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UAV Imagery with Deep Learning Based Land Use Classification Dataset in Ciyutuo Village Practice


XU Yaotian1,2LI Jingzhong3XU Yueping1,2LI Hongqing1,4XUE Bing*1
1 Shenyang Institute of Applied Ecology,Chinese Academy of Sciences,Shenyang 110016,China2 University of Chinese Academy of Sciences,Beijing 100049,China3 College of Urban and Environmental Sciences,Xuchang University,Xuchang 461000,Henan,China4 Department of Circular Economy and Recycling Technology,Technical University of Berlin,Berlin 10623,Germany

DOI:10.3974/geodb.2024.06.10.V1

Published:Jun. 2024

Visitors:2252       Data Files Downloaded:20      
Data Downloaded:137.01 MB      Citations:

Key Words:

human settlement,courtyard structure,UAV imagery,Ciyutuo Village,Deep Learning

Abstract:

The construction of human settlement family-courtyard structure dataset plays a key role in the refined identification rural spatial structure and the promotion of comprehensive rural revitalization. UAV Imagery with Deep Learning Based Land Use Classification Dataset in Ciyutuo Village Practice was developed using UAV imagery in September 2022 with deep learning and artificial visual interpretation methods on the QGIS and Geoscene Pro platform. The dataset includes: (1) courtyard distribution data, including residential courtyards, industrial courtyards and abandoned courtyards; (2) building distribution data, including farm buildings, industrial buildings and abandoned buildings; (3) vector data of roads and farmland in residential areas; (4) typical courtyard structure classification atlas. The dataset is archived in .shp and .tif formats, consisting of 65 data files, with data size of 8.97 MB (Compressed to 1 file with 6.84 MB). The article based on the dataset will be published at Journal of Global Change Data & Discovery, 2024.

Foundation Item:

Chinese Academy of Sciences (XDA28060302, XDA28090300); National Natural Science Foundation of China (41971166)

Data Citation:

XU Yaotian, LI Jingzhong, XU Yueping, LI Hongqing, XUE Bing*. UAV Imagery with Deep Learning Based Land Use Classification Dataset in Ciyutuo Village Practice[J/DB/OL]. Digital Journal of Global Change Data Repository, 2024. https://doi.org/10.3974/geodb.2024.06.10.V1.

References:


     [1] Liu, Y. S. Research on the urban-rural integration and rural revitalization in the new era in China [J]. Acta Geographica Sinica, 2018, 73(4): 637-650.
     [2] Zhou, Y., Huang, H., Liu, Y. S. The spatial distribution characteristics and influencing factors of Chinese villages [J]. Acta Geographica Sinica, 2020, 75(10): 2206-2223.
     [3] Xue, B., Dong, S. H., Lu, C. P., et al. Visible comparison of local planning and policies on rural revitalization [J]. Journal of Liaoning University (Natural Sciences Edition), 2019, 46(1): 1-9.
     [4] Zhou, Z. K., Zhang, C., Li, B. Z., et al. Research on optimization of rural human settlement space based on resource metabolism mechanism: A case study of ecological villages in Shandong Province [J]. Urban Development Studies, 2022, 29(6): 8-14.
     [5] Huang, J. Y., Cheng, G. Symbiotic space creation, Huiyu village, Shanxi province [J]. Planners, 2017, 33(3): 96-101.
     [6] Zhang, X. R., Yang, H. Establishing rural settlement basic unit for modern agricultural production [J]. Planners, 2021, 37(24): 5-12.
     [7] Xiong, Y., Huang, L. H., Zou, F., et al. Multifunctional spatial characteristics of rural areas and their type identification based on county scale: A Case of Hunan province [J]. Economic Geography, 2021, 41(6): 162-170.
     [8] Lei, Z. D., Yang, Y., Tian, H. Research on the technology for improving the living space performance of the elderly in residential buildings [J]. World Architecture, 2020(11): 98-103.
     [9] Shi, Y. Z., Zhao, L. L., Zhao, X. Y., et al. Spatiotemporal evolution and mechanism of rural transformation: a case study of Yuzhong county in Gansu province [J]. Progress in Geography, 2022, 41(12): 2311-2326.
     [10] Liang, X. Y., Jin, X. B., Sun, R., et al. Optimal allocation of land resources and its key issues from a perspective of food security [J]. Journal of Natural Resources, 2021, 36(12): 3031-3053.
     [11] Chen, Y., He, Y. H., Wu, X. Evaluation of rural sustainability and analysis of influencing factors in the New Era: Taking the Dongting Lake area of Hunan Province as an example [J]. Journal of Natural Science of Hunan Normal University, 2022, 45(2): 12-21.
     [12] Wang, Y. F., Li, T. T., Meng, X. T. Evaluation of China's rural human settlements quality and its spatiotemporal change characteristics from 2010 to 2020 [J]. Geographical Research, 2022, 41(12): 3245-3258.
     [13] Yang, S. C., Wu, Y. C., Chen, X. Y. Farmers' payment preferences and willingness for ecosystem services and influencing factors: Based on the survey data of farmers in Dali County, Shaanxi Province [J]. Environmental Protection Science, 2023, 49(2): 50-57.
     [14] Xue, B., Zhao, B. Y., Xiao, X., et al. A POI data-based study on urban functional areas of the resources-based city: A case study of Benxi, Liaoning [J]. Human Geography, 2020, 35(4): 81-90.
     [15] Zhang, L. Q., Geng, H., Liu, Y. S., et al. Spatial-temporal characteristics of rural settlements evolution in China [J]. Journal of Tongji University (Natural Science), 2022, 50(7): 967-974.
     [16] Yue, X. P., Guo, H. X., Li, D. Development and spatial layout of ecovillage in Tianjin [J]. Building Energy Efficiency, 2016, 44(3): 53-56.
     [17] Wei, B. P., Li, X. H. Talking about the energy-saving roof [J]. Scientific and Technological Information (Academic Research), 2008(6): 273.
     [18] Miao, H. M. Research on thermal insulation system of energy-saving roof in the dwelling house of villages and small towns [D]. Dalian: Dalian University of Technology, 2009.
     [19] Baccini, P., Brunner, P. H. Metabolism of the anthroposphere: analysis, evaluation, design [M]. The MIT Press, 2012.
     [20] Cui, Y. F., Wang, M. N. The status quo, problems and suggestions of the coordinated development of agricultural industry in Shenyang economic zone [J]. Agricultural Economy, 2023, 433(5): 23-24.
     

Data Product:

ID Data Name Data Size Operation
1 VillageCiyutuo_2022.rar 7014.83KB
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