Monitoring land changes is an important activity in landscape planning and resource management. In
this study, we analyze urban land changes in Atlanta metropolitan area through the combined use of
satellite imagery, geographic information systems (GIS), and landscape metrics. The study site is a fastgrowing
large metropolis in the United States, which contains a mosaic of complex landscape types. Our
method consisted of two major components: remote sensing-based land classification and GIS-based
land change analysis. Specifically, we adopted a stratified image classification strategy combined with
a GIS-based spatial reclassification procedure to map land classes from Landsat Thematic Mapper (TM)
scenes acquired in two different years. Then, we analyzed the spatial variation and expansion of urban
land changes across the entire metropolitan area through post classification change detection and a
variety of GIS-based operations.We further examined the size, pattern, and nature of land changes using
landscape metrics to examine the size, pattern, and nature of land changes. This study has demonstrated
the usefulness of integrating remote sensing with GIS and landscape metrics in land change analysis that
allows the characterization of spatial patterns and helps reveal the underlying processes of urban land
changes. Our results indicate a transition of urbanization patterns in the study site with a limited outward
expansion despite the dominant suburbanization process.
Monitoring land changes is an important activity in landscape planning and resource management. In
this study, we analyze urban land changes in Atlanta metropolitan area through the combined use of
satellite imagery, geographic information systems (GIS), and landscape metrics. The study site is a fastgrowing
large metropolis in the United States, which contains a mosaic of complex landscape types. Our
method consisted of two major components: remote sensing-based land classification and GIS-based
land change analysis. Specifically, we adopted a stratified image classification strategy combined with
a GIS-based spatial reclassification procedure to map land classes from Landsat Thematic Mapper (TM)
scenes acquired in two different years. Then, we analyzed the spatial variation and expansion of urban
land changes across the entire metropolitan area through post classification change detection and a
variety of GIS-based operations.We further examined the size, pattern, and nature of land changes using
landscape metrics to examine the size, pattern, and nature of land changes. This study has demonstrated
the usefulness of integrating remote sensing with GIS and landscape metrics in land change analysis that
allows the characterization of spatial patterns and helps reveal the underlying processes of urban land
changes. Our results indicate a transition of urbanization patterns in the study site with a limited outward
expansion despite the dominant suburbanization process.
การแปล กรุณารอสักครู่..
