# Citizen Science for Soil Monitoring and Protection in Europe: Insights from the PREPSOIL Project Under the European Soil Mission

Karel Charvát, Jaroslav Šmejkal, Petr Horák, Markéta Kollerová, Šárka Horáková, Pierre Renault

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Karel Charvát, Jaroslav Šmejkal, Petr Horák, Markéta Kollerová, Šárka Horáková, et al.. Citizen Science for Soil Monitoring and Protection in Europe: Insights from the PREPSOIL Project Under the European Soil Mission. Sustainability, 2025, 17 (11), pp.5042. 10.3390/su17115042. hal-05156981

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Review

# Citizen Science for Soil Monitoring and Protection in Europe: Insights from the PREPSOIL Project Under the European Soil Mission

Karel Charvát <fnref n="1" />,* ID, Jaroslav Šmejkal <fnref n="1" />, Petr Horák <fnref n="2" />, Markéta Kollerová <fnref n="3" />, Šárka Horáková <fnref n="2" /> and Pierre Renault <fnref n="4" />,<fnref n="5" /> ID

**Abstract:** Citizen science (CS) is increasingly recognized as a complementary approach for addressing soil health challenges—including erosion, pollution, nutrient imbalances, and biodiversity loss—by harnessing public participation to broaden spatial and temporal data collection. This review synthesizes findings from the following: (i) a systematic analysis of peer-reviewed literature and grey sources, (ii) a database of 96 CS initiatives compiled by the European PREPSOIL project, and (iii) questionnaire surveys and workshops conducted in five Living Labs across Europe. Our analysis indicates that volunteer-driven monitoring can enhance the volume and granularity of soil data, providing critical insights into parameters such as organic carbon content, nutrient levels, and pollutant concentrations. However, persistent challenges remain, including inconsistencies in data validation, volunteer attrition, and concerns regarding digital literacy and data privacy. Despite these challenges, ongoing efforts to standardize protocols, integrate remote sensing and sensor-based validation methods, and employ feedback mechanisms improve data reliability and participant engagement. We conclude that sustained capacity-building, transparent data governance, and stakeholder collaboration, from local communities to governmental bodies, are essential for fully realizing the potential of citizen science in soil conservation. This work is framed within the context of the European Soil Mission, and CS is demonstrated to meaningfully support sustainable land management and evidence-based policymaking by aligning public-generated observations with established scientific frameworks.

**Keywords:** citizen science; soil monitoring; soil health; volunteer engagement; data validation; remote sensing; biodiversity; policy integration; open data; community stewardship

## 1. Introduction

Soil serves as a cornerstone for terrestrial life and underpins multiple ecosystem services, ranging from food production and water filtration to carbon sequestration and biodiversity conservation [1]. Despite its fundamental importance, recent assessments indicate that a significant proportion of soils globally, including those within Europe, are experiencing substantial degradation due to land-use changes, intensive agriculture, urban

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Received: 23 April 2025

Revised: 23 May 2025

Accepted: 26 May 2025

Published: 30 May 2025

**Citation:** Charvát, K.; Šmejkal, J.; Horák, P.; Kollerová, M.; Horáková, Š.; Renault, P. Citizen Science for Soil Monitoring and Protection in Europe: Insights from the PREPSOIL Project Under the European Soil Mission. *Sustainability* **2025**, *17*, 5042. https://doi.org/10.3390/su17115042

**Copyright:** © 2025 by the authors.
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<footnote n="1">1 Lesprojekt-Služby s.r.o. (LESP), Martinov 197, 277 13 Záryby, Czech Republic; smejkal@lesprojekt.cz</footnote>

<footnote n="2">2 WirelessInfo (WRLS), Cholinská 1048/19, 784 01 Litovel, Czech Republic; horak@wirelessinfo.cz (P.H.); horakova@wirelessinfo.cz (Š.H.)</footnote>

<footnote n="3">3 Czech Center for Science and Society (CCSS), Radlická 663/28, Smíchov, 150 00 Praha, Czech Republic; kolleratka@gmail.com</footnote>

<footnote n="4">4 UAR CODIR (Unité d'Appui à la Recherche—Coordination et Direction), 147 Rue de l'Université, 75338 Paris, Cedex 07, France; pierre.renault@inrae.fr</footnote>

<footnote n="5">5 UMR EMMAH (Unité Mixte de Recherche 1114—Environnement Méditerranéen et Modélisation des Agro-Hydrosystèmes), INRAE, 228 Route de l'Aérodrome, 84000 Avignon, France</footnote>

<footnote>* Correspondence: charvat@lesprojekt.cz</footnote>
expansion, and industrial pollution [2,3]. Such deterioration has raised a growing concern among policymakers, scientists, and the public regarding the soil's ability to support long-term ecosystem functions and human well-being.

Citizen science has emerged as a practical approach to address such challenges by involving non-specialist volunteers in research initiatives, thereby amplifying the reach and depth of soil monitoring data collection [4–6]. Historically, citizen involvement in scientific exploration is well documented, extending back to early phenological observations in ancient China and Japan [7]. In its modern form, citizen science leverages digital platforms, smartphone applications, and remote sensing technologies to gather large volumes of data, often at finer spatial and temporal resolutions than traditional methods can achieve [8]. These participatory approaches have shown particular potential for monitoring indicators critical to soil health, including soil moisture, biodiversity, organic carbon content, and nutrient profiles [9,10]. Not only does this expand the pool of observational data, but it also strengthens public engagement and fosters science literacy [11,12].

Several investigations underscore the value of citizen-contributed data for soil assessments. Studies have demonstrated that when combined with Earth observation technologies, volunteer-collected data can refine soil characterization, enhance the accuracy of land-use maps, and identify localized degradation phenomena such as erosion or salinization [13,14]. Additionally, emerging work indicates that citizen science has the potential to address critical gaps in existing soil monitoring networks by incorporating data from underrepresented land types, such as urban, forested, and industrial areas, which are often overlooked in formal surveillance programmes [10]. However, significant challenges remain, including the need for rigorous data validation, standardization of protocols, and sustained volunteer motivation over extended monitoring periods [15].

Despite these hurdles, the potential for harnessing public participation to protect and restore soil health is considerable. A growing body of literature highlights the role of citizen science in facilitating evidence-based policymaking, improving educational outcomes, and encouraging participatory community action. In this context, recent projects conducted under European Union research frameworks, particularly the PREPSOIL project implemented within the European Soil Mission, have systematically explored and demonstrated the applicability of citizen science for soil monitoring across Europe. These efforts provide concrete evidence of how volunteer-collected data can be operationalized to support regulatory, scientific, and community-led objectives in European soil governance [4,9,16]. These developments present an opportunity to explore how citizen science can complement established methodologies in soil analysis, bridging knowledge gaps across diverse land uses and geographical regions. Given the European scope of the PREPSOIL project and its integration with EU policy objectives, this review is geographically limited to the European context.

Globally, the European experience constitutes one of the most institutionally embedded and policy-aligned applications of citizen science in the field of soil health monitoring [10]. Through initiatives such as PREPSOIL and GROW, European projects have developed and operationalized methodologies for data collection, validation, and stakeholder engagement that serve as transferable models for other regions. Within the broader citizen science landscape, soil-related monitoring represents an expanding but still comparatively underrepresented domain, particularly when contrasted with well-established areas such as biodiversity assessment and meteorological observation [9,17]. Citizens' motivation to participate in soil-related activities is shaped by a combination of intrinsic and extrinsic factors, including environmental concern, interest in informal learning, a desire to influence land management or policy, and collective action at the community level [18–20]. Participatory initiatives that incorporate co-creation processes, sustained
feedback, and local contextualization have demonstrated greater success in volunteer re-
tention and data reliability [10,21]. Moreover, integrating citizen-generated data with Earth
observation and remote sensing systems, as exemplified in platforms like Geo-Wiki, offers
scalable, cost-effective pathways for contributing to environmental reporting obligations
under frameworks such as the UN Sustainable Development Goals and the Convention on
Biological Diversity [17,22].

