presented the case studies [26,29], considering multiple (i.e. Various) cities in different continents/countries inside a single platform, under the miscellaneous category.

The solar cadasters covering national territories (6) are distributed over the following continents: America (1), Europe (4) and Oceania (1). While all the 18 regional solar cadasters are located mostly in Europe and 1 (one) in Asia. The urban scale is the most recurrent among the investigated solar cadasters (27), with two (2) cases in America, two (2) cases in Asia, 20 in Europe, one (1) in Oceania and one (2) covering multiple countries (Miscellaneous). The solar cadasters were categorized according to the Köppen [25] climate classification. In that regard, the solar cadasters that span across multiple climate zones such as national [29,31,57,65,73,76] and the cross-country ones [26] were excluded from this analysis. These are the national solar cadasters of Switzerland (Cfb, Dfb), United States of America (Af, Am, BWh, BSh, Csa, Csb, Cfa, Cfb, Cfc, Dfa, Dfb, Dwa, Dwb, Dfc, Dfd, Dwc, Dwd, ET, EF), Australia (Af, Aw, BWh, BWk, BSh, BSk, Csa, Csb, Cfa, Cfb, Cfc, Dfa, Dfb, Dfc), Germany (Dfb, Dfc, Cfa, Cfb, ET), Norway (Cfb, Cfc, Dfb, Dfc, ET, EF), Canada (considering the different cities with the solar cadasters: Dfb, BSk), and the cross-country solar cadaster (Af, Aw, BSh, BSk, Csa, Csb, Cfa, Cfb, Cfc). See the Appendix in Section a.2 for the description of the climate zone symbols' descriptions. Fig. 7 reports both the number of solar cadasters and their cumulative extension for each climate zone that is present in at least one of the case studies. The investigated solar
<figure><img src="image_11.png" /><figcaption>Fig. 5. World distribution of the cases study of solar cadasters with a focus on the Europe situation.</figcaption></figure>

cadasters were mostly developed for temperate (climate group C) and continental (climate group D) climates, but also one (1) case with dry arid climate (climate group B) was found in low latitude desert. The results found are distributed in the following climate zones: BWh (1), Cfb (33), Csa (1), Cwa (1), Dfb (6), Dfc (1) and Dwa (1).

The extension of the area that is analyzed by each solar cadaster (hereinafter referred to as “covered area”) was estimated to provide, along with the spatial scale, a complete overview of the geographical coverage of the solar cadasters. A duality of relationships is expressed in the graph. The first concerns the number of cadasters divided by the various climate zones (left y-axis in the Fig. 7), while the second concerns the total extension (calculated in km²) of the areas analyzed by the existing solar cadasters (right y-axis in the Fig. 7). A significant presence of cases (33) are located in the Cfb climate zone, while for the BWh, Csa, Cwa, Dfc and Dwa classes just 1 case per each was found and 6 cadasters for the Dfb category. The comparison between the solar cadasters in terms of both spatial scale and covered area is visualized in Fig. 8. Alongside the cross-country solar cadaster from IRENA, four solar cadasters [29,31,57,76] that are characterized by a national scale, but an undefined covered area (i.e., under development national solar cadasters that still cover solely part of the national territory) were excluded from this analysis. Hence, 46 solar cadasters were evaluated. Although the scale is usually positively correlated to the covered area (i. e., the greater the scale, the larger the covered area), the Fig. 8 highlights that there can be exceptions such as in the cases of small countries as Luxemburg [58] (ID: 32, national scale but relatively small covered area) or groups of small contiguous villages from the same region (regional scale but relatively small covered area) or extremely large urban areas as the Auckland [20] municipality (ID: 38, urban scale but relatively high covered area). The analysis of the covered area outlines the potential of the solar cadaster as a tool suitable for various spatial domains, ranging from a group of neighborhoods (~20 km² in the Solarkataster Burghausen [47], ID: 21) to a whole country (~380,000 km² in Norway [65], ID: 40).

## 3.2. Geometry model and solar data visualization

The accuracy of the geometric model of the solar cadasters is indicated by the LOD, ranging from LOD1 (box-shaped building volumes) to LOD3 (detailed model with sloped roof and additional 3D elements). Table 4 provides the number of solar cadasters per LOD.

Only the London [74] and Dubai [30] solar cadasters, were found to have pure LOD1. This is characterized by an over-simplified geometries

that simply extrude the footprint of the building on the ground, without any information on roof's geometry (i.e., slope inclinations on the roofs), and the buildings are modelled as boxes with different dimensions. Besides the pure LOD1, there is a hybrid LOD1 (LOD1*) consisting of a solar cadaster that has a LOD1 linked to a computational platform (Section 3.4) with a higher level of detail (usually LOD3). For example, the Bremen solar cadaster in Germany [44] has a LOD1; however, when a building is selected, a LOD3 geometry model is shown for the selected area. In total, four (4) solar cadasters were found to have a LOD1*. While, up to 8 solar cadasters exploit a geometry model that considers the presence of pitched rooftop, as in Wroclaw (Poland) [66] (LOD2). An intermediate level between LOD2 and LOD3, namely the LOD2.5, was introduced by Saretta et al. (2020) [78] with regards to the national solar cadaster of Switzerland [73]. This consists specifically in a LOD2 model that is enhanced with the architectural characteristics of façades. The LOD2.5 solar cadaster can estimate the urban solar energy potential of façades through building typological indicators without reaching the LOD3. Finally, most of the reviewed solar cadasters (36) are characterized by a LOD3. Such solar cadasters, as the Oslo Solar Cadaster [64], enable a more refined calculation of the rooftop solar potential by considering the presence of technical and architectural elements. In the analyzed cadaster, the modelling of the vegetation was found in almost all the platforms. Only for 6 solar cadasters it was not possible to determine whether this influenced the solar potential calculations or not. Despite an overall high LOD observed among the case studies, the visualization is mostly bi-dimensional. Indeed, the solely Solarkataster Kaiserslautern (Germany) [46] implemented a 3D model to estimate the solar potential of facades along with the roofs. Four (4) platforms analyze the solar potential of the ground and roofs, while the others (45) only report data for the roofs. Results from the analysis of the LOV in solar cadasters are shown in Table 5.

Six (6) of the reviewed solar cadasters achieve LOV1. In these cases, the average solar potential is estimated for each surface resulting in the use of solid color rather than gradients, as developed for the solar cadaster of the Flanders Region [32]. Changes in LOV between the solar cadaster and the computational platform are observed in the four (4) LOV1* solar cadasters, the same having a LOD1*. The gradient visualization (LOV2), created by interpolating the solar potential values estimated for the grid of test points, is the commonest among the reviewed case studies (40). Such solar cadasters usually visualize shadows and obstructing elements (e.g. chimneys, technical elements), as in the Brabant Region solar cadaster [62]. In these solar platforms the gradient visualization can be presented through either a mesh (36) or
<caption>**Table 3**</caption>

Tabular review of the solar cadasters according to information of geographical distribution and coverage.

<table><thead><tr><th>ID</th><th>Ref.</th><th>Name</th><th>Nation</th><th>City/Region</th><th>Climate zone</th><th>Scale</th><th>Extension [Km²]</th></tr></thead><tbody><tr><td>1</td><td>[30]</td><td>Solar Calculator – DEWA</td><td>Arab Emirates</td><td>Dubai</td><td>BWh</td><td>Urban</td><td>4,771.3</td></tr><tr><td>2</td><td>[31]</td><td>SunSPOT</td><td>Australia</td><td>***</td><td>Various</td><td>National</td><td>~ 7,688,000</td></tr><tr><td>3</td><td>[26]</td><td>IRENA – International Renewable Energy Agency</td><td>*</td><td>Miscellaneous</td><td>Various</td><td>Urban</td><td>–</td></tr><tr><td>4</td><td>[32]</td><td>Energiesparen – Vlaanderen</td><td>Belgium</td><td>Flanders Region</td><td>Cfb</td><td>Regional</td><td>13,625</td></tr><tr><td>5</td><td>[33]</td><td>Residential solar calculator</td><td>Canada</td><td>Calgary</td><td>Dfb</td><td>Urban</td><td>825.3</td></tr><tr><td>6</td><td>[29]</td><td>MyHEATSolar</td><td>China</td><td>Miscellaneous</td><td>Various</td><td>Regional</td><td>~1,080</td></tr><tr><td>7</td><td>[34]</td><td>Hong Kong Solar Irradiation Map</td><td></td><td>Hong Kong</td><td>Cwa</td><td></td><td>1,115</td></tr><tr><td>8</td><td>[16]</td><td>Cadastre solaire du Grand Annecy</td><td></td><td>Annecy</td><td></td><td></td><td>109.94</td></tr><tr><td>9</td><td>[35]</td><td>Cadastre solaire de Béziers Méditerranée</td><td></td><td>Béziers</td><td></td><td></td><td>303</td></tr><tr><td>10</td><td>[36]</td><td>Cadastre solaire de Montpellier Méditerranée Métropole</td><td></td><td>Montpellier</td><td></td><td></td><td>421.8</td></tr><tr><td>11</td><td>[37]</td><td>Cadastre solaire de Toulouse Métropole</td><td>France</td><td>Toulouse</td><td>Cfb</td><td>Urban</td><td>460</td></tr><tr><td>12</td><td>[38]</td><td>Cadastre solaire de Nantes Métropole</td><td></td><td>Nantes</td><td></td><td></td><td>523.4</td></tr><tr><td>13</td><td>[39]</td><td>Cadastre solaire de Bordeaux Métropole</td><td></td><td>Bordeaux</td><td></td><td></td><td>578.3</td></tr><tr><td>14</td><td>[40]</td><td>Cadastre solaire du Pôle territorial du Sud Gironde</td><td></td><td>Sud Gironde</td><td></td><td>Regional</td><td>2,519</td></tr><tr><td>15</td><td>[41]</td><td>Solarpotentialkataster Schwerin</td><td></td><td>Schwerin</td><td></td><td></td><td>130.5</td></tr><tr><td>16</td><td>[42]</td><td>Sonne Trifft Dach</td><td></td><td>Karlsruhe</td><td></td><td></td><td>173.5</td></tr><tr><td>17</td><td>[43]</td><td>GeoLIS LRA Starnberg – Solarkaster</td><td></td><td>Starnberg</td><td>Cfb</td><td>Urban</td><td>488</td></tr><tr><td>18</td><td>[44]</td><td>Solarkataster – Bremen</td><td></td><td>Bremen</td><td></td><td></td><td>326.7</td></tr><tr><td>19</td><td>[45]</td><td>Solarrechner Hamburger</td><td></td><td>Hamburg</td><td></td><td></td><td>755.3</td></tr><tr><td>20</td><td>[46]</td><td>Solarkataster Kaiserslautern</td><td></td><td>Kaiserslautern</td><td></td><td></td><td>139.7</td></tr><tr><td>21</td><td>[47]</td><td>Solarkataster Burghausen</td><td></td><td>Burghausen</td><td>Dfb</td><td></td><td>19.85</td></tr><tr><td>22</td><td>[48]</td><td>Solarkataster – RLP</td><td></td><td>Rhein-Pfalz-Kreis region</td><td></td><td></td><td>404.92</td></tr><tr><td>23</td><td>[49]</td><td>Solarkataster Hessen</td><td>Germany</td><td>Hessen</td><td></td><td></td><td>21,115</td></tr><tr><td>24</td><td>[50]</td><td>Solarkataster – NRW</td><td></td><td>Rhein-Sieg-Kreis region</td><td></td><td></td><td>1,153.2</td></tr><tr><td>25</td><td>[51]</td><td>Hannover Solarkataster</td><td></td><td>Hannover</td><td>Cfb</td><td>Regional</td><td>2,290</td></tr><tr><td>26</td><td>[52]</td><td>Landesweites Solarkataster Rheinland-Pfalz</td><td></td><td>Rheinland-Pfalz Region</td><td></td><td></td><td>19,858</td></tr><tr><td>27</td><td>[53]</td><td>Landkreis Leer</td><td></td><td>Leer</td><td></td><td></td><td>1,086</td></tr><tr><td>28</td><td>[54]</td><td>Solarpotenzial auf Dachflächen</td><td></td><td>Baden-Württemberg</td><td></td><td></td><td>35,751</td></tr><tr><td>29</td><td>[55]</td><td>Solarkataster – Landkreis Aurich</td><td></td><td>Aurich</td><td></td><td></td><td>1,287</td></tr><tr><td>30</td><td>[56]</td><td>Solaratlas Brandenburg</td><td></td><td>Brandenburg</td><td></td><td></td><td>29,479</td></tr><tr><td>31</td><td>[57]</td><td>Solarpotenzialkataster</td><td></td><td>***</td><td>Various</td><td>National</td><td>~ 357,592</td></tr><tr><td>32</td><td>[58]</td><td>Energie – Geoportal Luxembourg</td><td>Luxembourg</td><td>***</td><td>Cfb</td><td>National</td><td>2,586</td></tr><tr><td>33</td><td>[59]</td><td>Zonatlas – Wageningen</td><td></td><td>Wageningen</td><td></td><td></td><td>32.36</td></tr><tr><td>34</td><td>[60]</td><td>Zonatlas – Arnhem</td><td></td><td>Arnhem</td><td></td><td>Urban</td><td>101.54</td></tr><tr><td>35</td><td>[61]</td><td>Zonatlas – Amsterdam</td><td>Netherlands</td><td>Amsterdam</td><td>Cfb</td><td></td><td>219.3</td></tr><tr><td>36</td><td>[62]</td><td>Zonnescan – Brabant Region</td><td></td><td>Brabant Region</td><td></td><td></td><td>5,081</td></tr><tr><td>37</td><td>[63]</td><td>Zonatlas – Provincie Noord-Brabant</td><td></td><td>Noord-Brabant</td><td></td><td>Regional</td><td>5,081</td></tr><tr><td>38</td><td>[20]</td><td>Auckland Rooftop Solar Energy Potential</td><td>New Zealand</td><td>Auckland</td><td>Cfb</td><td>Urban</td><td>5,600</td></tr><tr><td>39</td><td>[64]</td><td>Oslo Solkart</td><td>Norway</td><td>Oslo</td><td>Dfc</td><td>Urban</td><td>454</td></tr><tr><td>40</td><td>[65]</td><td>Solkart Norge</td><td></td><td>***</td><td>Various</td><td>National</td><td>385,207</td></tr><tr><td>41</td><td>[66]</td><td>System Informacji Prezestrzennej</td><td>Poland</td><td>Wroclaw</td><td>Cfb</td><td>Urban</td><td>292.8</td></tr><tr><td>42</td><td>[67]</td><td>서울 Special시 에너지장비</td><td>South Korea</td><td>Seoul</td><td>Dwa</td><td>Urban</td><td>605.21</td></tr><tr><td>43</td><td>[68]</td><td>Solaratlas Valladolid</td><td>Spain</td><td>Valladolid</td><td>Csa</td><td>Urban</td><td>197.5</td></tr><tr><td>44</td><td>[69]</td><td>Stockholms solkarta</td><td></td><td>Stockholm</td><td></td><td>Urban</td><td>188</td></tr><tr><td>45</td><td>[70]</td><td>Linkoping karta</td><td>Sweden</td><td>Linkoping</td><td>Dfb</td><td>Regional</td><td>1,568</td></tr><tr><td>46</td><td>[71]</td><td>Solkartan Norrkoping</td><td></td><td>Norrkoping</td><td></td><td></td><td>2,048</td></tr><tr><td>47</td><td>[72]</td><td>G2SOLAIRE – Solar cadastre of Grand Geneva</td><td></td><td>Geneva</td><td>Cfb</td><td>Regional</td><td>2,000</td></tr><tr><td>48</td><td>[73]</td><td>Sonnendach und Sonnenfassade Berechnung von Potenzialen in Gemeinden</td><td>Switzerland</td><td>***</td><td>Various</td><td>National</td><td>41,285</td></tr><tr><td>49</td><td>[74]</td><td>Mayor of London</td><td>United Kingdom</td><td>London</td><td>Cfb</td><td>Regional</td><td>1,572</td></tr><tr><td>50</td><td>[75]</td><td>Duluth's Solar Suitability Application – Duluth Shines.</td><td>Minnesota (USA)</td><td>Duluth</td><td>Dfb</td><td>Urban</td><td>207.6</td></tr><tr><td>51</td><td>[76]</td><td>Project Sunroof – Google</td><td>**</td><td>***</td><td>Various</td><td>National</td><td>~ 9,826,675</td></tr></tbody></table>

* Different cities in America, Africa, Asia, and Oceania.

