The role of harmonized Landsat Sentinel-2 (HLS) products to reveal multiple trajectories and determinants of cropland abandonment in subtropical mountainous areas

被引:18
作者
Hong, Changqiao [1 ,2 ,3 ]
V. Prishchepov, Alexander [3 ]
Jin, Xiaobin [1 ]
Han, Bo [1 ]
Lin, Jinhuang [1 ]
Liu, Jingping [1 ]
Ren, Jie [4 ]
Zhou, Yinkang [1 ]
机构
[1] Nanjing Univ, Sch Geog & Ocean Sci, Nanjing 210023, Peoples R China
[2] Minist Nat Resources, Key Lab Coastal Zone Exploitat & Protect, Nanjing 210023, Peoples R China
[3] Univ Copenhagen, Dept Geosci & Nat Resources Management IGN, Oster Voldgade 10, DK-1350 Kobenhavn K, Denmark
[4] Guilin Univ Elect Technol, Sch Artificial Intelligence, Guilin 541004, Peoples R China
基金
中国国家自然科学基金;
关键词
Cropland abandonment; Satellite remote sensing; Support vector machines; Redundancy analysis (RDA); Rural landscape; FARMLAND ABANDONMENT; IMAGE CLASSIFICATION; TIME-SERIES; DRIVERS; CHINA; NDVI; RECULTIVATION; TRANSITION; LANDSCAPES; RESPONSES;
D O I
10.1016/j.jenvman.2023.117621
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Cropland abandonment is a widespread land-change process globally, which can stem from the accelerated outmigration of the population from rural to urban areas, socio-economic and political changes, catastrophes, and other trigger events. Clouds limit the utility of optical satellite data to monitor cropland abandonment in highly fragmented mountain agricultural landscapes of tropical and subtropical regions, including the south of China. Taking Nanjing County of China as an example, we developed a novel approach by utilizing multisource satellite (Landsat and Sentinel-2) imagery to map multiple trajectories of cropland abandonment (transitioning from cropland to grassland, shrubs and forest) in subtropical mountainous landscapes. Then, we employed a redundancy analysis (RDA) to identify the spatial association of cropland abandonment considering agricultural productivity, physiography, locational characteristics and economic factors. Results indicate the great suitability of harmonized Landsat 8 and Sentinel-2 images to distinguish multiple trajectories of cropland abandonment in subtropical mountainous areas. Our framework of mapping cropland abandonment resulted in good producer's (78.2%) and user's (81.3%) accuracies. The statistical analysis showed 31.85% of croplands cultivated in 2000 were abandoned by 2018, and more than a quarter of townships experienced cropland abandonment with high abandoned rates (>38%). Cropland abandonment mainly occurred in relatively unfavorable areas for agricul-tural production, for instance with a slope above 6 degrees. Slope and the proximity to the nearest settlement explained 65.4% and 8.1% of the variation of cropland abandonment at the township level, respectively. The developed approaches on both mapping cropland abandonment and modeling determinants can be highly relevant to monitor multiple trajectories of cropland abandonment and ascribe their determinants not only in mountainous China but also elsewhere and thus promote the formulation of land-use policies that aim to steer cropland abandonment.
引用
收藏
页数:13
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