Assessing the suitability of FROM-GLC10 data for understanding agricultural ecosystems in China: Beijing as a case study
文献类型： 外文期刊
作者： Dong, Shiwei 1 ; Gao, Bingbo 2 ; Pan, Yuchun 1 ; Li, Ruiyuan 3 ; Chen, Ziyue 3 ;
作者机构： 1.Beijing Acad Agr & Forestry Sci, Beijing Res Ctr Informat Technol Agr, Beijing, Peoples R China
2.China Agr Univ, Coll Land Sci & Technol, Beijing, Peoples R China
3.Beijing Normal Univ, Coll Global Change & Earth Syst Sci, Beijing 100875, Peoples R China
期刊名称：REMOTE SENSING LETTERS （ 影响因子：2.583； 五年影响因子：2.601 ）
ISSN： 2150-704X
年卷期： 2020 年 11 卷 1 期
页码：
收录情况： SCI
摘要： The first 10 m resolution global land-cover map, FROM-GLC10 was released in early March 2019. Due to its high spatial resolution and reliable global accuracy, we evaluated the suitability of FROM-GLC10 data for understanding agricultural ecosystems in Beijing using a comparable vector data set, Google Earth images and field survey data. The overall accuracy (OA) for FROM-GLC10 based on three data sets was 71.08%, 79.63% and 80.36%, respectively. Meanwhile, there were notable misclassifications between cropland, grassland and forest. The limited accuracy for these vegetation types might be attributed to the spatially mixed vegetation structures, seasonal variations of vegetation and the temporal inconsistence between Landsat and Sentinel data set. Due to its satisfactory OA, FROM-GLC10 data have the potential to be widely employed for evaluating the progress of large-scale ecological restoration projects. On the other hand, the data producers, who can pre-set and classify some customized land-cover types, consider time-series analysis and big data fusion methods and conduct large-scale verification, and data users, who can integrate different data sources, should work together to enhance the suitability and reliability of FROM-GLC10 data for understanding agricultural ecosystems in China.
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