Integrating remote sensing temporal trajectory and survey statistics to update land use/land cover maps
Remote sensing and land resource surveys have been used in recent decades for land use/land cover (LULC) mapping; however, keeping the developed LULC up-to-date and consistent with land survey statistics remains challenging. This study developed a practical and effective framework to automatically u...
| Main Authors: | , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2023-12-01
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| Series: | International Journal of Digital Earth |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.1080/17538947.2023.2274422 |
| _version_ | 1797640955126349824 |
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| author | Zhenrong Du Le Yu Xiyu Li Jiyao Zhao Xin Chen Yidi Xu Peng Yang Jianyu Yang Dailiang Peng Yueming Xue Peng Gong |
| author_facet | Zhenrong Du Le Yu Xiyu Li Jiyao Zhao Xin Chen Yidi Xu Peng Yang Jianyu Yang Dailiang Peng Yueming Xue Peng Gong |
| author_sort | Zhenrong Du |
| collection | DOAJ |
| description | Remote sensing and land resource surveys have been used in recent decades for land use/land cover (LULC) mapping; however, keeping the developed LULC up-to-date and consistent with land survey statistics remains challenging. This study developed a practical and effective framework to automatically update existing LULC products and bridge the gap between remote sensing classification results and land survey data. This study employed Landsat imagery time series, change detection algorithms, sample migration, and random forests to develop a framework for updating existing LULC products in China from 1980–2015 to 1980–2022. The updated LULC maps reflect the post-2015 LULC changes well and maintain continuity with the pre-2015 products. Additionally, a statistical space allocation method based on the minimum cross-entropy strategy was proposed to optimize the LULC maps, increasing the correlation coefficient (r) with China’s second and third national land survey statistics from 0.41–0.89 to 0.86–0.99. Thus, the framework and products developed in this study provide valuable tools for sustainable land use and policy planning. |
| first_indexed | 2024-03-11T13:38:37Z |
| format | Article |
| id | doaj.art-abde08e3dbb343119a81cc7e2d363f21 |
| institution | Directory Open Access Journal |
| issn | 1753-8947 1753-8955 |
| language | English |
| last_indexed | 2024-03-11T13:38:37Z |
| publishDate | 2023-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | International Journal of Digital Earth |
| spelling | doaj.art-abde08e3dbb343119a81cc7e2d363f212023-11-02T14:47:05ZengTaylor & Francis GroupInternational Journal of Digital Earth1753-89471753-89552023-12-011624428444510.1080/17538947.2023.22744222274422Integrating remote sensing temporal trajectory and survey statistics to update land use/land cover mapsZhenrong Du0Le Yu1Xiyu Li2Jiyao Zhao3Xin Chen4Yidi Xu5Peng Yang6Jianyu Yang7Dailiang Peng8Yueming Xue9Peng Gong10Tsinghua UniversityTsinghua UniversityTsinghua UniversityTsinghua UniversityShanxi UniversityUniversite Paris-SaclayChinese Academy of Agricultural SciencesChina Agricultural UniversityChinese Academy of SciencesChina Institute of Geo-Environmental MonitoringMinistry of Education Ecological Field Station for East Asian Migratory BirdsRemote sensing and land resource surveys have been used in recent decades for land use/land cover (LULC) mapping; however, keeping the developed LULC up-to-date and consistent with land survey statistics remains challenging. This study developed a practical and effective framework to automatically update existing LULC products and bridge the gap between remote sensing classification results and land survey data. This study employed Landsat imagery time series, change detection algorithms, sample migration, and random forests to develop a framework for updating existing LULC products in China from 1980–2015 to 1980–2022. The updated LULC maps reflect the post-2015 LULC changes well and maintain continuity with the pre-2015 products. Additionally, a statistical space allocation method based on the minimum cross-entropy strategy was proposed to optimize the LULC maps, increasing the correlation coefficient (r) with China’s second and third national land survey statistics from 0.41–0.89 to 0.86–0.99. Thus, the framework and products developed in this study provide valuable tools for sustainable land use and policy planning.http://dx.doi.org/10.1080/17538947.2023.2274422land useland coverchange detectionland surveystatistical constraints |
| spellingShingle | Zhenrong Du Le Yu Xiyu Li Jiyao Zhao Xin Chen Yidi Xu Peng Yang Jianyu Yang Dailiang Peng Yueming Xue Peng Gong Integrating remote sensing temporal trajectory and survey statistics to update land use/land cover maps International Journal of Digital Earth land use land cover change detection land survey statistical constraints |
| title | Integrating remote sensing temporal trajectory and survey statistics to update land use/land cover maps |
| title_full | Integrating remote sensing temporal trajectory and survey statistics to update land use/land cover maps |
| title_fullStr | Integrating remote sensing temporal trajectory and survey statistics to update land use/land cover maps |
| title_full_unstemmed | Integrating remote sensing temporal trajectory and survey statistics to update land use/land cover maps |
| title_short | Integrating remote sensing temporal trajectory and survey statistics to update land use/land cover maps |
| title_sort | integrating remote sensing temporal trajectory and survey statistics to update land use land cover maps |
| topic | land use land cover change detection land survey statistical constraints |
| url | http://dx.doi.org/10.1080/17538947.2023.2274422 |
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