Israel Oluwaseun Taiwo, Matthew Olomolatan Ibitoye, Sunday Olukayode Oladejo
et al.
In developing nations, such as Ekiti State, Nigeria, the utilization of remotely sensed data, particularly satellite and UAV imagery, remains significantly underexploited in land administration. This limits multi-resolution imagery’s potential in land governance and socio-economic development. This study examines factors influencing UAV adoption for land administration in Nigeria, mapping seven rural, peri-urban, and urban sites with orthomosaics (2.2 cm to 3.39 cm resolution). Boundaries were manually delineated, and parcel areas were calculated. Using the 0.05 m orthomosaic as a reference, the Horizontal Radial Root Mean Square Error (RMSEr) and Normalized Parcel Area Error (NPAE) were computed. Results showed a consistent increase in error with increasing resolution (0.1 m to 1 m), with RMSEr ranging from 0.053 m (formal peri-urban) to 2.572 m (informal rural settlement). Formal settlements with physical demarcations exhibited more consistent values. A comparison with GNSS data revealed that RMSEr values conformed to the American Society for Photogrammetry and Remote Sensing (ASPRS) Class II and III standards. The research demonstrates physical demarcations’ role in facilitating cadastral mapping, with formal settlements showing the highest suitability. This study recommends context-specific imagery resolution to enhance land governance. Key implications include promoting settlement typology awareness and addressing UAV regulatory challenges. NPAE values can serve as a metric for assessing imagery resolution fitness for cadastral mapping.
Despite its importance as a research issue, a widely accepted methodology of estimating land take resulting from urbanization has not yet been reached. Accurate geospatial datasets are currently available at a European and global level; however, different methods of quantifying urban land take could lead to diverse outputs, potentially resulting in underestimation. This can be alarming as encroaching urban sprawl is emerging as a major environmental challenge by destroying natural habitats, consuming productive agricultural land, and contributing to climate change by increasing energy demands. To address this knowledge gap, we propose an estimation of urban land take that combines cadastral parcels and building footprints. Land parcels can be considered as a suitable minimum mapping unit as they are directly related to the spatial level where economic decisions on land use conversion are made. The proposed geospatial method is compared to methods that depend on datasets of High Resolution Layer Imperviousness, Global Building Footprints (alone), Corine Land Cover, Urban Atlas, and Global Human Settlement Layer. The method is exemplified in case studies in Greece, specifically: (a) two islands of the South Aegean Region (Mykonos and Thera), that are heavily impacted by tourism development and sprawl and (b) a peri-urban zone (Thermaikos-Michaniona) within the metropolitan area of Thessaloniki, impacted by intense suburbanization. Results show that urban land consumes important shares of available land since the mid-20th century, this fact highlighting the dynamic encroachment of urban development. Calculation shows that other methods could underestimate urbanized areas by up to 80%–90%. In the discussion section, the advantages of shifting the focus from the pixel to the parcel are further justified, while explicit links to spatial planning policies for sprawl containment are drawn. Such policies could be informed by more realistic estimations of urban land take, in order to proceed with strategic and regulatory measures to support the ‘no net land take’ policy of Europe.
This article is dedicated to analyzing the accuracy of cadastral surveys using uncrewed aerial vehicles (UAVs). It explores the efficiency and precision of surveys conducted with UAVs in the context of cadastral work. The article examines the methods and technologies used to ensure high accuracy of geospatial data in the cadastral field through UAVs. Utilizing cutting-edge technologies and analyzing research results, the article highlights the possibilities and limitations of UAV applications in cadastral surveys and land mapping tasks. The research findings can benefit geodesy, cartography, and cadastre professionals, as well as developers and operators of uncrewed aerial vehicles. This work investigates a network of phototriangulation conducted using uncrewed aerial vehicles (UAVs). Network parameters evaluated include the number of images, flight altitude, camera focal length, image size, pixel size, and coverage area. The images were processed using Agisoft Metashape Professional software. The main results of automatic image measurement are provided, including the number of tie points in the network, average ray intersection residuals, and random root mean square errors of ground points. The work shows that the provided accuracy characteristics need to provide more information for a reliable assessment of results. Despite optimistic results, the accuracy distribution may need to be improved for confident cadastral data quality. A modernized software complex for phototriangulation calculation, BlockMSG, was used for a more detailed assessment. It is noted that the calculation results correspond to all initial data of the Agisoft Metashape program but without additional information and analysis of possible errors. The paper also discusses the importance of measurement accuracy and its impact on creating a 3D cadastre. Data on the distribution of linear errors of points are presented, indicating the importance of choosing the number of images to obtain accurate coordinates. The primary focus is the need for a thorough analysis of results and possible error sources to ensure high-quality cadastral data. Keywords: accuracy, cadastral surveys, unmanned aerial vehicles (UAVs), geodetic methods, geospatial data, analysis.
