{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,28]],"date-time":"2026-02-28T04:29:59Z","timestamp":1772252999000,"version":"3.50.1"},"reference-count":67,"publisher":"MDPI AG","issue":"14","license":[{"start":{"date-parts":[[2019,7,12]],"date-time":"2019-07-12T00:00:00Z","timestamp":1562889600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The objective to fast-track the mapping and registration of large numbers of unrecorded land rights globally has led to the experimental application of Artificial Intelligence in the domain of land administration, and specifically the application of automated visual cognition techniques for cadastral mapping tasks. In this research, we applied and compared the ability of rule-based systems within Object-Based Image Analysis (OBIA), as opposed to human analysis, to extract visible cadastral boundaries from very high-resolution World View-2 images, in both rural and urban settings. From our experiments, machine-based techniques were able to automatically delineate a good proportion of rural parcels with explicit polygons where the correctness of the automatically extracted boundaries was 47.4% against 74.24% for humans and the completeness of 45% for the machine compared to 70.4% for humans. On the contrary, in the urban area, automatic results were counterintuitive: even though urban plots and buildings are clearly marked with visible features such as fences, roads and tacitly perceptible to eyes, automation resulted in geometrically and topologically poorly structured data. Thus, these could neither be geometrically compared with human digitisation, nor actual cadastral data from the field. The results of this study provide an updated snapshot with regards to the performance of contemporary machine-driven feature extraction techniques compared to conventional manual digitising. In our methodology, using an iterative approach of segmentation and classification, we demonstrated how to overcome the weaknesses of having undesirable segments due to intra-parcel and inter-parcel variability, when using segmentation approaches for cadastral feature delineation. We also demonstrated how we can easily implement a geometric comparison framework within the Esri\u2019s ArcGIS software environment and firmly believe the developed methodology can be reproduced.<\/jats:p>","DOI":"10.3390\/rs11141662","type":"journal-article","created":{"date-parts":[[2019,7,12]],"date-time":"2019-07-12T11:49:38Z","timestamp":1562932178000},"page":"1662","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Comparing Human Versus Machine-Driven Cadastral Boundary Feature Extraction"],"prefix":"10.3390","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2444-8072","authenticated-orcid":false,"given":"Emmanuel","family":"Nyandwi","sequence":"first","affiliation":[{"name":"Department of Geography and Urban Planning, School of Architecture and Built Environment (SABE), College of Science and Technology (CST), University of Rwanda, Kigali City B.P 3900, Rwanda"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7612-5270","authenticated-orcid":false,"given":"Mila","family":"Koeva","sequence":"additional","affiliation":[{"name":"Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, 7500 AE Enschede, The Netherlands"}]},{"given":"Divyani","family":"Kohli","sequence":"additional","affiliation":[{"name":"Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, 7500 AE Enschede, The Netherlands"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1200-2068","authenticated-orcid":false,"given":"Rohan","family":"Bennett","sequence":"additional","affiliation":[{"name":"Department of Business Technology and Entrepreneurship, Swinburne Business School, BA1231 Hawthorn campus, Melbourne, VIC 3122, Australia"}]}],"member":"1968","published-online":{"date-parts":[[2019,7,12]]},"reference":[{"key":"ref_1","unstructured":"Winston, H.P. (1993). Artificial Intelligence, Library of Congress. [3rd ed.]."},{"key":"ref_2","unstructured":"Bennett, R., Gerke, M., Crompvoets, J., Ho, S., Schwering, A., Chipofya, M., and Wayumba, R. (2017, January 20\u201324). Building Third Generation Land Tools: Its4land, Smart Sketchmaps, UAVs, Automatic Feature Extraction, and the GeoCloud. Proceedings of the Annual World Bank Conference on Land and Poverty, Washington, DC, USA."