Title
Remote-Sensing and Modeling of the Potential Suitable Sites for Restoration in Dajiuhu Sub-alpine Wetland
Abstract
In view of the data limitations for mountain wetland, we validated the application of high spatial resolution satellite imagery and DEM for mountain wetland conservation and restoration in this paper. Dajiuhu wetland, a rare sub-alpine wetland which is threatened by degradation and currently poorly understood, was select as the study area. Although there are scarce of basis data in Dajiuhu wetland, spatial patterns of the wetland vegetation could be obtained from the remote sensing interpretation, and the classification could achieve the plant formation level via integrating the high spatial resolution images with field survey. Total classification accuracy is about 83%. Despite of the widespread manmade drainage systems and the great changes on topography, hydrology, vegetations and land-cover, the potential suitable sites for wetland restoration could be modeled and located by the spatial analyzing to the result of satellite imagery classification and a high resolution (10m) DEM. Total area of the simulated potential lakes is 107.03hm2, which is comparable with the original perennial lakes before 1950s. The research could provide basic data for the restoration of the Dajiuhu mountain wetland, and would be a useful tool to locate the potential suitable sites for wetland restoration.
Year
DOI
Venue
2009
10.1109/ESIAT.2009.362
ESIAT (2)
Keywords
Field
DocType
surfaces,image analysis,topography,spatial resolution,satellites,environmental management,indexes,digital elevation model,digital elevation models,high resolution,degradation,hydrology,spatial pattern,remote sensing,vegetation,image restoration,image classification
Drainage,Vegetation,Satellite imagery,Wetland conservation,Computer science,Hydrology,Remote sensing,Wetland,Digital elevation model,Land cover,Spatial ecology
Conference
Volume
Issue
Citations 
2
null
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
Fei Xiao100.68
Yun Du215316.11
Feng Ling330.76
Wang Xue Lei402.37