Study on shallow ground water index by Remote Sensing -Example of the Keriya Oasis
Résumé
The Keriya Oasis in china's Xinjiang region has shown obvious degradation of ecological environment due to numerous natural and anthropogenic factors. Information from remotely sensed data about shallow ground water level distribution has contributed significantly to an understanding of these environmental changes. In this paper, an index, called Shallow Ground Water Index or SGWI, was developed. Its calculation is based on remote sensing exploration of surface features depending on the ground water level. A ground water level distribution map was produced from a Landsat ETM+ image of Keriya Oasis with a correlation coefficient of 0.94.