},{"key":"ref_3","unstructured":"McDermott, M., Myers, M., and Augustinus, C. (2019, July 11). Valuation of Unregistered Lands: A Policy Guide. Available online: https:\/\/unhabitat.org\/books\/valuation-of-unregistered-lands-a-policy-guide\/."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Goldstein, S., and Naglieri, J. (2011). Encyclopedia of Child Behavior and Development, Springer Science + Business Media LLC.","DOI":"10.1007\/978-0-387-79061-9"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1479","DOI":"10.2307\/1130467","article-title":"Emergence and characterization of sex differences in spatial ability: A meta-analysis","volume":"56","author":"Linn","year":"1985","journal-title":"Child Dev."},{"key":"ref_6","unstructured":"Campbell, L., Campbell, B., and Dickinson, D. (1996). Teaching & Learning through Multiple Intelligences, Allyn and Bacon. [3rd ed.]."},{"key":"ref_7","unstructured":"Bennett, R. (2016, January 2\u20135). Cadastral Intelligence, Mandated Mobs, and the Rise of the Cadastrobots. Proceedings of the FIG Working Week 2016, Christchurch, New Zealand."},{"key":"ref_8","unstructured":"Bennett, R., Asiama, K., Zevenbergen, J., and Juliens, S. (2015, January 16\u201320). The Intelligent Cadastre. Proceedings of the FIG Commission 7\/3 Workshop on Crowdsourcing of Land Information, St Juliens, Malta."},{"key":"ref_9","first-page":"28","article-title":"A GEOBIA framework to estimate forest parameters from lidar transects, Quickbird imagery and machine learning: A case study in Quebec, Canada","volume":"15","author":"Chen","year":"2012","journal-title":"Int. J. Appl. Earth Observ. Geoinf."},{"key":"ref_10","first-page":"5020","article-title":"Geo-spatial Information Science The future of geospatial intelligence","volume":"20","author":"Dold","year":"2017","journal-title":"Future Geospat. Intell."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Blaschke, T., Lang, S., and Hay, G. (2008). Object-Based Image Analysis: Spatial Concepts for Knowledge-Driven Remote Sensing Applications, Springer Science & Business Media.","DOI":"10.1007\/978-3-540-77058-9"},{"key":"ref_12","first-page":"3517","article-title":"A new approach to corner extraction and matching for automated image registration","volume":"5","author":"Alkaabi","year":"2005","journal-title":"IGARSS"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"1383","DOI":"10.14358\/PERS.70.12.1383","article-title":"A Review of Techniques for Extracting Linear Features from Imagery","volume":"70","author":"Quackenbush","year":"2004","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_14","first-page":"691","article-title":"Big Data breaking barriers - first steps on a long trail","volume":"7","author":"Schade","year":"2015","journal-title":"ISPRS Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_15","first-page":"18","article-title":"Automated Feature Extraction","volume":"1","year":"2011","journal-title":"LiDAR"},{"key":"ref_16","unstructured":"Luo, X., Bennett, R., Koeva, M., and Quadros, N. (2017, May 23). Cadastral Boundaries from Point Clouds? Towards Semi-Automated Cadastral Boundary Extraction from ALS Data. Available online: https:\/\/www.gim-international.com\/content\/article\/cadastral-boundaries-from-point-clouds."},{"key":"ref_17","unstructured":"Donnelly, G.J. (2019, July 11). Fundamentals of Land Ownership, Land Boundaries, and Surveying, Available online: https:\/\/www.icsm.gov.au\/sites\/default\/files\/Fundamentals_of_Land_Ownership_Land_Boundaries_and_Surveying.pdf."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"27","DOI":"10.1080\/00050326.1986.10435202","article-title":"Cadastral and land information systems in developing countries","volume":"33","author":"Williamson","year":"1985","journal-title":"Aust. Surv."},{"key":"ref_19","first-page":"21","article-title":"The justification of cadastral systems in developing countries","volume":"51","author":"Williamson","year":"1997","journal-title":"Geomatica"},{"key":"ref_20","unstructured":"Williamson, I.P. (2000, January 25\u201327). Best practices for land administration systems in developing countries. Proceedings of the International Conference on Land Policy Reform, Jakarta, Indonesia."