** Different cities in USA and Puerto Rico.

*** Presence of multiple cities due to the National scale of the cadaster.

a Translation: Information on solar energy in the Metropolitan city of Seoul.

discontinuous points (4). The solar cadaster of Luxembourg [58] is the sole that achieves a LOV3, enabling the visualization of the solar metrics in three different representative months. Further insight into the correlation between the LOD and the LOV is provided in Table 6 by calculating the number of solar cadasters for each possible combination of LOD and LOV levels Table 7.

Table 6 highlights that a low LOV is not necessarily associated with a low LOD. In fact, there are only two (2) solar cadasters that have LOD1 and LOV1, while four (4) have LOV1 but LOD equal (3) or higher (1) than LOD2. Furthermore, LOV2 is mostly associated with LOD3 (35),

although five (5) exceptions, characterized by a LOD2, can be identified.

In order to clarify the relationship between LOD and LOV, a graphic representation has been produced (Appendix Section a.3) showing different types of available solar cadaster, corresponding to different levels of detail for the model and for the visualization side.

### 3.2.1. Additional information on calculation

The available area of the surfaces considered for the calculation of the solar potential is a particular aspect which connects the two topics just discussed in the previous sections (i.e. geometry model, and solar
<figure><img src="image_12.png" /><figcaption>Fig. 6. Number of solar cadasters distributed for: a) Scale of the solar cadaster and b) Continent distribution.</figcaption></figure>

<figure><img src="image_13.png" /><figcaption>Fig. 7. Climate zone distributions and solar cadasters extensions.</figcaption></figure>

<figure><img src="image_14.png" /><figcaption>Fig. 8. Ascending distribution of the solar cadasters according to the total extension and the scale.</figcaption></figure>

data visualization). Considering the whole roof as available for the installation of PV panels or considering only the most suitable parts (i.e. excluding areas with too low irradiation, parts that are too small, parts already occupied by other elements and shaded parts), implies a major change in the calculation of the solar potential data. 40 solar platforms provide general information on whether a roof or façade is suitable for the installation of PV panels. One example is the Arnhem [60] solar cadaster, where roofs are classified according to their suitability using three colors (red, yellow and green). Another possibility is to visualize a

gradient between more suitable and less suitable areas, as in the Stockholm Solar Cadaster [69]. Among these platforms, 25 provide visual information and use it during the solar availability calculation phase. This happens in the solar cadaster developed in Belgium, for the Flanders Region [32].

### 3.3. Regulations

This section focuses on the integration of cadastral data and heritage
<table><caption>**Table 4**
Number of solar cadasters distributed by LOD of the model.</caption><thead><tr><td>LOD</td><td>Number of Cadasters</td></tr></thead><tbody><tr><td>LOD1</td><td>2</td></tr><tr><td>LOD1*</td><td>4</td></tr><tr><td>LOD2</td><td>8</td></tr><tr><td>LOD2.5</td><td>1</td></tr><tr><td>LOD3</td><td>36</td></tr></tbody></table>

<table><caption>**Table 5**
Number of solar cadasters distributed by LOV of the solar data.</caption><thead><tr><td>LOV</td><td>Number of Cadasters</td></tr></thead><tbody><tr><td>LOV1</td><td>6</td></tr><tr><td>LOV1*</td><td>4</td></tr><tr><td>LOV2</td><td>40</td></tr><tr><td>LOV3</td><td>1</td></tr></tbody></table>

<table><caption>**Table 6**
Relationship between LOV and LOD by number of solar cadasters.</caption><thead><tr><td></td><td>LOV1</td><td>LOV1*</td><td>LOV2</td><td>LOV3</td></tr></thead><tbody><tr><td>LOD1</td><td>2</td><td>-</td><td>-</td><td>-</td></tr><tr><td>LOD1*</td><td>-</td><td>4</td><td>-</td><td>-</td></tr><tr><td>LOD2</td><td>3</td><td>-</td><td>5</td><td>-</td></tr><tr><td>LOD2.5</td><td>1</td><td>-</td><td>-</td><td>-</td></tr><tr><td>LOD3</td><td>-</td><td>-</td><td>35</td><td>1</td></tr></tbody></table>

protection laws into solar cadasters. Cadastral data, including all the information about the building (i.e. function, area, volume, energy category), are different from the Zoning restrictions, referring to all those constraints that are introduced by territorial and urban plans. Heritage protection laws are a specific limitation among the zoning restrictions, indicating the need to apply for planning permission of new projects. The solar cadasters that provide this information are presented in Table 8.

Overall, there are five (5) solar cadasters with cadastral data and 21 with cultural heritage information but only in three (3) solar cadasters, the solar cadasters of Switzerland [73], Wroclaw (Poland) [66], and Luxembourg [58], these two information layers co-exist. These solar cadasters permit to activate multiple layers containing data about, among the others, solar potential, proximity of watercourses, land use, local management plans, urban regulation plans, orthophotos, etc. The Table, in the Section a.4 of the Appendix, visualizes the regulation's characteristics of each solar cadaster.

### 3.4. Users' interaction in the solar cadaster platforms

This section investigates the diverse ways that users can interact with the solar cadasters' databases. Such interactions can take place either within the solar cadaster web page (also referred to as "main platform") or in a dedicated web page that serves as external calculator (hereinafter referred to as "external platform"). A first screening of the solar cadasters led to the identification of 17 solar cadasters allowing users to directly customize input variables (e.g. costs, productivity, economic return, number of PV panels), while the remaining (34) redirect the users towards external platforms (Table 9). Such external platforms can be implemented either by the same developers of the solar cadaster and local experts (7) or by a third part (27). Among the seven (7) solar cadasters with specific external platforms from the same developers, the Switzerland case study [73], implemented by SuisseEnergie [79], is exemplary. Regarding 27 external platforms developed by a third party, the analysis highlighted the existence of companies and advisors that

operate at national and international level to support and guide in the calculation and visualization of the various solar metrics. For example, the Cythelia Energy company [80] is involved in the development of diverse solar cadasters in France, providing external platforms to preliminary design the PV system based on costs, legal and planning requirements, and technical features. Alongside Cythelia Energy company that is involved in seven (7) solar cadasters, other developers identified are: Tetraeder.solar (supporting the calculation in 3 solar cadasters), SUN AREA (4), Ipsyscon.de (4), GEOPLEX (5), and ZONATLAS combined with Tetraeder.solar (4). Table 9 summarizes all the possible users' interactions distinguishing between what can be customized in the main platforms, what can be customized in the external platform and what can be customized in both.

It is mentioned whenever the main platform is linked to an external platform, as the interaction is mostly taking place in the external platform. Table 10 shows the number of cadasters for each type of interaction previously identified.

The most common interaction among the solar cadasters, found in 43 platforms, is represented by the Selection of panel numbers/area: 14 solar cadasters enable the interaction internally, 28 through external platforms, and 1 in both the main and the external platforms. The less frequent interaction (1) is the identification of the Environmental impact of the project and it is only customizable (internally) in the IRENA solar cadaster [26]. Three (3) solar cadasters allow the tax deduction of the interventions to be calculated through external platforms, as in the MN DNR calculator [81], connected to the Duluth's Solar Suitability Application [75]. Investment and cost calculation and Calculation of individual consumption have recorded by 38 (6 main, 29 external, 3 both) and 39 (8 main, 31 external) solar cadasters, respectively. This highlights how most of the inputs in the external platforms are related to business and economy, which represent the most interesting aspects besides the energy performance for private users and stakeholders.

The most interacted (7 inputs) platforms are represented by the following 4 [32,48,49,73]. For all of them it is possible to adapt the parameters related to Building features and function, Solar systems technology/efficiency, Selection of panel numbers/area, Investment and cost calculation, Calculation of customized consumption, Other technologies combined with PV. For two of them it is also possible to proceed with the Panel area drawing and for the others it can be found the Suggestion of one or more Installers. These parameters represent a high degree of interaction and give the users a very complete experience in adapting the project to their needs. On the other hand, there are four (4) solar cadasters [56,66,67,74] that allow just 1 (one) typology of users' interaction which corresponds reciprocally to Investment and cost calculation, Panel area drawing, and Solar systems technology/efficiency. In these cases, the platforms need to be thoroughly developed, as they are very poor in terms of customization of consumption parameters, savings, energy potential and calculation of incentives and taxation.

In conclusion, the total number of interactions in the external platforms (161) are higher than those in the internal platforms (61). This suggests that using external platforms can guarantee an increased level of interaction that involves a wider range of input parameters. However, creating an external platform, include to involve developers with previous experience in developing solar cadaster very likely to create a tool quickly available for users.

### 3.5. Metrics identification

The output results provided by the solar platforms were considered after the analysis of the input data in Table 10. These outputs, defined in Table 9 represent the metrics used to evaluate the information provided. A higher number of interactions does not always lead to a higher number of output results. However, it can help to provide more accurate and personalized output results according to the user's needs. In fact, the solar cadaster with the highest number of different output results does not correspond to any of the cases mentioned in the previous paragraph
<caption>**Table 7**</caption>

Tabular review of the solar web platforms according to information of the geometry model, the solar data visualization and additional information on calculations.

