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Annual 30-m land use/land cover maps of China for 1980-2015 from the integration of AVHRR, MODIS and Landsat data using the BFAST algorithm

文献类型：期刊论文

作者Xu, Yidi3; Yu, Le3,4; Peng, Dailiang5; Zhao, Jiyao3; Cheng, Yuqi3; Liu, Xiaoxuan3; Li, Wei3; Meng, Ran1; Xu, Xinliang2; Gong, Peng3,4
刊名SCIENCE CHINA-EARTH SCIENCES
出版日期2020-05-19
页码18
ISSN号1674-7313
关键词Land use land cover (LULC) Breaks for Additive Seasonal and Trend (BFAST) Change detection Annual China
DOI10.1007/s11430-019-9606-4
通讯作者Yu, Le(leyu@tsinghua.edu.cn)
英文摘要Annual land use land cover (LULC) change information at medium spatial resolution (i.e. at 30 m) is required in numerous subjects, such as biophysical modelling, land management and global change studies. Annual LULC information, however, is usually not available at continental or national scale due to reasons such as insufficient remote sensing data coverage or lack of computational capabilities. Here we integrate high temporal resolution and coarse spatial resolution satellite images (i.e., Moderate Resolution Imaging Spectroradiometer (MODIS) and Global Inventory Modelling and Mapping Studies (GIMMS) normalized difference vegetation index (NDVI)) with high spatial resolution datasets (China's Land-Use/cover Datasets (CLUDs) derived from 30-meter Landsat TM/ETM+/OLI) to generate reliable annual nominal 30 m LULC maps for the whole of China between 1980 and 2015. We also test the performance of a statistical based change detection algorithm (Breaks for Additive Seasonal and Trend), originally designed for tracking forest change, in classifying all-type LULC change. As a result, a nominal 30 m annual land use/land cover datasets (CLUD-A) from 1980 to 2015 was developed for the whole China. The mapping results were assessed with a change sample dataset, a regional annual validation sample set and a three-year China sample set. Of the detected change years, 75.61% matched the exact time of conversion within +/- 1 year. Annual mapping results provided a detail process of urbanization, deforestation, afforestation, water and cropland dynamics over the past 36 years. The consistent characterization of land change dynamics for China can be further used in scientific research and to support land management for policy-makers.
WOS关键词TIME-SERIES ; GRASSLAND DEGRADATION ; CROPLAND CHANGES ; SAMPLE SET ; DYNAMICS ; PATTERNS ; DISTURBANCE ; TRACKING ; TRENDS ; IMAGES
资助项目National Key R&D Program of China[2017YFA0604401] ; National Key R&D Program of China[2019YFA0606601] ; Tsinghua University Initiative Scientific Research Program[2019Z02CAU] ; Youth Innovation Promotion Association, Chinese Academy of Sciences[Y4YR1300QM]
WOS研究方向Geology
语种英语
出版者SCIENCE PRESS
WOS记录号WOS:000534729600001
资助机构National Key R&D Program of China ; Tsinghua University Initiative Scientific Research Program ; Youth Innovation Promotion Association, Chinese Academy of Sciences
源URL[http://ir.igsnrr.ac.cn/handle/311030/159620]  
专题中国科学院地理科学与资源研究所
通讯作者Yu, Le
作者单位1.Huazhong Agr Univ, Coll Nat Resources & Environm, Wuhan 430070, Peoples R China
2.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China
3.Tsinghua Univ, Dept Earth Syst Sci, Minist Educ, Key Lab Earth Syst Modeling, Beijing 100084, Peoples R China
4.Minist Educ Ecol Field Stn East Asian Migratory B, Beijing 100084, Peoples R China
5.Chinese Acad Sci, Inst Remote Sensing & Digital Earth, Key Lab Digital Earth Sci, Beijing 100094, Peoples R China
推荐引用方式
GB/T 7714		 Xu, Yidi,Yu, Le,Peng, Dailiang,et al. Annual 30-m land use/land cover maps of China for 1980-2015 from the integration of AVHRR, MODIS and Landsat data using the BFAST algorithm[J]. SCIENCE CHINA-EARTH SCIENCES,2020:18.
APA Xu, Yidi.,Yu, Le.,Peng, Dailiang.,Zhao, Jiyao.,Cheng, Yuqi.,...&Gong, Peng.(2020).Annual 30-m land use/land cover maps of China for 1980-2015 from the integration of AVHRR, MODIS and Landsat data using the BFAST algorithm.SCIENCE CHINA-EARTH SCIENCES,18.
MLA Xu, Yidi,et al."Annual 30-m land use/land cover maps of China for 1980-2015 from the integration of AVHRR, MODIS and Landsat data using the BFAST algorithm".SCIENCE CHINA-EARTH SCIENCES (2020):18.

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来源：地理科学与资源研究所

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