SCIENTIA GEOGRAPHICA SINICA ›› 2001, Vol. 21 ›› Issue (5): 447-451.doi: 10.13249/j.cnki.sgs.2001.05.447

Previous Articles     Next Articles

Estimating the Semimetals Effect of Chaohe River to Miyun Reservoir Using Multi-temporal TM Images

CHENG Cheng-qi1, MA Ting1, WANG Li-ming2, YANG De-hai1   

  1. 1. Institute of Remote Sensing & GIS, Peking University, Beijing 100871;
    2. Institute of Forest Ecology, China Academy of Forestry, Beijing 100091
  • Received:2001-06-08 Revised:2001-09-18 Online:2001-09-20 Published:2001-09-20

Abstract: The sediment, which is taken by rivers, will subside in the corporate action of river and reservoir on the estuarine area, when it enters into the reservoir. In theory, the quantity of sediments in water is correlated with the distance to the reservoir entrance. At the same time, the quantity of sediments in water has a certain relation with the reflection of water in every band of visible light, according to the result of experimentation and simulation. It happens that, the second and third bands of TM image lie just in the caroming and peak of reflection spectrum of the sandy water, thus the quantity of sand in water can be exactly reflected. Then we can make use of this characteristic to quantify the sediments in water. In this paper, the boundary of Chaohe River and Miyun Reservoir is taken an example. On the basis of the equation of the quantity of sediments and the negative exponent of reflection, together with multi-temporal TM image, a remote sensing spatial-distribution model of sedimentation course has been created, in which the principal axis of sedimentation course is researched and the combined method of recursive simulation and experiential formula is adopted. The meaning of each parameter of the model is discussed in order to describe the quantity and sedimentation of sediments in water. Finally, in the way of multi axis' simulation and spatial insertion analysis, the spatial distributed stimulant picture of the quantity of sediments in water is portrayed. After examination, this picture preferably reflects the quantity of sediments in water on the entrance of the reservoir, which provides a technical foundation for the remote sensing technology in inspecting the quantity of sediments in water.

CLC Number: 

  • X87/P333.4