多尺度下农村居民点空间分布特征及其影响因素研究
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摘要
[目的]为更精细、更科学地了解农村居民点空间分布特征及其影响因素,从多尺度角度进行对比分析,为农村居民点整理提供依据。[方法]基于空间自相关、核密度分析等方法,以广水市为例,从多尺度角度对2016年广水市农村居民点分布空间分布状况进行对比分析,并引入空间计量回归模型对其影响因素进行探究。[结果](1)对广水市农村居民点进行核密度分析时,搜索半径为1 800m最合理,广水市农村居民点核密度最大值为14. 26个/km~2;(2)对广水市农村居民点核密度估计值从县级、乡镇级、村级3个尺度分别进行全局空间自相关分析,Moran's I县级=0. 642 4、Moran's I乡镇级=0. 694 3、Moran's I村级=0. 808 2,全部表现为空间正相关,村级的空间集聚特征最显著、乡镇其次、县级相对最小;(3)局部自相关分析显示农村居民点核密度估计值高值区分布在城郊乡、骆店乡、马坪镇、长岭镇4乡镇,与该研究的核密度分析结果一致。(4)通过空间计量回归模型分析,农村居民点的影响因素:地形位指数>到城镇距离>到道路距离>到水系距离。[结论]文章从多尺度角度对农村居民点分布特征及其影响因素对比研究,以期为今后同方向的研究提供借鉴,为农村居民点整治、农村居民点空间演变研究、村镇规划、农村土地集约利用、乡村振兴等提供理论方法的支撑。
This research aims to master the characteristics of the spatial distribution of rural settlements and its influencing factors scientifically,and Carries out a comparative analysis from the multiscale,so as to provide the basis for the rural settlements. Based on the methods of spatial autocorrelation and nuclear density analysis,taking Guangshui city as an example,the spatial distribution of rural residential settlements in Guangshui city in 2016 was analyzed from a multi-scale perspective,and the influencing factors were explored by using spatial regression model. The results show that( 1) In the analysis of nuclear density of rural settlements in Guangshui,the search radius was 1800 m,and the maximum nuclear density of rural residential areas in Guangshui was 14. 26/km~2;( 2)From the global spatial auto-correlation analysis of the rural settlements kernel density estimate corp,Moran's I was0. 6424 at the county level,Moran's I township-level was 0. 6943,and village's Moran's I was 0. 8082,all showed positive correlation,the most significant features of space agglomeration was villages,followed by the towns,and county level was the smallest;( 3) From the local auto-correlation analysis,it showed that high value of the kernel density estimate of rural settlements was in Chengjiao,Luodian,Maping,Changling towns,and the result was consistent with the study of nuclear density;( 4) Through the analysis of spatial regression model,the influencing factors of rural settlements were showed as follows. The topographic digit index > the distance from town to town >the distance from road > the distance from river system. This research explores rural settlements distribution characteristics and influencing factors from multi-scale,in order to provide reference for future research in the same direction,and provides theoretical and methodological support for settlements spatial evolution,town planning and intensive utilization of rural land,and rural rejuvenation.
This research aims to master the characteristics of the spatial distribution of rural settlements and its influencing factors scientifically,and Carries out a comparative analysis from the multiscale,so as to provide the basis for the rural settlements. Based on the methods of spatial autocorrelation and nuclear density analysis,taking Guangshui city as an example,the spatial distribution of rural residential settlements in Guangshui city in 2016 was analyzed from a multi-scale perspective,and the influencing factors were explored by using spatial regression model. The results show that( 1) In the analysis of nuclear density of rural settlements in Guangshui,the search radius was 1800 m,and the maximum nuclear density of rural residential areas in Guangshui was 14. 26/km~2;( 2)From the global spatial auto-correlation analysis of the rural settlements kernel density estimate corp,Moran's I was0. 6424 at the county level,Moran's I township-level was 0. 6943,and village's Moran's I was 0. 8082,all showed positive correlation,the most significant features of space agglomeration was villages,followed by the towns,and county level was the smallest;( 3) From the local auto-correlation analysis,it showed that high value of the kernel density estimate of rural settlements was in Chengjiao,Luodian,Maping,Changling towns,and the result was consistent with the study of nuclear density;( 4) Through the analysis of spatial regression model,the influencing factors of rural settlements were showed as follows. The topographic digit index > the distance from town to town >the distance from road > the distance from river system. This research explores rural settlements distribution characteristics and influencing factors from multi-scale,in order to provide reference for future research in the same direction,and provides theoretical and methodological support for settlements spatial evolution,town planning and intensive utilization of rural land,and rural rejuvenation.
