Information Mining of Spatio-temporal Evolution of Lakes Based on Multiple Dynamic Measurements
نویسندگان
چکیده
Lakes are important water resources and integral parts of the natural ecosystem, and it is of great significance to study the evolution of lakes. The area of each lake increased and decreased at the same time in natural condition, only but the net change of lakes’ area is the result of the bidirectional evolution of lakes. In this paper, considering the effects of net fragmentation, net attenuation, swap change and spatial invariant part in lake evolution, a comprehensive evaluation indexes of lake dynamic evolution were defined,. Such degree contains three levels of measurement: 1) the swap dynamic degree (SDD) reflects the space activity of lakes in the study period. 2) the attenuation dynamic degree (ADD) reflects the net attenuation of lakes into non-lake areas. 3) the fragmentation dynamic degree (FDD) reflects the trend of lakes to be divided and broken into smaller lakes. Three levels of dynamic measurement constitute the three-dimensional "Swap attenuation fragmentation" dynamic evolution measurement system of lakes. To show its effectiveness, the dynamic measurement was applied to lakes in Jianghan Plain, the middle Yangtze region of China for a more detailed analysis of lakes from 1984 to 2014. In combination with spatial-temporal location characteristics of lakes, the hidden information in lake evolution in the past 30 years can be revealed.
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