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author:

Li, L. (Li, L..) [1] | Zheng, S. (Zheng, S..) [2] | Zhao, K. (Zhao, K..) [3] | Shen, K. (Shen, K..) [4] | Yan, X. (Yan, X..) [5] | Zhao, Y. (Zhao, Y..) [6]

Indexed by:

Scopus

Abstract:

In the past two decades, the Ministry of Agriculture and Rural Affairs of China (MARA) has issued a series of strict cultivated land protection policies to prevent the spread of farmland abandonment and maintain a dynamic balance between the quantity and quality of arable land. However, high-speed economic development, strict arable land protection policies, and ecological security and sustainable development strategies interacting with human activities have brought challenges to quantifying the effectiveness of arable land protection policies. In this study, we proposed a method to quantify the impacts of the arable land protection policies and evaluate the quantitative impacts on farmland abandonment in Guangdong Province after 2014 from the perspective of landscape ecology. The results illustrated that the landscape fragmentation of farmland abandonment in Guangdong Province decreased after the new arable land policies were issued. More annual farmland abandonment (AFA) shifted to seasonal farmland abandonment (SFA), revealing the considerable pronounced effects of farmland abandonment management. The new policies effectively restrained the area increase for AFA in the regions with lower rural population (RPOP) and lower gross domestic product (GDP), and reduced the fragmentation of AFA in the regions with the highest RPOP and lower GDP. Additionally, the new policies effectively restrained the fragmentation increase for SFA in the regions with lower RPOP and lower GDP, and reduced the area increase for SFA in the regions with the highest RPOP and lower GDP. The management effect was not that significant in the regions with higher RPOP and higher GDP. These findings will provide important data references for arable land decision making in southern China. © 2022 by the authors.

Keyword:

arable land protection policy CLUMondo model farmland abandonment landscape pattern

Community:

  • [ 1 ] [Li, L.]School of Management, Guangdong University of Technology, Guangzhou, 510520, China
  • [ 2 ] [Zheng, S.]School of Management, Guangdong University of Technology, Guangzhou, 510520, China
  • [ 3 ] [Zheng, S.]The Academy of Digital China, Fuzhou University, Fuzhou, 350108, China
  • [ 4 ] [Zhao, K.]School of Management, Guangdong University of Technology, Guangzhou, 510520, China
  • [ 5 ] [Shen, K.]Big Data Development Center, Ministry of Agriculture and Rural Affairs of the People’s Republic of China, Beijing, 100125, China
  • [ 6 ] [Yan, X.]Big Data Development Center, Ministry of Agriculture and Rural Affairs of the People’s Republic of China, Beijing, 100125, China
  • [ 7 ] [Zhao, Y.]Guangdong Research Center for Smart Land, School of Geography, South China Normal University, Guangzhou, 510631, China

Reprint 's Address:

  • [Li, L.]School of Management, China

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Related Keywords:

Source :

Remote Sensing

ISSN: 2072-4292

Year: 2022

Issue: 19

Volume: 14

5 . 0

JCR@2022

4 . 2 0 0

JCR@2023

ESI HC Threshold:51

JCR Journal Grade:1

CAS Journal Grade:2

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count: 2

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 0

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