<table><caption>**Table 8**</caption><thead><tr><th rowspan="2">ID</th><th rowspan="2">Ref.</th><th colspan="2">Geometry model</th><th colspan="3">Solar Data Visualization</th><th colspan="2">Additional information on calculation</th></tr><tr><th>LOD</th><th>Vegetation</th><th>Analyzed geometries</th><th>2D/3D</th><th>LOV</th><th>Identification of the most suitable areas</th><th>Inclusion of the available area in the calculations</th></tr></thead><tbody><tr><td>1</td><td>[30]</td><td>LOD1</td><td>No</td><td>Roofs</td><td>3D</td><td>LOV1</td><td>Yes – Single color</td><td>No</td></tr><tr><td>2</td><td>[31]</td><td>LOD2</td><td>Yes</td><td>Roofs and ground</td><td>2D</td><td>LOV2</td><td>No</td><td>No</td></tr><tr><td>3</td><td>[26]</td><td>LOD2</td><td>ND</td><td>Roofs</td><td>2D</td><td>LOV2</td><td>No</td><td>No</td></tr><tr><td>4</td><td>[32]</td><td>LOD2</td><td>Yes</td><td>Roofs</td><td>2D</td><td>LOV1</td><td>Yes – Gradient</td><td>Yes</td></tr><tr><td>5</td><td>[33]</td><td>LOD3</td><td>Yes</td><td>Roofs</td><td>2D</td><td>LOV2</td><td>Yes – Gradient</td><td>No</td></tr><tr><td>6</td><td>[29]</td><td>LOD3</td><td>Yes</td><td>Roofs</td><td>2D</td><td>LOV2</td><td>Yes – Gradient</td><td>No</td></tr><tr><td>7</td><td>[34]</td><td>LOD3</td><td>ND</td><td>Roofs</td><td>2D</td><td>LOV2</td><td>Yes – Gradient</td><td>Yes</td></tr><tr><td>8</td><td>[16]</td><td>LOD3</td><td>Yes</td><td>Roofs</td><td>2D</td><td>LOV2</td><td>Yes – Gradient</td><td>No</td></tr><tr><td>9</td><td>[35]</td><td>LOD3</td><td>Yes</td><td>Roofs</td><td>2D</td><td>LOV2</td><td>Yes – Gradient</td><td>Yes</td></tr><tr><td>10</td><td>[36]</td><td>LOD3</td><td>Yes</td><td>Roofs</td><td>2D</td><td>LOV2</td><td>Yes – Gradient</td><td>Yes</td></tr><tr><td>11</td><td>[37]</td><td>LOD3</td><td>Yes</td><td>Roofs</td><td>2D</td><td>LOV2</td><td>Yes – Gradient</td><td>Yes</td></tr><tr><td>12</td><td>[38]</td><td>LOD3</td><td>Yes</td><td>Roofs</td><td>2D</td><td>LOV2</td><td>Yes – Gradient</td><td>Yes</td></tr><tr><td>13</td><td>[39]</td><td>LOD3</td><td>Yes</td><td>Roofs</td><td>2D</td><td>LOV2</td><td>Yes – Gradient</td><td>Yes</td></tr><tr><td>14</td><td>[40]</td><td>LOD3</td><td>Yes</td><td>Roofs</td><td>2D</td><td>LOV2</td><td>Yes – Gradient</td><td>Yes</td></tr><tr><td>15</td><td>[41]</td><td>LOD3</td><td>Yes</td><td>Roofs</td><td>2D</td><td>LOV2</td><td>Yes – Single color</td><td>No</td></tr><tr><td>16</td><td>[42]</td><td>LOD3</td><td>Yes</td><td>Roofs</td><td>2D</td><td>LOV2</td><td>Yes – Gradient</td><td>No</td></tr><tr><td>17</td><td>[43]</td><td>LOD3</td><td>Yes</td><td>Roofs</td><td>2D</td><td>LOV2</td><td>Yes – Single color</td><td>Yes</td></tr><tr><td>18</td><td>[44]</td><td>LOD1*</td><td>Yes</td><td>Roofs</td><td>2D</td><td>LOV1*</td><td>Yes – Single color</td><td>No</td></tr><tr><td>19</td><td>[45]</td><td>LOD1*</td><td>Yes</td><td>Roofs</td><td>2D</td><td>LOV1*</td><td>Yes – Single color</td><td>No</td></tr><tr><td>20</td><td>[46]</td><td>LOD2</td><td>Yes</td><td>Roofs and facades</td><td>3D</td><td>LOV2</td><td>No</td><td>No</td></tr><tr><td>21</td><td>[47]</td><td>LOD1*</td><td>Yes</td><td>Roofs</td><td>2D</td><td>LOV1*</td><td>Yes – Single color</td><td>No</td></tr><tr><td>22</td><td>[48]</td><td>LOD3</td><td>Yes</td><td>Roofs</td><td>2D</td><td>LOV2</td><td>Yes – Gradient</td><td>No</td></tr><tr><td>23</td><td>[49]</td><td>LOD3</td><td>Yes</td><td>Roofs and ground</td><td>2D</td><td>LOV2</td><td>Yes – Gradient</td><td>No</td></tr><tr><td>24</td><td>[50]</td><td>LOD3</td><td>Yes</td><td>Roofs and ground</td><td>2D</td><td>LOV2</td><td>Yes – Gradient</td><td>No</td></tr><tr><td>25</td><td>[51]</td><td>LOD3</td><td>Yes</td><td>Roofs</td><td>2D</td><td>LOV2</td><td>Yes – Gradient</td><td>Yes</td></tr><tr><td>26</td><td>[52]</td><td>LOD3</td><td>Yes</td><td>Roofs</td><td>2D</td><td>LOV2</td><td>Yes – Gradient</td><td>Yes</td></tr><tr><td>27</td><td>[53]</td><td>LOD3</td><td>Yes</td><td>Roofs</td><td>2D</td><td>LOV2</td><td>Yes – Gradient</td><td>Yes</td></tr><tr><td>28</td><td>[54]</td><td>LOD3</td><td>Yes</td><td>Roofs</td><td>2D</td><td>LOV2</td><td>Yes – Gradient</td><td>Yes</td></tr><tr><td>29</td><td>[55]</td><td>LOD1*</td><td>Yes</td><td>Roofs</td><td>2D</td><td>LOV1*</td><td>Yes – Single color</td><td>No</td></tr><tr><td>30</td><td>[56]</td><td>LOD2</td><td>ND</td><td>Roofs</td><td>2D</td><td>LOV1</td><td>Yes – Single color</td><td>Yes</td></tr><tr><td>31</td><td>[57]</td><td>LOD3</td><td>Yes</td><td>Roofs</td><td>2D</td><td>LOV2</td><td>Yes – Gradient</td><td>Yes</td></tr><tr><td>32</td><td>[58]</td><td>LOD3</td><td>Yes</td><td>Roofs</td><td>2D</td><td>LOV3</td><td>Yes – Gradient</td><td>Yes</td></tr><tr><td>33</td><td>[59]</td><td>LOD3</td><td>Yes</td><td>Roofs</td><td>2D</td><td>LOV2</td><td>Yes – Single color</td><td>Yes</td></tr><tr><td>34</td><td>[60]</td><td>LOD3</td><td>Yes</td><td>Roofs</td><td>2D</td><td>LOV2</td><td>Yes – Single color</td><td>Yes</td></tr><tr><td>35</td><td>[61]</td><td>LOD3</td><td>Yes</td><td>Roofs</td><td>2D</td><td>LOV2</td><td>Yes – Single color</td><td>Yes</td></tr><tr><td>36</td><td>[62]</td><td>LOD3</td><td>Yes</td><td>Roofs</td><td>2D</td><td>LOV2</td><td>Yes – Gradient</td><td>Yes</td></tr><tr><td>37</td><td>[63]</td><td>LOD3</td><td>Yes</td><td>Roofs</td><td>2D</td><td>LOV2</td><td>Yes – Single color</td><td>Yes</td></tr><tr><td>38</td><td>[20]</td><td>LOD2</td><td>Yes</td><td>Roofs</td><td>2D</td><td>LOV2</td><td>No</td><td>No</td></tr><tr><td>39</td><td>[64]</td><td>LOD3</td><td>Yes</td><td>Roofs and ground</td><td>2D</td><td>LOV2</td><td>No</td><td>No</td></tr><tr><td>40</td><td>[65]</td><td>LOD2</td><td>ND</td><td>Roofs</td><td>2D</td><td>LOV1</td><td>Yes – Single color</td><td>No</td></tr><tr><td>41</td><td>[66]</td><td>LOD2</td><td>Yes</td><td>Roofs</td><td>2D</td><td>LOV2</td><td>No</td><td>No</td></tr><tr><td>42</td><td>[67]</td><td>LOD3</td><td>ND</td><td>Roofs</td><td>2D</td><td>LOV2</td><td>No</td><td>No</td></tr><tr><td>43</td><td>[68]</td><td>LOD3</td><td>Yes</td><td>Roofs</td><td>2D</td><td>LOV2</td><td>Yes – Gradient</td><td>Yes</td></tr><tr><td>44</td><td>[69]</td><td>LOD3</td><td>Yes</td><td>Roofs</td><td>2D</td><td>LOV2</td><td>Yes – Gradient</td><td>Yes</td></tr><tr><td>45</td><td>[70]</td><td>LOD3</td><td>Yes</td><td>Roofs</td><td>2D</td><td>LOV2</td><td>No</td><td>No</td></tr><tr><td>46</td><td>[71]</td><td>LOD3</td><td>Yes</td><td>Roofs</td><td>2D</td><td>LOV2</td><td>No</td><td>No</td></tr><tr><td>47</td><td>[72]</td><td>LOD3</td><td>Yes</td><td>Roofs</td><td>2D</td><td>LOV2</td><td>Yes – Gradient</td><td>Yes</td></tr><tr><td>48</td><td>[73]</td><td>LOD2.5</td><td>Yes</td><td>Roofs and facades</td><td>2D</td><td>LOV1</td><td>Yes – Single color</td><td>No</td></tr><tr><td>49</td><td>[74]</td><td>LOD1</td><td>Yes</td><td>Roofs</td><td>2D</td><td>LOV1</td><td>No</td><td>Yes</td></tr><tr><td>50</td><td>[75]</td><td>LOD3</td><td>ND</td><td>Roofs</td><td>2D</td><td>LOV2</td><td>Yes – Gradient</td><td>Yes</td></tr><tr><td>51</td><td>[76]</td><td>LOD3</td><td>Yes</td><td>Roofs</td><td>2D</td><td>LOV2</td><td>No</td><td>No</td></tr></tbody></table>

Number of solar cadasters correlated to the presence of Cadastral information and Heritage protection law constraints.

<table><thead><tr><th rowspan="2"></th><th rowspan="2"></th><th colspan="2">Heritage constraints</th></tr><tr><th>Yes</th><th>No</th></tr></thead><tbody><tr><td rowspan="2">Cadastral information</td><td>Yes</td><td>3</td><td>2</td></tr><tr><td>No</td><td>18</td><td>28</td></tr></tbody></table>

(i.e. with the highest number of customizable inputs). Although the Kaiserslautern solar cadaster [46] had 10 different output categories, there were only 2 possibilities to influence the inputs. This means that the output results obtained, although more numerous, are based on standard data and do not correspond to the real situation, leading to possible inaccuracies. An example of a good balance between input and output is the Belgian Solar Cadaster, which analyses the Flanders region

[32]. Starting from the alteration of 7 different inputs, the outputs obtained are a total of 9.

The distribution of the metrics among the analyzed solar cadasters has been summarized according to the metric's category (i.e. energy, technical, economic, and environmental) in Table 11.

The energy metrics, which are the most numerous (6), are the ones that are considered in the highest number of solar cadasters. Indeed, there are 51 solar cadasters that present at least one of the identified energy metrics. Even if the technical metrics are just 2, they are presented in 43 solar cadasters. The economic metrics, despite being less (4), are present in a significant number of solar cadasters (38) demonstrating that the developers tend to prioritize this information, which is relevant for the users. Conversely, there are still a few solar cadasters (31) that implemented the two identified environmental metrics. In Table 12, a cross analysis of the occurrence of the metrics in the reviewed solar cadasters is presented. In fact, a single solar cadaster can
<caption>**Table 9**</caption>

Tabular review of the solar web platforms with inputs of users' internal and external interaction and the outputs.

<table><thead><tr><th rowspan="2">Ref.</th><th rowspan="2">Presence of an external platform or calculator</th><th colspan="8">INPUTS</th><th colspan="10">OUTPUTS</th></tr><tr><th>Building features and function</th><th>Solar system specifications</th><th>Number (or area) of PV panels</th><th>Drawing of PV panels</th><th>Investment and costs</th><th>Energy demand</th><th>Combination of PV with other energy systems</th><th>System installer</th><th>Environmental impact</th><th>Tax deduction</th><th>Irradiance</th><th>Daylight</th><th>PV potential production</th><th>Thermal potential production</th><th>Energy self-sufficiency</th><th>Energy Storage</th><th>Optimal area for PV</th><th>Optimal size of solar thermal</th><th>Payback</th><th>Investment cost</th><th>Operational cost and savings</th><th>Subsidies</th><th>Avoided emissions</th><th>Relative indicators</th></tr></thead><tbody><tr><td>[30]</td><td>-</td><td>-</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>[31]</td><td>-</td><td>-</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>[26]</td><td>-</td><td>-</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>[32]</td><td>-</td><td>-</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>[33]</td><td>-</td><td>-</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>[29]</td><td>Gov. of Canada</td><td>-</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>o</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>[34]</td><td>-</td><td>-</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>[16]</td><td>Cythelia Energy</td><td>-</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>[35]</td><td>Cythelia Energy</td><td>-</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>[36]</td><td>Cythelia Energy</td><td>-</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>[37]</td><td>Cythelia Energy</td><td>-</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>[38]</td><td>Cythelia Energy</td><td>-</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>[39]</td><td>Cythelia Energy</td><td>-</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>[40]</td><td>Cythelia Energy</td><td>-</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>[41]</td><td>GEOFLY</td><td>-</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>[42]</td><td>SUN 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AREA</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>[49]</td><td>SUN AREA</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>[50]</td><td>SUN AREA</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>[51]</td><td>Ipsyscon.de</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>[52]</td><td>Ipsyscon.de</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>[53]</td><td>Ipsyscon.de</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>[54]</td><td>GEOPLEX</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>[55]</td><td>GEOPLEX</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>[56]</td><td>-</td><td>-</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>[57]</td><td>Tetraeder.solar</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>[58]</td><td>Tetraeder.solar</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>[59]</td><td>ZONATLAS + T.s.</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>[60]</td><td>ZONATLAS + T.s.</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>[61]</td><td>ZONATLAS + T.s.</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>[62]</td><td>-</td><td>-</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>[63]</td><td>ZONATLAS + T.s.</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>[20]</td><td>Solar Optimiser</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>[64]</td><td>-</td><td>-</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>[65]</td><td>-</td><td>-</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>[66]</td><td>-</td><td>-</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>[67]</td><td>-</td><td>-</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>[68]</td><td>Tetraeder.solar</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>[69]</td><td>Energi&klimat</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>[70]</td><td>-</td><td>-</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>[71]</td><td>-</td><td>-</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>[72]</td><td>SuisseEnergie and PRONOVO</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>[73]</td><td>SuisseEnergie</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>[74]</td><td>-</td><td>-</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>[75]</td><td>MN DNR calculator</td><td>-</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr><tr><td>[76]</td><td>-</td><td>-</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>•</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td><td>✓</td></tr></tbody></table>

• Interaction in the main platform; o Interaction in the external platform; • Interaction in both, main and the external, platforms; ✓ Output.

provide multiple output metrics as in the case of the Luxembourg solar cadaster [58], where *Optimal area for PV*, *PV potential production*, *Energy self-sufficiency*, *Investment cost* and *Payback* are estimated.

The diagonal (i.e., identical metric on both row and column), assesses the occurrence of each output metric in the reviewed solar cadasters. The *PV potential production* (43), the *Optimal area for PV* (43), the *Investment cost* (35), and the *Avoided emissions* (30) are the most used metrics for the energy, technical, economic, and environmental categories (Section 2.4). The less frequent values were respectively identified for *Daylight* (2), *Thermal sizing* (10), *Subsidies* (11), and *Relative indicators* (10). From the analysis, it is possible to note which couples of metrics occur most frequently in the solar cadasters. In this regard, the combination of the *Optimal area for PV* and the *PV potential production* is the commonest (38), followed by the co-occurrence of the *Investment cost*

and the *Optimal area for PV* (35). Other frequent couples of metrics are the *Investment cost* – *PV potential production* (30), the *Payback* – *Optimal area for PV* (30), the *Investment cost* – *Payback* (29), the *Investment cost* – *Energy self-sufficiency* (28), the *Optimal area for PV* – *Energy self-sufficiency* (28), the *Avoided emissions* – *Optimal area for PV* (27). Parameters such as *Thermal potential production* and *Thermal sizing* are less frequent and mostly provided in combination with *PV potential production* and *Optimal area for PV*. Similarly, the *Energy storage* is rarely utilized, while it is mostly presented in combination with *Energy self-sufficiency*, *Investment cost*, *Payback*, and *Avoided emissions*. Table 13 represents a cross analysis of the co-occurrence of the input variables (columns) and the output metrics (rows) in the reviewed solar cadasters.