The improvement of cadastral systems has become a major problem in Indonesia. Despite continuous efforts to digitize land cadastral maps, persistent difficulties such as gaps and overlaps remain in the cadastral data. This study utilizes the least squares adjustment method to improve the quality of land cadastral maps in Indonesia and address these difficulties. This method is preferred because of its ability to maintain the integrity of polygon forms and parcel areas, which are essential characteristics of cadastral mapping. In addition, the implementation seeks to provide visual indicators of the accuracy of adjustments, such as error ellipses and changes in parcel sizes. While errors in the vertex transformations within segments cause some gaps and overlaps to persist, these problems are addressed by post-processing approaches. The results indicate that this method can enhance the quality of land cadastral maps in Indonesia.
Investigates the development and implementation of digital cadastral map databases for Mosul District, Iraq, addressing the transition from traditional paper-based systems to modern geospatial technologies. The research explores the integration of Geographic Information Systems (GIS), remote sensing, and Global Positioning System (GPS) technologies to enhance cadastral mapping processes. Encompass data collection from diverse sources, including high-resolution satellite imagery, aerial photography, and existing cadastral maps. A comprehensive analysis of data types— vector, raster, Triangulated Irregular Network (TIN), and tabular—is conducted to establish an optimal database structure. The study delineates the technical capabilities of GIS in data processing, spatial analysis, and model preparation, emphasizing the importance of data accuracy and consistency. A systematic approach to data entry, including map scanning, georeferencing, and digitization, is presented. The research outlines the creation of a multi-layered geographic database, incorporating both spatial and descriptive data. Protocols for database updating using satellite imagery and field surveys are developed, ensuring the currency and reliability of cadastral information. The results demonstrate significant improvements in data management, spatial analysis capabilities, and information accessibility compared to traditional methods. The study concludes that digital cadastral databases offer enhanced decision-making support for land administration and urban planning in Mosul District. Contributes to the body of knowledge on modernizing cadastral systems in developing regions, providing insights into technological integration, data standardization, and the challenges associated with transitioning to digital cadastral management systems. The findings have implications for policy makers and land administrators seeking to implement similar systems in comparable urban contexts.
- This study presents a comparative analysis of the accuracy of cadastral parcel positions in Himare, utilizing different methods including the state cadastre agency (ASHK), orthophoto 2007-2015 data and Global Navigation Satellite System (GNSS) measurements. The cadastral parcel positions are crucial for land administration and management, making accuracy a paramount concern. Through a comprehensive examination, this research evaluates the positional accuracy of cadastral parcels by comparing ASHK data with orthophoto 2007-2015 imagery, as well as GNSS measurements. The study employs statistical analyses and spatial techniques to assess discrepancies and similarities among the different datasets. Findings from this research provide insights into the effectiveness and reliability of cadastral data sources in Himare, shedding light on potential discrepancies and areas for improvement in cadastral mapping and land management practices. Such insights are essential for enhancing the efficiency and accuracy of cadastral systems, thereby contributing to better-informed decision-making processes and sustainable land development in the region.
