Application of satellite imageries on the assessment of landuse changes and consequence environmental impacts
2009
Zarrinbal, M., Researches of Agricultural Natural Resources and Research Center of East Azarbaijan Province Iran | Rasouli, A.A., Member of Scientific Board of Tabriz University | Shafie, M., Expert of GIS in Qazvin Municipality
During the time, landcover and associated landuse patterns are changing very fast and the human factors play a major role in such drastic changes. Scientists have formerly attempted to identify the landuse altering processes and related environmental impacts. In the past decades, researchers have generally examined dissimilar sort of observations taking from the field operations and also arial photos for detection of different kind of changes which occurred by human actions or natural process. Nowadays, satellite images could be accurately processed, as an advanced technique in remote sensing, to determine the environment changes in a particular object of study between two or more time periods. In current study, it was primary viewed as an important process for monitoring of Qazvin plain landuse changes and latest but very fast industrial and urban developments to provide quantitative analysis of the spatial variation of landcovers in the area of interest. Accordingly, some image processing techniques such as: A supervised classification and its different algorithms specifically: Maximum likelihood, methods were utilized to evaluate landuse changes in the study area. All these methods were performed using Landsat TM and ETM+ data for 1987 and 2002 to detect spatially physical extension of the industrial and residential areas. Overall results have indicated that about 19.86 percent of landuse patterns have been changed through decreasing on pasture, dry-farming and orchard landuses in responding to the increasing of residential and industrial landcovers. In order to evaluate some associated environmental impacts in the region an arbitrary damage index was introduced and results were categorized into four different categories to inventor that the human processes at work can be more fully understood by applying new approached remote sensing technology. Final models indicate that more than 18 thousand hectares of landuse patterns could be recognized as destructive changes in the region.
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