When metrics like the *Optimal area for PV*, *PV potential production*, *Energy self-sufficiency*, *Payback*, *Investment cost*, and *Avoided emissions* are
<table><caption>**Table 10**
Number of solar cadasters for each user interactions in the internal and external platforms.</caption><thead><tr><th>User's interaction</th><th>Main platforms</th><th>External platforms</th><th>Internal and external platforms</th><th>Total</th></tr></thead><tbody><tr><td>Building features and function</td><td>3</td><td>19</td><td>-</td><td>22</td></tr><tr><td>Solar system specifications</td><td>12</td><td>14</td><td>-</td><td>26</td></tr><tr><td>Number (or area) of PV panels</td><td>14</td><td>28</td><td>1</td><td>43</td></tr><tr><td>Drawing of PV panels</td><td>6</td><td>-</td><td>-</td><td>6</td></tr><tr><td>Investment and costs</td><td>6</td><td>29</td><td>3</td><td>38</td></tr><tr><td>Energy demand</td><td>8</td><td>31</td><td>-</td><td>39</td></tr><tr><td>Combination of PV with other energy systems</td><td>4</td><td>26</td><td>-</td><td>30</td></tr><tr><td>System installers</td><td>7</td><td>11</td><td>-</td><td>18</td></tr><tr><td>Environmental impact</td><td>1</td><td>-</td><td>-</td><td>1</td></tr><tr><td>Tax deduction</td><td>-</td><td>3</td><td>-</td><td>3</td></tr><tr><td>Total</td><td>61</td><td>161</td><td>4</td><td>226</td></tr></tbody></table>

estimated, the most recurring ways for users to interact concern the selection of panel numbers/area, investment and cost calculation, calculation of customized consumption, and other technologies combined with PV. Conversely, the Panel area drawing, Tax deduction calculation, Environmental impact are the least frequent and they are only related to few output metrics (8).

Taking Selection of panel numbers/area as input, the most common related outputs are PV potential production (36) and Optimal area for PV (37). 32 solar cadasters have both these outputs. Considering these outputs among the most popular and using Calculation of customized consumption as an input value to compare, there are still 32 solar platforms that have both outputs, but they correspond in 28 cases with the previous ones. An example of a solar cadaster that contains both the mentioned inputs and outputs is the Flanders' solar cadaster [32].

# 4. Discussion

## 4.1. Research gaps and future developments of solar cadasters

Based on the observations made from the results section, this section outlines future developments of solar cadasters, focusing on both simulation environment and the platforms interface (i.e. user experience, accessibility, and interoperability with urban planning tools). These enhancements address research gaps identified in existing solar platforms, offering recommendations to improve accuracy, functionality, user engagement.

For the simulation environment, future solar cadasters should enhance the calculation of the building solar potential, with a specific focus on facades, inter-building reflections, and the time horizon of

analysis. Elements that limit the available area for solar installations, such as windows, doors, and balcony, should be considered, meanwhile integrating material optical properties into the model and supporting diverse time horizons (LOV3) should be prioritized. Although many current solar cadasters achieve LOD3, most are limited to rooftop analysis, with only two [46,73] considering facades, and none incorporating material information. Additionally, no existing platforms evaluate investments and energy production considering short-, medium- and long-term intervals considering climate change scenarios [46,73,82].

Challenges in modelling facades arise from current 3D city modelling techniques. Oblique airborne photogrammetry, which is commonly used to create Digital Surface Models (DSMs) and Digital Terrain Models (DTMs) [83], struggles with capturing façade details in dense urban settings. Ground-based LiDAR surveys, conducted by personnel or drones, can capture these geometries with more accuracy, although they are more time-consuming. Advances in image segmentation and element detection techniques [84,85] can aid in identifying overhangs and elements that cause shadowing and reduce the available area for solar installations, ultimately achieving the same LOD and LOV for facades as for rooftops.

Integrating material properties into the simulation environment enhances on one hand result accuracy [86], but on the other hand significantly increases the computational time. Advanced LiDAR technologies, such as the Leica ScanStation P30, enable the material recognition during the scanning process [87], generating detailed and realistic 3D point clouds with reflectivity data. Incorporating this information into the workflow for modelling solar inter-building reflections would be particularly beneficial in dense urban areas, where many buildings can shadow reciprocally, and there are multiple solar reflections between both the buildings and the ground.

The primary challenge in implementing solar cadasters at LOV3 is the increased computational power required [82]. A LOV3 solar cadaster would enables (i) assessing the seasonal variability of solar energy potential (using past data from diverse month), (ii) forecasting the energy production (using weather data for the upcoming days), (iii) evaluating climate change impacts on solar metrics (using diverse climate change scenarios and temporal windows). Notably, while seasonal solar variability is visualized in the Luxemburg solar cadaster [58], no existing platforms implement short-term forecasting or climate impact analysis.

Regarding the GUI, future solar cadasters should prioritize user experience, accessibility, and interoperability with urban planning tools. User-centered design will simplify navigation and data interpretation, providing customizable, layered views that serve both technical and non-technical users. Features such as settings localization (e.g., language, measurement units, time zones) and mobile-friendly interfaces will enhance accessibility. Integration with existing urban planning tools, like GIS and Building Information Modelling (BIM),

<table><caption>**Table 11**
Classification of the metrics.</caption><thead><tr><th>Metric's categories</th><th>Metrics</th><th>Occurrence</th><th>Occurrence (%)</th><th>Number of Solar Cadasters</th></tr></thead><tbody><tr><td rowspan="7">Energy</td><td>Irradiance</td><td>19</td><td>37.25 %</td><td rowspan="7">51</td></tr><tr><td>Daylight</td><td>2</td><td>3.92 %</td></tr><tr><td>PV potential production</td><td>43</td><td>84.31 %</td></tr><tr><td>Thermal potential production</td><td>4</td><td>7.84 %</td></tr><tr><td>Energy self-sufficiency</td><td>28</td><td>54.90 %</td></tr><tr><td>Energy Storage</td><td>11</td><td>21.57 %</td></tr><tr><td>Optimal area for PV</td><td>43</td><td>84.31 %</td></tr><tr><td rowspan="5">Technical</td><td>Optimal size of solar thermal</td><td>10</td><td>19.61 %</td><td rowspan="5">43</td></tr><tr><td>Payback</td><td>30</td><td>58.82 %</td></tr><tr><td>Investment cost</td><td>35</td><td>68.63 %</td></tr><tr><td>Operational cost and savings</td><td>20</td><td>39.22 %</td></tr><tr><td>Subsidies</td><td>11</td><td>21.57 %</td></tr><tr><td rowspan="2">Economic</td><td>Avoided emissions</td><td>30</td><td>58.82 %</td><td rowspan="2">38</td></tr><tr><td>Relative indicators</td><td>10</td><td>19.61 %</td></tr><tr><td>Environmental</td><td></td><td></td><td></td><td>31</td></tr></tbody></table>
<caption>**Table 12**</caption>

Cross-comparison of the metrics in the reviewed solar cadasters. The number in each cell indicates the contemporary occurrence of two metrics (e.g. in the cell corresponding to the 5th row and 3rd column, the number '23' indicates that there are 23 solar cadasters that have both the "Energy Self-sufficiency" and the "PV potential Production" among the estimated metrics).

<table><thead><tr><th></th><th>Irradiance</th><th>Daylight</th><th>PV potential production</th><th>Thermal potential production</th><th>Energy self sufficiency</th><th>Energy Storage</th><th>Optimal area for PV</th><th>Optimal size of solar thermal</th><th>Payback</th><th>Investment cost</th><th>Operational cost and savings</th><th>Subsidies</th><th>Avoided emissions</th><th>Relative indicators</th></tr></thead><tbody><tr><td>Irradiance</td><td>19</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Daylight</td><td>0</td><td>2</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>PV potential production</td><td>11</td><td>2</td><td>43</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Thermal potential production</td><td>4</td><td>0</td><td>4</td><td>4</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Energy self-sufficiency</td><td>8</td><td>0</td><td>23</td><td>1</td><td>28</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Energy Storage</td><td>5</td><td>0</td><td>6</td><td>0</td><td>11</td><td>11</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Optimal area for PV</td><td>12</td><td>2</td><td>38</td><td>2</td><td>28</td><td>11</td><td>43</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Thermal sizing</td><td>2</td><td>0</td><td>10</td><td>2</td><td>9</td><td>1</td><td>10</td><td>10</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Payback</td><td>10</td><td>2</td><td>25</td><td>2</td><td>23</td><td>11</td><td>30</td><td>10</td><td>30</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Investment cost</td><td>9</td><td>2</td><td>30</td><td>2</td><td>28</td><td>11</td><td>35</td><td>10</td><td>29</td><td>35</td><td></td><td></td><td></td><td></td></tr><tr><td>Operational cost and savings</td><td>7</td><td>0</td><td>20</td><td>3</td><td>14</td><td>0</td><td>18</td><td>9</td><td>14</td><td>17</td><td>20</td><td></td><td></td><td></td></tr><tr><td>Subsidies</td><td>2</td><td>0</td><td>11</td><td>0</td><td>10</td><td>0</td><td>11</td><td>7</td><td>10</td><td>11</td><td>9</td><td>11</td><td></td><td></td></tr><tr><td>Avoided emissions</td><td>11</td><td>2</td><td>25</td><td>3</td><td>16</td><td>11</td><td>27</td><td>4</td><td>22</td><td>22</td><td>7</td><td>3</td><td>30</td><td></td></tr><tr><td>Relative indicators</td><td>6</td><td>1</td><td>5</td><td>1</td><td>5</td><td>5</td><td>8</td><td>0</td><td>8</td><td>8</td><td>2</td><td>0</td><td>9</td><td>10</td></tr></tbody></table>

could extend solar cadasters' utility in energy and design planning. Real-time data and predictive capabilities could offer insights into future scenarios, enhancing proactive planning.

Virtual Reality (VR) integration could allow users to experience solar impacts in immersive urban scenes, aiding non-specialist understanding and facilitating stakeholder engagement. VR simulations could also help urban planners and community members experience potential installations on-site, training them in solar acceptance and assessment concepts and allowing them to simulate changes in solar performance over time.

Finally, the future solar cadasters should expand their metrics such as social metrics beyond the current four categories (i.e. energy, technology, economy, and environment) to include social considerations such as acceptance, visual impact, and level of integration. Metrics like visibility classification for PV installations, as demonstrated in recent studies [88,89], would offer valuable insights into social feasibility.

These improvements would make solar cadasters more versatile, user-friendly, and suitable for smart city needs, supporting broader adoption of solar energy solutions in urban settings.

## 4.2. Limitations of the study

The limitations of this study are presented and discussed in this section. The main limitation concerns the list of the reviewed solar cadasters, which include a comprehensive – non-exhaustive – database of existing solar cadasters in the world. This is due to multiple reasons such as the dynamic nature of solar cadasters and the presence of cultural barriers (i.e. language). As solar cadasters are tools that became recently popular, new web pages are developed, while the existing ones

can be dismissed temporarily (for maintenance or updating procedures) or after some time. Additionally, there is a lack of information about the releasing date of the existing solar cadasters and the dismissed solar cadasters (i.e., solar cadasters whose web domains are not functioning anymore). All these aspects make difficult to provide the state-of-the-arts about solar cadasters as well as to evaluate their evolution over time. Regarding the cultural barriers, these mostly concern the language barrier as most of the reviewed solar cadasters are from Europe or anglophone countries like the United States of America, Australia, Canada. For example, the Solar register of Tokyo [90] was retrieved with a non-academic search engine by using the native language of the country: "東京ソーラー屋根台帳". In some cases [26,34], this barrier has been overcome because, although the studies are based in Asia, Africa and Oceania, the producers of the platforms are part of an international community. Nonetheless, the methodological approach to detect and compile the list of solar cadasters can be considered comprehensive but not fully exhaustive. Another limitation concerning a technical aspect is the general lack of documentation regarding the source of input data and its production. This happen both for geometric data, in relation to techniques used to reproduce the 2D/3D model, and for climatic data, where it is difficult to identify the source, the time period and the calculation process/software used for meteorological data elaboration. The lack of knowledge of the sources of these data is therefore a weakness, as the data can be considered approximative. In addition, none of the identified platforms detect existing PV/solar installations and include their influence in the final energy potential calculations. The authors unsuccessfully tried to overcome this issue by contacting the developers of the platforms. Afterwards, these limitations were mitigated by accurately inspecting and testing the diverse solar
<table><caption>**Table 13**

Cross-comparison of the input and output metrics in the reviewed solar cadasters.</caption><thead><tr><th></th><th>Building features and function</th><th>Solar system specifications</th><th>Number (or area) of PV panels</th><th>Drawing of PV panels</th><th>Investment and costs</th><th>Energy demand</th><th>Combination of PV with other energy systems</th><th>System installer</th><th>Environmental impact</th><th>Tax deduction</th></tr></thead><tbody><tr><td>Irradiance</td><td>7</td><td>15</td><td>14</td><td>2</td><td>11</td><td>10</td><td>8</td><td>4</td><td>0</td><td>1</td></tr><tr><td>Daylight</td><td>0</td><td>0</td><td>1</td><td>0</td><td>0</td><td>2</td><td>0</td><td>1</td><td>0</td><td>0</td></tr><tr><td>PV potential production</td><td>17</td><td>19</td><td>36</td><td>5</td><td>32</td><td>33</td><td>25</td><td>18</td><td>1</td><td>3</td></tr><tr><td>Thermal potential production</td><td>2</td><td>3</td><td>4</td><td>0</td><td>2</td><td>2</td><td>2</td><td>3</td><td>0</td><td>0</td></tr><tr><td>Energy self sufficiency</td><td>14</td><td>11</td><td>27</td><td>3</td><td>27</td><td>26</td><td>22</td><td>9</td><td>1</td><td>2</td></tr><tr><td>Energy Storage</td><td>11</td><td>5</td><td>11</td><td>0</td><td>11</td><td>11</td><td>11</td><td>0</td><td>0</td><td>0</td></tr><tr><td>Optimal area for PV</td><td>21</td><td>20</td><td>37</td><td>5</td><td>36</td><td>37</td><td>29</td><td>15</td><td>1</td><td>3</td></tr><tr><td>Thermal sizing</td><td>2</td><td>2</td><td>10</td><td>0</td><td>9</td><td>9</td><td>9</td><td>8</td><td>0</td><td>0</td></tr><tr><td>Payback</td><td>15</td><td>9</td><td>25</td><td>2</td><td>26</td><td>27</td><td>22</td><td>12</td><td>1</td><td>2</td></tr><tr><td>Investment cost</td><td>17</td><td>13</td><td>31</td><td>4</td><td>30</td><td>31</td><td>25</td><td>14</td><td>1</td><td>3</td></tr><tr><td>Operational cost and savings</td><td>5</td><td>9</td><td>16</td><td>5</td><td>18</td><td>16</td><td>13</td><td>11</td><td>0</td><td>2</td></tr><tr><td>Subsidies</td><td>0</td><td>2</td><td>10</td><td>0</td><td>10</td><td>9</td><td>9</td><td>9</td><td>1</td><td>1</td></tr><tr><td>Avoided emissions</td><td>19</td><td>14</td><td>25</td><td>1</td><td>22</td><td>24</td><td>20</td><td>8</td><td>1</td><td>2</td></tr><tr><td>Relative indicators</td><td>7</td><td>7</td><td>8</td><td>0</td><td>7</td><td>8</td><td>6</td><td>5</td><td>0</td><td>1</td></tr></tbody></table>

