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The influence of canopy green vegetation fraction on spectral measurements over native tallgrass prairie

机译:天然草木草原冠层绿色植被覆盖率对光谱测量的影响

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Spectral vegetation indices (SVIs) calculated from remotely sensed data are routinely used to monitor spatial and temporal changes in vegetation biophysical characteristics. The most commonly used SVI, the Normalized Difference Vegetation Index (NDVI), has been criticized because of its sensitivity to atmospheric conditions and substrate reflectivity, as well as its insensitivity to increases in vegetation biomass past particular thresholds. Yet, the use of NDVT remains widespread and is attractive because of the ease with which it is calculated. This article examines the utility of NDVI for monitoring the biophysical characteristic of green vegetation fraction (GVF) in comparison to other SVIs suggested as improvements. Statistical relationships between spectral response, presented in the form of SVIs, and GVF of a native tallgrass prairie canopy are explored. Broadband spectra were gathered from close-range during the 1999 growing season at the Konza Prairie Biological Station (KPBS), located in the Flint Hills region of Kansas, USA. Through simple regression analyses, spectra were related to GVF estimates derived from digital color photogtaphs. SVIs evaluated are the NDVI, the Soil Adjusted Vegetation Index (SAVI), and the square of scaled NDVT (N{sup}(*2)). Results show that NDVI and N{sup}(*2) were statistically related to GVF (R{sup}2 for NDVI = .77, N{sup}(*2) = .78) throughout the growing season. The least-squares line defining the relationship between N{sup}(*2) and GVF approximated a 1:1 line. For June sample dates, all three SVIs were significant statistical predictors of GVF (R{sup}2 for NDVT = .89, N{sup}(*2) = .91, SAVI = .89). Regression coefficients for late-season sample dates were weaker, yet still significant in statistical terms (R{sup}2 for NDVI = .70, N{sup}(*2) = .70). While encouraging, these results suggest that further analyses are required to determine the usefulness of SVTs calculated from broadband devices for estimation of GVF when leaf litter dominates the scene.
机译:从遥感数据计算得出的光谱植被指数(SVI)通常用于监测植被生物物理特征的时空变化。人们最批评使用的SVI是归一化植被指数(NDVI),因为它对大气条件和基质反射率敏感,并且对超过特定阈值的植被生物量增长不敏感。但是,NDVT的使用仍然很广泛,并且由于其易于计算而具有吸引力。与其他建议改进的SVI相比,本文研究了NDVI在监测绿色植被部分(GVF)的生物物理特性方面的实用性。探索了光谱响应(以SVI形式表示)与原生草丛草原冠层的GVF之间的统计关系。在位于美国堪萨斯州弗林特山地区的Konza草原生物学站(KPBS)于1999年生长季节从近距离收集了宽带光谱。通过简单的回归分析,光谱与从数字彩色象形文字得出的GVF估计有关。评估的SVI是NDVI,土壤调整植被指数(SAVI)和NDVT的平方(N {sup}(* 2))。结果表明,在整个生长季节,NDVI和N {sup}(* 2)与GVF有统计学相关性(NDVI的R {sup} 2 = 0.77,N {sup}(* 2)= 0.78)。定义N {sup}(* 2)与GVF之间关系的最小二乘线近似为1:1。对于6月的采样日期,所有三个SVI都是GVF的重要统计预测指标(NDVT的R {sup} 2 = .89,N {sup}(* 2)= 0.91,SAVI = .89)。后期采样日期的回归系数较弱,但在统计意义上仍然显着(NDVI = .70的R {sup} 2,N {sup}(* 2)= 0.70)。尽管令人鼓舞,但这些结果表明,当树叶凋落物占主导地位时,需要进一步分析以确定从宽带设备计算出的SVT对估算GVF的有用性。

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