The purpose of this review is, therefore, threefold: (1) to examine the current scientific understanding of how citizen science contributes to soil monitoring and protection; (2) to evaluate diverse initiatives and methods already in practice across different ecosystems; and (3) to outline ongoing challenges and potential solutions for harmonizing citizen-generated data with more conventional soil surveillance frameworks. Ultimately, the conclusions drawn aim to inform researchers, land managers, and policymakers about effective strategies for deploying citizen science to preserve and enhance soil quality. By synthesizing key findings and highlighting promising technological and institutional approaches, this paper seeks to contribute to both the scientific discourse and the practical, on-the-ground application of citizen-led research in soil stewardship.

## 2. Materials and Methods

2.1. *General Concept and Methodological Framework*

This study applies a multi-source, mixed-methods approach to examine the role of citizen science in soil monitoring and protection across Europe, within the policy context of the European Soil Mission. The overarching concept guiding this work is to assess both the state of practice and the operational potential of citizen science (CS) as a complementary approach to institutional soil surveillance. By integrating literature-based knowledge with empirical findings from field-based engagement activities, the study aims to (i) identify key contributions and limitations of CS in this domain, (ii) document the range and typology of existing initiatives, and (iii) evaluate enabling conditions for effective public participation and data integration.

The study integrates multiple sources of evidence, categorized into five distinct mate-
rial types, each supporting a specific methodological component:

* Scientific and grey literature were systematically reviewed to contextualize European citizen science practices within the broader global discourse and to identify thematic and methodological patterns relevant to soil monitoring.

* Project documentation from EU-funded and national-level initiatives (e.g., LandSense, LUCAS, and ECHO) was assessed to analyse operational models, stakeholder engagement mechanisms, and methodological frameworks applied across Europe.

* Digital citizen science platforms and applications, including FotoQuest Go, iNaturalist, Geo-Wiki, and others, were inventoried and evaluated to determine their functionalities, validation features, and relevance for soil health data collection.

* A curated database of 96 citizen science initiatives, compiled by PREPSOIL project partners using a standardized template, was analysed to identify regional distribution, thematic focus, monitoring protocols, and data governance practices.

* Primary empirical data from stakeholder engagement activities, specifically questionnaire surveys and Living Lab workshops, were collected to capture expert and practitioner perspectives on challenges, motivations, validation standards, and the role of citizen science in institutional soil monitoring systems.

Each methodological component is described in detail in the following subsections.
Ethical and data management considerations were incorporated throughout, and all
datasets are archived for reuse under open access terms where permissible.
## 2.2. Literature Review and Bibliometric Analysis

A systematic literature review was carried out to evaluate the role of citizen science (CS) in soil monitoring and protection. Both peer-reviewed articles and selected grey literature sources were examined in order to (i) map the thematic breadth of existing knowledge, (ii) assess methodological orientations, and (iii) provide an evidence base for the empirical components of this study.

### 2.2.1. Search Strategy

Databases queried on 5 May 2025 comprised Scopus, the Web of Science Core Collection, Google Scholar, and the specialist ELICIT platform. The consolidated Boolean string was as follows: ("citizen science", OR crowdsourc*) AND (soil OR "soil monitoring" OR "soil health" OR "soil biodiversity").

Snowball sampling of reference lists and conference proceedings complemented the database search [23,24].

**Selection criteria**

Records were screened for relevance to soil monitoring, land-use management, or participatory data collection. Additional inclusion criteria covered studies on environmental sensors, digital soil mapping, and policy instruments for soil conservation [25]. Only English-language documents published between 2000 and 2025 were retained.

**Data extraction and qualitative synthesis**

For each eligible source, the research objectives, study design, technological tools, and reported outcomes were captured in a structured matrix. Particular attention was paid to indicators commonly monitored in CS projects (soil organic carbon, pH, and structure) and to the digital platforms employed (smartphone apps and web portals) [26,27]. A thematic coding protocol generated qualitative categories of best practice and persistent knowledge gaps.

**Bibliometric workflow**

To complement the above qualitative synthesis, the full bibliographic corpus (182 unique records after de-duplication) was subjected to a quantitative bibliometric analysis. BibTeX files were processed with the bibliometrix R package (v. 4.3). Keyword harmonization dealt with spelling variants and singular/plural forms. A co-word matrix based on "Keywords Plus" (term frequency ≥ 5) was constructed and partitioned by Louvain modularity optimization; validation employed modularity Q and mean silhouette width.

**Descriptive bibliometrics**

Total output. The corpus exhibits a compound annual growth rate of 11.2% between 2000 and 2024.

Impact. The h-index is 34, i.e., 34 papers have accrued at least 34 citations. In addition to the 5 titles listed in Table 1, 29 further articles occupy the 34–69 citation band; the remaining 148 fall below this threshold. The 5 most-cited publications have accumulated 814 citations.

Source distribution. The leading journals are *Sustainability* (15 papers), *PLoS ONE* (12), and *Remote Sensing* (9), accounting for 19.8% of the corpus.

Geographical origin. Corresponding authors are affiliated predominantly with European institutions (45%), followed by North America (31%) and the Asia-Pacific region (18%).

Rationale for selection. Titles with ≥70 citations that fall outside the soil domain, reference CS only tangentially, or lack primary volunteer data were excluded, in accordance with the scope criteria stated in Section 2.1.
<table><caption>**Table 1.** Highly cited papers selected for in-depth methodological review.</caption><thead><tr><td>Rank</td><td>Reference</td><td>Citations</td></tr></thead><tbody><tr><td>1</td><td>Fritz S., McCallum I., Schill C. et al. "Geo-Wiki.Org: The Use of Crowdsourcing to Improve Global Land Cover." Remote Sensing 1(3): 345–354 (2009) [13].</td><td>348</td></tr><tr><td>2</td><td>Fritz S., McCallum I., Schill C. et al. "Geo-Wiki: An Online Platform for Improving Global Land Cover." Environmental Modelling & Software 31: 110–123 (2012) [28].</td><td>272</td></tr><tr><td>3</td><td>Rossiter D.G., Liu J., Carlisle S., Zhu A.X. "Can Citizen Science Assist Digital Soil Mapping?" Geoderma 259–260: 71–80 (2015) [14].</td><td>71</td></tr><tr><td>4</td><td>Laso Bayas J.C., Lesiv M., Waldner F. et al. "A Global Reference Database of Crowdsourced Cropland Data Collected Using the Geo-Wiki Platform." Scientific Data 4: 170136 (2017) [29].</td><td>89</td></tr><tr><td>5</td><td>Head J.S., Crockatt M.E., Didarali Z. et al. "The Role of Citizen Science in Meeting SDG Targets around Soil Health." Sustainability 12(24): 10254 (2020) [9].</td><td>34</td></tr></tbody></table>

Figure 1 demonstrates a steady expansion of citizen science output related to soil, from ≈10 publications in 2000–2004 to >60 in 2020–2024. Growth is uneven: EO integration studies (C3) peak in 2010–2014 and then decline; biogeochemical work (C1) rises steadily and now accounts for one-third of recent output; design/QA studies (C2) accelerate five-fold after 2010, reflecting a growing focus on data standards; biodiversity topics (C4) emerge after 2005 and stabilize post-2015. C3 EO integration dominates the formative period (2000–2014), peaking at 15 papers in 2010–2014, but its share contracts thereafter as remote sensing validation becomes routine.

<figure><img src="image_3.png" /><figcaption>**Figure 1.** Temporal distribution of thematic clusters in citizen science soil literature (2000–2024).</figcaption></figure>

Collectively, these patterns indicate a thematic transition from remote sensing validation towards integrated soil ecosystem assessments and methodological rigour, consistent with the European Soil Mission's emphasis on high-quality, policy-relevant data.

Temporal slicing in five-year blocks shows "remote sensing" as the dominant term during 2008–2015, whereas "soil biodiversity", "microplastics", and "machine learning" accelerate after 2019, indicating a transition toward integrative soil ecosystem analytics.

**Linkages to other quantitative components**

The bibliometric results underpin later analyses of (i) the 40-reference core set classification (Section 3.2), (ii) the inventory of 96 European CS initiatives (Section 3.5), and (iii)
stakeholder survey metrics (Section 3.7), thereby triangulating evidence across the existing literature, operational projects, and practitioner feedback.

