草地退化的高光谱遥感监测方法

我国草地分布面积广,退化情况严重,实时、准确地监测草地的生态状况,对于区域气候、碳循环研究以及经济发展具有重要意义。利用地面实测光谱数据进行了高光谱草地退化监测研究。选择内蒙古呼伦贝尔市的温性草甸草原为研究对象,测量了草甸草原的羊草、克氏针茅、冷蒿等多种植物的叶片、冠层以及多种植物混合的群落反射率光谱数据。通过有效的光谱特征参量化方法,提取叶片和冠层光谱的光谱特征,准确区分了草甸草原的几种建群和退化指示草本植物,验证结果表明光谱识别的精度高于95%。以此为基础,利用线性光谱混合模型对群落植被的混合光谱数据进行混合光谱分解,得到各组分的覆盖度,误差在5%以内。该文的研究结果为高光谱遥感草地监测提供了有力依据。

Hyperspectral remote sensing monitoring of grassland degradation

The distributing of China's grassland is abroad and the status of grassland degradation is in serious condition. So achieving real-time and exactly grassland ecological monitoring is significant for the carbon cycle, as well as for climate and on regional economies. With the field measured spectra data as data source, hyperspectral remote sensing monitoring of grassland degradation was researched in the present article. The warm meadow grassland in Hulunbeier was chosen as a study object. Reflectance spectra of leaves and pure canopies of some dominant grassland species such as Leymus chinensis, Stipa krylovii and Artemisia frigid, as well as reflectance spectra of mixed grass community were measured. Using effective spectral feature parametrization methods, the spectral feature of leaves and pure canopies were extracted, so the constructive species and degenerate indicator species can be exactly distinguished. Verification results showed that the accuracy of spectral identification was higher than 95%. Taking it as the foundation, the spectra of mixed grass community were unmixed using linear mixing models, and the proportion of all the components was calculated, and the errors were less than 5%. The research results of this article provided the evidence of hyperspectral remote sensing monitoring of grassland degradation.