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The reprint "Land Administration 2.0" is an extension of the previous reprint "Remote Sensing for Land Administration", another Special Issue in Remote Sensing. This reprint unpacks the responsible use and integration of emerging remote sensing techniques into the domain of land administration, including land registration, cadastre, land use planning, land valuation, land taxation, and land development. The title was chosen as "Land Administration 2.0" in reference to both this Special Issue being the second volume on the topic "Land Administration" and the next-generation requirements of land administration including demands for 3D, indoor, underground, real-time, high-accuracy, lower-cost, and interoperable land data and information.
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The reprint "Land Administration 2.0" is an extension of the previous reprint "Remote Sensing for Land Administration", another Special Issue in Remote Sensing. This reprint unpacks the responsible use and integration of emerging remote sensing techniques into the domain of land administration, including land registration, cadastre, land use planning, land valuation, land taxation, and land development. The title was chosen as "Land Administration 2.0" in reference to both this Special Issue being the second volume on the topic "Land Administration" and the next-generation requirements of land administration including demands for 3D, indoor, underground, real-time, high-accuracy, lower-cost, and interoperable land data and information.
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The reprint "Land Administration 2.0" is an extension of the previous reprint "Remote Sensing for Land Administration", another Special Issue in Remote Sensing. This reprint unpacks the responsible use and integration of emerging remote sensing techniques into the domain of land administration, including land registration, cadastre, land use planning, land valuation, land taxation, and land development. The title was chosen as "Land Administration 2.0" in reference to both this Special Issue being the second volume on the topic "Land Administration" and the next-generation requirements of land administration including demands for 3D, indoor, underground, real-time, high-accuracy, lower-cost, and interoperable land data and information.
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What is land? Who owns it? Who can use it? How much is it worth? What can it be used for? These are the questions land administration seeks to answer responsibly, which requires trustworthy people, transparent processes, and reliable information systems. Spatial information is an essential ingredient, and is embedded in the cadastral plans, maps, and land registry records that are used to prove ownership, trade land, access credit, resolve land disputes, enable fair taxation, and support land use planning and development. In the past, ground-based surveying techniques were used to capture the information, however, advances in remote sensing are driving the development of approaches that are faster, lower in cost, more accurate, or more participatory. These can be used to build land administration systems that better support poverty reduction, rapid urbanization, vertical development, and complex infrastructure management. The contributions contained in this book unpack these developments and the potential impacts and explore applications of high-resolution satellite imagery, unmanned aerial vehicle imagery, laser scanning, airborne and terrestrial (LiDAR), machine learning, and artificial intelligence methods, as applied to land administration in parts of Europe, Asia, and Africa.
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What is land? Who owns it? Who can use it? How much is it worth? What can it be used for? These are the questions land administration seeks to answer responsibly, which requires trustworthy people, transparent processes, and reliable information systems. Spatial information is an essential ingredient, and is embedded in the cadastral plans, maps, and land registry records that are used to prove ownership, trade land, access credit, resolve land disputes, enable fair taxation, and support land use planning and development. In the past, ground-based surveying techniques were used to capture the information, however, advances in remote sensing are driving the development of approaches that are faster, lower in cost, more accurate, or more participatory. These can be used to build land administration systems that better support poverty reduction, rapid urbanization, vertical development, and complex infrastructure management. The contributions contained in this book unpack these developments and the potential impacts and explore applications of high-resolution satellite imagery, unmanned aerial vehicle imagery, laser scanning, airborne and terrestrial (LiDAR), machine learning, and artificial intelligence methods, as applied to land administration in parts of Europe, Asia, and Africa.
Choose an application
What is land? Who owns it? Who can use it? How much is it worth? What can it be used for? These are the questions land administration seeks to answer responsibly, which requires trustworthy people, transparent processes, and reliable information systems. Spatial information is an essential ingredient, and is embedded in the cadastral plans, maps, and land registry records that are used to prove ownership, trade land, access credit, resolve land disputes, enable fair taxation, and support land use planning and development. In the past, ground-based surveying techniques were used to capture the information, however, advances in remote sensing are driving the development of approaches that are faster, lower in cost, more accurate, or more participatory. These can be used to build land administration systems that better support poverty reduction, rapid urbanization, vertical development, and complex infrastructure management. The contributions contained in this book unpack these developments and the potential impacts and explore applications of high-resolution satellite imagery, unmanned aerial vehicle imagery, laser scanning, airborne and terrestrial (LiDAR), machine learning, and artificial intelligence methods, as applied to land administration in parts of Europe, Asia, and Africa.
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