The accuracy of positional data in cadastral mapping is crucial for various technical activities within the cadastre and related decision-making processes. With digital maps becoming ubiquitous in cadastral operations, assessing the positional accuracy of cadastral maps digitized from stable cadastre systems has become essential. These maps, categorized as DKM and KMD, present different challenges in determining their overall positional accuracy. While DKM maps offer high accuracy, KMD maps, derived from stable cadastre systems, pose challenges due to their varied origins, including potential positional errors inherited from historical data. This study proposes a methodology for assessing the positional accuracy of KMD maps by comparing digitized boundaries with actual field measurements. The evaluation considers factors such as cadastral area characteristics, available survey data, and the timing of digitization efforts. The study aims to categorize objects based on their positional accuracy by analysing shifts in boundary points and building positions. Results from testing in selected cadastral areas reveal varying degrees of accuracy in KMD maps. While some areas demonstrate high accuracy, others exhibit significant positional inaccuracies, particularly in peripheral regions or linear parcels. The study suggests that areas outside municipal boundaries may require immediate remapping to ensure accuracy. Overall, the findings highlight the importance of assessing and improving the positional accuracy of cadastral maps to enhance their utility in land management and decision-making processes. Further research in this area could focus on developing automated methods for detecting and correcting positional errors in digital cadastral maps.
Václav Šafář, Markéta Potůčková, Jakub Karas
et al.
The main challenge in the renewal and updating of the Cadastre of Real Estate of the Czech Republic is to achieve maximum efficiency but to retain the required accuracy of all points in the register. The paper discusses the possibility of using UAV photogrammetry and laser scanning for cadastral mapping in the Czech Republic. Point clouds from images and laser scans together with orthoimages were derived over twelve test areas. Control and check points were measured using geodetic methods (RTK-GNSS and total stations). The accuracy of the detailed survey based on UAV technologies was checked on hundreds of points, mainly building corners and fence foundations. The results show that the required accuracy of 0.14 m was achieved on more than 80% and 98% of points in the case of the image point clouds and orthoimages and the case of the LiDAR point cloud, respectively. Nevertheless, the methods lack completeness of the performed survey that must be supplied by geodetic measurements. The paper also provides a comparison of the costs connected to traditional and UAV-based cadastral mapping, and it addresses the necessary changes in the organisational and technological processes in order to utilise the UAV based technologies.
Accurate building extraction from remotely sensed images is essential for topographic mapping, cadastral surveying and many other applications. Fully automatic segmentation methods still remain a great challenge due to the poor generalization ability and the inaccurate segmentation results. In this work, we are committed to robust click-based interactive building extraction in remote sensing imagery. We argue that stability is vital to an interactive segmentation system, and we observe that the distance of the newly added click to the boundaries of the previous segmentation mask contains progress guidance information of the interactive segmentation process. To promote the robustness of the interactive segmentation, we exploit this information with the previous segmentation mask, positive and negative clicks to form a progress guidance map, and feed it to a convolutional neural network (CNN) with the original RGB image, we name the network as PGR-Net. In addition, an adaptive zoom-in strategy and an iterative training scheme are proposed to further promote the stability of PGR-Net. Compared with the latest methods FCA and f-BRS, the proposed PGR-Net basically requires 1–2 fewer clicks to achieve the same segmentation results. Comprehensive experiments have demonstrated that the PGR-Net outperforms related state-of-the-art methods on five natural image datasets and three building datasets of remote sensing images.
Accurate crop-type maps are urgently needed as input data for various applications, leading to improved planning and more sustainable use of resources. Satellite remote sensing is the optimal tool to provide such data. Images from Synthetic Aperture Radar (SAR) satellite sensors are preferably used as they work regardless of cloud coverage during image acquisition. However, processing of SAR is more complicated and the sensors have development potential. Dealing with such a complexity, current studies should aim to be reproducible, open, and built upon free and open-source software (FOSS). Thereby, the data can be reused to develop and validate new algorithms or improve the ones already in use. This paper presents a case study of crop classification from microwave remote sensing, relying on open data and open software only. We used 70 multitemporal microwave remote sensing images from the Sentinel-1 satellite. A high-resolution, high-precision digital elevation model (DEM) assisted the preprocessing. The multi-data approach (MDA) was used as a framework enabling to demonstrate the benefits of including external cadastral data. It was used to identify the agricultural area prior to the classification and to create land use/land cover (LULC) maps which also include the annually changing crop types that are usually missing in official geodata. All the software used in this study is open-source, such as the Sentinel Application Toolbox (SNAP), Orfeo Toolbox, R, and QGIS. The produced geodata, all input data, and several intermediate data are openly shared in a research database. Validation using an independent validation dataset showed a high overall accuracy of 96.7% with differentiation into 11 different crop-classes.
Juan Francisco Reinoso-Gordo, Rocío Romero-Zaliz, Carlos León-Robles
et al.
