{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,20]],"date-time":"2025-12-20T21:52:29Z","timestamp":1766267549981,"version":"build-2065373602"},"reference-count":31,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2020,6,20]],"date-time":"2020-06-20T00:00:00Z","timestamp":1592611200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Key R&amp;D Program of China","award":["2018YFC1508805","2016YFC0500508"],"award-info":[{"award-number":["2018YFC1508805","2016YFC0500508"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["31600351"],"award-info":[{"award-number":["31600351"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Strategic Priority Research Program of Chinese Academy of Sciences","award":["XDA20010302"],"award-info":[{"award-number":["XDA20010302"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>China\u2019s rural population has declined markedly with the acceleration of urbanization and industrialization, but the area under rural homesteads has continued to expand. Proper rural land use and management require large-scale, efficient, and low-cost rural residential surveys; however, such surveys are time-consuming and difficult to accomplish. Unmanned aerial vehicle (UAV) technology coupled with a deep learning architecture and 3D modelling can provide a potential alternative to traditional surveys for gathering rural homestead information. In this study, a method to estimate the village-level homestead area, a 3D-based building height model (BHM), and the number of building floors based on UAV imagery and the U-net algorithm was developed, and the respective estimation accuracies were found to be 0.92, 0.99, and 0.89. This method is rapid and inexpensive compared to the traditional time-consuming and costly household surveys, and, thus, it is of great significance to the ongoing use and management of rural homestead information, especially with regards to the confirmation of homestead property rights in China. Further, the proposed combination of UAV imagery and U-net technology may have a broader application in rural household surveys, as it can provide more information for decision-makers to grasp the current state of the rural socio-economic environment.<\/jats:p>","DOI":"10.3390\/ijgi9060403","type":"journal-article","created":{"date-parts":[[2020,6,22]],"date-time":"2020-06-22T06:46:12Z","timestamp":1592808372000},"page":"403","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Village-Level Homestead and Building Floor Area Estimates Based on UAV Imagery and U-Net Algorithm"],"prefix":"10.3390","volume":"9","author":[{"given":"Xueyan","family":"Zhang","sequence":"first","affiliation":[{"name":"Institute of Geographical Science and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China"},{"name":"Centre for Chinese Agricultural Policy, Chinese Academy of Sciences, Beijing 100101, China"}]}],"member":"1968","published-online":{"date-parts":[[2020,6,20]]},"reference":[{"key":"ref_1","first-page":"17","article-title":"Property rights and regulation: Evolution and reform of China\u2019s homestead system","volume":"6","author":"Liu","year":"2019","journal-title":"China Econ. Stud."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1016\/j.landusepol.2011.04.003","article-title":"Accelerated restructuring in rural China fueled by increasing vs. decreasing balance land-use policy for dealing with hollowed villages","volume":"29","author":"Long","year":"2012","journal-title":"Land Use Policy"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"6","DOI":"10.1016\/j.landusepol.2013.03.013","article-title":"Key issues of land use in China and implications for policy making","volume":"40","author":"Liu","year":"2014","journal-title":"Land Use Policy"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"524","DOI":"10.1016\/j.landusepol.2017.08.017","article-title":"Influencing factors of farmers\u2019 willingness to withdraw from rural homesteads: A survey in Zhejiang, China","volume":"68","author":"Chen","year":"2017","journal-title":"Land Use Policy"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"121","DOI":"10.1016\/j.habitatint.2016.07.007","article-title":"Restructuring rural settlements based on an analysis of inter-village social connections: A case in Hubei Province, Central China","volume":"57","author":"Tian","year":"2016","journal-title":"Habitat Int."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"285","DOI":"10.1016\/j.landusepol.2019.04.013","article-title":"Model of the influencing factors of the withdrawal from rural homesteads in China: Application of Grounded theory method","volume":"85","author":"Cao","year":"2019","journal-title":"Land Use Policy"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"135","DOI":"10.2298\/PAN1601135H","article-title":"Policy implications and impact of household registration system on peasants\u2019 willingness to return rural residential lands: Evidence from household survey in rural China","volume":"63","author":"Xu","year":"2016","journal-title":"Panoeconomicus"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1213","DOI":"10.1073\/pnas.1812969116","article-title":"Socioecological informed use of remote sensing data to predict rural household poverty","volume":"116","author":"Watmough","year":"2019","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"891","DOI":"10.1016\/j.landusepol.2016.10.024","article-title":"Formalizing informal homes, a bad idea: The credibility thesis applied to China\u2019s \u201cextra-legal\u201d housing","volume":"79","author":"Sun","year":"2018","journal-title":"Land Use Policy"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"115","DOI":"10.1016\/j.rse.2017.03.019","article-title":"Use of partial-coverage UAV data in sampling for large scale forest inventories","volume":"194","author":"Puliti","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_11","first-page":"210","article-title":"Rapid Investigation of disaster situation in extreme disaster area of Jiuzhaigou earthquake in Sichuan based on UAV remote sensing","volume":"33","author":"Deng","year":"2018","journal-title":"J. Catastrophology"},{"key":"ref_12","first-page":"144","article-title":"A measure to the building density and floor area ratio of rural settlements based on Da Jiang unmanned aerial vehicle remote sensing","volume":"37","author":"Yang","year":"2019","journal-title":"Mt. Res."