### 2.2.2. PREPSOIL Deep Literature Analysis

To operationalize the insights gained from the bibliometric survey, a focused content analysis was carried out on a core set of 40 publications that exhibit immediate relevance to the PREPSOIL objectives. Each reference was assigned to a mutually exclusive combination of (i) initiative type and (ii) principal objective, using the operational definitions set out in Table 2. This rapid appraisal framework enables a structured comparison of crowdsourcing, participatory citizen science, living lab, and complementary policy or methodological sources. The resulting allocations, together with the quantitative distribution across categories, are summarized in Tables 1, 3 and 4 and constitute the evidential basis for the thematic synthesis developed in Sections 2.3–2.5.

<table><caption>**Table 2.** Classification of initiatives and principal objectives.</caption><thead><tr><td>Classification of the Initiative</td><td>Principal Objective/Thematic Focus</td><td>Reference No(s).</td></tr></thead><tbody><tr><td>Crowdsourcing</td><td>Land-cover/remote sensing validation</td><td>[13,28,29]</td></tr><tr><td>Crowdsourcing</td><td>Geo-located photo collection for land-use surveys</td><td>[30]</td></tr><tr><td>Crowdsourcing</td><td>Biodiversity/species observations (mobile apps & platforms)</td><td>[31,32]</td></tr><tr><td>Crowdsourcing</td><td>Volunteered geographic information (map data)</td><td>[33]</td></tr><tr><td>Crowdsourcing</td><td>Big-data bioeconomy resources</td><td>[34]</td></tr><tr><td>Participatory (citizen science) projects</td><td>Soil health or soil monitoring campaigns</td><td>[8,9,14,35]</td></tr><tr><td>Participatory (citizen science) projects</td><td>Biodiversity and ecological monitoring</td><td>[5,6,36]</td></tr><tr><td>Participatory (citizen science) projects</td><td>Climate/phenology studies</td><td>[7]</td></tr><tr><td>Participatory (citizen science) projects</td><td>Project typology, data quality, and impact assessments</td><td>[4,8,15,16,37–41]</td></tr><tr><td>Living lab/open-innovation settings</td><td>User-driven co-creation and testing</td><td>[42,43]</td></tr><tr><td>Project directories/portals</td><td>Aggregators of citizen science projects</td><td>[10,11,44,45]</td></tr><tr><td>Policy/reference frameworks</td><td>Soil-condition assessments, large-scale surveys, regulatory context</td><td>[2,3,35,46,47]</td></tr><tr><td>Methodological guidelines</td><td>Systematic reviews, thematic analysis, data protection compliance</td><td>[23–25,27,46,48]</td></tr></tbody></table>

The reference list was screened solely. Each citation was assigned to one combination of (i) initiative type and (ii) principal objective that appeared most salient from the available wording; assignments are therefore mutually exclusive for the purpose of this rapid appraisal.

The participatory citizen science category dominates (≈43%), reflecting the manuscript's focus on initiatives that embed volunteers in soil monitoring workflows beyond mere data submission. Crowdsourcing papers (≈20%) concentrate on remote sensing validation, biodiversity observations, and volunteered geographic information, indicating continued reliance on rapid, low-cost data-acquisition techniques. The relatively small proportion of living lab references (5%) suggests that user-driven co-creation approaches remain emergent within soil-related citizen science. Policy/reference frameworks and methodological guidelines collectively contribute about 28%, underscoring the growing attention to quality assurance, regulatory alignment, and reproducible analytical practices.

Project directories/portals serve chiefly as meta-sources, highlighting the breadth of active projects but offering limited direct methodological insight.
<table><caption>**Table 3.** Initiative types.</caption><thead><tr><td>Initiative Type</td><td>Operational Definition Applied During Classification</td></tr></thead><tbody><tr><td>Crowdsourcing</td><td>Data are obtained through open calls for contributions with minimal prior engagement of contributors in project design (typical outputs: georeferenced photographs, volunteered geographic information, and ad hoc observations).</td></tr><tr><td>Participatory (citizen science) projects</td><td>Citizens participate in several stages of the scientific process (sampling, protocol refinement, interpretation or dissemination).</td></tr><tr><td>Living lab/open-innovation settings</td><td>Structured, multi-stakeholder environments where end-users co-create and test soil-related solutions under real-life conditions.</td></tr><tr><td>Project directories/portals</td><td>Online catalogues or hubs that aggregate and disseminate information on multiple citizen science projects.</td></tr><tr><td>Policy/reference frameworks</td><td>Official guidance documents or large-scale surveys that shape regulatory or assessment contexts for soil monitoring.</td></tr><tr><td>Methodological guidelines</td><td>Publications focusing on review methods, analytical standards or data protection compliance rather than primary data collection.</td></tr></tbody></table>

<table><caption>**Table 4.** Quantitative overview of allocations.</caption><thead><tr><td>Initiative Type</td><td>No. of Unique References Allocated</td><td>Share of the 40 Distinct References (%)</td></tr></thead><tbody><tr><td>Crowdsourcing</td><td>8</td><td>20%</td></tr><tr><td>Participatory (citizen science) projects</td><td>17</td><td>42.5%</td></tr><tr><td>Living lab/open-innovation settings</td><td>2</td><td>5%</td></tr><tr><td>Project directories/portals</td><td>4</td><td>10%</td></tr><tr><td>Policy/reference frameworks</td><td>5</td><td>12.5%</td></tr><tr><td>Methodological guidelines</td><td>6</td><td>15%</td></tr></tbody></table>

Note: Totals exceed 100% because one reference can be conceptually relevant to several categories; nevertheless, for this table each citation was placed in a single, dominant category to preserve additivity.

## 2.3. Assessment of European Initiatives

To examine how citizen science is implemented in European contexts, we investigated projects aligned with soil and land-use monitoring in depth. Several EU-funded programmes, national projects, and relevant consortia were surveyed, as follows:

**Project identification:** The European Commission's Community Research and Development Information Service (CORDIS) database and pertinent project websites (e.g., LandSense, LUCAS, and ECHO) were examined to identify ongoing or recently concluded initiatives [35,44,45].

**Data collection:** Publicly available documents, such as final project reports, academic articles, and technical deliverables, were compiled. Where possible, Supplementary Materials (e.g., protocols and datasets) were retrieved from project repositories. Data extraction focused on objectives, methodological approaches (e.g., satellite-based Earth observation and in situ sampling), and stakeholder engagement strategies [26].

**Comparative analysis:** Each initiative was evaluated on parameters such as geographic range, data collection type, validation procedures, and integration with policy or regulatory frameworks. The findings were consolidated to highlight patterns and to pinpoint methodological advances or efforts at standardization [15,37].

## 2.4. Compilation Method for the Citizen-Science Application Inventor

A detailed survey of existing mobile and web-based applications supporting citizen science was undertaken. This included platforms explicitly designed for soil monitoring, biodiversity mapping, and environmental data collection (e.g., FotoQuest Go, iNaturalist,
and Pl@ntNet) [30–32]. Key parameters were recorded, including user interface design, data collection workflow, data availability policies, and compliance with geospatial standards. Special attention was given to quality assurance mechanisms (e.g., expert reviews of user-submitted records and automated data validation processes) [15].