Sometimes it is necessary to know the transformation to apply to a mapping shape in order to locate its true place. Such an operation can be computed if a corresponding reference object exists and we can identify corresponding points in both shapes. Nevertheless our approach does not need to match any corresponding point beforehand. The method proposed defines a polygon in the frequency domain—two periodic functions are derived from a polygonal or polygon. According to the theory of elliptic Fourier descriptors those two periodic functions can be expressed by Fourier expansions. The transformation can be computed using the coefficients of the harmonics from the corresponding shapes without taking into account where each polygon vertex is placed in the spatial domain. The transformation parameters will be derived by a least squares approach. The geomatics and geosciences applications of this method go from photogrammetry, geographic information system, computer vision, to cadaster and real estates.
Fabian Brondi Rueda, Gabriele Garnero, Giovanni Righetti
et al.
The study and analysis of climate change is a global challenge against which environmental, but also economic and social changes, will be measured.
This memorandum illustrates the recent activities carried out by the IGN Peru in collaboration with European institutions.
Sophie Crommelinck, Rohan Bennett, Markus Gerke
et al.
Unmanned Aerial Vehicles (UAVs) have emerged as a rapid, low-cost and flexible acquisition system that appears feasible for application in cadastral mapping: high-resolution imagery, acquired using UAVs, enables a new approach for defining property boundaries. However, UAV-derived data are arguably not exploited to its full potential: based on UAV data, cadastral boundaries are visually detected and manually digitized. A workflow that automatically extracts boundary features from UAV data could increase the pace of current mapping procedures. This review introduces a workflow considered applicable for automated boundary delineation from UAV data. This is done by reviewing approaches for feature extraction from various application fields and synthesizing these into a hypothetical generalized cadastral workflow. The workflow consists of preprocessing, image segmentation, line extraction, contour generation and postprocessing. The review lists example methods per workflow step—including a description, trialed implementation, and a list of case studies applying individual methods. Furthermore, accuracy assessment methods are outlined. Advantages and drawbacks of each approach are discussed in terms of their applicability on UAV data. This review can serve as a basis for future work on the implementation of most suitable methods in a UAV-based cadastral mapping workflow.
Brian Bramanto, Irwan Gumilar, Muhammad Taufik
et al.
In Indonesia, Global Navigation Satellite System (GNSS) has become one of the important tool in survey mapping, especially for cadastral purposes like land registration by using Real Time Kinematic (RTK) GNSS positioning method. The conventional RTK GNSS positioning method ensure high accuracy GNSS position solution (within several centimeters) for baseline less than 20 kilometers. The problems of resolving high accuracy position for a greater distance (more than 50 kilometers) becomes greater challenge. In longer baseline, atmospheric delays is a critical factor that influenced the positioning accuracy. In order to reduce the error, a modified LAMBDA ambiguity resolution, atmospheric correction and modified kalman filter were used in this research. Thus, this research aims to investigate the accuracy of estimated position and area in respect with short baseline RTK and differential GNSS position solution by using NAVCOM SF-3040. The results indicate that the long-range single baseline RTK accuracy vary from several centimeters to decimeters due to unresolved biases.
Antonio Lanorte, Fortunato De Santis, Biagio Tucci
Remote sensing data can usefully support the fire management operational applications in different spatial and temporal scales with a synoptic point of view and low cost technologies. The satellite monitoring systems together with other geographic information, historical data and field measurements, can provide the fire management operators useful tools of fire danger assessment, fire prevention, fire-fighting and post-fire planning. The
FIRE-SAT monitoring system was applied to a fire event which developed in a wildland-urban interface area of the Potenza town (Basilicata, Italy) on July 2015, in order to assess the fire occurrence danger, to evaluate the fire effects and to simulate the fire propagation.
Federico Capriuoli, Davide Colangelo, Luca Curto
et al.
QUIRINALE 3D VR is a software for the navigation in virtual reality of the Quirinale Palace. It is the result of an innovative 3D reconstruction project developed by the Italian companies Geocart and Digital Lighthouse aiming to the enhancement of the Quirinale through the most innovative techniques of Digital Heritage field. The project, based on the integration of existing methodologies and novel processes
for cultural heritage digitization supported by computer graphics, has created a unique result in terms of user involvement, also by means of immersive experience.