Hyper-spectral characteristics of rolled-leaf desert vegetation in the Hexi Corridor, China

来源 :干旱区科学 | 被引量 : 0次 | 上传用户:wangyu1221
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Desert plants survive harsh environment using a variety of drought-resistant structural modifications and physio-ecological systems.Rolled-leaf plants roll up their leaves during periods of drought,making it difficult to distinguish between the extal structures of various types of plants,it is therefore necessary to carry out spectral characteristics analysis for species identification of these rolled-leaf plants.Based on hyper-spectral data measured in the field,we analyzed the spectral characteristics of seven types of typical temperate zone rolled-leaf desert plants in the Hexi Corridor,China using a variety of mathematical transformation methods.The results show that:(1) during the vigorous growth period in July and August,the locations of the red valleys,green peaks,and three-edge parameters,namely,the red edge,the blue edge,and the yellow edge of well-developed rolled-leaf desert plants are essentially consistent with those of the majority of terrestrial vegetation types;(2) the absorption regions of liquid water,i.e.,1400-1500 and 1600-1700 nm,are the optimal bands for distinguishing various types of rolled-leaf desert plants;(3) in the leaf reflectance regions of 700-1250 nm,which is controlled by cellular structure,it is difficult to select the characteristic bands for differentiation rolled-leaf desert vegetation;and (4) after processing the spectral reflectance curves using a first-order differential,the envelope removal method,and the normalized differential ratio,we identify the other characteristic bands and parameters that can be used for identifying various types of temperate zone rolled-leaf desert plants,i.e.,the 510-560,650-700 and 1330-1380 nm regions,and the red edge amplitude.In general,the mathematical transformation methods in the study are effective tools to capture useful spectral information for species identification of rolled-leaf plants in the Hexi Corridor.
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