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Yomralioglu, T., and McLaughlin, J. (2017). Cadastre: Geo-Information Innovations in Land Administration, Springer.","DOI":"10.1007\/978-3-319-51216-7"},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Teunissen, P., and Montenbruck, O. (2017). Springer Handbook of Global Navigation Satellite Systems, Springer.","DOI":"10.1007\/978-3-319-42928-1"},{"key":"ref_23","unstructured":"Zevenbergen, J., and Bennett, R. (2015, January 18\u201320). The visible boundary: More than just a line between coordinates. In Proceeding of GeoTechRwanda, Kigali, Rwanda."},{"key":"ref_24","unstructured":"Rogers, S., Ballantyne, B., and Ballantyne, C. (2017, January 20\u201324). Rigorous Impact Evaluation of Land Surveying Costs: Empiricial evidence from indigenous lands in Canada. Proceedings of the 2017 World Bank Conference on Land and Poverty, Washington, DC, USA."},{"key":"ref_25","first-page":"1","article-title":"Land administration reform: indicators of success and future challenges","volume":"37","author":"Burns","year":"2007","journal-title":"Agric. Rural Dev. Discuss. Pap."},{"key":"ref_26","unstructured":"Zevenbergen, J. (2004). A systems approach to land registration and cadastre. Nordic J. Surv. Real Estate Res., 1."},{"key":"ref_27","unstructured":"Windrose (2017, July 03). Evolution of Surveying Techniques\u2014Windrose Land Services. Available online: https:\/\/www.windroseservices.com\/evolution-surveying-techniques\/."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Crommelinck, S., Bennett, R., Gerke, M., Nex, F., Yang, M.Y., and Vosselman, G. (2016). Review of automatic feature extraction from high-resolution optical sensor data for UAV-based cadastral mapping. Remote Sens., 8.","DOI":"10.3390\/rs8080689"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Luo, X., Bennett, R.M., Koeva, M., and Lemmen, C. (2017). Investigating Semi-Automated Cadastral Boundaries Extraction from Airborne Laser Scanned Data. Land, 6.","DOI":"10.3390\/land6030060"},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Deininger, K., Augustinus, C., Enemark, S., and Munro-Faure, P. (2010). First experiences with a high-resolution imagery-based adjudication approach in Ethiopia. Innovations in Land Rights Recognition, Administration, and Governance, The International Bank for Reconstruction and Development\/The World Bank.","DOI":"10.1596\/978-0-8213-8580-7"},{"key":"ref_31","unstructured":"Lennartz, S.P., and Congalton, R.G. (2004, January 23\u201328). Classifying and Mapping Forest Cover Types Using Ikonos Imagery in the Northeastern United States. Proceedings of the ASPRS Annual Conference Proceedings, Denver, CO, USA."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"2256","DOI":"10.3390\/rs4082256","article-title":"Object-Based Classification of Urban Areas Using VHR Imagery and Height Points Ancillary Data","volume":"4","author":"Salehi","year":"2012","journal-title":"Remote. Sens."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"8281","DOI":"10.1038\/s41598-017-08119-2","article-title":"High-resolution mapping based on an Unmanned Aerial Vehicle (UAV) to capture paleoseismic offsets along the Altyn-Tagh fault, China","volume":"7","author":"Gao","year":"2017","journal-title":"Sci. Rep."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"312","DOI":"10.1080\/00396265.2016.1268756","article-title":"Using UAVs for map creation and updating. A case study in Rwanda","volume":"50","author":"Koeva","year":"2018","journal-title":"Surv. Rev."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"75","DOI":"10.1080\/14498596.2017.1345667","article-title":"A procedure for semi-automated cadastral boundary feature extraction from high-resolution satellite imagery","volume":"63","author":"Wassie","year":"2017","journal-title":"J. Spat. Sci."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"3511","DOI":"10.1109\/TGRS.2010.2047260","article-title":"Using aerial imagery and GIS in automated building footprint extraction and shape recognition for earthquake risk assessment of urban inventories","volume":"48","author":"Sahar","year":"2010","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_37","first-page":"103","article-title":"Fiat and bona fide Boundaries: Towards an ontology of spatially extended objects","volume":"1329","author":"Smith","year":"1997","journal-title":"Philos. Phenomenol. Res."