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Investigating landscape pattern and its dynamics in Daqing, China

  • Texas State University
  • CAS - Northeast Institute of Geography and Agricultural Ecology

Research output: Contribution to journalArticlepeer-review

50 Scopus citations

Abstract

The landscape pattern of Daqing city, China has undergone a significant change in 1990-2000 as a result of the rapid urbanization process. The focus of this paper is to quantitatively capture landscape pattern and its spatial dynamics of Daqing city at the landscape level over the 10 years span. A traditional supervised classification (maximum likelihood classification) was carried out on Daqing region using three sets of Landsat Thematic Mapper (TM) imagery, respectively acquired in 1990, 1996, and 2000, and the classification results were transformed to polygon layers and input into geographic information system (GIS) software. In order to facilitate our examination of landscape pattern and its dynamics in Daqing, we chose two categories of landscape indices with supplementary ecological meanings. They are patch-based indices and spatial heterogeneity-based indices. Specifically, for the first category, three representative indices (Patch size coefficient variation, Landscape shape index, and Area-weighted mean patch fractal dimension) were calculated. For the latter category, Shannon's diversity index, Contagion index, Proximity index, and Fragment index were chosen and computed. Based on the derived indices, a general trend of landscape change was revealed: wetland was degraded into grassland resulting in a more fragmented pattern, whereas grassland was cultivated and taken over by agriculture. Forest coverage decreased with the small patch replaced by grassland and agriculture, while city was sprawling by merging neighbouring land cover and land use types. GIS-based landscape index, coupled with remote sensing analysis, proved its unique value and effectiveness in assessing landscape pattern and dynamics.

Original languageEnglish
Pages (from-to)2259-2280
Number of pages22
JournalInternational Journal of Remote Sensing
Volume26
Issue number11
DOIs
StatePublished - Jun 10 2005

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