cadasters. Moreover, this limitation is barely affecting the reliability of this work that focuses on other aspects than simulation engine such as the analysis of users' interaction, the solar metrics, the geometry model, and solar data visualization. Finally, another limitation concerned the lack of scientific literature on solar cadasters. During the *Step 1* of the scientific research process (Section 2.1) most of the literature concerned solar studies, dealing with individual buildings or neighborhoods, rather than web platforms, or short reviews of solar simulation tools and workflows (e.g. Ladybug for Grasshopper, Radiance). As a result of the *Stages* (a, b, c) of the research, only 20 of 51 solar cadasters have as supporting technical materials, 17 scientific papers (14 journal article and 3 conference proceedings) referring to 11 web platforms and 11 technical reports referring to 9 solar web platforms. The analysis of the scientific literature concerning the solar cadasters highlighted how some of the developers of the reviewed solar cadasters are currently working on some part of the advancements mentioned in this section. For example, the developers of the Geneva Solar Cadaster [72] are investigating the geometric reconstruction of the facades with the aim of identifying the available surfaces for Building Integrated Photovoltaics (BIPVs) systems in the vertical surfaces (i.e. facades) in urban areas [91]. Similarly, the developers of the solar cadaster of Switzerland [73] are defining diverse façade archetypes to provide an indicative scenario by displaying the expected solar potential values based on the available irradiation of the whole building surfaces [92]. The same solar cadaster's data were exploited to identify façade elements using image segmentation based on Generative Adversarial Networks (GANs) [93]. In this regard, a new test version of Switzerland national solar cadaster is made available in 3D from 20 June 2024 [94]. However, at the moment,

only solar irradiation on the ground can be calculated, excluding the possibility to calculate the buildings solar potential as well.

### 4.3. Contribution to sustainable development goals in high- and low-income countries

Solar cadasters align with the United Nations (UN) requirement to invest in advanced data collection and hold the potential to serve as platforms for establishing partnerships that strengthen the science-policy-society interface, enabling collaborative efforts to accomplish SDGs [95,96]. By making solar resource data available to PPP, these platforms facilitate informed decision-making and large-scale technology adoption, accelerating the environmental transition toward climate neutral cities (SDG11). In alignment with the target 12.c.1, which aims to “remove fossil-fuel subsidies,” solar cadasters also contribute to achieving SDG 12 (responsible consumption and production) by promoting cleaner and more sustainable energy practices.

Interactive platforms for solar energy planning can enhance PPP awareness, knowledge and perception, thereby increasing acceptance and willingness to invest in solar energy (point 1 in Fig. 9). This generates a valuable advantage by stimulating innovation in the solar energy sector and shaping the market, contributing to SDG 8 (decent work and economic growth) and SDG 9 (industry, innovation, technology and infrastructure).

Additionally, solar cadasters can facilitate partnerships within PPP, providing a common basis for mutual understanding (point 2 in Fig. 9). This shared understanding can serve as proof of concept for decision-makers when defining incentives or de-taxation policies (point 3 in
<figure><img src="image_15.png" /><figcaption>**Fig. 9.** The five main potentialities of use of solar cadaster and the three spheres of foundation which might be affected using solar cadaster with the users (i.e. PPP) involved in.</figcaption></figure>

Fig. 9). Comprehensive legislation, coupled with basic knowledge that does not require specialized expertise and supported by adequate subsides and incentives, can significantly boost the massive adoption of solar systems. This, in turn, can help reduce the costs of solar systems, prevent social inequality (SDG 10), and mitigate energy poverty (SDG 1).

Solar cadasters support individual and private entities in identifying clear steps towards solar system installation, thus smoothing the process and maximizing its impacts (point 4 in Fig. 9). The functionalities of solar cadasters enable a better understanding of factors beyond the mere cost of investment [97].

Finally, the private sector can exploit solar cadasters to assess the state of technological advancement in the solar energy sector and identify opportunities for innovation and market growth in solar systems (point 5 in Fig. 9). The potentiality for innovation of solar cadasters is founded at the intersection of three spheres of actions (Fig. 9), which are:

* the *Intent sphere*, representing the overall beliefs, paradigms, and goals that shape the direction of a user towards the decision to install solar systems (Personal sphere or people-private sphere).

* the *Design sphere*, consisting in the institutional superstructure that enable conditions for the installation of solar systems (e.g. information flow, rules, institutions, and capacities).

* the *Feedback & Parameters sphere*, regarding the interconnections between different actors and elements involved, which steer internal dynamics towards the installation.

Both these two aspects, *Design* and *Feedback & Parameters*, are dealing with the political decisions/actions, while the parameters (i.e. that variables that measure typical characteristic of a solar system) are at support of policy makers or experts to support their decision for incentives, standards, guidelines contributing to increase the implementation of solar systems installations. Feedback and parameters are driving forces to assess the effectiveness of the practical sphere.

The analysis of the status of solar energy digitalization and solar web platforms shows that high-income countries (HIC) – with a gross domestic product (GDP) greater than 58.26 $10^3$ USD – are at the forefront of these digital services, which allow to optimize the exploitation of solar energy. Indeed, PPP actions related to solar energy are often fragmented and occur primarily at the building level rather than at the neighborhood or city scale, significantly limiting their overall impact. Following this, HIC are investing in solar web platforms to promote more systematic and integrated energy strategies, ensuring universal access to affordable and clean energy while enhancing energy efficiency (SDG 7).

In HIC, there is a pressing need to reduce energy consumption while simultaneously producing green energy, particularly in urban environments. To accelerate the adoption of RES, it is increasingly essential to take advantage of cities, where conditions necessary for scaling up technologies are endemically present. Cities represent the nexus of decarbonation strategies [98] for energy and buildings, as they offer, regardless of the country's GDP, a higher density of energy use and greater opportunities to harness economic capital and technical expertise.

Conversely, the role of solar cadasters in low-income countries (LIC) – with a GDP lower than $6.7 \ 10^3$ USD – primarily focuses on supporting energy planning strategies aimed at achieving energy equity access rights. Solar cadasters can play a key role in expanding electricity access in underserved regions by visualizing and quantifying the solar energy potential. This enables localized solutions and optimizes resource allocation, addressing socio-economic disparities and bridging the energy gap sustainably [99]. Additionally, they support off-grid rural electrification initiatives by identifying areas with high solar potential, contributing to lifting families above the poverty line (SDG 1) and empowering communities with basic electricity access [100].

However, Bartolucci et al. [101] discussed several barriers to installing PV systems in LIC, including a lack of local high-tech electric grid infrastructure and economic constraints, such as insufficient budgets, grants, and subsidies to assist landlords and housing associations in funding retrofit projects. Moreover, due to economic deficiencies and limited access to advanced technologies, energy retrofits or the installation of RES are often performed using upcycled or decommissioned components and assemblies [102]. Further challenges outlined in the literature [103,104] include the risk of vandalism, such as the unauthorized removal of upcycled components after installation, and the absence of sustainable policies to promote strategies for achieving near-zero-emission buildings. To overcome these barriers, collaboration among local governments, supranational entities, and NGOs is essential. These entities must provide access to non-repayable financing supports, expertise and tools, including solar cadasters and GDP data, to prioritize the allocation of economic sources (SDG 17 – Collaborative efforts for the goals).

Access to electricity improves living standards, helping communities to accomplish with the SDG2 (zero hunger) and SDG3 (good health and wellbeing). Furthermore, solar cadasters can aid governmental organization and NGOs to prioritize and optimize PV installations in social service buildings, such as hospitals and schools, ensuring access to essential facilities like medical equipment, computers, and the internet (SDG 4).

In LIC, solar cadasters further contribute to SDG 8 (decent work and economic growth) by increasing real GDP per capita and creating
opportunities for economic development. They also support SDG 10 (reduced inequalities) by fostering inclusivity and enabling marginalized populations, including women and the elderly, to continue thriving in rural and remote areas.

## 4.4. Conclusions

This paper presents a collection of 51 solar cadasters which are representative of the state of the art of solar web platforms, providing insight into their characteristics (i.e., LOD, LOV) and functioning (i.e., users' interaction, solar metrics). The review highlights that solar cadasters are a relevant resource to increase the visualization and exploitation of solar potential of a territory, landscapes, or urban area by informing the users on the solar irradiation on the urban surfaces over different time periods (i.e. daily, monthly, seasonally, yearly).

Each cadaster was analyzed in its structure, and the process involved the following steps: (i) Definition of solar mapping, solar cadasters, and solar atlas; (ii) Literature review on the existing solar cadaster; (iii) Surveying of the existing solar cadasters; (iv) Identification of the strengths and the weaknesses of the solar cadasters, according to the geographical distribution and coverage, the geometric model, the solar data visualization, the regulations, the user interaction in the platform and the identification of the metrics; (v) Definition of pathways for further research by identifying the main research gaps.

After all the described processes the key findings obtained from the study are listed below:

*   **Geographical distribution and coverage:** The largest number of solar cadasters cover urban areas (27), followed by regional (18) and national (6) scale. On the other hands, also if they are representing the minority, in terms of coverage, the national solar cadasters are reaching the highest coverage values (e.g. ~380,000 km² in Norway). The highest concentration of solar cadasters (41) can be found on the European continent and this finding also corresponds to the highest amount of data for climate class Cfb (33).

*   **Geometry model and solar data visualization:** Although most of the solar cadasters (36) are highly developed from a geometric point of view (LOD3), the data visualization part is still very underdeveloped. Just two (2) platforms give information about the façade's results and only one (1) of them permits the 3D visualization of the model.

*   **Regulations:** In most cases (28), the Heritage constraints and the Cadastral information are not considered, also if they consist of useful information for the design of new projects (especially applied on the facades).

*   **User interaction in the solar cadaster platforms:** Among user interactions, all the inputs that can be modified by the users in the online platform were analyzed. The most frequent interactions in the solar cadasters were found to be the Selection of panel numbers/area (43), the Calculation of customized consumption (39), and the Investment and cost calculation (38).

*   **Metric identification:** The outputs given by the platforms were analyzed to define the principal metrics of the results. The metrics with the highest occurrence resulted to be the Optimal area for PV (43), the PV potential production (43), and the Investment cost (35).

The review's findings show that this is a cutting-edge topic in which many nations are working on, and the results are useful in understanding the future research developments to create more advanced and accurate solar cadasters. This work identified the future progresses in the research method:

*   The creation of an open-access exhaustive database (e.g. in Excel format) thus any expert can include more solar cadasters starting from this review to achieve a more comprehensive worldwide overview.

*   The pro-active involvement of users. Involving users in this research could help to overcome language and cultural barriers, allowing access to data worldwide. Furthermore, solar cadasters should offer more user-interactive functionalities and more simulations of energy production by novel PV technologies as soon as these products are maturing (e.g. simulation of solar potential on vertical surfaces – facades – has started to be visualized in solar cadasters when the BIPV technology started to be mature in the market).

*   Completion of solar cadasters' Metadata. Cooperation from developers is needed to overcome barriers related to the knowledge of the technical aspects of the platforms. More scientific documentation needs to be provided by platform providers/operators to know the quality and the origin of the data used in the calculation and modeling.

*   Collaboration between governments, NGOs and municipalities is essential to address LIC-specific challenges such as inadequate high-tech infrastructure, limited financial resources and economic constraints. This collaborative approach is not just contributing to the SDG but can support inclusive development and the widespread adoption of renewable energy technologies by fostering capacity building, bridging the energy access gap, and creating opportunities for economic growth.

By offering a high degree of interaction and customization, the solar cadasters allow individual users (i.e., people), municipality and stakeholders' (i.e., public, and private) – PPP’s engagement and participation. In this way, individual users can actively interact with the platform in the pre-design phase of solar systems simulating different scenarios for the cost and investment calculations, being aware of the solar energy potential and solar systems deployment. The public sector can use the platform to proceed with more informed and strategic decision-making processes for urban/national energy planning, assessing the impact of policy interventions in the design and installation phase. Municipalities can use this instrument to gain control over the data of the energy production in cities. In this regard, the solar cadasters represent more a comprehensive database that integrates various data layers to facilitate solar planning development. These are intuitive, interactive, and accessible platforms that are useful for both public actors such as municipalities and policymakers, private stakeholders (i.e., investors, firms) but also for end users (i.e., public) to independently visualize the solar potential on their own buildings and make evaluation for interventions and investments on solar energy systems. Understanding the current performances of the solar cadasters make it possible to identify new perspectives and developments of these tools, as they are useful to develop informed urban energy planning strategies, accelerate clean-energy transitions, increase the public and private sector engagement support innovation, and contribute to the achievement of the Sustainable Development Goals in both high-income and low-income countries.

### CRediT authorship contribution statement

**M. Giorio:** Writing – original draft, Visualization, Validation, Software, Methodology, Formal analysis, Data curation, Conceptualization.

**M. Manni:** Writing – review & editing, Visualization, Supervision, Methodology, Formal analysis, Conceptualization. **N.I. Köker:** Conceptualization. **C. Bertolin:** Writing – review & editing, Visualization, Supervision, Methodology, Conceptualization. **M. Thebault:** Formal analysis. **G. Lobaccaro:** Writing – review & editing, Supervision, Resources, Project administration, Methodology, Funding acquisition, Conceptualization.

### Acknowledgments

The authors gratefully acknowledge the support from the Norwegian Research Council (research project FRIPRO-FRINATEK no. 324243 HELIOS - eHancing optimal ExpLoitation of Solar energy in Nordic cities
through the digitalization of built environment). Within this project the authors wish also to acknowledge both the Faculty of Engineering and the Department of Civil and Environmental Engineering of the Norwegian University of Science and Technology for the support in terms of resources and infrastructures.

