摘要
了解和掌握干旱区薄叶荒漠植物的光谱特征,不仅可为干旱荒漠区植物的遥感识别奠定基础,且对于干旱区的生态环境调控、演变及遥感反演等都具有重要的意义。以荒漠植物种丰富的河西走廊为研究区,利用全光谱便携式地物光谱仪测定13种灌木和9种草本薄叶荒漠植被地物反射光谱,对其光谱特征曲线、光谱特征参数及植被指数进行分析研究。结果表明,1)植被反射光谱波形大致相同,总体符合植被光谱特征的规律性;灌木植被和草本植被各在4个波段区间植被反射率差异明显,可用于识别荒漠植物;2)蓝边、黄边、红边位置及红谷、绿峰出现的波段范围差异不大,而蓝边、黄边、红边的斜率和面积各有差异;3)DVI值明显高于NDVI、SAVI、RVI、RDVI,利用同一种植被的5种植被指数的值同时大或小的排列顺序区分测定的大部分灌木植被和草本植被。
The understanding and mastering the spectral characteristics of desert plants with thin leaves in arid region can not only lay the ground for remote sensing identification of drought desert plants, but also has vital significance for ecological environment control, evolution and remote sensing inversion and so on. Take Hexi Corridor of Gansu as research area,which is rich in desert plants, using Fieldspec 4 Standard- Res(FS4S)Spectroradiometer,surface reflective spectra of 13 kinds of desert shrubs and 9 species of herba ceous vegetations were measured. The correlationships between their spectral characteristic curves, spectral characteristic parameters and the spectral reflectance of vegetation index were analyzed. The results showed 1) waveforms of vegetation reflection spectra were approximately the same with the regularity of the spec- tral characteristics of vegetation. Shrubs and herbaceous vegetations in each of the four bands could be used to distinguish different desert plants because vegetation reflectance differences were significant. 2) Blue, yellow,and red edge positions and red valley, green peak appeared in the band range, while the blue, yellow,and red edge slopes and areas were different. 3) DVI values were significantly higher than those of NDVI,SAVI,RVI,RDVI. The majority of shrub vegetations and herbaceous vegetations could be distin- guished by using five vegetation indices of the same plant.
出处
《西北林学院学报》
CSCD
北大核心
2017年第6期74-81,共8页
Journal of Northwest Forestry University
基金
国家自然科学基金(31360204、41361001、31560235、41361004)
甘肃省杰出青年基金项目(145RJDA327)
甘肃省青年科技基金计划项目(145RJYA262)
关键词
光谱特征
荒漠植物
光谱曲线
反射率
spectral reflectance characteristics
thin leaf desert plant
spectral curve
reflectance