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經(jīng)濟欠發(fā)達地區(qū)撂荒耕地空間格局與驅(qū)動因素分析
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國家自然科學(xué)基金項目(41201387,、41671405)和河南省高等學(xué)校重點科研項目(17A170010)


Analysis of Spatial Pattern and Driving Factors for Abandoned Arable Lands in Underdevelopment Region
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    摘要:

    基于遙感(RS),、地理信息系統(tǒng)(GIS)技術(shù)、支持向量機(SVM)和景觀指數(shù)等方法,,提出了撂荒耕地信息提取的技術(shù)路線和研究思路,。以河南省羅山縣子路鎮(zhèn)為研究區(qū),,采用2013、2015年春秋兩季的4景Landsat-8 OLI遙感影像,,提取該鎮(zhèn)撂荒耕地及其時空分布信息,,進而分析地形、交通,、灌溉條件和耕作半徑等幾個農(nóng)業(yè)生產(chǎn)條件對子路鎮(zhèn)耕地撂荒的影響,,得出利用遙感影像提取撂荒耕地的正確率達到90%以上;該區(qū)域撂荒耕地主要分為季節(jié)性撂荒和常年性撂荒,,且季節(jié)性撂荒較為嚴重,;地形、交通,、灌溉和耕作半徑均影響耕地撂荒的時空分布,,且地形因素中的坡度影響最大。研究結(jié)果不僅能夠?qū)?jīng)濟欠發(fā)達地區(qū)撂荒耕地空間信息提取,、驅(qū)動因素分析提供技術(shù)支撐,,而且也可為國家糧食安全以及區(qū)域可持續(xù)發(fā)展政策的制定提供依據(jù)。

    Abstract:

    With rapid urbanization and industrialization, rural work forces have migrated to cities, leading to remarkable reduction in rural poulation. So large amounts of arable lands have been abandoned in China in recent years. Abandoned arable lands in under development region of China have seriously affected the redline of arable land and national food security, which has become a major practical problem facing urban-rural integration. Multispectral remote sensing has the advantage of wide range and high speed in terms of data acquisition. It has great potential in the study of lands use. A new research approach and technical roadmap were proposed for abandoned land information extraction based on remote sensing, geographic information system, support vector machines and landscape ecological index. The study area, Zilu town, Henan province, China, is a typical underdevelopment region. Four scenes Landsat-8 OLI data from 2013 to 2015 were used to extract abandoned arable land, and its spatialtemporal distribution was analyzed based on landscape metrics. Furthermore, analysis of driving factors was conducted, such as terrain, traffic, irrigation conditions and farming radius in terms of the impact of abandoned arable lands in the study area. The results showed that the accuracy of extracting abandoned arable lands using RS was above 90%. The area of abandoned arable lands was divided into seasonal and perennial abandoned, and the former was more severe. The factors of terrain, traffic, irrigation conditions and farming radius affected the spatial-temporal distribution of abandoned arable lands, and the slope of the terrain had the greatest impact. The results can provide technical support for spatial information extraction of abandoned arable land in underdevelopment region, and can be applied to establishment of regional sustainable development policy.

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牛繼強,林昊,牛櫻楠,樊勇,唐文武.經(jīng)濟欠發(fā)達地區(qū)撂荒耕地空間格局與驅(qū)動因素分析[J].農(nóng)業(yè)機械學(xué)報,2017,48(2):141-149. NIU Jiqiang, LIN Hao, NIU Yingnan, FAN Yong,TANG Wenwu. Analysis of Spatial Pattern and Driving Factors for Abandoned Arable Lands in Underdevelopment Region[J]. Transactions of the Chinese Society for Agricultural Machinery,2017,48(2):141-149.

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  • 收稿日期:2016-08-22
  • 最后修改日期:2017-02-10
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  • 在線發(fā)布日期: 2017-02-10
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