Remote Sensing Imagery-Based Automated Land-Use Change Study

Our ability to change ourselves and our surroundings increases with each technological advance. Changes today are more extensive and occur more rapidly than ever before. The significance of these changes increases as the world's population grows, the available land base declines, and the resiliency of our environment becomes increasingly taxed. As a result, many organizations need to monitor change in land-cover and land-use.A large portion of arid and semi-arid region is located in Eastern and Northern China. These vast landscapes are vulnerable to environmental changes and changes in surface properties caused by inappropriate or too intense land uses, inducing a significant impact on the climate through modifications of hydrological processes. According to the level of stress (of human and/or climatic origin) different degrees of soil erosion, vegetation cover decrease and, ultimately, land degradation occur. As a consequence, the hydrologic processes and patterns are altered and the overall biodiversity and productivity of the rangelands deteriorate. A close monitoring of these biomes is needed to ensure the sustainable management of these very fragile and widespread landscapes and to watch global warming-driven ecological changes potentially occurring on the desert margins which are considered the most sensitive areas.The data obtained from the Landsat Thermatic Mapper sensor provide an unique opportunity, due to its more accurate radiometric calibration and geometric registration, as well as its additional blue and SWIR spectral for possible soil corrections, to utilize remote sensing measurements to address these scientifically and socially critical issues.Change detection is a technique used to determine the change between two or more time periods of a particular object of study. Change detection is an important process in monitoring and managing natural resources and urban development because it provides quantitative analysis of the spatial distribution in the population of interest. A large number of change-detection techniques have been developed, but little has been done to quantitatively assess the accuracies of these techniques.The objective of this research is to present the change-detection procedure in the form of a successful combination of radiometric and geometric correction of the imagery and subsequent assessment of land cover change. We present here a unique means of using only Landsat imagery without reference data for the assessment of change in a semi-arid land in western Jilin during the period 2000 to 2002. Analyses of standard accuracy and spatial agreement are performed to compare the new images (hereafter called "change images") representing the change between the two dates. Spatial agreement evaluates the conformity in the classified "change pixels" and "no-change pixels" at the same location on different change images and comprehensively examines the different techniques. This method would enable authorities to monitor land degradation efficiently and accurately.This dissertation assess the information content and accuracy of Landsat ETM+ digital images in land-cover change detection in the Tongyu, Zhenlai and Baicheng areas of western Jilin, China. Change-detection techniques of spectral image differencing, normalized difference vegetation index differencing, principal components analysis, and tasseled-cap transformation differencing, albedo differencing and a combination of spectral image differencing and principal component analysis were applied to yield 18...