引文
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[14]姜广辉,张凤荣,谭雪晶.北京市平谷区农村居民点用地空间结构调整.农业工程学报,2008,24(11):69-75.
[15]刘仙桃,郑新奇,李道兵.基于Voronoi图的农村居民点空间分布特征及其影响因素研究——以北京市昌平区为例.生态与农村环境学报,2009,25(2):30-33.
[16]黄聪,赵小敏,郭熙,等.基于核密度的余江县农村居民点布局优化研究.中国农业大学学报,2016(11):165-174.
[17]洪步庭,伍文.基于GIS的农村居民点空间演变特征及其影响因素.国土资源科技管理,2014(3):40-50.
[18]韦素琼,张金前,陈健飞.基于空间自相关的闽台城镇建设用地分布研究.地理科学进展,2007(3):11-17.
[19]焦贝贝,石培基,刘春芳,等.黄土高原低山丘陵区农村居民点分布与地形因子关系研究——以兰州市七里河区为例.资源科学,2013(8):1719-1727.
[20]张晗,赵小敏,欧阳真程,等.基于空间自相关的耕地质量空间差异特征及耕地保护分区——以江西省上高县为例.水土保持研究,2018(1):304-312.
[21]李君,李小建.综合区域环境影响下的农村居民点空间分布变化及影响因素分析——以河南巩义市为例.资源科学,2009(7):1195-1204.
[22]王诗雨,雷国平.基于GIS的垦区农村居民点空间分布特征及影响因素分析.国土资源情报,2012(11):41-45.
[23]车明亮,聂宜民,姜曙千,等.平邑山区农村居民点分形特征及影响因素.农业工程学报,2010(S2):360-365.
[24]曲衍波,姜广辉,张凤荣,等.基于农户意愿的农村居民点整治模式.农业工程学报,2012(23):232-242.
[25]孔雪松,刘艳芳,邹亚锋,等.基于农户意愿的农村居民点整理潜力测算与优化.农业工程学报,2010(8):296-301.
[26]李胜坤,张毅,闫欣,等.竹溪县农村居民点景观格局及空间分布特征.水土保持研究,2014,21(4):203-207.
[27]任平,洪步庭,周介铭.基于空间自相关模型的农村居民点时空演变格局与特征研究.长江流域资源与环境,2015,24(12):1993-2002.
[28]毕秀晶,宁越敏.长三角大都市区空间溢出与城市群集聚扩散的空间计量分析.经济地理,2013,33(1):46-53.
[29] ANSElin L,FLORAX R,REY SJ. Advances in Spatial Econometrics:Methodology,Tools and Applications. New York,Springer,2004.
[30]宋文,等.基于空间自相关的区域农村居民点分布与环境的关系研究.中国农业资源与区划,2016,37(12):70-77.
[31]喻红,曾辉,江子瀛.快速城市化地区景观组分在地形梯度上的分布特征研究.地理科学,2001,21(1):64-69.
[2]刘彦随,等.中国农村空心化的地理学研究与整治实践.地理学报,2009,64(10):1193-1202.
[3]姜广辉,张凤荣,颜国强,等.科学发展观指导下的农村居民点布局调整与整理.国土资源科技管理,2005,22(4):109-116.
[4]金其铭.我国农村聚落地理研究历史及近今趋向.地理学报,1988,43(4):311-317.
[5]姜广辉,张凤荣,陈军伟,等.基于Logistic回归模型的北京山区农村居民点变化驱动力分析.农业工程学报,2007,23(5):81-87.
[6] Tan Minghong,Li Xiubin. The changing settlements in rural areas under urban pressure in China:Patterns,driving forces and policy implications. Landscape and Urban Planning,2013,120:170-177.
