摘要: |
[目的]尝试借鉴景观格局的研究思路,对农村居民点破碎化程度进行评价及其影响因素分析,为当前“新农村建设”中合理进行土地整治提供辅助依据。[方法]充分考虑农村居民点的规模、形状和分布特征,构建了乡镇尺度上的农村居民点综合破碎度评价模型,并利用多元回归模型对其影响因素进行了分析,提出了居民点整理模式的针对性建议。[结果]以沿海平原地区——山东日照为例的研究结果表明:(1)农村居民点破碎度综合指数(FCI)能够较好地反映沿海平原地区农村居民点的空间分异特征; 沿海地区FCI大于内陆地区,形成了“阶梯状”的空间分布格局。(2)多元回归模型可以较为准确地探测出破碎度影响因素; 研究区FCI的显著影响因素包括距海岸线的距离、距县城的距离、坡度、道路密度等。[结论]通过分析不同等级破碎度的分布特征及其影响因素,可以为各地政府因地制宜开展土地整治、城乡协调发展和新农村建设的土地利用决策提供参考依据。 |
关键词: 农村居民点破碎度多元回归模型影响因素土地整治 |
DOI: |
分类号:F301 |
基金项目:国家自然科学基金项目“空间贫困视角下的中国农村多尺度贫困度量及其时空分布耦合效应分析” (41771157)、国家重点研发计划项目“新型城镇化建设与管理空间信息综合服务及应用示范”(2018YFB0505400)、北京市长城学者资助项目(CIT&TCD20190328)、全国统计科学研究重点项目“大数据空间信息技术支持下的多维多尺度贫困动态监测与评估”(2018LZ27)、北京市教委科研计划项目“基于自发地理信息的道路网多尺度空间数据变化探测与更新方法研究”(KM201810028014)、首都师范大学青年燕京学者项目和首都师范大学科技创新平台建设项目 |
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EXAMINING COMPREHENSIVE FRANMENTATION DEGREE OF RURAL RESIDENTS AND ITS INFLUENCING FACTORS*——A CASE STUDY FROM RIZHAO, SHANDONG |
Qi Wenping1,2,3,4,Wang Yanhui2,3,4※, Liang Chenxia2, 3, 4, Cheng Xu1
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1.CETC Big Data Research Institute Co., Ltd., Guiyang, Guizhou 550022;2.Beijing Key Laboratory of Resource Environment and Geographic Information System, Capital Normal University, Beijing 100048, China; 3.Key Laboratory of 3 Dimensional Information Acquisition and Application, Ministry of Education, Capital Normal University ,Beijing 100048, China; 4.State Key Laboratory Incubation Base of Urban Environmental Processes and Digital Simulation, Capital Normal University, Beijing 100048, China
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Abstract: |
Using the research ideas of landscape pattern for reference, this paper tries to evaluate the fragmentation degree of rural residential and analyze its influencing factors, so as to provide auxiliary basis for land consolidation in the current "new rural construction". Taking full account of the scale, shape and distribution characteristics of rural settlements, a comprehensive fragmentation evaluation model of rural settlements at the township level is constructed, and its influencing factors are analyzed by using multiple regression model, and pertinent suggestions for the settlement consolidation model are put forward. Taking Rizhao in Shandong Province as an example, the results show that: (1) The comprehensive index of rural settlements fragmentation (FCI) can better reflect the spatially heterogeneous distribution of rural settlements in coastal plain areas; FCI in coastal areas is larger than that in inland areas, presenting a typical stepped structure. (2) Multivariate regression model can more accurately detect the impact factors of fragmentation; the significant impact factors of FCI in the study area include distance from coastline, distance from county seat, slope, road density and so on. By analyzing the distribution characteristics and influencing factors of different levels of fragmentation degree, the study can provide reference for local governments to carry out land consolidation, coordinated development of urban and rural areas and land use decision making of new rural construction. |
Key words: rural residential fragmentation multiple regression model influential factors land rearrangement |