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Using negative soil adjustment factor in soil-adjusted vegetation index (SAVI) for aboveground living biomass estimation in arid grasslands

机译:在干旱草原上使用土壤调整植被指数(Savi)中的负土壤调节因子

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All values of soil adjustment factor (L) from 0 to 1 in the soil-adjusted vegetation index (SAVI) were found to be undesirable in arid areas with sparse vegetation cover. We hypothesized that the negative soil adjustment factor in the SAVI would be satisfactory in arid areas. In the study, we explored the potential of negative soil adjustment factor in the SAVI against a set of field measurements during the growing season of 2009 in the desert steppe of Inner Mongolia, China. As hypothesized, negative soil adjustment factor was found to give satisfactory reduction of soil background noise. SAVI (L = -0.2) (R-2 = 0.64, RMSE = 18.4 g m(-2), rRMSE = 25.5%, n = 120) provided dramatic improvements over optimal NDVI (normalized difference vegetation index) (that is, SAVI (L = 0)) (R-2 = 0.44, RMSE = 22.7 g m(-2), rRMSE = 31.4%, n = 120) for aboveground living biomass (AGB) estimation among tested vegetation indices. A physical basis for the negative soil adjustment factor was also explored. Results showed that, the intersected points between approximate vegetation isolines and soil line were situated in the domain of positive values of NIR (near-infrared) and red in the first quadrant of NIR-red plane, and the slopes of vegetation isolines increased with increasing AGB in the desert steppe, thus resulting in negative factor by shifting the origin toward positive intersected points. This runs counter to reported vegetation isolines behavior for SAVI, in which the intersected points were situated in the region of negative values of NIR and red in the third quadrant. The good performance of negative factor was also observed for percent green cover (PGC) estimation in the desert steppe. We further proposed a conceptual model to describe vegetation isolines behavior in arid grasslands. Our findings will complement widely used soil adjustment factor. Further study is needed to validate the negative soil factor and test the conceptual model in other arid grasslands.
机译:在土壤调整后的植被指数(Savi)中,土壤调整因子(L)的所有值都被发现在具有稀疏植被覆盖的干旱地区是不希望的。我们假设Savi中的负土壤调整因子在干旱地区令人满意。在研究中,我们在中国内蒙古沙漠草原在2009年生长季节期间探讨了萨维中的消极土壤调整因子的潜力。如假设,发现消极土壤调整因子令人满意地减少了土壤背景噪音。 Savi(L = -0.2)(R-2 = 0.64,RMSE = 18.4 gm(-2),RRMSE = 25.5%,n = 120)提供了对最佳NDVI(归一化差异植被指数)的显着改善(即,SAVI( L = 0))(R-2 = 0.44,RMSE = 22.7克(-2),RRMSE = 31.4%,n = 120)用于测试植被指数之间的地上生物量(AGB)估计。还探讨了负土壤调整因子的物理基础。结果表明,近似植被中的近似植被分离素和土线之间的相交点位于NIR - 红色平面的第一个象限中NIR(近红外线)和红色的阳性值,并且植被ISOLINE的斜率随着增加而增加AGB在沙漠草原中,从而导致消极因素朝向积极的相交点。这与报告的植被ISOLLINE行为进行计数器,其中相交点位于第三象限中的NIR和红色的负值区域中。在沙漠草原中的绿色覆盖百分比(PGC)估计也观察到负面因子的良好性能。我们进一步提出了一种概念模型来描述干旱草原中的植被Iscoline行为。我们的调查结果将补充广泛使用的土壤调整因子。需要进一步研究以验证负土壤因子并测试其他干旱草原的概念模型。

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