A study on vegetation vigour as affected by soil properties using remote sensing approach

N. Karthikeyan, M. C. Shashikkumar, J. Ramanamurthy
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引用次数: 5

Abstract

Vegetation is a complex phenomenon with large amount of inherent spectral, spatial and temporal variability and it is typically characterized by strong absorption in the red wavelengths and high reflectance in the near infra-red (NIR) wavelengths of the electromagnetic spectrum. The images generating from various Vegetation Indices like Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI) etc. from multispectral imagery can provide valuable vegetation information about an area. Soil background conditions exert considerable influence on partial canopy spectra and calculated vegetation indices. Therefore, it is important to monitor the vegetation vigour changes with respect to the soil background conditions. For this purpose, a suitable remote sensing based algorithm i.e. Soil Adjusted Vegetation Index (SAVI) was selected and applied for the study. The analysis of vegetation vigour changes was done for different time series in the part of Andhra Pradesh state. The MODIS vegetation index images of 250m resolution were used. NDVI and NDWI images were derived for red and black soil types, with reference to that the SAVI model was created and executed in ERDAS IMAGINE platform. In SAVI equation, the soil adjusted factor ‘L’ was modified with different values and multivariate SAVI images were derived for both red and black soil regions. In the various red soil regions, the SAVI with ‘L’ value as 0.25, 0.3, 0.4 and 0.5 produced the fair result on soil and vegetation reflectance variations over the crop season. Similarly in the different black soil region, the vegetation cover is medium and SAVI with ‘L’ value as 0.3 and 0.4 produced the fair result on soil and vegetation variation. This study was done with only the two types of soil regions and with minimal datasets. The analysis part of the study can be extended with multiple data sets and different seasons.
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土壤性质对植被活力影响的遥感研究
植被是一种复杂的现象,具有大量的固有光谱、时空变异性,其典型特征是电磁波谱中红色波长的强吸收和近红外波长的高反射率。利用多光谱影像的归一化植被指数(NDVI)、归一化水体指数(NDWI)等植被指数生成的图像可以提供有关某一地区的宝贵植被信息。土壤背景条件对部分冠层光谱和计算的植被指数影响较大。因此,监测植被活力随土壤背景条件的变化具有重要意义。为此,选择了一种适合的遥感算法——土壤调整植被指数(SAVI)进行研究。对安得拉邦部分地区不同时间序列的植被活力变化进行了分析。采用分辨率为250m的MODIS植被指数影像。参考在ERDAS IMAGINE平台上创建并执行SAVI模型,导出了红土和黑土类型的NDVI和NDWI图像。在SAVI方程中,对土壤调整因子L进行不同值的修正,得到了红土和黑土地区的多元SAVI图像。在各红壤区,“L”值分别为0.25、0.3、0.4和0.5的SAVI对作物季节土壤和植被反射率变化的反映效果较好。同样,在不同的黑土区,植被覆盖度中等,“L”值为0.3和0.4的SAVI对土壤和植被的变化效果较好。本研究仅使用了两种类型的土壤区域和最少的数据集。研究的分析部分可以扩展为多个数据集和不同的季节。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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