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"401","DOI":"10.2307\/2653492","article-title":"Fiat and Bona Fide Boundaries","volume":"60","author":"Smith","year":"2000","journal-title":"Philos. Phenomenol. Res."},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Radoux, J., and Bogaert, P. (2017). Good Practices for Object-Based Accuracy Assessment. Remote Sens., 9.","DOI":"10.3390\/rs9070646"},{"key":"ref_40","first-page":"386","article-title":"An integrated approach for updating cadastral maps in Pakistan using satellite remote sensing data","volume":"18","author":"Ali","year":"2012","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_41","unstructured":"Mumbone, M., Bennett, R.M., Gerke, M., and Volkmann, W. (2015). Innovations in Boundary Mapping: Namibia, Customary Land and UAV\u2019s, University of Twente Faculty of Geo-Information and Earth Observation (ITC)."},{"key":"ref_42","first-page":"325","article-title":"Unmanned aerial systems in the process of juridical verification of cadastral border","volume":"2","author":"Rijsdijk","year":"2013","journal-title":"ISPRS Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"12042","DOI":"10.1088\/1755-1315\/47\/1\/012042","article-title":"Comparison Effectiveness of Pixel Based Classification and Object Based Classification Using High Resolution Image in Floristic Composition Mapping (Study Case: Gunung Tidar Magelang City)","volume":"47","author":"Aryaguna","year":"2016","journal-title":"IOP Conf. Ser. Earth Environ. Sci."},{"key":"ref_44","unstructured":"Audebert, N., Le Saux, B., and Lefevre, S. (2016, January 20\u201324). Semantic Segmentation of Earth Observation Data Using Multimodal and Multi-scale Deep Networks. Proceedings of the Asian Conference on Computer Vision (ACCV16), Taipei, Taiwan."},{"key":"ref_45","first-page":"94050","article-title":"Building and road detection from large aerial imagery","volume":"Volume 9405","author":"Saito","year":"2015","journal-title":"Image Processing: Machine Vision Applications VIII"},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Xie, S., and Tu, Z. (2015, January 7\u201313). Holistically-nested edge detection. Proceedings of the IEEE International Conference on Computer Vision, Washington, DC, USA.","DOI":"10.1109\/ICCV.2015.164"},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"11372","DOI":"10.3390\/rs61111372","article-title":"Object-based land-cover mapping with high resolution aerial photography at a county scale in midwestern USA","volume":"6","author":"Li","year":"2014","journal-title":"Remote Sens."},{"key":"ref_48","unstructured":"O\u2019Neil-Dunne, J., and Schuckman, K. (2019, July 11). GEOG 883 Syllabus\u2014Fall 2018 Remote Sensing Image Analysis and Applications. Available online: https:\/\/www.e-education.psu.edu\/geog883\/book\/export\/html\/230."},{"key":"ref_49","unstructured":"Kohli, D., Bennett, R., Lemmen, C., Kwabena, A., and Zevenbergen, J. (June, January 29). A Quantitative Comparison of Completely Visible Cadastral Parcels Using Satellite Images: A Step towards Automation. Proceedings of the FIG Working Week 2017: Surveying the World of Tomorrow\u2014From Digitalisation to Augmented Reality, Helsinki, Finland."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"1809","DOI":"10.1080\/01431161.2016.1278312","article-title":"A machine learning approach for agricultural parcel delineation through agglomerative segmentation","volume":"38","year":"2017","journal-title":"Int. J. Remote Sens."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"13107","DOI":"10.1117\/1.OE.53.1.013107","article-title":"Nearest-neighbor diffusion-based pan-sharpening algorithm for spectral images","volume":"53","author":"Sun","year":"2014","journal-title":"Opt. Eng."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"119","DOI":"10.1016\/j.isprsjprs.2013.11.018","article-title":"Automated parameterisation for multi-scale image segmentation on multiple layers","volume":"88","author":"Csillik","year":"2014","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_53","unstructured":"Trimble. (n.d) (2019, July 11). eCognition Essentials. Ecognition developer. Developer ruleset. Available online: http:\/\/www.ecognition.com\/."