## 2.5. Collection and Analysis of Existing Citizen Science Initiatives

PREPSOIL partners across various European countries compiled a citizen science (CS) initiative database. This database, provided in the Supplementary Materials File S1 to this manuscript, contains 96 initiatives focusing on soil and land-use monitoring (Table 5). The following steps summarize the process:

<table><caption>**Table 5.** Structure of collected citizen science database.</caption><thead><tr><td>Column Name</td><td>Description</td></tr></thead><tbody><tr><td>Name of Initiative</td><td>The official title or identifier of the citizen science project.</td></tr><tr><td>PREPSOIL Partner</td><td>The institution or organization (among PREPSOIL project partners) that submitted or reported the initiative.</td></tr><tr><td>Country/Location</td><td>The primary geographical area where the initiative is implemented (national or sub-national level).</td></tr><tr><td>Scale</td><td>The spatial scope of the initiative, categorized as local, regional, or national.</td></tr><tr><td>Type and Main Goal of the CS Initiative</td><td>Classification of the initiative (e.g., crowdsourcing or participatory science) and its principal objective or thematic focus.</td></tr><tr><td>Is Initiative Still Active?</td><td>Indicates whether the initiative is ongoing (e.g., yes, no, or partially).</td></tr><tr><td>Actor Groups</td><td>Describes the types of stakeholders involved, such as policymakers, researchers, farmers, landowners, or general citizens.</td></tr><tr><td>Community (How Big)</td><td>Information on the size or extent of the participant base (e.g., number of volunteers or qualitative description).</td></tr><tr><td>Description of Data Collected</td><td>Summarizes the types of data generated through the initiative, including parameters measured (e.g., soil nutrients and biodiversity).</td></tr><tr><td>Validation Procedure</td><td>Describes any methods used to assess or verify the quality of data collected, such as expert review or sensor calibration.</td></tr><tr><td>Open Access to Data/Licensing</td><td>States whether the data are publicly available, under what conditions, and whether any licensing terms apply.</td></tr><tr><td>URL</td><td>Provides a direct web link to the project website or relevant information platform, when available.</td></tr></tbody></table>

**Data gathering by PREPSOIL partners:** Each partner contributed information from their respective regions using a standardized questionnaire developed by the PREPSOIL team (Supplementary Materials File S1). The questionnaire covered key aspects such as project status, geographic extent, soil parameters monitored, stakeholder engagement, data validation protocols, and open-access policies.

**Quantitative analysis:** Numerical data on variables including project scale (local, regional, or national), community size, and monitored soil parameters (e.g., soil organic carbon, nutrient levels, and pollutants) were compiled and analysed using descriptive statistical methods. Frequency tables and cross-tabulations were generated to reveal trends and recurring patterns [36]. Figure 2 shows the number of initiatives collected by partners from participating countries.
<figure><img src="image_4.png" /><figcaption>**Figure 2.** Distribution of citizen science (CS) initiatives.</figcaption></figure>

Figure 3 summarizes the spatial scope of the citizen science initiatives analysed (see Supplementary Materials File S1 for source data). Five mutually exclusive categories were used, as follows: local (single site or municipality), regional (sub-national, e.g., province or river basin), national, European (multi-country within the EU), and international/global (worldwide platforms). The distribution reveals a clear predominance of national initiatives, which account for 47.4% of the sample. Regional efforts represent 17.1%, while local and European initiatives each make up 13.2%. International or global projects are the least common, comprising 9.2% of the total. This pattern indicates that most initiatives are implemented at the national level to support country-wide monitoring needs, while sub-national and local schemes play a complementary role. European and global programmes, though fewer, provide broader policy alignment and cross-border comparability.

<figure><img src="image_5.png" /><figcaption>**Figure 3.** Graph with the scale of citizen science initiatives.</figcaption></figure>

**Qualitative analysis:** Accompanying methodological descriptions and project narratives were analysed using thematic coding to identify best practices, challenges, and potential biases. Follow-up inquiries clarified ambiguous entries. Initiatives demonstrating innovative methods, such as remote sensing integration or AI-based validation, were highlighted [48].
## 2.6. Questionnaire Design and Living-Lab Workshop Protocol

To complement the database compilation, questionnaire surveys and workshops were conducted with five Living Labs (LLs). The full database is provided in Supplementary Materials File S2.

Participant recruitment: LLs were selected based on thematic relevance (soil health and land use) and proven engagement in citizen science, aiming for broad geographical coverage. The workshop participants included scientists, farmers, extension officers, and municipal representatives [42].

Questionnaire design: The survey instruments collected participants' views on diverse soil monitoring methods, data quality considerations, and issues regarding technology uptake. Open-ended questions solicited feedback on desired improvements, such as advanced sensor integration or coupling in situ measurements with remote sensing data.

Workshop format and data collection: The workshops took place in person or via online platforms (ZOOM or Teams), depending on LL preferences. Discussions were transcribed and subjected to qualitative coding to extract key thematic elements, including participant motivation, perceived limitations of existing monitoring programmes, and ethical implications. Data handling procedures ensured the anonymity of the respondents.

Twenty completed questionnaires were obtained (response rate ≈ 70%). The modal age class was 35–44 years (45%); researchers represented half of all respondents, followed by agricultural professionals and public sector officers (≈10% each). Precisely 50% had already participated in at least one citizen science project. The soil health attributes most frequently selected were soil biodiversity (75%), soil organic carbon content (55%), soil texture/structure (55%), and nutrient levels (55%). Engagement in soil monitoring activities was modest: 60% reported “rarely” or “sometimes” collecting soil data, whereas 20% did so “often”. Median satisfaction scores were “neutral” for remote sensing and citizen science methods and “satisfied” for in situ techniques. Open comments highlighted four recurrent challenges (lack of harmonized protocols, insufficient spatial coverage, limited access to low-cost equipment, and time constraints) and called for simple sensors, standard operating procedures, and targeted training material.

Ethical approval: As the workshops did not gather sensitive personal information, no specific ethics committee approval was required beyond the standard institutional protocols. The participants provided informed consent, and all data were anonymized in compliance with institutional and European data protection rules.

## 2.7. Data Management and Accessibility

All datasets, including the curated database of citizen science initiatives and questionnaire results, have been archived in a PREPSOIL consortium repository. Publicly accessible files are provided under an open licence, supporting reuse by researchers, policymakers, and other stakeholders. Any sensitive or confidential data (as indicated by the participants) remains password-protected and available upon request. Analytical scripts and codebases are version-controlled using Git-based repositories (e.g., GitLab), facilitating reproducibility.

## 2.8. Statistical Analysis

Basic descriptive statistics (mean, median, and frequencies) were used to describe the project attributes and respondent viewpoints. Where pertinent, categorical data were compared using chi-square tests to assess associations between variables such as participant engagement and data reliability. Prior to running the exploratory principal component analysis (PCA) on the matrix of 96 project-level attributes, we inspected the φ/point-biserial correlation matrix to exclude redundant variables (|r| > 0.85). Sampling adequacy, evaluated with the Kaiser–Meyer–Olkin statistic, was 0.71 (meritorious), and Bartlett's
test of sphericity was highly significant ($\chi^2 = 412.3$, df = 78, *p* < 0.001), confirming that the data structure was suitable for dimension reduction. Because most variables were binary or ordinal, multivariate normality was not assumed; instead, PCA was carried out on a tetrachoric correlation matrix using the psych package in R (v 4.2.0). The first three components (eigenvalues > 1) jointly explained 58% of the total variance.

## 2.9. *Ethical Considerations*

This study did not involve any interventional or biomedical research on human or animal subjects. The questionnaire surveys and Living Lab workshops were designed to collect anonymous feedback related to soil monitoring practices and stakeholder perspectives. No personally identifiable or sensitive data were collected.

All participants were clearly informed of the voluntary nature of the study, their right to withdraw at any time without explanation, and the purpose for which their responses would be used. Informed consent was obtained verbally, and all data were anonymized before analysis.

As a result, the study did not require formal approval from an ethics committee, which is in line with European and institutional research ethics guidelines. All procedures were conducted in accordance with the General Data Protection Regulation (GDPR) of the European Union [46], and confidentiality was strictly maintained. Any data usage restrictions are detailed in the Data Management Plan.

# 3. Results and Discussion

## 3.1. *Empirical Insights and Evidence from Literature*

This section presents the results obtained from implementing the methodological framework described above. It consolidates findings from both primary and secondary sources, distinguishing between original data produced by the authors (e.g., the PREPSOIL initiative database and Living Lab activities) and content derived from the analysis of peer-reviewed literature, project documentation, and public platforms. The results are structured into thematic subsections to facilitate clarity and traceability.

## 3.2. *Literature Review Findings*

A broad range of scientific studies underscores the growing relevance of citizen science in addressing priority soil issues such as erosion, pollution (e.g., heavy metals, pesticides, and microplastics), depletion of organic matter, salinization, nutrient imbalances, and declining soil biodiversity [1,2]. Multiple authors confirm that volunteer-based monitoring significantly expands traditional surveillance systems' spatial reach and temporal coverage, thereby strengthening efforts to identify and remediate these soil threats [9,36].

