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基于脱钩理论与LMDI模型的农村居民点演化特征及驱动因素分解
引用本文:刘书畅,叶艳妹,林耀奔.基于脱钩理论与LMDI模型的农村居民点演化特征及驱动因素分解[J].农业工程学报,2019,35(12):272-280.
作者姓名:刘书畅  叶艳妹  林耀奔
作者单位:1. 浙江大学公共管理学院,杭州 310058;2. 城乡建设用地节约集约利用实验室,北京 100812,1. 浙江大学公共管理学院,杭州 310058;2. 城乡建设用地节约集约利用实验室,北京 100812,1. 浙江大学公共管理学院,杭州 310058;2. 城乡建设用地节约集约利用实验室,北京 100812
基金项目:国家社会科学基金重大项目(14ZDA039)
摘    要:为研究中国农村人口与农村居民点用地变化协同关系和驱动因素,以促进农村居民点用地集约利用,该文基于农村人地变化脱钩和城乡人口转型视角,以全国和31个省级行政区域为研究区,将Tapio脱钩模型和对数平均迪式指数分解法(logarithmic mean Divisia index,LMDI)应用于农村人地协调演化研究及驱动效应分解。结果表明,近20 a来,中国城乡发展经历了快速转型,农村常住人口持续减少,降幅约为30.7%,而同期农村居民点规模不减反增,农村人地演化关系失衡,建设用地趋于粗放利用;中国及各地区农村人口和居民点变化的脱钩关系主要表现为强负脱钩,其中东部和西部地区负脱钩程度较为严重,且负脱钩程度总体上呈加剧趋势;1996—2008和2009—2016年期间,中国农村居民点规模分别增加了2.020×105 hm2、7.275×105 hm2,其中农村居民点利用集约度效应、城乡人口结构效应、城镇化效应、区域总人口效应的贡献量分别为33.497×105、-116.833×105、71.813×105、13.544×105 hm2和36.689×105、-68.271×105、32.164×105、6.692×105 hm2;不同时段各效应贡献度不同,1996—2008年城镇化效应大于农村居民点利用集约度效应,而在2009年之后,农村居民点利用集约度效应逐渐超过城镇化效应,成为农村居民点增加的主导因素。

关 键 词:土地利用  农村  模型  农村居民点  演化特征  Tapio脱钩  LMDI
收稿时间:2018/12/12 0:00:00
修稿时间:2019/2/16 0:00:00

Evolution characteristics and decomposition of driving factors on rural residential land based on decoupling theory and LMDI model
Liu Shuchang,Ye Yanmei and Lin Yaoben.Evolution characteristics and decomposition of driving factors on rural residential land based on decoupling theory and LMDI model[J].Transactions of the Chinese Society of Agricultural Engineering,2019,35(12):272-280.
Authors:Liu Shuchang  Ye Yanmei and Lin Yaoben
Institution:1. School of Public Affairs, Zhejiang University, Hangzhou 310058, China; 2. Laboratory of Rural-Urban Construction Land Economical and Intensive Use, Beijing 100812, China,1. School of Public Affairs, Zhejiang University, Hangzhou 310058, China; 2. Laboratory of Rural-Urban Construction Land Economical and Intensive Use, Beijing 100812, China and 1. School of Public Affairs, Zhejiang University, Hangzhou 310058, China; 2. Laboratory of Rural-Urban Construction Land Economical and Intensive Use, Beijing 100812, China
Abstract:Abstract: In order to study the coupling relationship between rural population and rural residential land area change and promote the economization and intensification level of rural residential land, in this paper the Tapio decoupling model was introduced to reveal the decoupling degree of rural population-land change. From the perspective of urban and rural demographic shift, the factors decomposition model for rural residential land expansion was established. The logarithmic mean Divisia index (LMDI) was adopted to quantitatively analyze the influencing factors accounting for the changes in rural residential land area. The change of rural residential land area was decomposed into 4 main driving effects including rural residential land intensive use effect, urban-rural population structure effect, urbanization effect and total population effect. The addition decomposition method was used to measure the magnitude of 4 driving effects. The rural residential land area of China (1996-2016) and 31 provinces or municipalities (2000-2016) were taken as example. The results show that China has experienced rapid urban-rural transformation in the past few years. Rural population continues to decrease, presenting a 30.7 percent decline. But in the meantime, the total area of rural residential land increases continuously. The changes in rural residential land area among different provinces (municipalities) varied obviously, and overall the eastern and western regions indicated a greater growth. The relationship between rural population and rural residential land change is uncoordinated, and rural residential land tends to be more extensively utilized. From the decoupling index of China and 31 provinces or municipalities, the decoupling relationship between rural population and residential land area change were mainly characterized by strong negative decoupling. The degree of negative decoupling in the eastern and western regions was more serious than that in the central areas. What''s more, the degree of negative decoupling is generally deteriorating. The values of 4 driving effects were measured from 1996-2016. The results indicated that the scale of rural residential land in China increased by 2.020×105 hm2 from 1996 to 2008 including a decrease of 116.833×105 hm2 caused by urban-rural population structure effect, and the increase of 33.497×105, 71.813×105, 13.544×105 hm2 for rural residential land intensive use effect, urbanization effect and total population effect, respectively. Additionally, during 2009-2016, the scale of rural residential land in China increased by 7.275×105 hm2. The rural residential land intensive use effect, urbanization effect and total population effect caused the increase of 36.689×105, -68.271×105, 32.164×105, 6.692×105 hm2, respectively. Among 4 driving effects, the urban-rural population structure effect was stronger than the others. The contribution of 4 driving effects to the change in rural residential land area in different periods performed differently. The value of urbanization effect was greater than that of rural residential land intensive use effect during 1996-2008, but after 2009, the rural residential land intensive use effect gradually exceeded the urbanization effect, and become the dominant factor caused the increase of rural residential land. Therefore, strengthening the planning and management of rural residential land, gradually promoting rural residential land consolidation, and actively exploring the exit mechanism of rural residential land may be effective measures for improving the intensification level of rural land use.
Keywords:land use  rural areas  models  rural residential land  evolution characteristics  Tapio decoupling method  LMDI
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