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"111705","DOI":"10.1016\/j.rse.2020.111705","article-title":"Developing a method to estimate building height from Sentinel-1 data","volume":"240","author":"Li","year":"2020","journal-title":"Remote Sens. Environ."},{"key":"ref_14","first-page":"11","article-title":"3D reconstruction of buildings with single UAV image","volume":"4","author":"Wang","year":"2004","journal-title":"Remote Sens. Inf."},{"key":"ref_15","first-page":"29","article-title":"Target detection of Rural Buildings in UAV remote sensing images based on convolutional neural network","volume":"19","author":"Ren","year":"2019","journal-title":"J. Nanjing Norm. Univ. (Eng. Technol. Ed.)"},{"key":"ref_16","first-page":"160","article-title":"Hollow village building detection method using high resolution remote sensing image based on CNN","volume":"48","author":"Li","year":"2017","journal-title":"Trans. Chin. Soc. Agric. Mach."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"2793","DOI":"10.1007\/s10489-018-01396-y","article-title":"Automatic crack detection for tunnel inspection using deep learning and heuristic image post-processing","volume":"49","author":"Protopapadakis","year":"2019","journal-title":"Appl. Intell."},{"key":"ref_18","unstructured":"Viola, P., and Jones, M. (2001, January 8\u201314). Rapid object detection using a boosted cascade of simple features. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2001, Kauai, HI, USA."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"129","DOI":"10.1016\/j.autcon.2019.04.005","article-title":"Computer vision-based concrete crack detection using U-net fully convolutional network","volume":"104","author":"Liu","year":"2019","journal-title":"Autom. Constr."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Navab, N., Hornegger, J., Wells, W.M., and Frangi, A.F. (2015, January 5\u20139). U-Net: Convolutional Networks for Biomedical Image Segmentation. Proceedings of the Medical Image Computing and Computer-Assisted Intervention\u2014MICCAI 2015, Munich, Germany.","DOI":"10.1007\/978-3-319-24553-9"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Papadomanolaki, M., Vakalopoulou, M., and Karantzalos, K. (2019). A novel object-based deep learning framework for semantic segmentation of very high-resolution remote sensing data comparison with convolutional and fully convolutional networks. Remote Sens., 11.","DOI":"10.3390\/rs11060684"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"2707","DOI":"10.1016\/j.procs.2010.04.304","article-title":"Jaccard index based availability prediction in enterprise grids","volume":"1","author":"Rahman","year":"2012","journal-title":"Procedia Comput. Sci."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"861","DOI":"10.1016\/j.patrec.2005.10.010","article-title":"An introduction to ROC analysis","volume":"27","author":"Fawcett","year":"2006","journal-title":"Pattern Recognit. Lett."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"105361","DOI":"10.1016\/j.cmpb.2020.105361","article-title":"Computer-aided diagnosis of breast ultrasound images using ensemble learning from convolutional neural networks","volume":"190","author":"Moon","year":"2020","journal-title":"Comput. Methods Programs Biomed."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Wallance, L., Lucieer, A., Malenovsky, Z., Truner, D., and Vopenka, P. (2016). Assessment of forest structure using two UAV techniques: A comparison of airborne laser scanning and structure from motion (SfM) point clouds. Forests, 7.","DOI":"10.3390\/f7030062"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Gonz\u00e1lez-Jaramillo, V., Fries, A., and Bendix, J. (2019). AGB estimation in a tropical mountain forest (TMF) by means of RGB and multispectral images using an unmanned aerial vehicle (UAV). Remote Sens., 11.","DOI":"10.3390\/rs11121413"},{"key":"ref_27","unstructured":"Agisoft (2014). Agisoft Photoscan UserManual, Agisoft LLC. Available online: http:\/\/www.agisoft.com\/downloads\/user-manuals."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"172","DOI":"10.1016\/j.biosystemseng.2018.10.018","article-title":"Mapping the 3D structure of almond trees using UAV acquired photogrammetric point clouds and object-based image analysis","volume":"176","author":"Castro","year":"2018","journal-title":"Biosyst. Eng."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"107034","DOI":"10.1016\/j.comnet.2019.107034","article-title":"A modular CNN-based building detector for remote sensing images","volume":"168","author":"Konstantinidis","year":"2019","journal-title":"Comput. Netw."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"38","DOI":"10.1016\/0924-2716(95)98236-S","article-title":"Towards automatic building extraction from high-resolution digital elevation models","volume":"50","author":"Weidner","year":"1995","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"112","DOI":"10.1016\/j.isprsjprs.2018.04.011","article-title":"Monitoring height and greenness of non-woody floodplain vegetation with UAV time series","volume":"141","author":"Wimala","year":"2018","journal-title":"ISPRS J. Photogram. Remote Sens."}],"container-title":["ISPRS International Journal of Geo-Information"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2220-9964\/9\/6\/403\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T09:41:07Z","timestamp":1760175667000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2220-9964\/9\/6\/403"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,6,20]]},"references-count":31,"journal-issue":{"issue":"6","published-online":{"date-parts":[[2020,6]]}},"alternative-id":["ijgi9060403"],"URL":"https:\/\/doi.org\/10.3390\/ijgi9060403","relation":{},"ISSN":["2220-9964"],"issn-type":[{"type":"electronic","value":"2220-9964"}],"subject":[],"published":{"date-parts":[[2020,6,20]]}}}