Land Cover Extraction in the Ejina Oasis by Hyperspectral Remote Sensing

The extraction of land surface coverage is the basis of ecological environment evaluation，vegetation change analysis and regional ecological and hydrological processes.Aerial hyperspectral remote sensing has great advantage in land surface coverage extraction，such as flexible，wide coverage，high spatial resolution and high spectral resolution.Research area has landscape characteristics of vegetation，landscape fragmentation and heterogeneity in Ejina Poplar Forest National Nature Reserve.Comparison and analysis of two methods of dimension reduction based on minimum noise transform and principal component analysis，three supervised classification methods based on maximum likelihood method，support vector machine and object|oriented classification.Land surface coverage is extracted by NDVI threshold segmentation，minimum noise transform dimensionality reduction method and maximum likelihood classification method according to the characteristics of landscape fragmentation，heterogeneity and high redundancy of hyperspectral data based on the Airborne Hyperspectral Data of Ejina oasis in the lower reaches of Heihe.The land surface coverage results overall accuracy and Kappa coefficient are 87.95% and 0.885 by random sampling based on airborne remote sensing data.The results show that the classification results of high accuracy can provide effective parameters for ecological research.