Monitoring And Analysising Of Desertification In Mu Us Sandy Land Based On Differential Index

With the increasingly prominent global environmental problems,the human living environment is affected by human activities and climate change,which makes the issue of environmental change receive global attention.As an ideal area to study global desertification change and the first large-scale desert successfully controlled in China,MU US Sandy land has been widely recognized by the international academic and the world.With the progress of science and the deepening of human understanding,the research on MU US sandyland has been constantly enriched and expanded,and many valuable Suggestions and measures have been put forward for sand control and sand control.In this paper,a region located in the hinterland of MU US sandyland on the ordos plateau with both spatial heterogeneity and ecological fragility was selected as the research area.Various software platforms such as Arc GIS,ENVI and Global Mapper were used to analyze the dynamic changes of desertification in the research area from 1995 to 2015 by means of man-machine interaction.The main work contents are as follows:(1)NDVI-Albedo feature space is es Tab.lished.NDVI and Albedo data were obtained based on the improved pixel binary model and the surface Albedo inversion model es Tab.lished by Liang.The most representative sample points were selected to extract the corresponding NDVI and Albedo data.The ndvi-albedo feature space was es Tab.lished under the support of SPSS software.(2)the desertification difference index model is optimized.Based on the ndvi-albedo feature space,the existing desertification difference index model was optimized to solve the shortcomings of the original model in water area monitoring and improve the precision and efficiency of desertification inversion.(3)the degree of desertification in the study area was graded based on the natural discontinuity grading method.The desertification situation of the study area was monitored by using the difference index model of desertification(DDI)and the difference index model of optimized desertification respectively,and the degree of desertification in the study area was divided into four grades of non-light,medium and heavy desertification according to the threshold obtained by the natural discontinuity point classification method.(4)the dynamic change characteristics of desertification in the study area were analyzed.The desertification distribution in the study area was extracted by combining supervised classification and visual interpretation,and the desertification classification map of different degrees was obtained.Then,based on Arc GIS platform,the desertification area transfer matrix and the desertification dynamic change map were obtained,and the desertification dynamic change in the research area was analyzed from the three aspects of area change characteristics,spatial change characteristics and time evolution characteristics.(5)the influencing factors of desertification change in the study area were analyzed.Through the mathematical statistics of climatic spatial interpolation data and socio-economic data in the research area,and combining with the data of vegetation distribution in the research area obtained by the natural decision tree classification method,the natural and human factors affecting vegetation coverage and desertification development in the research area were analyzed.In this paper,desertification monitoring is carried out by optimizing DDI model,and better results are obtained in water area monitoring,accuracy,efficiency and other aspects.From 1995 to 2015,the desertification in the study area showed a weakening trend.Finally,the influencing factors are evaluated and analyzed.