| 经济欠发达地区撂荒耕地空间格局与驱动因素分析 |
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| 引用本文： | 牛继强,林昊,牛樱楠,樊勇,唐文武.经济欠发达地区撂荒耕地空间格局与驱动因素分析[J].农业机械学报,2017,48(2):141-149. |
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| 作者姓名： | 牛继强 林昊 牛樱楠 樊勇 唐文武 |
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| 作者单位： | 信阳师范学院地理科学学院,信阳师范学院地理科学学院,信阳师范学院地理科学学院,信阳师范学院地理科学学院,北卡罗来纳大学夏洛特分校地理与地球科学系 |
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| 基金项目： | 国家自然科学基金项目（41201387、41671405）和河南省高等学校重点科研项目（17A170010） |
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| 摘 要： | 基于遥感(RS)、地理信息系统(GIS)技术、支持向量机(SVM)和景观指数等方法,提出了撂荒耕地信息提取的技术路线和研究思路。以河南省罗山县子路镇为研究区,采用2013、2015年春秋两季的4景Landsat-8 OLI遥感影像,提取该镇撂荒耕地及其时空分布信息,进而分析地形、交通、灌溉条件和耕作半径等几个农业生产条件对子路镇耕地撂荒的影响,得出利用遥感影像提取撂荒耕地的正确率达到90%以上;该区域撂荒耕地主要分为季节性撂荒和常年性撂荒,且季节性撂荒较为严重;地形、交通、灌溉和耕作半径均影响耕地撂荒的时空分布,且地形因素中的坡度影响最大。研究结果不仅能够对经济欠发达地区撂荒耕地空间信息提取、驱动因素分析提供技术支撑,而且也可为国家粮食安全以及区域可持续发展政策的制定提供依据。
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| 关 键 词： | 撂荒耕地 遥感 地理信息系统 空间格局 驱动因素 |
| 收稿时间： | 2016/8/22 0:00:00 |
| 修稿时间： | 2017/2/10 0:00:00 |
Analysis of Spatial Pattern and Driving Factors for Abandoned Arable Lands in Underdevelopment Region |
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| NIU Jiqiang,LIN Hao,NIU Yingnan,FAN Yong and TANG Wenwu.Analysis of Spatial Pattern and Driving Factors for Abandoned Arable Lands in Underdevelopment Region[J].Transactions of the Chinese Society of Agricultural Machinery,2017,48(2):141-149. |
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| Authors: | NIU Jiqiang LIN Hao NIU Yingnan FAN Yong and TANG Wenwu |
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| Institution: | School of Geographic Sciences, Xinyang Normal University,School of Geographic Sciences, Xinyang Normal University,School of Geographic Sciences, Xinyang Normal University,School of Geographic Sciences, Xinyang Normal University and Department of Geography and Earth Science, University of North Carolina at Charlotte |
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| 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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