黄土丘陵沟壑区枯枝落叶层和土壤的光谱差异特征分析

摘要

枯枝落叶层在植被防止土壤侵蚀的功效中发挥着主导作用，枯落层的光谱特征分析将为遥感估算枯落层盖度提供重要依据。该文利用陕北延河流域典型植被群落土壤和枯落层样本的光谱测试数据，分析土壤和枯落层在在可见光-近红外波段（400～1100 nm）和短波红外波段（1100～2500μm）的光谱差异特征及主要影响因素，并进一步评价归一化植被指数（NDVI，normalized difference vegetation index）和归一化衰败植被指数（NDSVI，normalized difference senescent vegetation index）、归一化差值耕作指数（NDTI，normalized difference tillage index）、纤维素吸收指数（CAI，cellulose absorption index）等植被指数区分土壤和枯落层的有效性。结果表明，在可见光-近红外波段土壤和枯落层的反射光谱特征相似，两者难以区分，但在短波红外波段的1700和2100 nm处因枯落层具有纤维素吸收特征而与土壤存在差异。含水量对土壤和枯落层反射光谱特征的影响强烈，水分的存在降低了土壤和枯落层在整个光谱范围的差异性。光谱空间中枯落线和土壤线的关系表明，NDVI 指数难以反映土壤和枯落层的光谱差异特征；由于宽波段的影响，利用多光谱指数NDSVI和NDTI表征枯落层信息具有一定的局限性；高光谱指数CAI利用了枯落层与土壤在2100 nm处的差异特征，能够较好地区分出土壤与枯落层，该研究为利用遥感技术有效提取枯落层等衰败植被信息提供了新的途径。%Plant litter plays a critical role in controlling and protecting soil against water erosion and increasing soil organic carbon. The presence of plant litter efficiently reduces erosion and surface runoff, and influences the cycle of nutrients, carbon, and energy in ecosystem. Remote sensing can provide a new way to differentiate litter from soil, and spectral difference of plant litter and soil is the primary basis for the remotely sensed estimation of plant litter coverage. By using spectral measurement of the soil and litter samples of typical vegetation communities in the Yanhe River basin of Northern Shaanxi, the difference of spectral characteristics between soil and litter in the VIS-NIR (400-1 100 nm) and SWIR (1 100-2 500μm) wavelengths and main impact factors were analyzed; the effectiveness of NDVI (normalized difference vegetation index) and typical senescent vegetation indexes such as NDSVI (normalized difference senescent vegetation index), NDTI (normalized difference tillage index) and CAI (cellulose absorption index) was evaluated to distinguish litter from soil. The results showed that the spectral behaviors of soil and litter were similar in the VIS-NIR wavebands, and the main difference between soil and litter was that the slopes of spectra of the litter samples were slightly greater than that of the soil samples. The two water absorption bands, centered at 1 400 and 1 900 nm, had the common spectral features in soil and litter within the SWIR waveband, while diagnostic features could be observed at 1 700 and 2 100 nm in the reflectance spectra of the dried litter samples, which were associated with the cellulose-lignin absorptions. Water content influenced the reflectance spectra of soil and litter samples obviously, and the reflectance of wet soil and litter was reduced by half compared to dry soil and litter. The cellulose-lignin absorption at 2100 nm obscured and disappeared in the reflectance spectra of wet litter samples, the spectra shape of the wet litter appeared very similar to that of wet soil, and hence it was indistinguishable between soil and litter. The existence of residue line which presents the linear regression relationship between any couple of TM bands was first verified with the litter samples. According to the relationship of soil line and residue line in feature space of two TM bands, residue line existed (R2=0.86) and was closed to soil line (R2=0.97) between TM3-TM4 wavebands, the NDVI values of soil samples were similar to the litter samples, and spectral differences of soil and litter can't be characterized by NDVI. TheR2 of 0.81 illustrated the existence of soil line, but residue line (R2=0.10) can’t be observed between TM3-TM5 wavebands, and the NDSVI values of soil and litter samples were mixed and featureless. Both soil line (R2=0.95) and residue line (R2=0.65) existed between TM5-TM7 wavebands, and NDTI values of soil and litter samples were still in proximity to each other. Due to low spectral resolution, there were limitations for multispectral indexes (like NDSVI and NDTI) to extract the information of litter. The spectral separability between soil and litter can be represented by the hyperspectral index CAI, which takes the advantage of obvious difference between soil and litter at 2 100 nm and thereby presents a good result for distinguishing litter from soil.