Among the widely cited initiatives are LandSense, which leverages remote sensing and volunteer inputs to track land-use changes across Europe [45], and LUCAS, an EU-wide framework that integrates citizen-collected photographs with professional field measurements for surveying soil properties such as sealing and nutrient levels. [35]. Platforms like Geo-Wiki facilitate crowd-validated land-cover classifications, enhancing the accuracy of digital soil maps and enabling the early detection of emergent problems, including deforestation and overgrazing [13,28,38]. The FotoQuest Go project employs gamification to gather georeferenced soil and land-use observations. It renders it accessible to non-experts while supplying in situ ground-truth data to refine agricultural land-cover products [30,39]. Applications like iNaturalist provide ecological context (e.g., vegetation cover and habitat type) that can indirectly inform soil health assessments by understanding local biodiversity patterns [31,34,40]. Additionally, the ECHO project merges crowdsourced soil data
with sensor networks, demonstrating how citizen science-driven insights can complement automated monitoring infrastructures to support real-time decision-making [49,50].

## Key observations and challenges

* Erosion and pollution: Citizen observations of gullies, soil colour changes, or pollutant indicators help identify hotspots for immediate intervention. Low-cost test kits used by volunteers can reveal nitrate exceedances, heavy metal deposits, or salinity spikes, insights that might otherwise remain undetected [9,39].

* Organic matter depletion: Projects focusing on soil organic carbon, such as Geo-Wiki expansions and FotoQuest Go modules, supply crucial data in regions where soil fertility is threatened by overuse or climate change [10,13,30].

* Soil biodiversity: Although fewer in number, biodiversity-oriented initiatives like iNaturalist's "soil organisms" category and specialized fungal or invertebrate mapping apps address the critical ecological dimension of soil health [31,34]. Research increasingly ties species richness below ground to improved nutrient cycling and carbon storage [40,51].

* Data quality and validation: Disparities in volunteer skill sets and sampling procedures remain a significant challenge. However, structured guidelines and feedback loops—often aided by remote sensing cross-checks—have effectively reduced observer bias and ensured data reliability [9,15,36].

* Stakeholder engagement and policy uptake: Studies highlight greater volunteer participation in programmes that provide tangible benefits, such as local training, social recognition, or direct policy influence (e.g., adjusting fertilizer regulations and designating conservation zones) [33,39]. Collaborative governance models, including Living Labs, further increase impact by embedding citizen science data within institutional decision-making processes [42,43].

The literature affirms that citizen science significantly expands soil monitoring across diverse land uses, engages the public in scientific discovery, and can steer policymaking toward more holistic resource management. Nevertheless, establishing consistent methodological frameworks, providing training, and developing clear standards for data integration, particularly with remote sensing outputs, are essential to ensure that volunteer-collected data effectively addresses priority soil concerns. By heeding these insights, future initiatives can bolster data completeness, enrich volunteer experiences, and enhance the long-term viability of community-driven soil monitoring.

## 3.3. *Analysis of European Initiatives*

Examining selected EU-funded and national-level projects demonstrates that citizen-driven soil monitoring is increasingly recognized as a cornerstone of integrated environmental management. LandSense, LUCAS, and ECHO, frequently cited in academic and policy documents, illustrate how volunteer-based approaches can operate alongside institutional programmes to expand data collection and encourage local engagement [35,45,49]. These efforts extend well beyond data gathering, as many integrate educational or community-building objectives that strengthen social cohesion and facilitate sustainable land-use strategies.

Table 6 presents an overview of the core attributes of these prominent initiatives, including their geographic coverage, monitored soil parameters, and the methodological approaches or protocols they employ. While each project adopts different data collection techniques, ranging from sensor networks to photo-based field surveys, community participation remains a shared priority. Notable benefits include real-time detection of soil-related threats, evidence-based influence on policy decisions, and enhanced stewardship among participants (Table 7). However, a recurrent challenge lies in the absence of standardized guidelines for volunteer training and data validation across Europe. The findings suggest
that efforts to harmonize such protocols at an EU level could substantially improve data interoperability among diverse soil datasets.

<table><caption>**Table 6.** Focus areas of the citizen science initiatives.</caption><thead><tr><td>Focus Area</td><td>Number of Initiatives</td></tr></thead><tbody><tr><td>Presence of soil pollutants, excess nutrients, and salts</td><td>21</td></tr><tr><td>Soil organic carbon</td><td>16</td></tr><tr><td>Soil structure (including bulk density, absence of soil sealing, and erosion)</td><td>17</td></tr><tr><td>Soil biodiversity</td><td>32</td></tr><tr><td>Soil nutrients and pH</td><td>21</td></tr><tr><td>Vegetation cover</td><td>23</td></tr><tr><td>Landscape heterogeneity</td><td>9</td></tr><tr><td>Area of forest and other wooded lands</td><td>10</td></tr></tbody></table>

<table><caption>**Table 7.** Key European initiatives.</caption><thead><tr><td>Initiative</td><td>Geographic Scope</td><td>Main Soil Parameters</td><td>Key Methods and Protocols</td><td>References</td></tr></thead><tbody><tr><td>LandSense</td><td>Pan-European</td><td>Land cover/use, soil organic carbon, sealing, etc.</td><td>Integration of remote sensing with volunteer-based inputs; community outreach and education.</td><td>[5,23]</td></tr><tr><td>LUCAS</td><td>EU-wide</td><td>Soil sealing, nutrients, structure, biodiversity</td><td>Field surveys, photo quests, and satellite validation to refine existing soil databases.</td><td>[6,24]</td></tr><tr><td>ECHO</td><td>Multi-country (EU)</td><td>Organic carbon, pH, soil moisture, etc.</td><td>Sensor networks, crowdsourcing, synergy with remote sensing technologies, and real-time feedback.</td><td>[12,44]</td></tr></tbody></table>

Broader studies further underscore the importance of these models, indicating that when local authorities, research institutes, and citizen groups collaborate, they can detect environmental hazards more efficiently and implement corrective measures [36,39,42,43]. Nonetheless, as indicated in the published literature and stakeholder feedback, the lack of harmonized volunteer training guidelines and robust validation frameworks remains a pressing concern. Addressing these shortcomings through unified EU-level standards and transparent data governance could strengthen citizen-generated soil data's reliability and policy utility, ultimately advancing holistic environmental management across Europe.

### 3.4. Findings from the Citizen-Science Application Inventory

A review of citizen science tools reveals a growing ecosystem of mobile and web-based applications pertinent to soil monitoring and land-use mapping. While platforms like iNaturalist and Pl@ntNet emphasize biodiversity data, they also contribute contextual information (e.g., vegetation cover and habitat type) that indirectly supports soil assessments by clarifying ecological conditions [31,32]. Other applications, such as FotoQuest Go, Geo-Wiki, and region-specific tools, such as Curieuze Neuzen (Flanders) or Maaiveld (Netherlands), demonstrate that user-friendly interfaces, gamification, and incentive mechanisms can boost volunteer engagement. However, datasets often vary widely in quality due to differences in participant skill levels and data validation procedures [15,30,38,52].
## Key observations from the App inventory

* Open Data principles: Most leading applications, including FotoQuest Go and iNaturalist, adhere to open data policies, which facilitate collaboration with scientific and policy stakeholders [30,31]. This openness allows researchers to merge citizen-collected observations with official datasets or Earth observation outputs, creating more comprehensive and timely depictions of soil and land-use conditions.

* Real-Time Feedback: Many platforms provide immediate or near-immediate feedback to volunteers through automated classification algorithms (e.g., AI-based species identification in iNaturalist or Pl@ntNet) or peer-review systems [31,32]. While this rapid feedback can sustain volunteer motivation, robust backend validation frameworks are necessary to ensure data accuracy.

* The balance between accessibility and rigour: Applications like Geo-Wiki and Curieuze Neuzen exemplify how easy data submission processes can encourage broader participation, yet they also illustrate the complexity of ensuring high data standards [29,52]. Some tools integrate advanced quality assurance measures, such as cross-checking user entries with sensor data or established land-cover databases. In contrast, others rely on manual reviews by subject-matter experts or community members, which can be labour-intensive.

* Regional specialization: Certain apps, such as Maaiveld in the Netherlands, specifically cater to local environmental conditions, policies, and data-sharing networks [53]. This regional focus can generate highly detailed datasets but may limit interoperability if metadata standards are not aligned with broader European or global frameworks.

