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Remote Sensing
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Editorial Board Members’ Collection Series: Remote Sensing for 3D Land...
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Editorial Board Members’ Collection Series: Remote Sensing for 3D Land Administration

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Urban Remote Sensing".

Deadline for manuscript submissions: closed (26 June 2024) | Viewed by 5627

Special Issue Editors

Dr. Mila Koeva

E-Mail Website1 Website2
Guest Editor
Department of Urban and Regional Planning and Geo-Information Management, University of Twente, Drienerlolaan 5, 7522 NB Enschede, The Netherlands
Interests: 3D land information; photogrammetry and remote sensing; UAV; 3D modeling and visualization/digital twins
Special Issues, Collections and Topics in MDPI journals
Dr. Rohan Bennett

E-Mail Website
Guest Editor
Department of Business Technology and Entrepreneurship, School of Business, Law and Entrepreneurship, Swinburne University of Technology, Hawthorn, VIC 3122, Australia
Interests: ICT4D; land informatics; digital business
Special Issues, Collections and Topics in MDPI journals
Dr. Claudio Persello

E-Mail Website
Guest Editor
Faculty of Geo-Information Science and Earth Observation (ITC) of the University of Twente, Department of Earth Observation Science, P.O. Box 217, 7500 AE Enschede, The Netherlands
Interests: remote sensing; machine learning; deep learning
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Peter Van Oosterom

E-Mail Website
Guest Editor
Department of OTB, TU-Delft, Delft, The Netherlands
Interests: spatial databases; map generalization; 3D cadastre; point clouds; geomatics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The United Nations’ sustainable development goal (SDG), particularly indicator 1.4.2, promotes tenure security for all. Despite this, based on global estimates, around 70% of land to people’s relationships are still not recorded. This fact is mainly due to the expensive and time-consuming nature of the conventional systems for land registration such as the use of high-precision ground survey methods. In this regard, this Special Issue aims at gathering innovative solutions in the field of 2D and 3D land administration. Over the past decade, there has been significant progress in the usage of active and passive remote sensing techniques such as RGB and multispectral sensors, LiDAR, RADAR, etc. In addition, artificial intelligence (AI) methods have been extensively explored and tested for cadastral boundary extraction. The developments towards the 3rd dimension should also not be left unmentioned. Therefore, building from the popularity of the previously published two Special Issues related to the usage of remote sensing techniques for land administration, in the current Special Issue, we encourage submissions on topics such as:

  • Innovative remote sensing AI-based methods in support of cadastral mapping
  • 2D and 3D land registration, valuation and taxation
  • Geospatial data acquisition, processing and modelling in support of 2D and 3D land tenure recording
  • Design and testing of innovative methods based on remotely sensed data for cadastre boundary extraction

Dr. Mila Koeva
Dr. Rohan Bennett
Dr. Claudio Persello
Prof. Dr. Peter Van Oosterom
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • artificial intelligence for LA
  • machine learning for LA
  • 2D/3D land data
  • automatic feature extraction
  • land valuation and taxation
  • 2D/3D land use planning and development

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (2 papers)

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Research

30 pages, 32487 KiB  
Article
Fitness of Multi-Resolution Remotely Sensed Data for Cadastral Mapping in Ekiti State, Nigeria
by Israel Oluwaseun Taiwo, Matthew Olomolatan Ibitoye, Sunday Olukayode Oladejo and Mila Koeva
Remote Sens. 2024, 16(19), 3670; https://doi.org/10.3390/rs16193670 - 1 Oct 2024
Cited by 1 | Viewed by 1953
Abstract
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 [...] Read more.
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. Full article
(This article belongs to the Special Issue Editorial Board Members’ Collection Series: Remote Sensing for 3D Land Administration)
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24 pages, 7207 KiB  
Article
Furthering Automatic Feature Extraction for Fit-for-Purpose Cadastral Updating: Cases from Peri-Urban Addis Ababa, Ethiopia
by Mekonnen Tesfaye Metaferia, Rohan Mark Bennett, Berhanu Kefale Alemie and Mila Koeva
Remote Sens. 2023, 15(17), 4155; https://doi.org/10.3390/rs15174155 - 24 Aug 2023
Cited by 5 | Viewed by 2684
Abstract
Fit-for-purpose land administration (FFPLA) seeks to simplify cadastral mapping via lowering the costs and time associated with conventional surveying methods. This approach can be applied to both the initial establishment and on-going maintenance of the system. In Ethiopia, cadastral maintenance remains an on-going [...] Read more.
Fit-for-purpose land administration (FFPLA) seeks to simplify cadastral mapping via lowering the costs and time associated with conventional surveying methods. This approach can be applied to both the initial establishment and on-going maintenance of the system. In Ethiopia, cadastral maintenance remains an on-going challenge, especially in rapidly urbanizing peri-urban areas, where farmers’ land rights and tenure security are often jeopardized. Automatic Feature Extraction (AFE) is an emerging FFPLA approach, proposed as an alternative for mapping and updating cadastral boundaries. This study explores the role of the AFE approach for updating cadastral boundaries in the vibrant peri-urban areas of Addis Ababa. Open-source software solutions were utilized to assess the (semi-) automatic extraction of cadastral boundaries from orthophotos (segmentation), designation of “boundary” and “non-boundary” outlines (classification), and delimitation of cadastral boundaries (interactive delineation). Both qualitative and quantitative assessments of the achieved results (validation) were undertaken. A high-resolution orthophoto of the study area and a reference cadastral boundary shape file were used, respectively, for extracting the parcel boundaries and validating the interactive delineation results. Qualitative (visual) assessment verified the completed extraction of newly constructed cadastral boundaries in the study area, although non-boundary outlines such as footpaths and artifacts were also retrieved. For the buffer overlay analysis, the interactively delineated boundary lines and the reference cadastre were buffered within the spatial accuracy limits for urban and rural cadastres. As a result, the quantitative assessment delivered 52% correctness and 32% completeness for a buffer width of 0.4 m and 0.6 m, respectively, for the interactively delineated and reference boundaries. The study proposed publicly available software solutions and outlined a workflow to (semi-) automatically extract cadastral boundaries from aerial/satellite images. It further demonstrated the potentially significant role AFE could play in delivering fast, affordable, and reliable cadastral mapping. Further investigation, based on user input and expertise evaluation, could help to improve the approach and apply it to a real-world setting. Full article
(This article belongs to the Special Issue Editorial Board Members’ Collection Series: Remote Sensing for 3D Land Administration)
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