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辽宁省农村村落空间分布格局及影响因素分析

Spatial Distribution Pattern of Rural Villages in Liaoning Province and Analysis of Influencing Factors
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摘要 鉴于村落作为农村人口居住和生活的重要载体,对于农村发展规划具有重要作用,文章开展了辽宁省农村村落提取研究。通过村落的规模特征、空间分布特点,探究地形地貌、坡度、坡向、水系、经济、与县级驻地的距离和道路交通等因素,对村落空间分布进行分析。结果表明:辽宁省村落主要为小型和中型村落,超过总体村落的60%,村落规模分布呈现“中间大,两边小”的特点;村落在辽南沿海地区分布较密集,辽西北分布较稀疏;村落主要分布在海拔低于500 m的区域,分布在坡度小于15°区域的村落占总体村落的97.47%,阳坡与平坡是村落分布的重要选择;村落分布与经济因素呈“正相关”,与县级驻地的距离呈“负相关”;在距离道路2 km和河流5 km以内是村落分布的主要区域。 In view of the village as an important carrier of rural population’s residence and life,it plays an important role in rural development planning.Based on the scale characteristics and spatial distribution characteristics of villages,factors such as landform,slope,slope direction,water system,economy,distance from county resident and road traffic are explored to analyze the spatial distribution of villages.The results show that the villages in Liaoning province are mainly small and medium-sized villages,accounting for more than 60%of the total villages.The distribution of village size presents the characteristics of“large in the middle and small on both sides”.The villages are densely distributed in the coastal areas of southern Liaoning,but sparsely distributed in the northwestern Liaoning.Villages are mainly distributed in areas below 500 m above sea level,and 97.47%of the villages are located in areas with slopes less than 15°.Sunny slope and flat slope are important choices for village distribution.Village distribution is positively correlated with economic factors.There is a negative correlation between the distance and county station.Within 2 km from the road and 5 km from the river is the main area of village distribution.
作者 柳杨 赵泉华 贾淑涵 李玉 LIU Yang;ZHAO Quanhua;JIA Shuhan;LI Yu(School of Geomatics,Liaoning Technical University,Fuxin,Liaoning 123000,China)
出处 《遥感信息》 CSCD 北大核心 2023年第5期81-88,共8页 Remote Sensing Information
基金 辽宁省教育厅基本科研项目(LJKZZ20220048) 辽宁省自然科学基金计划项目(2022-MS-400)。
关键词 辽宁省 农村村落 空间格局 影响因素 遥感影像 Liaoning province rural village spatial pattern influencing factor remote sensing image
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