资源科学 ›› 2016, Vol. 38 ›› Issue (4): 714-727.doi: 10.18402/resci.2016.04.13

• 土地资源 • 上一篇    下一篇

基于空间自相关的区域农地变化驱动力研究——以珠三角地区为例

曹祺文1(), 吴健生1,2, 仝德1(), 张晓娜3, 卢志强1, 司梦林1   

  1. 1. 北京大学城市规划与设计学院城市人居环境科学与技术重点实验室,深圳518055
    2. 北京大学城市与环境学院资源与环境地理系地表过程与模拟教育部重点实验室,北京100871
    3. 天津工业大学管理学院,天津300387
  • 收稿日期:2015-08-17 修回日期:2015-12-27 出版日期:2016-04-25 发布日期:2016-04-25
  • 作者简介:

    作者简介:曹祺文,男,河南洛阳人,硕士生,主要研究方向为土地科学和景观生态学。E-mail:cqwgufeng@pku.edu.cn

  • 基金资助:
    国家自然科学基金面上项目(41271101)

Drivers of regional agricultural land changes based on spatial autocorrelation in the Pearl River Delta,China

CAO Qiwen1(), WU Jiansheng1,2, TONG De1(), ZHANG Xiaona3, LU Zhiqiang1, SI Menglin1   

  1. 1. Key Laboratory of Urban Habitant Environment Science and Technology,School of Urban Planning and Design,Peking University,Shenzhen 518055,China
    2. Laboratory of Earth Surface Processes of Ministry of Education,College of Urban and Environmental Sciences,Peking University,Beijing 100871,China
    3. School of Management,Tianjin Polytechnic University,Tianjin 300387,China
  • Received:2015-08-17 Revised:2015-12-27 Online:2016-04-25 Published:2016-04-25

摘要:

近年来,随着社会经济的快速发展,农地保护工作压力逐渐增大,掌握区域农地变化规律及其驱动力是制定可持续土地利用政策的基础。本文以珠三角地区为例,利用2000年和2010年土地利用遥感监测数据、基础地理空间数据和统计年鉴数据,分析了该区农地变化特征,然后在构建传统Logistic模型基础上引入空间自相关因子,采用AutoLogistic模型从自然、社会经济、空间距离和土地利用特征的空间自相关性等方面探讨了区域尺度农地变化驱动力。结果表明:①2000-2010年该区耕地、林地等农地以净减少为主,景观破碎度有所提高,耕地成为建设用地扩张的主要来源;②农地属性变化和土地开发强度的空间自相关性均为农地变化的重要驱动力,其他驱动力中耕地变化主要受地均GDP变化、到最近铁路的距离、总人口密度变化、年日照时数倾向率等因子影响,林地变化主要受地均GDP变化、总人口密度变化、坡度、到最近道路等因子影响;③同传统Logistic模型相比,采用能反映土地利用特征空间自相关性的AutoLogistic模型更适用于区域农地变化驱动力研究。

关键词: 农地变化, 驱动力, 空间自相关, Logistic模型, AutoLogistic模型, 珠三角地区

Abstract:

Land use/cover change(LUCC)is at the core of global change and agricultural land change is important in the study of LUCC. With socio-economic development,pressure on agri-cultural land protection has been increasing in China. To develop sustainable land use policy, we need to understand regional agricultural land changes and driving forces. Using land use monitoring data,basic geographic spatial data and statistical yearbooks,we analyzed characteristic of agricultural land change in the Pearl River Delta Area,China. Traditional Logistic modeling and AutoLogistic modeling which bring in spatial autocorrelation were compared to investigate the drivers of agricultural land change at regional scale from the perspectives of natural,socio-economic,spatial distance and spatial autocorrelation of land use characteristics. We found that cultivated land and forest in this region decreased from 2000 to 2010,leading to further fragmentation. Cultivated land has become a main source of expansion of construction land. And,both spatial autocorrelation of agricultural land property and land development intensity are important driving forces of agricultural land change. As for other driving forces,cultivated land change was mainly affected by factors such as ‘change of per kilometer GDP',‘distance to nearest railway',‘change of total population density',‘tendency rate of annual sunshine hours'. Forest changes were mainly affected by ‘change of per kilometer GDP',‘change of total population density',‘slope' and ‘distance to nearest road'. Compared with traditional Logistic modeling,the AutoLogistic model is more suited to study driving forces of regional agricultural land change.

Key words: agricultural land change, driving forces, spatial autocorrelation, Logistic model, Autologistic model, Pearl River Delta Area