The authors are grateful to the International Energy Agency, and the Solar Heating & Cooling Programme, for their continuous support of our work in IEA SHC Task 51 "Solar Energy in Urban Planning" and IEA SHC Task 63 "Solar Neighborhood Planning".

# Appendix

## a.1 Other solar platforms

<table><thead><tr><th>N.</th><th>Link</th><th>Name</th><th>Country</th><th>City/Region</th><th>Date of access</th></tr></thead><tbody><tr><td colspan="6"><strong>Non-open access cadasters</strong></td></tr><tr><td>1</td><td>https://mapdwell.com/en/solar#assessment</td><td>Solar System – Mapdwell</td><td>USAChile</td><td>California (San Francisco)Colorado (Boulder)<br>District of Columbia (Washington)Massachusetts<br>(Cambridge, Boston)AntofagastaLo<br>BarnecheaVitacura</td><td>Nov.<br>2023</td></tr><tr><td>2</td><td>https://gmp-environmental-solar.web.app/#intro</td><td>Solar API Demo</td><td>World</td><td>World</td><td>Oct.<br>2023</td></tr><tr><td colspan="6"><strong>Platform out of order</strong></td></tr><tr><td>1</td><td>http://solar.geocontent.de/mertert/</td><td>Solarpotentialkataster Mertert</td><td>Luxembourg</td><td>Mertert</td><td>Dec.<br>2023</td></tr><tr><td>2</td><td>http://solar.geocontent.de/dudelange/</td><td>Solarpotentialkataster Dudelange</td><td>Luxembourg</td><td>Dudelange</td><td>Dec.<br>2023</td></tr><tr><td>3</td><td>https://maps.vdl.lu/calcite/index.html?webmap<br>=1c070881e0504f4fa3023942520909c8&menua<br>bout=true&activepanel=about&aboutsumma<br>ry=false&aboutdescription=true</td><td>Solarpotentialkataster Ville</td><td>Luxembourg</td><td>Ville</td><td>Nov.<br>2023</td></tr><tr><td>4</td><td>https://experience.arcgis.com/experience/128fe<br>14264e348cbaa9668c90a04b62b</td><td>Starigrad solar model</td><td>Northern<br>Croatia</td><td>Starigrad</td><td>Oct.<br>2023</td></tr><tr><td>5</td><td>https://kbhkort.kk.dk/spatialmap?&selectorgro<br>ups=themecontainer%20bygninger%20detalje<br>r&mapext=702689.6%206165734.4%<br>20747310.4%206186265.6&layers=theme-start<br>kort%20theme-disclaimer%20theme_bymodel_b<br>ygning solgrupper_40&mapheight=807&map<br>width=1748&profile=solanalyser</td><td>–</td><td>Denmark</td><td>Copenhagen</td><td>Oct.<br>2023</td></tr><tr><td>6</td><td>https://solarmap.lacounty.gov/</td><td>Solar map</td><td>USA</td><td>Los Angeles</td><td>Nov.<br>2023</td></tr><tr><td>7</td><td>https://geo.osnabrueck.de/solar/ipsyscon.de</td><td>–</td><td>Germany</td><td>Osnabrück</td><td>Nov.<br>2023</td></tr><tr><td>8</td><td>https://stadsatlas.malmo.se/solkarta/</td><td>Solkartan</td><td>Sweden</td><td>Malmo</td><td>Nov.<br>2023</td></tr><tr><td>9</td><td>https://app.dumpark.com/sunlight/sf</td><td>–</td><td>USA</td><td>San Francisco</td><td>Nov.<br>2023</td></tr><tr><td>10</td><td>https://nantes-metropole.insunwetrust.solar/simu<br>lateur</td><td>In sun we trust</td><td>France</td><td>Nantes</td><td>Nov.<br>2023</td></tr><tr><td>11</td><td>https://gis.cityofboston.gov/solarboston/</td><td>Solarboston</td><td>USA</td><td>Boston</td><td>Nov.<br>2023</td></tr><tr><td>12</td><td>https://experience.arcgis.com/experience/d82a52<br>97696840bc907756482da895b</td><td>Koper solar model</td><td>Slovenia</td><td>Koper</td><td>Nov.<br>2023</td></tr><tr><td>13</td><td>https://lisboaenova.org/cartasolarlisboa</td><td>Lisboa enova</td><td>Portugal</td><td>Lisbon</td><td>Nov.<br>2023</td></tr><tr><td>14</td><td>https://www.pvcity.pt/viewer</td><td>Solar Potential Viewer</td><td>Portugal</td><td>Lisbon</td><td>Dec.<br>2023</td></tr><tr><td>15</td><td>https://energia.sistemapiemonte.it/ittb-torino</td><td>Cities On Power: Il portale solare</td><td>Italy</td><td>Turin</td><td>Nov.<br>2024</td></tr><tr><td>16</td><td>https://cadastresolaire.iresen.org/</td><td>Cadastre solaire – Ville de<br>Benguerir</td><td>Morocco</td><td>Benguerir</td><td>Nov.<br>2024</td></tr><tr><td colspan="6"><strong>Solar Atlases</strong></td></tr><tr><td>1</td><td>https://pvwatts.nrel.gov/pvwatts.php</td><td>PVWatts</td><td>World</td><td>World</td><td>Oct.<br>2023</td></tr><tr><td>2</td><td>https://re.jrc.ec.europa.eu/pvg_tools/en/</td><td>PVGIS – Photovoltaic<br>Geographical Information System</td><td>World</td><td>World</td><td>Oct.<br>2023</td></tr><tr><td>3</td><td>https://globalsolaratlas.info/map?<br>c=62.977069,10.772095,9&s = 63.434<br>853,10.39444&m=site</td><td>Global Solar Atlas</td><td>World</td><td>World</td><td>Oct.<br>2023</td></tr><tr><td>4</td><td>https://nsrdb.nrel.gov/data-viewer</td><td>NSRDB – National Solar<br>Radiation Database</td><td>World</td><td>World</td><td>Oct.<br>2023</td></tr><tr><td>5</td><td>https://www.soda-pro.com/web-services/<br>radiation/helioclim-1/helioclim-1-info</td><td>Helioclim 1</td><td>World</td><td>World</td><td>Oct.<br>2023</td></tr><tr><td colspan="6"><strong>Solar Mapping</strong></td></tr><tr><td>1</td><td>https://experience.arcgis.com/experience/fcb<br>650607a9148a688e23f8b7ff38d65/page/Map/</td><td>Rooftop Solar Potential</td><td>Canada</td><td>Peterborough</td><td>Dec.<br>2023</td></tr></tbody></table>

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<table><thead><tr><th>N.</th><th>Link</th><th>Name</th><th>Country</th><th>City/Region</th><th>Date of access</th></tr></thead><tbody><tr><td>2</td><td>https://kartta.hel.fi/3d/solar/#/</td><td>Aurinkoenergiapotentiaali</td><td>Finland</td><td>Helsinki</td><td>Nov.<br>2023</td></tr><tr><td>3</td><td>https://budapest.hu/zold-budapest/klima-e-s-kornyezetvedelem/nappal-hajtva/szolar-terkep</td><td>Budapest Szolár Térkép</td><td>Hungary</td><td>Budapest</td><td>Oct.<br>2023</td></tr><tr><td>4</td><td>https://webgis.eurac.edu/solartirol/</td><td>Tirol - Bolzano</td><td>Italy</td><td>Tirol</td><td>Nov.<br>2023</td></tr><tr><td>5</td><td>https://sit.comune.bolzano.it/carto_dbt/init?lan<br>g-it#SitSun/maps/map</td><td>Carto - solar map for the city of<br>Bolzano</td><td>Italy</td><td>Bolzano</td><td>Dec.<br>2023</td></tr><tr><td>6</td><td>https://webgis.provincia.tn.it/wgt/?lang=it<br>&topic=19&bgLayer=orto20<br>15&layers=ammcom,irraggiamento_wms,<br>aree_idonee,aree_non_idonee,tetti,vinc_ind_zr_a,<br>vinc_dir_bea&layersVisibility=false=true>true>true,<br>true>true>true&X=5103366.34&Y=664560<br>.04&zoom=9&layers_opacity=1,1,0,8,0,8,1,1,0<br>.7&catalogNodes=94</td><td>Potenziale fotovoltaico Provincia<br>autonoma di Trento</td><td>Italy</td><td>Trento</td><td>Dec.<br>2023</td></tr><tr><td>7</td><td>https://opendata.bristol.gov.uk/datasets/ec82ac7<br>9d9774cb59765327aa4fa450c_22/explore?locat<br>ion=51.454539 %2C.2.596983%2C17.21</td><td>Open data Bristol</td><td>UK</td><td>Bristol</td><td>Oct.<br>2023</td></tr><tr><td>8</td><td>https://solar.energyatlas.ucla.edu/map.html#map</td><td>County Community Solar<br>Opportunities Map<br>Stadt Wien</td><td>USA<br>Austria</td><td>Los Angeles<br>Wien</td><td>Oct.<br>2023<br>Oct.<br>2023</td></tr><tr><td>9</td><td>https://www.wien.gv.at/umweltgut/public/grafik<br>.aspx?ThemePage=9&书mark=FF5YRh<br>s0JEbDZbZEHjJLRDnCjrGPfAdwccKCTH3ui0k<br>Ps1sMkmoGZjjW-amRGA07JWd0S5LrYHZvcEPs-c</td><td>Northern Virginia Solar Map</td><td>USA</td><td>Northern Virginia</td><td>Oct.<br>2023</td></tr><tr><td>10</td><td>https://nvrc.maps.arcgis.com/apps/webappviewer/<br>/index.html?id=ef5c5dc969f341cc986cd431d94c<br>dfe9</td><td>NY Solar Map</td><td>USA</td><td>New York</td><td>Oct.<br>2023</td></tr><tr><td>11</td><td>https://nysolarmap.com/</td><td>Chicago Solar Map</td><td>USA</td><td>Chicago</td><td>Oct.<br>2023</td></tr><tr><td>12</td><td>https://www.elevatenp.org/chi-solar-map/<br>#16.65/41.927579/-87.70523</td><td>Potencial Solar de Lisboa</td><td>Portugal</td><td>Lisbon</td><td>Oct.<br>2023</td></tr><tr><td>13</td><td>https://www.solis-lisboa.pt/mapa-solar-de-li/</td><td>Karta solarnog potencijala</td><td>Northern<br>Croatia</td><td>Koprivnica</td><td>Dec.<br>2023</td></tr><tr><td>14</td><td>https://www.arcgis.com/apps/MapJournal/index.<br>html?appid=03da64a0ce8940e4ba63a4c<br>e9e59be7a</td><td>Solar Roadmap Web Map</td><td>USA</td><td>Long Island</td><td>Nov.<br>2023</td></tr><tr><td>15</td><td>https://tnc.maps.arcgis.com/apps/webappviewe<br>r/index.html?id=d61dfb3bad544dbea16397e<br>08f084ff1</td><td>GO Solar ready</td><td>USA</td><td>—</td><td>Dec.<br>2023</td></tr><tr><td>16</td><td>https://gis.oki.org/solar/#</td><td>Solar potential in Vitoria-Gasteiz</td><td>Spain</td><td>Vitoria-Gasteiz</td><td>Oct.<br>2023</td></tr><tr><td>17</td><td>http://proyectos.hei-tecnalia.com/SHCityApp3<br>DTiles/SHCityApp.html?project=SHCityWebApp</td><td>Energy Barcelona</td><td>Spain</td><td>Barcelona</td><td>Dec.<br>2023</td></tr><tr><td>18</td><td>https://www.energia.barcelona/es/mapa-cuan<br>ta-energia-puedes-generar</td><td>Potencialidad solar</td><td>Spain</td><td>Madrid</td><td>Nov.<br>2023</td></tr><tr><td>19</td><td>https://www.arcgis.com/apps/mapviewer/index.<br>html?layers=a643ece5eaf94d898d0b45ed08e<br>5a580</td><td>Potencial de Energía Solar de<br>Edificios</td><td>Spain</td><td>Nation</td><td>Nov.<br>2024</td></tr><tr><td>20</td><td>https://eficiencia-energetica.ign.es/solar/?x=-41<br>340.8033178965&y=4925752.340442745&z=19<br>&b=IGNBaseTodo.tms&c=radiacion_solar</td><td>Cadastre Solaire</td><td>France</td><td>Paris</td><td>Oct.<br>2023</td></tr><tr><td>21</td><td>https://capgeo sig.paris.fr/Apps/CadastreSolaire/</td><td>Energie Atlas</td><td>Germany</td><td>Berlin</td><td>Oct.<br>2023</td></tr><tr><td>22</td><td>https://energieatlas.berlin.de/</td><td>SITG - Le Territoire Genevois A<br>La Carte<br>Geodaten</td><td>Switzerland<br>Austria</td><td>Geneve<br>Graz</td><td>Oct.<br>2023<br>Oct.<br>2023</td></tr><tr><td>23</td><td>https://map.sitg.ch/app/?mapresources<br>=GEOTHERMIE%2CENERGIE_</td><td>Solingen Solar Cadastre</td><td>Germany</td><td>—</td><td>Oct.<br>2023</td></tr><tr><td>24</td><td>https://geodaten.graz.at/WebOffice/synserver?<br>project=solar_pv&client=core</td><td>Solar energy Bristol</td><td>UK</td><td>Bristol</td><td>Oct.<br>2023</td></tr><tr><td>25</td><td>https://solingen.de/inhalt/solarkataster-karte</td><td>Zonnescan</td><td>Netherlands</td><td>Amersfoort</td><td>Oct.<br>2023</td></tr><tr><td>26</td><td>https://maps.bristol.gov.uk/pinpoint/?address<br>=51+B27+2RD&service=localinfo&theme=no<br>ne&layer=solar+potential&mapopts=legend</td><td>SolarTO Map</td><td>Canada</td><td>Toronto</td><td>Oct.<br>2023</td></tr><tr><td>27</td><td>https://zonnedakje.nl/kaart</td><td>Otovo / In Sun We Trust</td><td>France</td><td>—</td><td>Dec.<br>2023</td></tr><tr><td>28</td><td>https://www.toronto.<br>ca/services-payments/water-enviro<br>nment/net-zero-homes-buildings/solar-to/solarto<br>-map/#location=&lat=43.704367&lng=-79.3110<br>75&zoom=13</td><td></td><td></td><td></td><td></td></tr><tr><td>29</td><td>https://www.otovo.fr/</td><td></td><td></td><td></td><td></td></tr></tbody></table>