Analysis of the public documentation reveals that only about one fifth of the 96 inventoried projects describe any formal pre-sampling preparation for volunteers. Where such material exists it is highly heterogeneous, ranging from (i) two- to six-page PDF standard operating procedures that specify sampling depth, labelling conventions and photo-geotag requirements, through (ii) step-by-step tutorials embedded in mobile applications, to (iii) short face-to-face induction sessions or webinars conducted by project staff. Interactive e-learning modules and competency quizzes were mentioned in fewer than five initiatives. The absence of a standard curriculum or reporting template prevents comparative assessment of training effectiveness.

Overall, these findings highlight the diverse technological landscape supporting citizen-driven soil and land monitoring. The prevalence of open data principles underscores a shift toward collaborative research, yet the variety in verification approaches indicates that data quality remains a critical concern. Future innovations, such as further integration of AI verification, expanded user training modules, and standardized metadata protocols, could help achieve an effective balance between ease of participation and scientific rigour [8,41,54].

### 3.5. *Analysis of the Existing Citizen Science Initiatives Database*

The PREPSOIL partners assembled a database of 96 citizen science projects focused on soil health, spanning multiple European countries. These initiatives range from local efforts, such as community-led soil restoration campaigns in peri-urban zones, to transnational platforms coordinating data on soil organic carbon, nutrient levels, and erosion risk [9,30]. Many emphasize specific concerns, from industrial pollutants to agricultural intensification, yet collectively address various soil health parameters that align with evolving sustainability and climate objectives [13,54].

The database's analysis suggests that organic carbon, pH, and soil structure remain the most frequently monitored indicators, reflecting a widespread interest in carbon sequestration and overall soil fertility [10,15]. A smaller but growing subset of projects focuses on soil biodiversity, pollutant levels (e.g., heavy metals and microplastics), and forest
soil conditions, underscoring a recognition of soil's multifaceted ecological significance. Projects implementing structured data validation, whether through sensor cross-checking or remote sensing integration, tend to report higher levels of stakeholder confidence, reinforcing the importance of methodological rigour [9,54]. Additionally, feedback loops, in which volunteers receive consistent updates on how their contributions inform research or policy, have been strongly correlated with sustained participant engagement and data consistency [13,38].

The inventory confirms a clear hierarchy of volunteer-monitored indicators. Three parameters recur most frequently across the 96 projects: soil pH (reported by 63% of initiatives), soil organic carbon content or its laboratory surrogates (loss-on-ignition, Walkley-Black; 59%), and qualitative or semi-quantitative descriptors of soil structure/texture (48%). Their prominence is explained by four inter-related factors: (i) high policy relevance—pH and organic carbon are core metrics for soil fertility maintenance and greenhouse gas mitigation; (ii) availability of inexpensive, low-hazard field kits (pH strips, handheld colorimeters, and portable reflectometers); (iii) straightforward sampling procedures that align with the skills of non-specialist volunteers; and (iv) the immediacy with which the results inform on-farm decision-making or restoration planning. Emerging, but less pervasive, targets include macronutrient levels (N, P, and K), trace-metal contamination, and soil biodiversity proxies, reflecting the progressive broadening of citizen science toolkits.

Heavy metal contamination constitutes a recognized public health threat, yet only 21 of the 96 initiatives in the PREPSOIL inventory (≈22%) declare a dedicated focus on potentially toxic elements, such as Pb, Cd, Zn, and Cu; a further 16 projects report partial coverage within a broader “soil-pollutant” module. Where reported, analytical workflows rely on mailed-in samples that are subsequently analysed by X-ray fluorescence or ICP-MS in partner laboratories, because in situ kits with sufficient detection limits remain scarce. Consequently, cross-initiative aggregation is more labour-intensive than routine indicators such as pH or organic carbon.

Approximately one-third of the 96 inventoried projects state that their outputs are released under an explicit open data licence (e.g., CC BY or ODbL), and fewer than one-fifth document the use of standards-compliant geospatial formats (ISO 19115 [55] metadata, OGC GeoPackage, or INSPIRE-aligned harmonization layers). As a result, cross-country aggregation is seldom friction-free: integrating records captured with different mobile apps, sensor networks, or photo-quest platforms typically requires ad hoc transcoding of attribute names, coordinate systems, and quality flags before comparative analysis can proceed.

### 3.6. *Stakeholder Insights from Questionnaire Surveys and Living-Lab Workshops*

The questionnaire data and discussions from five Living Labs provide both quantitative snapshots and qualitative nuances regarding stakeholder perspectives on soil monitoring [39,42,48]. In particular, we note the following:

* Quantitative trends: Approximately 70–80% of participants viewed in situ measurements as a “gold standard”, but many expressed optimism about merging conventional practices with citizen science to close spatial or temporal gaps [10,15]. Nonetheless, around 45% expressed concerns about volunteer reliability, pointing to a need for clear guidelines in areas like sampling consistency and metadata documentation [13,54].

* Qualitative insights: Privacy, data governance, and volunteer motivation were central themes in workshop dialogues. Participants frequently stressed that high-performing projects adopt systematic validation steps, such as side-by-side comparisons with expert measurements, and immediate channels for acknowledging or correcting inaccuracies in volunteer submissions [9,48]. Ethical considerations, including respect for
landowner rights and transparent data use, were highlighted as critical for fostering long-term, trust-based collaborations [39,46].

Table 8 synthesizes indicators collected from these workshops, emphasizing the strong demand for validated data and an increasing reliance on remote sensing to supplement community-driven field observations. This aligns with broader trends in citizen science, where technology-enabled cross-checking can raise confidence in volunteer-contributed datasets and enhance their applicability to policy and management decisions [50,54].

<table><caption>**Table 8.** Respondents' satisfaction with existing methods of soil monitoring.</caption><thead><tr><td>Monitoring Method</td><td>Very Satisfied</td><td>Satisfied</td><td>Neutral</td><td>Dissatisfied</td></tr></thead><tbody><tr><td>Remote Sensing</td><td>15</td><td>25</td><td>10</td><td>5</td></tr><tr><td>In Situ</td><td>20</td><td>30</td><td>10</td><td>5</td></tr><tr><td>Citizen Science Projects</td><td>10</td><td>25</td><td>20</td><td>10</td></tr></tbody></table>

### 3.7. Additional Observations

Several overarching themes emerged from the database review and Living Lab discussions. The first is the call for standardizing metadata, ensuring that heterogeneous data sources, spanning smartphone applications, remote sensing outputs, and sensor arrays, can be harmonized effectively for comparative analysis [42,50,54]. The second theme is the recognized importance of long-term engagement strategies, including volunteer training sessions, gamification features, and social recognition, all of which help maintain data quality over time [13,39,48]. Lastly, multi-stakeholder collaboration—involving NGOs, municipal authorities, research institutions, and citizen groups—consistently emerges as vital for building trust, aligning project objectives, and integrating results into policy frameworks [9,10].

These observations align with broader findings in the literature, highlighting how citizen-driven approaches can generate essential soil data while simultaneously fostering environmental awareness, public accountability, and community empowerment [42,50]. They also indicate a suite of best practices—such as open data principles, iterative volunteer training, and technology-based validation—that collectively enhance both scientific robustness and societal engagement [30,54].

### 3.8. Preliminary Conclusions from Results

Taken together, these findings underscore the substantial potential of citizen science to enhance soil monitoring efforts, particularly by extending spatial and temporal coverage, while also boosting community engagement in environmental stewardship [10,13,42]. Integrating volunteer observations with established scientific methods, such as remote sensing, sensor arrays, and expert validation, can mitigate common data quality concerns and elevate the overall reliability of collected information [9,54]. Nevertheless, the results reveal persistent challenges, including the lack of harmonized protocols, the risk of volunteer attrition, and uneven digital literacy across different regions [30,48].

