| 多尺度下的南方山地丘陵区耕地质量空间自相关分析——以江西省黎川县为例 |
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| 引用本文： | 张晗,赵小敏,欧阳真程,郭熙,李伟峰,匡丽花,叶英聪,黄聪,汪晓燕.多尺度下的南方山地丘陵区耕地质量空间自相关分析——以江西省黎川县为例[J].中国生态农业学报,2018,26(2):263-273. |
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| 作者姓名： | 张晗 赵小敏 欧阳真程 郭熙 李伟峰 匡丽花 叶英聪 黄聪 汪晓燕 |
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| 作者单位： | 江西农业大学江西省鄱阳湖流域农业资源与生态重点实验室/南方粮油作物协同创新中心 南昌 330045;江西农业大学国土资源与环境学院 南昌 330045;江西农业大学土地科学研究所 南昌 330045,江西农业大学江西省鄱阳湖流域农业资源与生态重点实验室/南方粮油作物协同创新中心 南昌 330045;江西农业大学土地科学研究所 南昌 330045;南京农业大学公共管理学院南京 210095,江西农业大学江西省鄱阳湖流域农业资源与生态重点实验室/南方粮油作物协同创新中心 南昌 330045;江西农业大学国土资源与环境学院 南昌 330045,江西农业大学江西省鄱阳湖流域农业资源与生态重点实验室/南方粮油作物协同创新中心 南昌 330045;江西农业大学国土资源与环境学院 南昌 330045;江西农业大学土地科学研究所 南昌 330045,江西农业大学江西省鄱阳湖流域农业资源与生态重点实验室/南方粮油作物协同创新中心 南昌 330045;江西农业大学国土资源与环境学院 南昌 330045,南京农业大学公共管理学院南京 210095,江西农业大学江西省鄱阳湖流域农业资源与生态重点实验室/南方粮油作物协同创新中心 南昌 330045;江西农业大学国土资源与环境学院 南昌 330045,江西农业大学江西省鄱阳湖流域农业资源与生态重点实验室/南方粮油作物协同创新中心 南昌 330045;江西农业大学国土资源与环境学院 南昌 330045,江西农业大学江西省鄱阳湖流域农业资源与生态重点实验室/南方粮油作物协同创新中心 南昌 330045;江西农业大学国土资源与环境学院 南昌 330045 |
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| 基金项目： | 国家自然科学基金项目（41361049）和江西省自然科学基金项目（20122BAB204012）资助 |
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| 摘 要： | 分析不同尺度下的耕地质量空间分布格局,是提高耕地质量与加强耕地保护建设的基础。选取耕地质量等别监测试点县江西省黎川县为研究区,运用加权平均法、变异系数法和空间自相关分析法,以国家级耕地质量指数为空间变量,分别从县级、乡镇级和村级尺度上探讨了耕地质量的空间关联程度及其分异规律。研究结果表明:1)研究区耕地质量呈现出"南北高,东西低"的空间分布规律,耕地质量指数Mora’s I值表现为国家利用等指数国家经济等指数国家自然等指数,县级、乡镇级和村级耕地质量指数的Moran’s I值依次降低,三者均呈显著的空间正自相关集聚态势。2)随着空间尺度的不同,耕地质量指数具有不同的空间关联度,自然等指数受空间尺度影响较大,经济等指数其次,利用等指数最小。3)正相关高-高型和低-低型耕地以组团形式聚集分布,负相关高-低型和低-高型耕地无明显的集中区域,多以零星状分布。研究结果显示耕地质量空间差异对空间尺度的变化较为敏感,可为区域高标准基本农田建设、土地综合整治、耕地质量监测和耕地保护与管理分区提供借鉴参考。
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| 关 键 词： | 山地丘陵区 耕地质量 空间自相关 空间尺度 黎川县 |
| 收稿时间： | 2017/6/3 0:00:00 |
| 修稿时间： | 2017/8/3 0:00:00 |
Multi-scale spatial autocorrelation analysis of cultivated land quality in China's southern hillside areas: A case study of Lichuan County, Jiangxi Province |
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| ZHANG Han,ZHAO Xiaomin,OUYANG Zhencheng,GUO Xi,LI Weifeng,KUANG Lihu,YE Yingcong,HUANG Cong and WANG Xiaoyan.Multi-scale spatial autocorrelation analysis of cultivated land quality in China's southern hillside areas: A case study of Lichuan County, Jiangxi Province[J].Chinese Journal of Eco-Agriculture,2018,26(2):263-273. |
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| Authors: | ZHANG Han ZHAO Xiaomin OUYANG Zhencheng GUO Xi LI Weifeng KUANG Lihu YE Yingcong HUANG Cong and WANG Xiaoyan |
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| Institution: | Key Laboratory of Poyang Lake Basin Agricultural Resources and Ecology of Jiangxi Province, Jiangxi Agricultural University/Southern Regional Collaborative Innovation Center for Grain and Oil Crops in China, Nanchang 330045, China;College of Land Resources and Environment, Jiangxi Agricultural University, Nanchang 330045, China;Institute of Land Science, Jiangxi Agricultural University, Nanchang 330045, China,Key Laboratory of Poyang Lake Basin Agricultural Resources and Ecology of Jiangxi Province, Jiangxi Agricultural University/Southern Regional Collaborative Innovation Center for Grain and Oil Crops in China, Nanchang 330045, China;Institute of Land Science, Jiangxi Agricultural University, Nanchang 330045, China;College of Public Administration, Nanjing Agricultural University, Nanjing 210095, China,Key Laboratory of Poyang Lake Basin Agricultural Resources and Ecology of Jiangxi Province, Jiangxi Agricultural University/Southern Regional Collaborative Innovation Center for Grain and Oil Crops in China, Nanchang 330045, China;College of Land Resources and Environment, Jiangxi Agricultural University, Nanchang 330045, China,Key Laboratory of Poyang Lake Basin Agricultural Resources and Ecology of Jiangxi Province, Jiangxi Agricultural University/Southern Regional Collaborative Innovation Center for Grain and Oil Crops in China, Nanchang 330045, China;College of Land Resources and Environment, Jiangxi Agricultural University, Nanchang 330045, China;Institute of Land Science, Jiangxi Agricultural University, Nanchang 330045, China,Key Laboratory of Poyang Lake Basin Agricultural Resources and Ecology of Jiangxi Province, Jiangxi Agricultural University/Southern Regional Collaborative Innovation Center for Grain and Oil Crops in China, Nanchang 330045, China;College of Land Resources and Environment, Jiangxi Agricultural University, Nanchang 330045, China,College of Public Administration, Nanjing Agricultural University, Nanjing 210095, China,Key Laboratory of Poyang Lake Basin Agricultural Resources and Ecology of Jiangxi Province, Jiangxi Agricultural University/Southern Regional Collaborative Innovation Center for Grain and Oil Crops in China, Nanchang 330045, China;College of Land Resources and Environment, Jiangxi Agricultural University, Nanchang 330045, China,Key Laboratory of Poyang Lake Basin Agricultural Resources and Ecology of Jiangxi Province, Jiangxi Agricultural University/Southern Regional Collaborative Innovation Center for Grain and Oil Crops in China, Nanchang 330045, China;College of Land Resources and Environment, Jiangxi Agricultural University, Nanchang 330045, China and Key Laboratory of Poyang Lake Basin Agricultural Resources and Ecology of Jiangxi Province, Jiangxi Agricultural University/Southern Regional Collaborative Innovation Center for Grain and Oil Crops in China, Nanchang 330045, China;College of Land Resources and Environment, Jiangxi Agricultural University, Nanchang 330045, China |