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<table><thead><tr><th>N.</th><th>Link</th><th>Name</th><th>Country</th><th>City/Region</th><th>Date of access</th></tr></thead><tbody><tr><td>30</td><td>https://solea.gr/athens-solar-cadastre/</td><td>Athens Solar Cadastre</td><td>Greece</td><td>Athens</td><td>Nov. 2023</td></tr><tr><td>31</td><td>https://cartographie.ma/</td><td>Cadastre Solaire</td><td>Morocco</td><td>Rabat, Casablanca, Benguerir, Dakhla, Bouskoura, Mohammed</td><td>Dec. 2023</td></tr><tr><td>32</td><td>https://byfornyelsespuljer.kk.dk/solcellepuljen</td><td>Byfornyelsespuljer</td><td>Denmark</td><td>Copenaghen</td><td>Dec. 2023</td></tr><tr><td>33</td><td>https://stadsatlas.malmo.se/solkarta/</td><td>Solkarta</td><td>Sweden</td><td>Malmo</td><td>Dec. 2023</td></tr><tr><td>34</td><td>https://geomel.lillemetropole.fr/adws/app/984 8da76-ab4f-11ec-a1eb-43e41a482e27/</td><td>Cadastre solaire de la MEL</td><td>France</td><td>Lille</td><td>Oct. 2023</td></tr><tr><td>35</td><td>https://monpotentielsolaire.smartidf.services/fr</td><td>Mon potential solaire</td><td>France</td><td>–</td><td>Oct. 2023</td></tr><tr><td>36</td><td>https://geoportal.muenchen.de/portal/solarpot enzial/</td><td>Geo Portal München</td><td>Germany</td><td>München</td><td>Oct. 2023</td></tr><tr><td>37</td><td>https://geoportal.saarland.de/mapbender/frames /index.php?gui_id=Geoportal -SL-2020&WMC=4521</td><td>Solardachkataster</td><td>Germany</td><td>SL – Saarland (Wadern, Neunkirchen, St. Wendel, Saarlouis)</td><td>Oct. 2023</td></tr><tr><td>38</td><td>https://www.salzburg.gv.at/sagismobile/sagison line/map/Energie/Solar</td><td>Salzburg solar map</td><td>Austria</td><td>Salzburg</td><td>Nov. 2023</td></tr><tr><td>39</td><td>https://www.tirolsolar.at/#9/47.1461/11.7192</td><td>Tirolsolar</td><td>Austria</td><td>Tirol</td><td>Nov. 2023</td></tr><tr><td>40</td><td>https://geoportal.saarland.de/mapbender/frames /index.php?gui_id=Geoportal -SL-2020&WMC=4521</td><td>Solardachkataster</td><td>Germany</td><td>–</td><td>Dec. 2023</td></tr><tr><td>41</td><td>https://tokyosolar.netmap.jp/map/Map.html?ll=3 5.6664494154,139.3160825534</td><td>Solar register Tokyo</td><td>Japan</td><td>Tokyo</td><td>Feb. 2024</td></tr><tr><td>42</td><td>https://www.google.com/maps/dir/63.4018457, 10.4195877/42.55127,21.9153482/ @42.5636543,21.9183607,12920m/data=!3m1! 1e3!4m5!4m4!1m1!4e1!1m0!3e0? entry=ttu% 26g_ep=EgoyMDI0MTAyOS4wIKXMDSoASAFQA w%3D%3D</td><td>GisVranje</td><td>Serbia</td><td>Vranje</td><td>Nov. 2024</td></tr></tbody></table>

## a.2 Köppen climate classification scheme symbols description

<table><thead><tr><th>1st letter</th><th>2nd letter</th><th>3rd letter</th></tr></thead><tbody><tr><td>A (Tropical)</td><td>f (Rainforest)<br>m (Monsoon)<br>w (Savanna, dry winter)<br>s (Savanna, dry summer)</td><td></td></tr><tr><td>B (Dry)</td><td>W (Arid Desert)<br>S (Semi-Arid Steppe)<br>w (Dry winter)</td><td>h (Hot)<br>k (Cold)<br>a (Hot summer)</td></tr><tr><td>C (Temperate)</td><td>f (No dry season)<br>s (Dry summer)</td><td>b (Warm summer)<br>c (Cold summer)<br>a (Hot summer)</td></tr><tr><td>D (Continental)</td><td>w (Dry winter)<br>f (No dry season)<br>s (Dry summer)</td><td>b (Warm summer)<br>c (Cold summer)<br>d (Very cold winter)<br>T (Tundra)<br>F (Ice cap)</td></tr><tr><td>E (Polar)</td><td></td><td></td></tr></tbody></table>
a.3 Relationship between LOD and LOV in solar cadasters

<figure><img src="image_16.png" /></figure>
a.4 Tabular review of the solar web platforms according to information of the regulations

<table><thead><tr><td>ID</td><td>Ref.</td><td>Cadastral information</td><td>Heritage constraints</td></tr></thead><tbody><tr><td>1</td><td>[30]</td><td>No</td><td>No</td></tr><tr><td>2</td><td>[31]</td><td>No</td><td>No</td></tr><tr><td>3</td><td>[26]</td><td>No</td><td>No</td></tr><tr><td>4</td><td>[32]</td><td>No</td><td>No</td></tr><tr><td>5</td><td>[33]</td><td>No</td><td>No</td></tr><tr><td>6</td><td>[29]</td><td>No</td><td>No</td></tr><tr><td>7</td><td>[34]</td><td>No</td><td>No</td></tr><tr><td>8</td><td>[16]</td><td>No</td><td>Yes</td></tr><tr><td>9</td><td>[35]</td><td>No</td><td>Yes</td></tr><tr><td>10</td><td>[36]</td><td>No</td><td>Yes</td></tr><tr><td>11</td><td>[37]</td><td>No</td><td>Yes</td></tr><tr><td>12</td><td>[38]</td><td>No</td><td>Yes</td></tr><tr><td>13</td><td>[39]</td><td>No</td><td>Yes</td></tr><tr><td>14</td><td>[40]</td><td>No</td><td>Yes</td></tr><tr><td>15</td><td>[41]</td><td>No</td><td>No</td></tr><tr><td>16</td><td>[42]</td><td>No</td><td>Yes</td></tr><tr><td>17</td><td>[43]</td><td>No</td><td>No</td></tr><tr><td>18</td><td>[44]</td><td>No</td><td>No</td></tr><tr><td>19</td><td>[45]</td><td>No</td><td>No</td></tr><tr><td>20</td><td>[46]</td><td>No</td><td>No</td></tr><tr><td>21</td><td>[47]</td><td>No</td><td>Yes</td></tr><tr><td>22</td><td>[48]</td><td>No</td><td>Yes</td></tr><tr><td>23</td><td>[49]</td><td>No</td><td>No</td></tr><tr><td>24</td><td>[50]</td><td>No</td><td>No</td></tr><tr><td>25</td><td>[51]</td><td>No</td><td>No</td></tr><tr><td>26</td><td>[52]</td><td>No</td><td>Yes</td></tr><tr><td>27</td><td>[53]</td><td>No</td><td>Yes</td></tr><tr><td>28</td><td>[54]</td><td>No</td><td>No</td></tr><tr><td>29</td><td>[55]</td><td>No</td><td>No</td></tr><tr><td>30</td><td>[56]</td><td>No</td><td>No</td></tr><tr><td>31</td><td>[57]</td><td>No</td><td>Yes</td></tr><tr><td>32</td><td>[58]</td><td>Yes</td><td>Yes</td></tr><tr><td>33</td><td>[59]</td><td>No</td><td>No</td></tr><tr><td>34</td><td>[60]</td><td>No</td><td>No</td></tr><tr><td>35</td><td>[61]</td><td>No</td><td>Yes</td></tr><tr><td>36</td><td>[62]</td><td>No</td><td>No</td></tr><tr><td>37</td><td>[63]</td><td>No</td><td>No</td></tr><tr><td>38</td><td>[20]</td><td>No</td><td>No</td></tr><tr><td>39</td><td>[64]</td><td>No</td><td>Yes</td></tr><tr><td>40</td><td>[65]</td><td>No</td><td>No</td></tr><tr><td>41</td><td>[66]</td><td>Yes</td><td>Yes</td></tr><tr><td>42</td><td>[67]</td><td>No</td><td>No</td></tr><tr><td>43</td><td>[68]</td><td>No</td><td>Yes</td></tr><tr><td>44</td><td>[69]</td><td>No</td><td>No</td></tr><tr><td>45</td><td>[70]</td><td>Yes</td><td>No</td></tr><tr><td>46</td><td>[71]</td><td>Yes</td><td>No</td></tr><tr><td>47</td><td>[72]</td><td>No</td><td>Yes</td></tr><tr><td>48</td><td>[73]</td><td>Yes</td><td>Yes</td></tr><tr><td>49</td><td>[74]</td><td>No</td><td>Yes</td></tr><tr><td>50</td><td>[75]</td><td>No</td><td>No</td></tr><tr><td>51</td><td>[76]</td><td>No</td><td>No</td></tr></tbody></table>

References

[1] F.J.M.M. Nijssen, et al., *The momentum of the solar energy transition*, Nat. Commun. 14 (1) (2023) 6542.

[2] M. Formolli, T. Kleiven, G. Lobaccaro, *Assessing solar energy accessibility at high latitudes: A systematic review of urban spatial domains, metrics, and parameters*, Renew. Sustain. Energy Rev. 177 (2023) 113231.

[3] M. Manni, et al., *Ten questions concerning planning and design strategies for solar neighborhoods*, Build. Environ. 246 (2023).

[4] Kanters, J., M. Wall, and E. Kjellsson. *The solar map as a knowledge base for solar energy use*, in *Energy Procedia*. 2014. Elsevier Ltd.

[5] Batel, S. and D. Rudolph, *A critical approach to the social acceptance of renewable energy infrastructures*. A critical approach to the social acceptance of renewable energy infrastructures. 2021: Springer International Publishing. 3-19.

[6] S. Freitas, et al., *Modelling solar potential in the urban environment: State-of-the-art review*, Renew. Sustain. Energy Rev. 41 (2015).

[7] P. Ni, et al., *Simulation of solar radiation on metropolitan building surfaces: A novel and flexible research framework*, Sustain. Cities Soc. 93 (2023) 104469.

[8] G. Desthieux, et al., *Solar energy potential assessment on rooftops and facades in large built environments based on lidar data, image processing, and cloud computing*. Methodological background, application, and validation in Geneva (solar cadaster), Frontiers Built Environ. 4 (2018).

[9] G. Lobaccaro, et al., *A methodological analysis approach to assess solar energy potential at the neighborhood scale*, Energies 12 (18) (2019).

[10] K. Bódís, et al., *A high-resolution geospatial assessment of the rooftop solar photovoltaic potential in the European Union*, Renew. Sustain. Energy Rev. 114 (2019) 109309.

[11] EUKI project Solar Adria. Mapping solar potential in pilot municipalities - Deliverable D.II.1. 2021.

[12] S. Anselmo, M. Ferrara, *Trends and Evolution of the GIS-Based Photovoltaic Potential Calculation*, Energies 16 (2023), https://doi.org/10.3390/en16237760.

[13] A. Bieda, A. Cienciala, *Towards a Renewable Energy Source Cadastre - A Review of Examples from around the World*, Energies 14 (23) (2021) 8095.

[14] M. Segreto, et al., *Trends in social acceptance of renewable energy across Europe - a literature review*, Int. J. Environ. Res. Public Health 17 (24) (2020) 1-19.

[15] R. Pedruzzi, et al., *Review of mapping analysis and complementarity between solar and wind energy sources*, Energy 283 (2023) 129045.

[16] Energy, C. Cadastre solaire du Grand Annecy. [cited: October 2024]; Available from: https://grand-annecy.cadastre-solaire.fr/.

[17] *Solar Heating and Cooling (SHC) Programme by the International Energy Agency (IEA)*, Task 63 "Solar Neighborhood Planning" Available from: https://task63.iea-shc.org/.
[18] Kanters, J., et al., *Opportunities for Improved Workflows and Development Needs of Solar Planning Tools. Report from SHC Task 63: Solar Neighborhood Planning and work performed in Subtask C: Solar planning tools*. July 2024.

[19] Solis. *Potencial Solar de Lisboa*. [cited: November 2023]; Available from: https://www.solis-lisboa.pt/mapa-solarde-li/.

[20] Optimiser, S. Auckland Rooftop Solar Energy Potential. [cited: October 2023];
Available from: https://solarpower.cer.auckland.ac.nz/.

[21] PVGIS. Photovoltaic Geographical Information System. [cited: October 2023];
Available from: https://re.jrc.ec.europa.eu/pvg tools/en/.

[22] M.J. Page, et al., *The PRISMA 2020 statement: an updated guideline for reporting systematic reviews*, BMJ 2021 (2020) 372.

[23] N. McMeekin, et al., *How methodological frameworks are being developed: evidence from a scoping review*, BMC Med. Res. Method. 20 (1) (2020) 173.

[24] D. Johnson, et al., *Gamification for health and wellbeing: A systematic review of the literature*, Internet Interv. 6 (2016) 89–106.

[25] M. Kottek, et al., *World Map of the Köppen-Geiger climate classification updated*, Meteorol. Z. 15 (3) (2006) 259–263.

[26] IRENA. International Renewable Energy Agency, SolarCity Simulator. [cited: November 2023]; Available from: https://solarcity.irena.org/?_gl=1*182k4n4*_ga*MTc2MTQWnJyMi4XnJg1NDQ0OTxg*_ga_7W6ZEF19K4*MTY4NQTOKNDk4MC4LxJAuMTY4NQTOKNDk4MC42MC4WlJ.A_#en/locations.

[27] Nouvel, R., et al., *CityGML-based 3D City Model for Energy Diagnostics and Urban Energy Policy Support*, in IBPSA World. 2013.

[28] F. Biljecki, H. Ledoux, J. Stoter, *Does a Finer Level of Detail of a 3D City Model Bring an Improvement for Estimating Shadows? in: A. Abdul-Rahman (Ed.), *Advances in 3D Geoinformation Springer International Publishing, Cham*, 2017, pp. 31–47.

[29] Sunroof, P. *MyHEATSolar*. [cited: November 2024]; Available from: https://solar.myheat.ca/.

