{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,9]],"date-time":"2026-06-09T05:54:00Z","timestamp":1780984440178,"version":"3.54.1"},"reference-count":53,"publisher":"MDPI AG","issue":"19","license":[{"start":{"date-parts":[[2022,10,5]],"date-time":"2022-10-05T00:00:00Z","timestamp":1664928000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41930648"],"award-info":[{"award-number":["41930648"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["KYCX22_1587"],"award-info":[{"award-number":["KYCX22_1587"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["KF-2020-05-025"],"award-info":[{"award-number":["KF-2020-05-025"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Postgraduate Research &amp; Practice Innovation Program of Jiangsu Province","award":["41930648"],"award-info":[{"award-number":["41930648"]}]},{"name":"Postgraduate Research &amp; Practice Innovation Program of Jiangsu Province","award":["KYCX22_1587"],"award-info":[{"award-number":["KYCX22_1587"]}]},{"name":"Postgraduate Research &amp; Practice Innovation Program of Jiangsu Province","award":["KF-2020-05-025"],"award-info":[{"award-number":["KF-2020-05-025"]}]},{"name":"Open Fund of Key Laboratory of Urban Land Resources Monitoring and Simulation, Ministry of Natural Resources","award":["41930648"],"award-info":[{"award-number":["41930648"]}]},{"name":"Open Fund of Key Laboratory of Urban Land Resources Monitoring and Simulation, Ministry of Natural Resources","award":["KYCX22_1587"],"award-info":[{"award-number":["KYCX22_1587"]}]},{"name":"Open Fund of Key Laboratory of Urban Land Resources Monitoring and Simulation, Ministry of Natural Resources","award":["KF-2020-05-025"],"award-info":[{"award-number":["KF-2020-05-025"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Accurate and timely access to building rooftop information is very important for urban management. The era of big data brings new opportunities for rooftop extraction based on deep learning and high-resolution satellite imagery. However, collecting representative datasets from such big data to train deep learning models efficiently is an essential problem that still needs to be explored. In this study, geospatial stratified and optimized sampling (GSOS) based on geographical priori information and optimization of sample spatial location distribution is proposed to acquire representative samples. Specifically, the study area is stratified based on land cover to divide the rooftop-dense stratum and the rooftop-sparse stratum. Within each stratum, an equal amount of samples is collected and their spatial locations are optimized. To evaluate the effectiveness of the proposed strategy, several qualitive and quantitative experiments are conducted. As a result, compared with other common sampling approaches (e.g., random sampling, stratified random sampling, and optimized sampling), GSOS is superior in terms of the abundance and types of collected samples. Furthermore, two quantitative metrics, the F1-score and Intersection over Union (IoU), are reported for rooftop extraction based on deep learning methods and different sampling methods, in which the results based on GSOS are on average 9.88% and 13.20% higher than those based on the other sampling methods, respectively. Moreover, the proposed sampling strategy is able to obtain representative training samples for the task of building rooftop extractions and may serve as a viable method to alleviate the labour-intensive problem in the construction of rooftop benchmark datasets.<\/jats:p>","DOI":"10.3390\/rs14194961","type":"journal-article","created":{"date-parts":[[2022,10,10]],"date-time":"2022-10-10T03:07:28Z","timestamp":1665371248000},"page":"4961","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Improving the Performance of Automated Rooftop Extraction through Geospatial Stratified and Optimized Sampling"],"prefix":"10.3390","volume":"14","author":[{"given":"Zhuo","family":"Sun","sequence":"first","affiliation":[{"name":"The Key Laboratory of Virtual Geographic Environment (Ministry of Education of PRC), Nanjing Normal University, Nanjing 210023, China"},{"name":"The State Key Laboratory Cultivation Base of Geographical Environment Evolution, Nanjing 210023, China"},{"name":"The Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3898-0863","authenticated-orcid":false,"given":"Zhixin","family":"Zhang","sequence":"additional","affiliation":[{"name":"The School of Geography and Ocean Science, Nanjing University, Nanjing 210023, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8922-8789","authenticated-orcid":false,"given":"Min","family":"Chen","sequence":"additional","affiliation":[{"name":"The Key Laboratory of Virtual Geographic Environment (Ministry of Education of PRC), Nanjing Normal University, Nanjing 210023, China"},{"name":"The State Key Laboratory Cultivation Base of Geographical Environment Evolution, Nanjing 210023, China"},{"name":"The Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China"},{"name":"The Jiangsu Provincial Key Laboratory for NSLSCS, School of Mathematical Science, Nanjing Normal University, Nanjing 210023, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0423-7430","authenticated-orcid":false,"given":"Zhen","family":"Qian","sequence":"additional","affiliation":[{"name":"The Key Laboratory of Virtual Geographic Environment (Ministry of Education of PRC), Nanjing Normal University, Nanjing 210023, China"},{"name":"The State Key Laboratory Cultivation Base of Geographical Environment Evolution, Nanjing 210023, China"},{"name":"The Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0852-4074","authenticated-orcid":false,"given":"Min","family":"Cao","sequence":"additional","affiliation":[{"name":"The Key Laboratory of Virtual Geographic Environment (Ministry of Education of PRC), Nanjing Normal University, Nanjing 210023, China"},{"name":"The Key Laboratory of Urban Land Resources Monitoring and Simulation, Ministry of Natural Resources, Shenzhen 518034, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yongning","family":"Wen","sequence":"additional","affiliation":[{"name":"The Key Laboratory of Virtual Geographic Environment (Ministry of Education of PRC), Nanjing Normal University, Nanjing 210023, China"},{"name":"The State Key Laboratory Cultivation Base of Geographical Environment Evolution, Nanjing 210023, China"},{"name":"The Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,10,5]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"665","DOI":"10.1080\/13658810410001702030","article-title":"Assessing the worldwide developments of national spatial data clearinghouses","volume":"18","author":"Crompvoets","year":"2004","journal-title":"Int. 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