Classification and changes of vegetation in Sugan Lake wetland in the extreme arid region
Wetland is the most biodiverse ecosystem on Earth,and wetland vegetation plays a crucial role in maintaining the stability and functionality of these ecosystems,so mastering wetland vegetation types and distri-bution characteristics is extremely important for biodiversity conservation.Due to factors such as lacking or un-systematic vegetation community information and remote sensing resolution,the research on vegetation distribu-tion in arid wetlands is limited.Taking the Sugan Lake wetland in the northern part of the Qaidam Basin of the ex-tremely arid region in northwest China as the study area,based on the field vegetation survey data of 116 points and 626 unmanned aerial vehicle image sample points data,Sentinel-1 Synthetic Aperture Radar(Synthetic Ap-erture Radar,SAR)data and Sentinel-2 Multispectral Imager imagery(MultiSpectral Instrument,MSI)data were used to construct a new remote sensing feature database.The vegetation in Sugan Lake wetland was classi-fied and mapped using the Random Forest algorithm.The results show that:(1)The combination of SAR and MSI data can improve the accuracy of wetland vegetation classification,with overall accuracy of wetland vegeta-tion classification exceeding 0.81 for the years 2019-2023,and Kappa coefficients of 0.82,0.84,0.86,0.82,and 0.82 respectively.(2)From 2019 to 2023,the area of Sugan Lake wetland remained stable,with a vegeta-tion distribution area of 783.90 km2.The distribution area ofreed(Phragmites australis)communities increased by 28.49 km2,and the area of leymus(Leymus secalinus)communities increased by 27.21 km2.In contrast,the coverage of triglochin palustre(Triglochin palustre)and eleocharis palustris(Eleocharis palustris)communities decreased by 64.49 km2.It is preliminarily considered that increased runoff and grazing prohibition policies are important reasons for the changes in wetland vegetation distribution.This study provides an effective method for surveying vegetation in arid area wetlands.High-quality dynamic monitoring of wetland vegetation offers theoret-ical references for the construction of ecological civilization and restoration measures.
remote sensing monitoringarid regionSugan Lake wetlandrandom forest algorithmvegeta-tion classification
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万方数据
