Temporal and spatial change detecting (1998–2003) and predicting of land use and land cover in Core corridor of Pearl River Delta (China) by using TM and ETM+ images

Article

Abstract

Land use/land cover (LULC) has a profound impact on economy, society and environment, especially in rapid developing areas. Rapid and prompt monitoring and predicting of LULC’s change are crucial and significant. Currently, integration of Geographical Information System (GIS) and Remote Sensing (RS) methods is one of the most important methods for detecting LULC’s change, which includes image processing (such as geometrical-rectifying, supervised-classification, etc.), change detection (post-classification), GIS-based spatial analysis, Markov chain and a Cellular Automata (CA) models, etc. The core corridor of Pearl River Delta was selected for studying LULC’s change in this paper by using the above methods for the reason that the area contributed 78.31% (1998)-81.4% (2003) of Gross Domestic Product (GDP) to the whole Pearl River Delta (PRD). The temporal and spatial LULC’s changes from 1998 to 2003 were detected by RS data. At the same time, urban expansion levels in the next 5 and 10 years were predicted temporally and spatially by using Markov chain and a simple Cellular Automata model respectively. Finally, urban expansion and farmland loss were discussed against the background of China’s urban expansion and cropland loss during 1990–2000. The result showed: (1) the rate of urban expansion was up to 8.91% during 1998–2003 from 169,078.32 to 184,146.48 ha; (2) the rate of farmland loss was 5.94% from 312,069.06 to 293,539.95 ha; (3) a lot of farmland converted to urban or development area, and more forest and grass field converted to farmland accordingly; (4) the spatial predicting result of urban expansion showed that urban area was enlarged ulteriorly compared with the previous results, and the directions of expansion is along the existing urban area and transportation lines.

Keywords

LULC Change detection Predict Core corridor of Pearl River Delta Markov chain CA model China Remote sensing 

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Copyright information

© Springer Science+Business Media B.V. 2007

Authors and Affiliations

  1. 1.State Key Laboratory of Organic Geochemistry, Guangzhou Institute of GeochemistryChinese Academy of SciencesGuangzhouPeople’s Republic of China
  2. 2.School of GeographySouth China Normal UniversityGuangzhouPeople’s Republic of China
  3. 3.Graduate School of the Chinese Academy of SciencesBeijingPeople’s Republic of China
  4. 4.Faculty of Science and TechnologyUniversity of MacauMacaoPeople’s Republic of China
  5. 5.Guangzhou Institute of Geochemistry, Chinese Academy of SciencesGuangzhouPeople’s Republic of China

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