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1990—2017年河北省易县土地利用时空格局动态变化
引用本文:董光,何兰,王艺积,熊瑞东,程武学.1990—2017年河北省易县土地利用时空格局动态变化[J].中国农业资源与区划,2020,41(1):242-249.
作者姓名:董光  何兰  王艺积  熊瑞东  程武学
作者单位:四川师范大学地理与资源科学学院,成都610068; 四川师范大学西南土地资源评价与监测教育部重点实验室,成都610068,四川师范大学地理与资源科学学院,成都610068; 四川师范大学西南土地资源评价与监测教育部重点实验室,成都610068,四川师范大学地理与资源科学学院,成都610068; 四川师范大学西南土地资源评价与监测教育部重点实验室,成都610068,四川师范大学地理与资源科学学院,成都610068; 四川师范大学西南土地资源评价与监测教育部重点实验室,成都610068,四川师范大学地理与资源科学学院,成都610068; 四川师范大学西南土地资源评价与监测教育部重点实验室,成都610068
基金项目:四川省科技厅应用基础项目“星机地协同的若尔盖草地鼠害遥感监测研究”(2017JY0155); 四川省科技厅应用基础项目“基于互联网+多阶段遥感反演的区域水稻参数逐地块监测技术研究”(2017JY0284)
摘    要:目的]河北省易县是太行山片区的典型区,土地利用与经济发展特征明显。研究该县土地利用时空格局动态变化,可以为区域生态建设与可持续发展提供一定的参考。方法]通过对Landsat中分辨率遥感影像解译分析,获取易县1990年、2000年、2010年和2017年的土地利用格局,在深入分析土地利用转移矩阵、动态度、信息熵的基础上,对土地利用变化程度的进行有效空间化,探索土地利用在不同地形梯度上的变化规律。结果]1990—2017年,研究区耕地和草地的面积均明显减少,主要转移为林地和建设用地,建设用地净增14241.38hm^2;动态度持续增大,表明土地利用变化日渐活跃,其中近7年的动态度达到2.50%;4个时间节点的信息熵值分别为1.309、1.330、1.349、1.353,呈不断升高趋势,表明快速城市化进程中各类产业发展所需的用地类型已经逐渐完善,区域发展逐渐走向成熟。土地利用变化总体趋向自然生态方向,平原地区城市化率最高,偏离自然生态方向较大;低山丘陵地区的城市化率较低,趋向自然生态方向程度显著。结论]通过分层次、多算法相结合,能够深入有效地分析土地利用时空格局动态变化特征,对于该地区的生态建设和可持续发展具有重要意义。

关 键 词:易县  土地利用变化程度指数  动态度  信息熵  地形梯度
收稿时间:2018/4/16 0:00:00

STUDY ON SPATIO TEMPORAL PATTREN OF LAND USE CHANGE IN YI COUNTY, HEBEI PROVINCE FROM 1990 TO 2017
Dong Guang,He Lan,Wang Yiji,Xiong Ruidong and Cheng Wuxue.STUDY ON SPATIO TEMPORAL PATTREN OF LAND USE CHANGE IN YI COUNTY, HEBEI PROVINCE FROM 1990 TO 2017[J].Journal of China Agricultural Resources and Regional Planning,2020,41(1):242-249.
Authors:Dong Guang  He Lan  Wang Yiji  Xiong Ruidong and Cheng Wuxue
Institution:(The Institute Geography and Resources Science,Sichuan Normal University,Chengdu,Sichuan 610068,China;Key Lab of Land Resources Evaluation and Monitoring in Southwest,Ministry of Education,Sichuan Normal University,Chengdu,Sichuan 610068,China)
Abstract:Yixian county, Hebei province, is a typical area of Taihang Mountains, which has typical characteristics in land use and economic development. This research aims to master the dynamic change of land use spatial temporal pattern in this county, so as to provide reference for ecological construction and sustainable development of this region. In this research, the land use patterns of Yixian County in 1990, 2000, 2010 and 2017 were obtained through interpretation and analysis of Landsat medium resolution remote sensing images. On the basis of in depth analysis of land use transfer matrix, dynamic degree and information entropy, the degree of land use change was spatialized. And then the rule of land use change on the terrain gradient was explored. The results showed that the area of cultivated land and grassland in the study area decreased significantly from 1991 to 2017. And the decrease was mainly transferred to forest land and construction land, of which the net increase of construction land was 14 241.38 hm2. The dynamic degree of land use was increasing, which indicated that land use change was becoming more and more active, with the dynamic degree reached 2.50% in the past seven years. The information entropy of land use structure in 1990, 2000, 2010 and 2017 was 1.309, 1.330, 1.349 and 1.353, respectively. And the increasing entropy indicated that the type of land needed for the development of various industries in the process of rapid urbanization had been gradually improved, and the regional development had gradually become mature. In the past 27 years, the direction of land use change was generally natural and ecologically friendly. In the study area, the urbanization rate of plain area was the highest, which deviated from the natural ecological direction. The urbanization rate of hilly area was low, which tended to the degree of natural ecology. The conclusion of this study is that the combination of hierarchical and multi algorithm can deeply and effectively analyze the dynamic characteristics of spatial and temporal patterns of land use, which is of great significance to the ecological construction and development decision making in this area.
Keywords:Yi county  land use change degree  dynamic degree  information entropy  terrain gradient
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