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"73","DOI":"10.1080\/14498596.2017.1404500","article-title":"Understanding the cadastre in rural areas in Poland after the socio-political transformation","volume":"64","author":"Noszczyk","year":"2019","journal-title":"J. Spat. Sci."},{"key":"ref_55","unstructured":"Al-Kadi, O.S. (2019, July 11). Supervised Texture Segmentation: A Comparative Study, 1\u20135. Available online: https:\/\/arxiv.org\/ftp\/arxiv\/papers\/1601\/1601.00212.pdf."},{"key":"ref_56","doi-asserted-by":"crossref","unstructured":"Ayyub, B.M. (2001). Elicitation of Expert Opinions for Uncertainty and Risks, CRC Press.","DOI":"10.1201\/9781420040906"},{"key":"ref_57","unstructured":"Perera, A., Drew, C., and Johnson, C. (2012). What is expert knowledge, how is such knowledge gathered, and how do we use it to address questions in landscape ecology?. Expert Knowledge and Its Application in Landscape Ecology, Springer Science + Business Media, LLC."},{"key":"ref_58","first-page":"379","article-title":"Performance evaluation for automatic feature extraction","volume":"33","author":"McKeown","year":"2000","journal-title":"Int. Arch. Photogramm. Remote Sens."},{"key":"ref_59","doi-asserted-by":"crossref","unstructured":"Koeva, M., Bennett, R., Gerke, M., Crommelinck, S., St\u00f6cker, C., Crompvoets, J., and Zein, T. (2017). Towards Innovative Geospatial Tools for Fit-For-Purpose Land Rights Mapping. Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci., 42.","DOI":"10.5194\/isprs-archives-XLII-2-W7-37-2017"},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"1232","DOI":"10.1109\/TGRS.2009.2029570","article-title":"A Novel Protocol for Accuracy Assessment in Classification of Very High-Resolution Images","volume":"48","author":"Persello","year":"2010","journal-title":"Geosci. Remote Sens. IEEE Trans."},{"key":"ref_61","first-page":"144","article-title":"Discrepancy measures for selecting optimal combination of parameter values in object-based image analysis","volume":"68","author":"Liu","year":"2012","journal-title":"ISPRS"},{"key":"ref_62","unstructured":"Carron, J. (2019, July 11). \u201cViolin Plots 101: Visualizing Distribution and Probability Density.\u201d Mode blog. Available online: https:\/\/mode.com\/blog\/violin-plot-examples."},{"key":"ref_63","unstructured":"Trimble (2014). Ecognition Developer 9.0\u2013Reference Book, Trimble Documentation."},{"key":"ref_64","first-page":"754","article-title":"Variability of operator performance in remote-sensing image interpretation: The importance of human and external factors","volume":"35","author":"Gardin","year":"2014","journal-title":"IJRS"},{"key":"ref_65","first-page":"89","article-title":"Creating Cadastral Maps in Rural and Urban Areas of Using High Resolution Satellite Imagery","volume":"2009","author":"Alkan","year":"2009","journal-title":"Appl. Geo-Inform. Soc. Environ."},{"key":"ref_66","first-page":"39","article-title":"Land Information Extraction with Boundary Preservation for High Resolution Satellite Image","volume":"120","author":"Suresh","year":"2015","journal-title":"Int. J. Comput. Appl."},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"67","DOI":"10.1016\/j.isprsjprs.2014.07.002","article-title":"Comparing supervised and unsupervised multiresolution segmentation approaches for extracting buildings from very high-resolution imagery","volume":"96","author":"Belgiu","year":"2014","journal-title":"ISPRS J. Photogramm. Remote Sens."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/11\/14\/1662\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T13:04:58Z","timestamp":1760187898000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/11\/14\/1662"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,7,12]]},"references-count":67,"journal-issue":{"issue":"14","published-online":{"date-parts":[[2019,7]]}},"alternative-id":["rs11141662"],"URL":"https:\/\/doi.org\/10.3390\/rs11141662","relation":{"has-preprint":[{"id-type":"doi","id":"10.20944\/preprints201905.0342.v1","asserted-by":"object"}]},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,7,12]]}}}