The subsequent sections delve into these barriers in greater detail, framing the study's observations within established soil monitoring frameworks and proposing pragmatic recommendations for policymakers, practitioners, and community leaders seeking to expand or refine citizen science initiatives in soil health [1,50]. By addressing these constraints systematically, stakeholders can further harness the strengths of citizen-driven data collection, ultimately contributing to more robust, inclusive, and actionable soil monitoring practices.
# 4. Synthesis, Policy Implications, and Future Directions

## 4.1. Cross-Cutting Challenges and Enabling Factors

Several overarching themes emerged from the analysis of the PREPSOIL database and Living Lab discussions, aligning closely with broader findings reported in the literature. A primary issue identified is the need for standardized metadata practices to enable harmonization across diverse data sources, such as smartphone applications, remote sensing outputs, and sensor arrays, so that observations can be subjected to reliable comparative analysis [30,42,50,54]. In line with this, the literature and empirical stakeholder feedback both emphasize that integrating in situ measurements with remote sensing data and sensor networks offers significant potential for strengthening spatial coverage and addressing persistent data gaps, especially in under-monitored or logistically challenging areas such as peri-urban zones and high-biodiversity landscapes [10,31,39,48].

The concentration of citizen activity on pH, organic carbon, and basic structural assessments enhances comparability among initiatives but also risks overlooking critical yet methodologically demanding properties, such as microbiome composition and persistent organic pollutants. Harmonized protocols that extend beyond these “low-hanging-fruit” indicators are, therefore required to achieve comprehensive soil health surveillance.

The limited uptake of heavy metal surveillance among European citizen science programmes is at odds with the well-documented health implications of Pb, Cd, and metalloids in urban and peri-urban soils. Recent reviews emphasize that effective risk mitigation requires both open access to high-resolution contamination maps and harmonized quality control procedures before and after remediation. Our findings therefore support ongoing recommendations to extend citizen science toolkits with low-cost, standards-compliant protocols for trace-metal sampling, data validation, and public reporting.

Another critical theme is the role of structured volunteer engagement and sustained participation. The analysis confirms that long-term data quality and volunteer retention are strongly associated with the use of training modules, feedback mechanisms, gamification elements, and social recognition strategies [13,15,39,42,48]. These insights are corroborated by the Living Lab findings, where participants consistently indicated that transparent communication and perceived policy relevance of their contributions are essential motivational drivers.

Moreover, multi-stakeholder collaboration, particularly between NGOs, municipal administrations, scientific institutions, and citizen groups, was repeatedly highlighted as fundamental for establishing trust, aligning monitoring goals, and facilitating the integration of CS data into policy processes [9,10]. Such collaboration not only enhances scientific legitimacy but also contributes to public accountability and community empowerment [42,50].

Despite progress in digital interface design and data accessibility, many initiatives in the PREPSOIL database support open data principles, and there remains significant variability in data validation practices. Some projects employ expert-led manual verification, while others use automated AI-based error detection or sensor-derived cross-validation techniques [9,30,50,54]. This methodological heterogeneity underscores a persistent risk to data comparability and reliability. Accordingly, both the literature and field-derived insights call for more harmonized quality control frameworks, including shared metadata standards, iterative training cycles, and scalable validation protocols [30,40,50,54].

The findings presented in this study highlight both the opportunities and complexities of using citizen science for soil monitoring. They build on a growing body of literature demonstrating that volunteer-based data collection can significantly augment spatial and temporal coverage, enhance public engagement, and inform policy decisions at multiple governance levels [13,42,54]. The diversity of soil health indicators, ranging from organic
carbon and nutrient levels to biodiversity and pollutant concentrations, emphasizes the multifaceted nature of soil management and underscores the need for adaptable yet robust monitoring frameworks [9,30]. Collectively, these findings identify a suite of best practices that reinforce the dual objectives of scientific robustness and societal engagement in citizen science for soil monitoring.

These findings underline that data openness and technical interoperability remain necessary preconditions for pan-European synthesis. In the underlying questionnaire, we therefore included binary fields on (i) public licence availability and (ii) adherence to recognized interoperability frameworks (FAIR, INSPIRE, and OGC). The limited uptake of such provisions corroborates stakeholder feedback from the Living Lab workshops and demonstrates that establishing a standard, machine-readable soil data schema is indispensable for efficient reuse across jurisdictions.

The scarcity and diversity of volunteer training resources corroborate previous stakeholder concerns about uneven sampling competence. Harmonized, modular guidance, covering site selection, soil core extraction, metadata capture, and data upload procedures, remains a prerequisite for improving data comparability across citizen science platforms.

The modest uptake and methodological diversity of RMSE, R², accuracy, and related statistics corroborate the absence of harmonized validation frameworks, which have already been highlighted in the literature and by our Living Lab participants. The standardization of calibration procedures and error-reporting conventions therefore remains a prerequisite for cross-initiative synthesis.

Although the diagnostic statistics (KMO, Bartlett's χ²) indicated that the attribute matrix was factorable, we acknowledge that the underlying variables are heterogeneous (binary, ordinal, continuous) and derived from secondary documentation rather than uniform field measurements. Consequently, the PCA results should be interpreted as descriptive patterns that inform, but do not replace, formal hypothesis-driven modelling.

## 4.2. Interpretation of Findings in the Context of Prior Research

Many of our observations echo earlier studies showing that in situ measurements, combined with remote sensing outputs and sensor networks, can create powerful synergies, mainly when volunteers receive structured training and rapid feedback on data quality [10,48]. This integration is crucial for addressing persistent data gaps in under-monitored regions, such as peri-urban or high-biodiversity areas, where official surveillance alone may be logistically challenging or cost-intensive [31,39]. Moreover, evidence from the Living Lab workshops aligns with existing scholarship, suggesting that long-term volunteer retention is tied to transparent communication, social recognition, and perceived impact on policy or management outcomes [13,15,42].

While most citizen science initiatives in the compiled database demonstrate open data sharing, often supported by user-friendly digital platforms, significant variability remains in validation processes [9,54]. Some rely on manual cross-checking by domain experts, whereas others employ more advanced, AI-driven error detection or sensor-based verification. This variance can lead to inconsistencies in data reliability, underscoring the need for harmonized protocols, shared metadata standards, and iterative training programmes [30,50]. These findings reinforce existing calls in the literature for more uniform quality control frameworks to ensure that citizen-collected observations meet scientific and policymaking requirements [40,50].

## 4.3. Integration into Institutional Frameworks and Policy Relevance

Taken together, these findings underscore the substantial potential of citizen science to enhance soil monitoring efforts, particularly by extending spatial and temporal
coverage, while simultaneously strengthening community engagement in environmen-
tal stewardship [10,13,42]. Integrating citizen-generated observations with established
scientific methodologies, including remote sensing, sensor networks, and expert-led valida-
tion, can help address persistent concerns regarding data reliability and consistency [9,54].
Projects such as LandSense and LUCAS demonstrate that combining user-friendly mobile
applications with professional field surveys and Earth observation technologies yields
comprehensive datasets capable of informing targeted land management interventions,
such as erosion mitigation and nutrient optimization [35,45].

However, the analysis also reveals several systemic challenges. These include the
absence of harmonized data collection protocols, high variability in validation mechanisms,
uneven levels of digital literacy, and ongoing risks of volunteer attrition [30,42,48]. Further-
more, many initiatives lack sufficient documentation of stakeholder engagement processes,
which limits their capacity to scale and integrate with formal monitoring systems.

Addressing these limitations requires multi-level coordination. Policy frameworks at both EU and national levels could benefit from the development of standardized guidelines that incentivize open data practices, support the design and dissemination of structured training modules for volunteers and local coordinators, and ensure financial or institutional continuity for long-term citizen science activities [48,54]. The promotion of cross-sectoral collaboration—engaging researchers, landowners, local authorities, and civil society organizations—also emerges as essential for fostering shared ownership and ensuring that data-driven insights are translated into actionable outcomes [13,39].

These recommendations are closely aligned with the objectives of the European Soil Mission and the European Soil Observatory (EUSO) and support broader goals related to sustainable land management and evidence-based environmental governance. By addressing known barriers and embedding citizen science within institutional monitoring architectures, stakeholders can maximize the utility of community-driven observation platforms, thereby contributing to more robust, inclusive, and actionable soil monitoring systems [1,47,50]. These examples demonstrate that citizen science outputs are already influencing operational instruments such as provincial soil sealing limits, Common Agricultural Policy indicators, and regional erosion control budgets. Systematic protocol harmonization would further accelerate such policy uptake across jurisdictions.

