Quantifying the agreement and accuracy characteristics of four satellite-based LULC products for cropland classification in China

Jie Xue ¹Xianglin Zhang ²Songchao Chen ³Bifeng Hu ⁴Nan Wang ²Zhou Shi⁵

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作者信息

1. Department of Land Management,Zhejiang University,Hangzhou 310058,China
2. Institute of Applied Remote Sensing and Information Technology,College of Environmental and Resource Sciences,Zhejiang University,Hangzhou 310058,China
3. Institute of Applied Remote Sensing and Information Technology,College of Environmental and Resource Sciences,Zhejiang University,Hangzhou 310058,China;ZJU-Hangzhou Global Scientific and Technological Innovation Center,Zhejiang University,Hangzhou 311215,China
4. Department of Land Resource Management,School of Public Finance and Public Administration,Jiangxi University of Finance and Economics,Nanchang 330013,China;Key Laboratory of Data Science in Finance and Economics,Jiangxi University of Finance and Economics,Nanchang 330013,China
5. Institute of Applied Remote Sensing and Information Technology,College of Environmental and Resource Sciences,Zhejiang University,Hangzhou 310058,China;Key Laboratory of Spectroscopy Sensing,Ministry of Agriculture and Rural Affairs,Hangzhou 310058,China
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Abstract

Various land use and land cover(LULC)products have been produced over the past decade with the development of remote sensing technology.Despite the differences in LULC classification schemes,there is a lack of research on assessing the accuracy of their application to croplands in a unified framework.Thus,this study evaluated the spatial and area accuracies of cropland classification for four commonly used global LULC products(i.e.,MCD12Q1 V6,GlobCover2009,FROM-GLC and GlobeLand30)based on the harmonised FAO criterion,and quantified the relationships between four factors(i.e.,slope,elevation,field size and crop system)and cropland classification agreement.The validation results indicated that MCD12Q1 and GlobeLand30 performed well in cropland classification regarding spatial consistency,with overall accuracies of 94.90 and 93.52%,respectively.The FROM-GLC showed the worst performance,with an overall accuracy of 83.17%.Overlaying the cropland generated by the four global LULC products,we found the proportions of complete agreement and disagreement were 15.51 and 44.72%for the cropland classification,respectively.High consistency was mainly observed in the Northeast China Plain,the Huang-Huai-Hai Plain and the northern part of the Middle-lower Yangtze Plain,China.In contrast,low consistency was detected primarily on the eastern edge of the northern and semiarid region,the Yunnan-Guizhou Plateau and southern China.Field size was the most important factor for mapping cropland.For area accuracy,compared with China Statistical Yearbook data at the provincial scale,the accuracies of different products in descending order were:GlobeLand30,FROM-GLC,MCD12Q1,and GlobCover2009.The cropland classification schemes mainly caused large area deviations among the four products,and they also resulted in the different ranks of spatial accuracy and area accuracy among the four products.Our results can provide valuable suggestions for selecting cropland products at the national or provincial scale and help cropland mapping and reconstruction,which is essential for food security and crop management,so they can also contribute to achieving the Sustainable Development Goals issued by the United Nations.

Key words

global LULC products/cropland mapping/accuracy evaluation/food security/China

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基金项目

National Key Research and Development Program of China(2022YFB3903503)

National Natural Science Foundation of China(U1901601)

Science and Technology Project of the Department of Education of Jiangxi Province,China(GJJ210541)

出版年

2024

农业科学学报(英文)

中国农业科学院农业信息研究所

农业科学学报(英文)

CSTPCD

影响因子：0.576

ISSN：2095-3119

参考文献量3

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