![Sample our Geography journals, sign in here to start your FREE access for 14 days]({"type":"image" , "src" : "/sda/5937/TOC-Subject-Sample-2021-Geography.jpg"})
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.
Acknowledgments
The study was supported by one grant to L. Wang from Texas Remote Sensing Consortium, and one of the knowledge innovation projects of Chinese Academy of Sciences: Digital Reconstruction of LUCC of Northeast Region over the last 100 years, subject number KZCX2‐SW‐320‐1.