Identification And Evolution Analysis Of Grassland Shrub Encroachment Based On Low-Altitude UAV

Shrub encroachment as one of the core processes of land desertification in arid and semi-arid areas,occurs widely in grassland ecosystems in China,gradually changing the original structure and function of grassland ecosystems.we carried out shrub identification based on remote sensing with a low-altitude UAV,combined with a field investigation,at a shrub encroachment in Xilinhot,Inner Mongolia.Then rose to a large area to conduct research on shrub encroachment,with a view to providing help for shrub encroachment remote sensing identification methods and shrub encroachment invasion research.An analysis of variance of the normalized differential vegetation index for shrubland,grassland,and bare land determined that the segmentation threshold of the bare and vegetated lands was-0.08.The vegetation covered area was extracted using this threshold and four object-oriented machine learning classification classifiers,i.e.,Decision Tree(DT),Bayes,k-nearest neighbor(KNN),and Support Vector Machine(SVM),were used to identify the shrubs.Results showed that the tool used to evaluate the optimal segmentation scale,i.e.,estimation the scale parameter,could rapidly determine the segmentation parameters,obtain shrub and grass images.We effectively avoided blind selection and increased the number of calculations by using the feature selection and optimization tool to select 18 object features with the highest degree of discrimination.A comparison of results from the different classifiers revealed that the Bayes classifier had the highest classification accuracy,with an overall accuracy and Kappa coefficient of 92%and 0.83,respectively.Its classification results matched the image features well and identified individual shrubs precisely.According to Bayes classification,shrubs covered 14.74%of the study area,and the average crown was 0.6 m2.The results of the remote sensing experiments were almost the same as those from ground-based measurements in the field.A sensitivity experiment on the sample size showed that:1)SVM obtained a high classification accuracy with relatively few counts in the training sample but was sensitive to parameter settings,which may lead to abnormal classification results.2)the Bayes classifier had a high precision with stable number of samples,if sufficient training samples were provided.3)the overall classification accuracy of the DT classifier varied with the number of samples,and 4)the overall accuracy of the KNN classifier was the lowest among the four classifiers.Due to their different algorithmic features and different sensitivities to the number of training samples,the selection of a suitable classifier depends on the surface object being observed and spatial resolution of the image,along with the scope of the study area.Shrub research based on the classification results of large-scale research areas found that the growth status of shrubs in the study area was related to topography,grazing,hydrology and other factors,and the historical process of shrub encroachment invasion was extracted based on the area of shrub crowns.UAV remote sensing has created a new perspective for the study of grassland shrub encroachment in traditional ecology.However,the impact of nature and human beings on the invasion of grassland shrub involves all aspects of the problem.The study of grassland shrub is still in a shallow level of exploration.The follow-up work has a long way to go,and there are quite a lot of problems need to be deeper level Research.