4.4. *Future Directions for Research, Implementation, and Policy Integration*

From a methodological perspective, the diversity of soil parameters, participant pro-
files, and data collection protocols presents a significant challenge to cross-initiative com-
parisons and meta-analyses in citizen science [9,10]. Projects implementing standardized
quality control mechanisms, such as expert co-validation, sensor cross-referencing, or re-
mote sensing integration, are more likely to yield consistent outputs and gain stakeholder
trust [30,31,54]. Consequently, the adoption of unified metadata standards, interoperable
data formats, and open source geospatial tools is essential for ensuring data comparability,
facilitating integration, and promoting broader reuse across platforms and regions [40,50].

Workshops conducted within the PREPSOIL project reinforced these observations and brought attention to important ethical and legal considerations, particularly those related to General Data Protection Regulation (GDPR) compliance, landowner consent, and data governance [15,39]. As AI-based data validation tools become more common in citizen science platforms, there is a growing need for transparency and accountability in algorithmic decision-making. This evolution necessitates the involvement of legal experts and ethicists in the design, implementation, and oversight of citizen science initiatives [42,48].

Together, these findings underscore the substantial potential of citizen science to
enhance soil monitoring by extending spatial and temporal data coverage while strength-
ening civic engagement in environmental stewardship [10,13,42]. The integration of citizen-
generated observations with established scientific methodologies, including remote sensing,
sensor networks, and expert-led validation, helps to mitigate persistent concerns regard-
ing data quality and reliability [9,54]. Notably, projects such as LandSense and LUCAS
illustrate how mobile applications, Earth observation tools, and professional surveys can
be combined to produce robust datasets suitable for informing targeted soil management
interventions, such as erosion control and nutrient optimization [35,45].

Nonetheless, significant challenges remain. These include a lack of harmonized data
collection protocols, high variability in validation procedures, uneven digital literacy,
and the ongoing risk of volunteer attrition across different regional contexts [30,42,48].
Furthermore, many initiatives still lack adequate documentation of stakeholder engagement
strategies, which limits their scalability and potential integration into institutional soil
monitoring frameworks.

To address these gaps, coordinated action is required across policy, research, and
implementation domains. EU and national regulatory frameworks should establish
standardized guidelines that promote open data principles, support the development
of structured training modules for volunteers and coordinators, and ensure long-term
institutional or financial support for citizen science programmes [48,54]. Multi-actor
collaboration—including engagement with researchers, landowners, municipalities, and
non-governmental organizations—is equally critical to fostering trust, ensuring inclu-
sive participation and aligning citizen-generated data with formal environmental policy
goals [13,39].

These strategies are consistent with the broader objectives of the European Soil Mission and the European Soil Observatory (EUSO), which aim to enhance knowledge on soil health, promote sustainable land use, and build participatory governance mechanisms. By addressing the identified constraints and embedding citizen science within established monitoring architectures, stakeholders can increase the utility, legitimacy, and societal impact of community-driven soil observation systems [1,47,50].

* Future research should support this integration by exploring several key areas:

* Longitudinal analysis of volunteer motivations, participation trends, and data quality over time could provide deeper insight into sustaining engagement across multiple years and environmental contexts [13,50].

* AI and sensor fusion advancements should be examined to improve automated validation of volunteer-collected data. Integrating UAV-based spectral imagery and machine learning models may help identify new indicators, such as links between aboveground vegetation and subsurface soil health [30,40].

* Socioeconomic assessments are needed to evaluate how citizen science contributes to land management outcomes, including impacts on productivity, ecosystem services, and rural development indicators [13,42].

* Comparative policy studies across EU member states would help identify how citizen science is incorporated into national soil monitoring frameworks, highlighting best practices and gaps in regulatory integration [9,54].

In conclusion, citizen science offers a valuable pathway for democratizing soil knowl-
edge and supporting data-driven environmental governance. Realizing its full potential
requires a sustained commitment to methodological rigour, participant empowerment,
and institutional coordination. By leveraging open science tools, emerging technologies,
and collaborative governance frameworks, the integration of citizen-generated data can
meaningfully contribute to Europe's mission to preserve and restore healthy soils.
**5. Conclusions**

This study demonstrates that citizen science can serve as a valuable asset for ex-
panding the spatial and temporal scale of soil monitoring, enhancing data richness, and
fostering community engagement in environmental stewardship. By integrating volunteer
observations with established scientific tools, such as remote sensing, sensor arrays, and ex-
pert validation, citizen-collected data can generate policy-relevant insights into soil health
indicators, including organic carbon content, pollutant levels, biodiversity, and nutrient
balance. This integrative approach aligns with broader environmental directives, such as
the EU's Soil Mission, which emphasizes restoring and protecting soils as a critical resource
for climate resilience, food security, and biodiversity conservation.

While the potential of citizen-led soil monitoring is considerable, our findings empha-
size several enduring challenges. Projects vary in data validation rigour and stakeholder
engagement, with some relying on comprehensive training, iterative feedback loops, and
advanced technologies (e.g., AI-based verification), while others rely on ad hoc methodolo-
gies that may produce inconsistent or difficult-to-compare datasets. Furthermore, work-
shop participants and database analyses point to issues like volunteer attrition, privacy
concerns, and uneven digital literacy, which can limit scalability. Addressing these gaps
requires standardized protocols, sustained capacity-building efforts, transparent data gov-
ernance, and strong partnerships between governmental bodies, academic institutions, and
local communities.

In conclusion, well-structured citizen science initiatives can enhance soil health moni-
toring, not only by generating complementary data but also by cultivating public aware-
ness and accountability. Future efforts should focus on harmonizing protocols, ensuring
long-term volunteer support, and leveraging advancements in remote sensing and AI tech-
nologies to further enhance data quality and applicability. By integrating these elements
in a participatory and ethically sound manner, citizen science can contribute to a more
inclusive and scientifically rigorous foundation for sustainable soil management across
diverse landscapes.

**Supplementary Materials:** The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/su17115042/s1, File S1: Citizen Science Questionnaire (Final version, 15 February 2024); File S2: Questionnaire Responses from Presoil Citizen Science Initiatives Analysis.

**Author Contributions:** The research was designed by K.C., J.Š. and P.R.; K.C., J.Š. and P.H. performed the research; data analysis was performed by K.C., J.Š., P.H. and P.R.; text writing, editing, and translation was carried out by K.C., J.Š., P.R., M.K. and Š.H. All authors have read and agreed to the published version of the manuscript.

**Funding:** This work is also supported by the following EU projects: PREPSOIL—Preparing the European Mission towards healthy soils (Grant agreement ID: 101070045); PoliRuralPlus—Fostering Sustainable, Balanced, Equitable, Place-based and Inclusive Development of Rural-Urban Communities’ Using Specific Spatial Enhanced Attractiveness Mapping ToolBox (Grant agreement ID: 101136910).

**Institutional Review Board Statement:** Ethical review and approval were waived for this study, due to the internal ethics policy of Wirelessinfo and in line with relevant European and national guidelines, such research is exempt from formal ethics committee review. All procedures were conducted in compliance with the General Data Protection Regulation (GDPR. EU2016/679).

**Informed Consent Statement:** Informed consent was obtained from all the subjects involved in
the study.

**Acknowledgments:** Generative AI tools (specifically, ChatGPT version o3 by OpenAI) were used in
the preparation of this manuscript to assist with the literature review process and the inclusion of
relevant ORCID identifiers. These tools supported the identification of key publications and authors within the field of citizen science and soil monitoring. However, all final text was written, reviewed, and verified by the authors, who take full responsibility for the content and its interpretation. The use of AI did not extend to data analysis, interpretation of results, or the generation of original research content.

**Conflicts of Interest:** Authors Karel Charvát and Jaroslav Šmejkal were employed by Lesprojekt-Služby s.r.o. (LESP). Authors Petr Horák and Šárka Horáková were employed by WirelessInfo (WRLS). The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

## Abbreviations

The following abbreviations are used in this manuscript:

CCSS Czech Center for Science and Society

CORDIS Community Research and Development Information Service

CS Citizen Science

DOAJ Directory of Open Access Journals

EU European Union

EUSO European Soil Observatory

GDPR General Data Protection Regulation

INRAE French National Research Institute for Agriculture, Food and Environment

LD Linear dichroism

LESP Lesprojekt-služby s.r.o.

LL Living Lab

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