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| Abstract: | Cultivated lands are among the most fundamental resources for national food security and sustainable social development. Scientific analysis of the spatial distribution patterns and evolutionary characteristics of cultivated land quality is significant for the protection and layout optimization of cultivated lands. Analysis of the spatial distribution of cultivated land quality at different scales is the basis of cultivated land quality improvement and strengthening of cultivated land protection. This paper was based on cultivated land quality monitoring experimental unit in Lichuan County in Jiangxi Province and then used weighted average, variation coefficient, and spatial autocorrelation to analyze spatial disparity characteristics of cultivated land quality. Multi-scale spatial autocorrelation analysis of cultivated land quality research is a hot research area. The innovation in this paper was the introduction of natural land grade index, use of the grade index and economic grade index as the space variable to separately explore and discuss the degree of spatial correlation and spatial disparity of cultivated land quality at county-scale, township-scale and village-scale in GIS environment. The results of the research showed that:1) Cultivated land quality index was high in the south and north and low in the west and east in Lichuan County. When the threshold distance was 400 m, there was a significant spatial autocorrelation in cultivated land quality. The Moran''s I value of natural land grade index was highest, followed by economical land grade index, and land use grade index was the lowest. The Moran''s I value of cultivated land quality from county to township and then to village scales decreased systematically. Multi-scale spatial autocorrelation analysis of cultivated land quality exhibited a significant aggregation of spatial distribution in Lichuan County. 2) It was found that different types of cultivated land quality indexes had remarkably different spatial correlations at different spatial scales. For the influence degree of spatial scale, land use grade index was greatly affected by spatial scale, followed by natural land index, and the economic land grade index was the weakest. For the coefficient of variation of cultivated land quality index, fluctuation in Moran''s I value for cultivated land at village-scale was far greater than that at township scale. While at the same spatial scale, the coefficient of variation of natural land index was strongest, followed by economic land index and then land use index. 3) The results based on local indicators of spatial association (LISA) showed that positive spatial autocorrelation of cultivated land quality, included the high-high type and the low-low type, emerged as the shape of the cluster and in the form of group, while the negative spatial autocorrelation contained the high-low type and low-high type was fragmented in space. The results of the study showed that spatial disparity in cultivated land quality was sensitive to spatial scale. Therefore, for cultivated land quality improvement and protection, there was the need to pay more attention to spatial disparity of cultivated land quality at town scale and village scale. Also based on the difference in spatial correlation degree among the natural conditions, utilization conditions and economic benefits, it was possible to explore cultivated land quality improvement and protection measures that met actual ground situations in the study area. The results of the study provided the needed references for the construction of high-standard basic farmlands, land reclamation, regional cultivated land quality monitoring, cultivated land protection, partitioning and management of cultivated lands, cultivated land quality improvement and spatial optimization of cultivated land quality. |
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| Keywords: | Mountain-hilly area Cultivated land quality Spatial autocorrelation Spatial scale Lichuan County |
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