北京市农林科学院机构知识库

Characterizing spatiotemporal dynamics of land cover with multi-temporal remotely sensed imagery in Beijing during 1978-2010

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文献类型：外文期刊

作者： Zhao, Jinling ¹ ; Guo, Wei ² ; Huang, Wenjiang ³ ; Huang, Linsheng ¹ ; Zhang, Dongyan ¹ ; Yang, Hao ⁴ ; Yuan, Lin ⁴ ;

作者机构： 1.Anhui Univ, Key Lab Intelligent Comp & Signal Proc, Minist Educ, Hefei 230039, Peoples R China

2.Henan Agr Univ, Coll Informat & Management Sci, Zhengzhou 450002, Peoples R China

3.Chinese Acad Sci, Inst Remote Sensing & Digital Earth, Beijing 100094, Peoples R China

4.Beijing Acad Agr & Forestry Sci, Beijing Res Ctr Informat Technol Agr, Beijing 100097, Peoples R China

关键词： Land cover;Landsat imagery;Remote sensing;Change detection;Driving forces analysis

期刊名称：ARABIAN JOURNAL OF GEOSCIENCES （影响因子：1.827；五年影响因子：1.985 ）

ISSN： 1866-7511

年卷期： 2014 年 7 卷 10 期

页码：

收录情况： SCI

摘要： To facilitate urban planning and management in fast-growing metropolitan areas, it is highly necessary to detect the spatiotemporal changes of different land cover types. This study aimed at identifying Beijing's land cover types and detecting the characteristics of their spatiotemporal changes using time series remote sensing and GIS techniques from 1978 to 2010. A total of 16 Landsat MSS/TM/ETM+ images were collected during the spring and late summer seasons. After preprocessing the dataset, artificial neural network was used to perform the land cover classification. Consequently, four maps were generated for 1978, 1992, 2000, and 2010, with six classes (agriculture, woodland, grassland, water, urban, and barren land) according to the level I classification scheme. Three transition matrices were constructed to represent all possible changes that occur in the landscape. The results showed that agriculture, barren land, and grassland had an increase in area, while urban, water, and woodland had a reduction within the study area. A total of 2,032.341 km(2) agriculture was reduced and 2,359.146 km(2) woodland was increased. In the three periods for 1978-1992, 1992-2000, 2000-2010, agriculture had the largest amount of transfer out primarily to urban class around central urban areas and woodland had the most transfer in mainly from barren land in mountainous areas. More importantly, the driving forces analysis including economic development, growth of population and construction areas, and institutional policies was conducted to find out the primary factors inducing the land cover change.

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