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: | , , , |
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| Formato: | article |
| Lenguaje: | ZH |
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Agro-Environmental Protection Institute, Ministry of Agriculture
2021
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/5322465d304649f7b90240997772d7f1 |
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| Sumario: | 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. |
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