# Remote Sensing for Land Administration
## 1 Introduction
These approaches have been argued to deliver the prescribed coordinate accuracies, often set, it must be said, overly bluntly, at centimeter-level in surveying laws and regulations [19]. More recently, increasing attention is afforded to applying advances in photogrammetry and remote sensing to the domain land administration. In the context of land administration, these approaches are considered 'indirect' surveying techniques, in contrast to 'direct' or ground-based methods [26]. Photogrammetry is the techniques and tools for extracting multi-dimensional geospatial information from images, needed for mapping activities [27]. Remote sensing is the process of scanning or monitoring the physical characteristics of the surface of the earth, measuring the emitted radiation at a distance. For this purpose, cameras, sensors or scanners with RGB (red, green, blue), hyperspectral, LiDAR (light detection and ranging), or RADAR (radio detection and ranging) capabilities are used. These sensors can be mounted on conventional aerial vehicles (i.e., airplanes), space-borne satellites (i.e., enabling high and very-high resolution satellite imagery (HRSI and VHRSI), unmanned aerial vehicles (UAVs), amongst others [28]. It is worth noting that whilst application of photogrammetry and remote sensing to land administration has a lengthy history [29], it is the novel tools and techniquesemerging in those fields that drive renewed and increased interest. These are specifically focused on the transfer of 'cadastral intelligence' from human actors to machines [30], and make use of enhanced image processing tools, artificial intelligence, and machine learning techniques [31]. The abovementioned developments in remote sensing and photogrammetry, applied to land administration, are the focus of this special issue. The aim is to provide a snapshot of contemporary experimentations, demonstrations, implementations, and impacts from a diverse range of case contexts. From a broad perspective, the special issue presents: (i) comparisons of alternate remote sensing techniques for 2D and 3D data capture relevant to land administration (including UAV imagery, VHRSI, RADAR, LiDAR, and multi-spectral approaches); (ii) design and testing of techniques for 2D and 3D cadastral feature extraction from remotely-sensed data sources (including machine learning, pattern recognition, neural networks, semi-automated methods, algorithm design, and object-based approaches); (iii) modelling of data production workflows for scaled 2D and 3D cadastral production (including segmentation techniques, line extraction, contour generation, and pre/post-processing requirements); and (iv) observations from illustrative cases highlighting leading practices in data integration and utilization for 2D and 3D land administration (including both city, provincial, and national level examples). More specifically, the special issue consists of nine (9) individual works; developed by multi-disciplined research and practitioner teams; across Europe, Asia, and Africa; variously using qualitative and quantitative research methods with a diversity of days sources; all with reference back to land administration applications (Table 1). The next section outlines each work and synthesizes the overarching contribution of the special issue.