Spatio-temporal characteristics and driving factors of cultivated land change in various agricultural regions of China: A detailed analysis based on county-level data

被引:16
作者
Li, Xia [1 ]
Zhang, Xiaohan [1 ]
Jin, Xianghao [1 ]
机构
[1] Changan Univ, Coll Land Engn, Xian 710054, Peoples R China
关键词
Change of time and space; Driving mechanism; GWR model; The county scale; SPATIAL-PATTERNS;
D O I
10.1016/j.ecolind.2024.112485
中图分类号
X176 [生物多样性保护];
学科分类号
090705 ;
摘要
The agricultural sector constitutes a pivotal component of China's economy. Considering China's substantial population, alterations in cultivated land hold considerable potential to influence agricultural output, consequently impacting the livelihoods of a substantial portion of the populace. Therefore, understanding the dynamics of cultivated land is crucial for ensuring food security.From 2000 to 2020, this research amalgamates county-level land cover, environmental variables, and socio-economic indicators to examine the spatiotemporal dynamics of cultivated land expansion across diverse agricultural sectors in China, elucidating associated causal factors. The following deduction is presented: (1) Variations in the extent of cultivated land exhibit diversity across distinct agricultural regions. It has spatial heterogeneity. (2) From 2000 to 2020, among China's nine primary agricultural regions, those east of the Hu Line mainly experienced an expansion trend in cultivated land. The intensity of cultivated land expansion was highest in the northern arid and semi-arid regions, followed by the Qinghai-Tibet Plateau, albeit with a predominant slow expansion. In the agricultural areas west of the Hu line, except for the Northeast Plain, the expansion intensity of cultivated land was not significant, and the cultivated land was mainly contracted, with a patchy distribution. (3) Both natural and socio-economic factors influence cultivated land changes in China. Altitude and precipitation stand out as the dominant natural influencers, whereas within the realm of socio-economic considerations, population density, the disposable income per capita among rural inhabitants, the total power of agricultural machinery, the gross value of primary industry output, and the total power of agricultural machinery collectively exert influence on alterations in cultivated land. Different indicators have varying positive or negative effects on cultivated land.
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页数:12
相关论文
共 51 条
[1]   Spatial analysis of factors affecting fertilizer use efficiency in China: an empirical study based on geographical weighted regression model [J].
Bai, Xiuguang ;
Zhang, Tianwen ;
Tian, Shujuan ;
Wang, Yanan .
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH, 2021, 28 (13) :16663-16681
[2]   Spatial-temporal characteristics and influencing factors of farmland expansion in different agricultural regions of Heilongjiang Province, China [J].
Chen, Hang ;
Meng, Fei ;
Yu, Zhenning ;
Tan, Yongzhong .
LAND USE POLICY, 2022, 115
[3]   Spatio-temporal evolution of the early-warning status of cultivated land and its driving factors: A case study of Heilongjiang Province, China [J].
Chen, Lili ;
Song, Ge ;
Meadows, Michael E. ;
Zou, Chaohui .
LAND USE POLICY, 2018, 72 :280-292
[4]   The spatial association of ecosystem services with land use and land cover change at the county level in China, 1995-2015 [J].
Chen, Wanxu ;
Chi, Guangqing ;
Li, Jiangfeng .
SCIENCE OF THE TOTAL ENVIRONMENT, 2019, 669 :459-470
[5]  
CHENG X, 1992, WORLD DEV, V20, P1127, DOI 10.1016/0305-750X(92)90005-G
[6]   Spatio-Temporal Analysis of Cultivated Land from 2010 to 2020 in Long'an County, Karst Region, China [J].
Dong, Jianhui ;
Yun, Wenju ;
Wu, Kening ;
Li, Shaoshuai ;
Liu, Bingrui ;
Lu, Qiaoyuan .
LAND, 2023, 12 (02)
[7]   The carbon emission reduction effect of agricultural policy--Evidence from China [J].
Du, Yingying ;
Liu, Haibin ;
Huang, Hui ;
Li, Xiaohan .
JOURNAL OF CLEANER PRODUCTION, 2023, 406
[8]   Cropland abandonment in China: Patterns, drivers, and implications for food security [J].
Guo, Andong ;
Yue, Wenze ;
Yang, Jun ;
Xue, Bing ;
Xiao, Wu ;
Li, Mengmeng ;
He, Tingting ;
Zhang, Maoxin ;
Jin, Xin ;
Zhou, Qiushi .
JOURNAL OF CLEANER PRODUCTION, 2023, 418
[9]   Identifying the spatiotemporal dynamic of PM2.5 concentrations at multiple scales using geographically and temporally weighted regression model across China during 2015-2018 [J].
Guo, Bin ;
Wang, Xiaoxia ;
Pei, Lin ;
Su, Yi ;
Zhang, Dingming ;
Wang, Yan .
SCIENCE OF THE TOTAL ENVIRONMENT, 2021, 751
[10]   Estimating ground-level PM2.5 concentrations in Beijing using a satellite-based geographically and temporally weighted regression model [J].
Guo, Yuanxi ;
Tang, Qiuhong ;
Gong, Dao-Yi ;
Zhang, Ziyin .
REMOTE SENSING OF ENVIRONMENT, 2017, 198 :140-149