[7] Shi Yaqi,Sun Xiang,Zhu Xiaodong,et al. Characterizing growth types and analyzing growth density distribution in response to urban growth patterns in peri-urban areas of Lianyungang City. Landscape and Urban Planning,2012,105(4):425-433.
[8]韩非,蔡建明.我国半城市化地区乡村聚落的形态演变与重建.地理研究,2011,30(7):1271-1284.
[9]周国华,贺艳华,唐承丽,等.论新时期农村聚居模式研究.地理科学进展,2010,29(2):186-192.
[10]] A. H. Potosyan. Geographical features and development regularities of rural areas and settlements distribution in mountain countries. Annals of Agrarian Science,2017.
[11] Maria Bonaventura Forleo,Vincenzo Giaccio,Agostino Giannelli,Luigi Mastronardi,Nadia Palmieri. Socio-Economic Drivers,land Cover Changes and the Dynamics of Rural Settlements:Mt. Matese Area(Italy. European Countryside,2017,9(3)
[12] Vasco Barbosa-Brando,inés SantéRiveira,Rafael Crecente Maseda. Evolution of Legal Criteria for the Identification and Zoning of Rural Settlements in Galicia,NW Spain. European Planning Studies,2015,23(2)
[13]梁友嘉,钟方雷,徐中民.基于RS和GIS的张掖市土地利用景观格局变化及驱动力.兰州大学学报:自然科学版,2010,46(5):24-30.
[14]姜广辉,张凤荣,谭雪晶.北京市平谷区农村居民点用地空间结构调整.农业工程学报,2008,24(11):69-75.
[15]刘仙桃,郑新奇,李道兵.基于Voronoi图的农村居民点空间分布特征及其影响因素研究——以北京市昌平区为例.生态与农村环境学报,2009,25(2):30-33.
[16]黄聪,赵小敏,郭熙,等.基于核密度的余江县农村居民点布局优化研究.中国农业大学学报,2016(11):165-174.
[17]洪步庭,伍文.基于GIS的农村居民点空间演变特征及其影响因素.国土资源科技管理,2014(3):40-50.
[18]韦素琼,张金前,陈健飞.基于空间自相关的闽台城镇建设用地分布研究.地理科学进展,2007(3):11-17.
[19]焦贝贝,石培基,刘春芳,等.黄土高原低山丘陵区农村居民点分布与地形因子关系研究——以兰州市七里河区为例.资源科学,2013(8):1719-1727.
[20]张晗,赵小敏,欧阳真程,等.基于空间自相关的耕地质量空间差异特征及耕地保护分区——以江西省上高县为例.水土保持研究,2018(1):304-312.
[21]李君,李小建.综合区域环境影响下的农村居民点空间分布变化及影响因素分析——以河南巩义市为例.资源科学,2009(7):1195-1204.
[22]王诗雨,雷国平.基于GIS的垦区农村居民点空间分布特征及影响因素分析.国土资源情报,2012(11):41-45.
[23]车明亮,聂宜民,姜曙千,等.平邑山区农村居民点分形特征及影响因素.农业工程学报,2010(S2):360-365.
[24]曲衍波,姜广辉,张凤荣,等.基于农户意愿的农村居民点整治模式.农业工程学报,2012(23):232-242.
[25]孔雪松,刘艳芳,邹亚锋,等.基于农户意愿的农村居民点整理潜力测算与优化.农业工程学报,2010(8):296-301.
[26]李胜坤,张毅,闫欣,等.竹溪县农村居民点景观格局及空间分布特征.水土保持研究,2014,21(4):203-207.
[27]任平,洪步庭,周介铭.基于空间自相关模型的农村居民点时空演变格局与特征研究.长江流域资源与环境,2015,24(12):1993-2002.
[28]毕秀晶,宁越敏.长三角大都市区空间溢出与城市群集聚扩散的空间计量分析.经济地理,2013,33(1):46-53.
[29] ANSElin L,FLORAX R,REY SJ. Advances in Spatial Econometrics:Methodology,Tools and Applications. New York,Springer,2004.
[30]宋文,等.基于空间自相关的区域农村居民点分布与环境的关系研究.中国农业资源与区划,2016,37(12):70-77.
[31]喻红,曾辉,江子瀛.快速城市化地区景观组分在地形梯度上的分布特征研究.地理科学,2001,21(1):64-69.