[30] Solar Calculator - DEWA Dubai. [cited: November 2024]; Available from: https://www.dewa.gov.ae/en/consumer/solar-community/solar-calc.

[31] SunSPOT Australia. [cited: November 2023]; Available from: https://www.sunspot.org.au/.

[32] VEKA. Energiesparen - Vlaanderen. [cited: October 2023]; Available from: https://apps.energiesparen.be/zonnekaart.

[33] Residential solar calculator Calgary. [cited: November 2023]; Available from:
https://www.calgary.ca/environment/programs/residential-solar-calculator.html.

[34] Hong Kong Solar Irradiation Map. [cited: November 2024]; Available from:
https://solarmap.emsd.gov.hk/map/.

[35] Energy, C. Cadastre solaire de Béziers Méditerranée. [cited: October 2023];
Available from: https://beziers-mediterranee.cadastre-solaire.fr/.

[36] Energy, C. Cadastre solaire de Montpellier Méditerranée Métropole. [cited: October 2023]; Available from: https://montpellier3m.cadastre-solaire.fr/.

[37] Energy, C. Cadastre solaire de Toulouse Métropole. [cited: October 2023]; Available from: https://toulouse-metropole.cadastre-solaire.fr/.

[38] Energy, C. Cadastre solaire de Nantes Métropole. [cited: October 2023]; Available from: https://nantes-metropole.cadastre-solaire.fr/.

[39] Energy, C. Cadastre solaire de Bordeaux Métropole. [cited: October 2023];
Available from: https://marenov-bordeaux-metropole.cadastre-solaire.fr/.

[40] Energy, C. Cadastre solaire du Pôle territorial du Sud Gironde. [cited: October 2023]; Available from: https://pole-territorial-sud-gironde.cadastre-solaire.fr/.

[41] GEOFLY. Solarpotentialkataster Schwerin. [cited: November 2023]; Available from:
https://solar.geocontent.de/schwerin/.

[42] SUNAREA. Sonne Trifft Dach. [cited: October 2023]; Available from: https://www.gpm-webgis-10.de/geoapp/solarkataster/karlsruhe/.

[43] Ipsysconde. GeoLIS LRA Starnberg *Solarkataster*. [cited: October 2023]; Available from: https://geolis.lk.starnberg.de/GeoLISmapapps/resources/apps/SolarkatasterVollstaendig/index.html?lang=de.

[44] GEOPLEX. Solarkataster Bremen. [cited: November 2023]; Available from:
https://www.solarkataster-bremen.de/#s=map/.

[45] GEOPLEX. Solarrechner Hamburger. [cited: November 2023]; Available from:
https://www.solarrechner-hamburg.de/#s=map/.

[46] stadtkaiserslautern. Solarkataster Kaiserslautern. [cited: October 2023]; Available from: https://geoportal.kaiserslautern.de/solar/#/.

[47] GEOPLEX. Solarkataster Burghausen. [cited: November 2023]; Available from:
https://burghausen-solar.de/#s=screen.

[48] SUNAREA. Solarkataster - RLP. [cited: October 2023]; Available from: https://www.gpm-webgis-10.de/geoapp/solarkataster/rlp/.

[49] SUNAREA. Solarkataster Hessen. [cited: October 2023]; Available from: https://www.gpm-webgis-12.de/geoapp/frames/index_ext2.php?gui_id=hessen_sod_03.

[50] SUNAREA. Solarkataster - NRW [cited: October 2023]; Available from: https://www.gpm-webgis-13.de/geoapp/kataster/rheinsiegkreis/.

[51] Ipsysconde. Hannover Solarkataster. [cited: November 2023]; Available from:
https://hannit.maps.arcgis.com/apps/webappviewer/index.html?id=ae44d505b53a493cb3f15c36e310786.

[52] Ipsysconde. Landesweites Solarkataster Rheinland-Pfalz. [cited: November 2023];
Available from: https://solarkataster.rlp.de/#null.

[53] Ipsysconde. Landkreis Leer [cited: November 2023]; Available from: https://solarkleer.ipsyscon.de/de/kartenanwendung/.

[54] GEOPLEX. Solarpotenzial auf Dachflächen. [cited: November 2023]; Available from: https://www.energieatlas-bw.de/sonne/dachflachen/solarpotenzial-auf-dachflächen.

[55] GEOPLEX. Solarkataster - Landkreis Aurich. [cited: November 2023]; Available from: https://www.solarkataster-aurich.de/#s=borders.

[56] energieportal. Solaratlas Brandenburg. [cited: October 2023]; Available from:
https://energieportal-brandenburg.de/cms/inhalte/tools/solaratlas-brandenburg/mein-dach/.

[57] Tetraedersolar. SOLARPOTENZIALKATASTER. [cited: October 2023]; Available from: https://www.solare-stadt.de/home/spk/.

[58] Tetraedersolar. Energie - Geoportal Luxembourg. [cited: October 2023]; Available from: https://map.geoportal.lu/theme/energie?bgLayer=basemap_2015_global&version=3&zoom=18&X=680916&Y=6403063&lang=fr&rotation=0&layers=1813&opacities=1&time=&crosshair=false.

[59] Zonatlas. Wageningen. [cited: November 2023]; Available from: https://www.zonatlas.nl/wageningen/ontdek-de-zonatlas/.

[60] Zonatlas. Arnhem. [cited: November 2023]; Available from: https://www.zonatlas.nl/arnhem/.

[61] Zonatlas. Amsterdam. [cited: November 2023]; Available from: https://www.zonatlas.nl/amsterdam/ontdek-de-zonatlas/.

[62] Zonnescan Brabant Region. [cited: November 2023]; Available from: https://www.zonnescanbrabant.nl/.

[63] Zonatlas. Provincie Noord-Brabant. [cited: November 2023]; Available from:
https://www.zonatlas.nl/provincie-noord-brabant/ontdek-de-zonatlas/.

[64] OsloKommune. Oslo Solkart. [cited: November 2023]; Available from: https://od2.pbe.oslo.kommune.no/solkart/.

[65] Solcellespesialisten. SolKart.no. Solar cell specialist AS 2024 [cited: November 2023]; Available from: https://solkart.no/search/.

[66] System Informacji Prezestrzennej - Wroclaw. [cited: November 2023]; Available from: https://gis.um.wroc.pl/imap/?gpmap=M.

[67] *서울특별시 에너지장치 (Information on solar energy in the metropolitan city of Seoul)*. [cited: November 2024]; Available from: https://energyinfo.seoul.go.kr/solarmap?menu-id=Z080600.

[68] Tetraedersolar. Solaratlas Valladolid. [cited: October 2023]; Available from:
https://solaratlas.es/valladolid/map/.

[69] Stockholms solkarta. [cited: October 2023]; Available from: https://solkartan.miljo.stockholm.no/stockholms-solkarta/.

[70] Linkoping karta. [cited: October 2023]; Available from: http://kartan.linkoping.se/spatialmap?&mapext=184985%206476575%20187593%206477756&layers=theme-bakgrundskarta%20theme-bakgrundskarta-text%20theme-byggaochbo-solkarta-veg&mapheight=842&mapwidth=1853&profile=lkkarta.

[71] Solkartan Norrkoping. [cited: October 2023]; Available from: https://kartor.norrkoping.se/spatialmap?selectorgroups=solkartan&mapext=130781.2%206496688.8726761%20132317.2%206497422.4726761&layers=bk SOLKARTAN%20kommunkart&mapheight=922&mapwidth=1925&profile=solkartan.

[72] G2SOLAIRE. Solar cadastre of Grand Geneva. [cited: September 2023]; Available from: https://apps.sitg-lab.ch/solaire/.

[73] SuisseEnergie. Sonnendach.ch und Sonnenfassade.ch: Berechnung von Potenzialen in Gemeinden. [cited: November 2023]; Available from: https://map.geo.admin.ch/index.html?lang=it&topic=energie&bgLayer=ch.swisstopo.swissimage&layers=ch.bfe.solarenergie-eignung-daecher.ch.bfe.kleinwasserkraftpotentiale.ch.bfe.statistik-wasserkraftanlagen.ch.bfe.abgeltung-wasserkraftnutzung.ch.bfe.solarenergie-eignung-fassaden&layers_opacity=1,1,1,0.75,1&E=2671949.60&N=1183864.86&zoom=0&catalogNodes=2419,2420,2427,2480,2429,2431,2434,2436,2767,2441,3206&layers visibility=true=false=false=false>true.

[74] Mayor of London. [cited: November 2023]; Available from: https://maps.london.gov.uk/lsm/.

[75] Duluth's Solar Suitability Application - Duluth Shines! [cited: November 2023];
Available from: https://maps.umn.edu/DuluthShines/.

[76] Google. Project Sunroof. [cited: December 2023]; Available from: https://sunroof.withgoogle.com/.

[77] D. Li, et al., *An Overview of the Research on the Correlation between Solar Energy Utilization Potential and Spatial Morphology*, Results Eng. (2024) 103444.

[78] E. Saretta, P. Bonomo, F. Frontini, *A calculation method for the BIPV potential of Swiss façades at LOD2.5 in urban areas: A case from Ticino region*, Sol. Energy 195 (2020) 150–165.

[79] SuisseEnergie. [cited: October 2023]; Available from: https://www.svizzeraenergia.ch/.

[80] Cythelia Energy. [cited: November 2023]; Available from: https://www.cythelia.fr/.

[81] MN DNR calculator. Available from: https://www.dnr.state.mn.us/energysmart/why/calculator.html.

[82] A.A. Tehrani, et al., *Predicting solar radiation in the urban area: A data-driven analysis for sustainable city planning using artificial neural networking*, Sustain. Cities Soc. 100 (2024) 105042.

[83] J. Liang, et al., *Solar3D: An open-source tool for estimating solar radiation in urban environments*, ISPRS Int. J. Geo Inf. 9 (9) (2020).

[84] H. Fan, W. Yao, Q. Fu, *Segmentation of Sloped Roofs from Airborne LiDAR Point Clouds Using Ridge-Based Hierarchical Decomposition*, Remote Sens. (Basel) 6 (4) (2014) 3284–3301.

[85] Y. Zhou, et al., *A geographic information system-based large scale visibility assessment tool for multi-criteria photovoltaic planning on urban building roofs*, Renew. Sustain. Energy Rev. 188 (2023) 113885.

[86] M. Reichler, et al., *Semantic segmentation of raw multispectral laser scanning data from urban environments with deep neural networks*, ISPRS Open Journal of Photogrammetry and Remote Sensing 12 (2024) 100061.
[87] M. Oytun, G. Atasoy, *Effect of Terrestrial Laser Scanning (TLS) parameters on the accuracy of crack measurement in building materials*, Autom. Constr. 144 (2022) 104590.

[88] T. Soha, V. Sugár, B. Hartmann, *City-scale analysis of PV potential and visibility in heritage environment using GIS and LiDAR*, Energ. Buildings 311 (2024) 114124.

[89] Y. Zhou, et al., *A geographic information system-based large scale visibility assessment tool for multi-criteria photovoltaic planning on urban building roofs*, Renew. Sustain. Energy Rev. 188 (2023).

[90] *Solar register of Tokyo*. [cited: February 2024]; Available from: https://tokyosolar.netmap.jp/map/index_map.html.

[91] G. Desthieux, et al., *Solar potential on facades at urban scale: an integrated approach combining solar and digital building modelling*, J. Phys. Conf. Ser. 2600 (4) (2023) 042004.

[92] Bonomo, P., et al., bFAST: A Methodology for Assessing the Solar Potential of Façades in Existing Building Stocks. 2018.

[93] A. Duran, C. Waibel, A. Schlueter, *Estimating surface utilization factors for BIPV applications using pix2pix on street captured façade images*, J. Phys. Conf. Ser. 2600 (4) (2023) 042005.

[94] *Confederazione Svizzera - geo.admin.ch*. [cited: October 2023]; Available from: https://map.geo.admin.ch/#/map?lang=it&center=2660000,1190000&z=1&bgLayer=ch.swisstopo.pixelkarte-farbe&topic=ech&swisssearch=Solare+Einstrahlung+horizontal&layers=ch.swisstopo.zeitreihen@year=1864,f:ch.bfs.gebaeude_wohnungs_register,f:ch.bav.haltestellen-oev,f:ch.swisstopo.swisstlm3d-wanderwege,f:ch.astra.wanderland-sperrungen_unleitungen,f:ch.bfe.solarenergie-einstrahlung_0Grad.

[95] United Nations (UN). *General Assembly, Resolution 72/229, Culture and Sustainable Development, Work of the Statistical Commission pertaining to the 2030 Agenda for Sustainable Development*.

*Sustainable Development (A/RES/71/313 Archived 28 November 2020 at the Wayback Machine)*.

[96] F. Biermann, T. Hickmann, C.-A. Sénit, *The Political Impact of the Sustainable Development Goals, Transforming Governance through Global Goals?* (2022).

[97] Directorate-General for Research and Innovation (European Commission). *100 climate-neutral cities by 2030 - by and for the citizens*. 2020.

[98] A.O.M. Maka, T. Ghalut, E. Elsaye, *The pathway towards decarbonisation and net-zero emissions by 2050: The role of solar energy technology*, Green Technol. Sustainability 2 (3) (2024) 100107.

[99] G. Koster, W. van Sark, B. Ricker, *Solar potential for social benefit: Maps to sustainably address energy poverty utilizing open spatial data in data poor settings*, Energy Sustain. Dev. 80 (2024) 101453.

[100] T.D. Heeten, et al., *Understanding the present and the future electricity needs: Consequences for design of future Solar Home Systems for off-grid rural electrification*. 2017 International Conference on the Domestic Use of Energy (DUE), 2017.

[101] B. Bartolucci, F. Frasca, C. Bertolin, LCA- and nZER-based methodology for identifying optimal low environmental impact interventions for existing buildings, Energy Sustain. Dev. 82 (2024) 101543.

[102] A. van der Heide, et al., *Towards a Successful Re-Use of Decommissioned Photovoltaic Modules*. 30 (8) (2021) 910-920.

[103] O.B. Adegun, O.O. Olusoga, E.C. Mbuya, *Prospects and problems of vertical greening within low-income urban settings in sub-Saharan Africa*, J. Urban Ecol. 8 (1) (2022).

[104] O. Ogut, J.N. Tzortzi, C. Bertolin, *Creating a roadmap to forecast future directions in vertical green structures as a climate change mitigation strategy: a critical review of technology-driven applications*, Sustainability 16 (2024), https://doi.org/10.3390/su16114543.