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

doi:10.1016/j.jia.2023.06.005

Journal of Integrative Agriculture

2024, Vol. 23

Issue (1): 283-297 DOI: 10.1016/j.jia.2023.06.005

Agro-ecosystem & Environment

Advanced Online Publication | Current Issue | Archive | Adv Search

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

Jie Xue¹, Xianglin Zhang², Songchao Chen^{2, 3}, Bifeng Hu^{4, 5}, Nan Wang², Zhou Shi^{2, 6#}

¹Department of Land Management, Zhejiang University, Hangzhou 310058, China

²Institute of Applied Remote Sensing and Information Technology, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China

³ 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

⁵ Key Laboratory of Data Science in Finance and Economics, Jiangxi University of Finance and Economics, Nanchang 330013, China

⁶ Key Laboratory of Spectroscopy Sensing, Ministry of Agriculture and Rural Affairs, Hangzhou 310058, China

Abstract
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摘要

随着遥感技术的发展，在过去的十几年中出现大量土地利用和土地覆盖（LULC）产品。然而，各种LULC产品的分类体系存在差异，尚缺乏在统一框架下评估各产品中耕地分类精度的研究。因此，本研究以FAO的分类体系为标准，统一四种常用的全球LULC产品（即MCD12Q1 V6、GlobCover2009、FROM-GLC和GlobeLand30）的耕地分类体系，评估各产品中耕地分类的空间分布一致性与准确性和面积的准确性，并量化坡度、海拔、田块面积和耕作制度与耕地空间分布一致性的关系。结果表明，在空间分布的准确性方面，MCD12Q1和GlobeLand30表现良好，总体准确率分别为94.90和93.52%；FROM-GLC表现最差，总体准确率为83.17%。在空间分布的一致性方面，四种LULC产品的耕地像元完全一致和不一致的比例分别为15.51和44.72%。高度一致性区域主要出现在东北平原、黄淮海平原和中下游长江平原北部，低度一致性区域主要出现在华北半干旱区东部边缘、云贵高原和华南地区。田块面积是影响耕地制图的核心因素。在面积准确性方面，与《中国统计年鉴》数据对比，各产品在省级尺度的面积准确性从高到低依次为：GlobeLand30、FROM-GLC、MCD12Q1和GlobCover2009。耕地分类体系的不同是造成四种产品间面积偏差、空间分布和面积准确性差异主要的原因。本研究为国家及省级尺度耕地产品选择提供数据支撑，为进一步提升耕地制图精度提供理论参考。本研究结果有助于粮食安全和作物管理相关研究的开展，对实现联合国提出的可持续发展目标意义重大。

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.

Keywords: global LULC products cropland mapping accuracy evaluation food security China

Received: 16 February 2023 Accepted: 08 May 2023

Fund:

This study was supported by the National Key Research and Development Program of China (2022YFB3903503), the National Natural Science Foundation of China (U1901601), and the Science and Technology Project of the Department of Education of Jiangxi Province, China (GJJ210541)

About author: Jie Xue, E-mail: xj2019@zju.edu.cn; #Correspondence Zhou Shi, E-mail: shizhou@zju.edu.cn

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Jie Xue, Xianglin Zhang, Songchao Chen, Bifeng Hu, Nan Wang, Zhou Shi. 2024.

Quantifying the agreement and accuracy characteristics of four satellite-based LULC products for cropland classification in China . Journal of Integrative Agriculture, 23(1): 283-297.

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