Remotely sensed data have been the most important data source for environment change study in the past 30 years. Large collections of remote sensing imagery have provided a solid foundation for spatio-temporal analyses of the environment and the impact of human activities. This study seeks an efficient and practical methodology for integrating multi-temporal and multi-scale remotely sensed data from various sources with a monitoring time frame of 30 years, including historical and state-of-the-art high-resolution satellite imagery. Based on this, spatio-temporal patterns of environmental change, which is largely represented by changes in land cover (e.g., vegetation and water), were analysed for the given time frame. Multi-scale and multi-temporal remotely sensed data, including Landsat MSS, TM, ETM and SPOT HRV, were used to detect changes in land use in the past 30 years in Tarim River, Xinjiang, China. The study shows that by using the auto-classification approach an overall accuracy of 85%-90% with a Kappa coefficient 0.66-0.78 was achieved for the classification of individual images. The temporal trajectory of land-use change was established and its spatial pattern was analysed to obtain a better understanding of the human impact on the fragile ecosystem of China's arid environment.
|Title of host publication||Advances in Spatial Analysis and Decision Making|
|Subtitle of host publication||a selection of peer-reviewed papers presented at the ISPRS Workshop on Spatial Analysis and Decision Making, 3-5 December, 2003, Hong Kong, China|
|Editors||Zhilin Li, Qiming Zhou, Wolfgang Kainz|
|Number of pages||12|
|ISBN (Print)||9058096521, 9789058096524|
|Publication status||Published - 1 Jan 2003|
|Name||International Society for Photogrammetry and Remote Sensing (ISPRS) Book Series|