Rapid monitoring of abandoned farmland and information on regulation achievements of government based on remote sensing technology
文献类型:期刊论文
作者 | Luo, Kaisheng2,3; Moiwo, Juana P.1 |
刊名 | ENVIRONMENTAL SCIENCE & POLICY
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出版日期 | 2022-06-01 |
卷号 | 132页码:91-100 |
关键词 | Abandoned farmland Remote sensing contribution of government regulation Recultivation Satellite imagery |
ISSN号 | 1462-9011 |
DOI | 10.1016/j.envsci.2022.02.019 |
通讯作者 | Luo, Kaisheng(luokaisheng@cigit.ac.cn) |
英文摘要 | Farmland abandonment has become a worldwide phenomenon, and remote sensing technology has been used to monitor this phenomenon. However, information on only the final net change in abandoned farmland can be obtained based on existing methods, and the various components and contributions of government regulation cannot be identified. These methods therefore cannot meet the needs for the management of abandoned farm -land or related policy-adjustments. Therefore, this study uses Longyan Prefecture in China as the study area, and GF-1 satellite images as the main data source, to propose a new rapid monitoring method for abandoned farmland that can reflect and separate the government's regulatory contribution to changes in farmland aban-donment. The results show that the abandoned farmland in the study area generally expanded from 2015 to 2019. Despite this observation, government regulation has made some achievements. In 2015-2017 and 2017-2019, 41.72% and 41.67% of the new increased abandoned farmland was offset, respectively, delaying the process of farmland-abandonment. However, the achievement of government regulation decreased by 23.86% in 2017-2019 compared with that during 2015-2017. The results show that our method can reflect the process of farmland abandonment and the contribution of government regulation, can be applied on a large scale, and provides comparable results among regions. Offsetting the newly increased abandoned farmland by improving the contribution of government regulation is an important and direct way to curb farmland abandonment, but special attention should be given to the scientific nature and full implementation of policies in actual manage-ment practices.& nbsp;Data Availability: The Chinese GF-1 Satellite images were downloaded from the China Center for Resources Satellite Date and Application website (http://www.cresda.com/EN/). The Advanced Land Observing Satellite (ALOS) data downloaded from the National Aeronautics and Space Administration (NASA) (https://search.asf. alaska.edu/#/). The vector boundary of the research area was obtained from the Chinese Resource and Envi-ronment Science and Data Center (https://www.resdc.cn/). Most of the field samples for evaluating the accuracy of the land classification results downloaded from Global Change Data & Discovery (http://www.geodoi.ac.cn/ WebEn/doi.aspx?Id=1502). |
资助项目 | National Natural Science Foundation of China[41801200] ; Independent Deployment Foundation of the Chongqing Institute of Green and Intelligent Technology, CAS[2020000062] |
WOS研究方向 | Environmental Sciences & Ecology |
语种 | 英语 |
WOS记录号 | WOS:000787885700009 |
出版者 | ELSEVIER SCI LTD |
源URL | [http://119.78.100.138/handle/2HOD01W0/15874] ![]() |
专题 | 中国科学院重庆绿色智能技术研究院 |
通讯作者 | Luo, Kaisheng |
作者单位 | 1.Njala Univ, Sch Technol, Dept Agr Engn, Njala Campus, Njala, Sierra Leone 2.Chinese Acad Sci, Chongqing Inst Green & Intelligent Technol, Chongqing 400714, Peoples R China 3.Univ Chinese Acad Sci, Chongqing Sch, Chongqing 400714, Peoples R China |
推荐引用方式 GB/T 7714 |
Luo, Kaisheng,Moiwo, Juana P.. Rapid monitoring of abandoned farmland and information on regulation achievements of government based on remote sensing technology [J]. ENVIRONMENTAL SCIENCE & POLICY,2022,132:91-100. |
APA |
Luo, Kaisheng,&Moiwo, Juana P..(2022). Rapid monitoring of abandoned farmland and information on regulation achievements of government based on remote sensing technology .ENVIRONMENTAL SCIENCE & POLICY,132,91-100. |
MLA |
Luo, Kaisheng,et al." Rapid monitoring of abandoned farmland and information on regulation achievements of government based on remote sensing technology ".ENVIRONMENTAL SCIENCE & POLICY 132(2022):91-100. |
入库方式: OAI收割
来源:重庆绿色智能技术研究院
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