Extraction of abandoned farmland based on MaxEnt model: A case study of Wusheng County, Sichuan Province

Clarifying the problem of abandoned farmland at the township level is of great significance for the protection of farmland and food security. Based on domestic GF-1 remote sensing image, coupling the influence factors and image spectrum information of abandoned farmland and taking Wusheng County, wh...

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Autores principales: LUO Yahong, GONG Jianzhou, LI Tianxiang, HU Yueming
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Publicado: Agro-Environmental Protection Institute, Ministry of Agriculture 2021
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Acceso en línea:https://doaj.org/article/5322465d304649f7b90240997772d7f1
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spelling oai:doaj.org-article:5322465d304649f7b90240997772d7f12021-12-03T02:29:42ZExtraction of abandoned farmland based on MaxEnt model: A case study of Wusheng County, Sichuan Province2095-681910.13254/j.jare.2021.0470https://doaj.org/article/5322465d304649f7b90240997772d7f12021-11-01T00:00:00Zhttp://www.aed.org.cn/nyzyyhjxb/html/2021/6/20210615.htmhttps://doaj.org/toc/2095-6819Clarifying the problem of abandoned farmland at the township level is of great significance for the protection of farmland and food security. Based on domestic GF-1 remote sensing image, coupling the influence factors and image spectrum information of abandoned farmland and taking Wusheng County, where the problem of abandoned arable land is more prominent as the case area, the study is to explore the potential of using MaxEnt model to extract the information of perennial and seasonal abandoned farmland, reveal the spatial and temporal differentiation of abandoned farmland and its influencing factors. The results showed that the MaxEnt model had high accuracy and efficiency in the identification of abandoned farmland, which can be applied to extract the information of abandoned farmland. The relative error between seasonal abandoned farmland area and statistical yearbook was less than 10%. In 2018, the perennial abandoned farmland in Wusheng County was mainly distributed in the hilly and mountainous areas with an altitude of more than 300 m, and a few were scattered in the low-lying areas along the Jialing River. The seasonal abandoned farmland was generally distributed in each town, and the local distribution was patchy. During the 2015-2018, the area of perennial, seasonal and total abandoned farmland remained stable. This study suggested that MaxEnt model had great application potential and superiority in extracting abandoned farmland information. Perennials and seasonal abandoned farmland had different spatio-temporal differentiation patterns. The former was due to terrain, traffic and irrigation conditions, while the latter was due to farming radius and irrigation conditions.This study enriched the method of extracting abandoned farmland information based on remote sensing images, enhanced the cognition of the spatio-temporal differentiation patterns and attribution of abandoned farmland, and provided research support for the practice of rational use and management of rural farmland.LUO YahongGONG JianzhouLI TianxiangHU YuemingAgro-Environmental Protection Institute, Ministry of Agriculturearticlemaxent modelabandoned farmlandremote sensing imagespatio-temporal differentiationwusheng countyAgriculture (General)S1-972Environmental sciencesGE1-350ZHJournal of Agricultural Resources and Environment, Vol 38, Iss 6, Pp 1084-1093 (2021)
institution DOAJ
collection DOAJ
language ZH
topic maxent model
abandoned farmland
remote sensing image
spatio-temporal differentiation
wusheng county
Agriculture (General)
S1-972
Environmental sciences
GE1-350
spellingShingle maxent model
abandoned farmland
remote sensing image
spatio-temporal differentiation
wusheng county
Agriculture (General)
S1-972
Environmental sciences
GE1-350
LUO Yahong
GONG Jianzhou
LI Tianxiang
HU Yueming
Extraction of abandoned farmland based on MaxEnt model: A case study of Wusheng County, Sichuan Province
description Clarifying the problem of abandoned farmland at the township level is of great significance for the protection of farmland and food security. Based on domestic GF-1 remote sensing image, coupling the influence factors and image spectrum information of abandoned farmland and taking Wusheng County, where the problem of abandoned arable land is more prominent as the case area, the study is to explore the potential of using MaxEnt model to extract the information of perennial and seasonal abandoned farmland, reveal the spatial and temporal differentiation of abandoned farmland and its influencing factors. The results showed that the MaxEnt model had high accuracy and efficiency in the identification of abandoned farmland, which can be applied to extract the information of abandoned farmland. The relative error between seasonal abandoned farmland area and statistical yearbook was less than 10%. In 2018, the perennial abandoned farmland in Wusheng County was mainly distributed in the hilly and mountainous areas with an altitude of more than 300 m, and a few were scattered in the low-lying areas along the Jialing River. The seasonal abandoned farmland was generally distributed in each town, and the local distribution was patchy. During the 2015-2018, the area of perennial, seasonal and total abandoned farmland remained stable. This study suggested that MaxEnt model had great application potential and superiority in extracting abandoned farmland information. Perennials and seasonal abandoned farmland had different spatio-temporal differentiation patterns. The former was due to terrain, traffic and irrigation conditions, while the latter was due to farming radius and irrigation conditions.This study enriched the method of extracting abandoned farmland information based on remote sensing images, enhanced the cognition of the spatio-temporal differentiation patterns and attribution of abandoned farmland, and provided research support for the practice of rational use and management of rural farmland.
format article
author LUO Yahong
GONG Jianzhou
LI Tianxiang
HU Yueming
author_facet LUO Yahong
GONG Jianzhou
LI Tianxiang
HU Yueming
author_sort LUO Yahong
title Extraction of abandoned farmland based on MaxEnt model: A case study of Wusheng County, Sichuan Province
title_short Extraction of abandoned farmland based on MaxEnt model: A case study of Wusheng County, Sichuan Province
title_full Extraction of abandoned farmland based on MaxEnt model: A case study of Wusheng County, Sichuan Province
title_fullStr Extraction of abandoned farmland based on MaxEnt model: A case study of Wusheng County, Sichuan Province
title_full_unstemmed Extraction of abandoned farmland based on MaxEnt model: A case study of Wusheng County, Sichuan Province
title_sort extraction of abandoned farmland based on maxent model: a case study of wusheng county, sichuan province
publisher Agro-Environmental Protection Institute, Ministry of Agriculture
publishDate 2021
url https://doaj.org/article/5322465d304649f7b90240997772d7f1
work_keys_str_mv AT luoyahong extractionofabandonedfarmlandbasedonmaxentmodelacasestudyofwushengcountysichuanprovince
AT gongjianzhou extractionofabandonedfarmlandbasedonmaxentmodelacasestudyofwushengcountysichuanprovince
AT litianxiang extractionofabandonedfarmlandbasedonmaxentmodelacasestudyofwushengcountysichuanprovince
AT huyueming extractionofabandonedfarmlandbasedonmaxentmodelacasestudyofwushengcountysichuanprovince
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