Anthropogenic Disturbances Affect the Relationship Between Spectral Indices and the Biometric Variables of Brazilian Savannas

ABSTRACT According to previous studies involving biometric variables modeling using remote sensing (RS), data did not consider the effects of anthropogenic disturbance as relevant factor. The main objective of this study was to model aboveground biomass (AGB) and total wood volume (TWV) of Brazilian Savanna biome using vegetation indices (VI) from LANDSAT 5 TM. Multiple linear regression (MLR) and random forest (RF) algorithm were applied across 641 field plots of cerrado sensu stricto of the state of Minas Gerais, Brazil, comparing two models: non-stratified, and stratified according to plot’s anthropization degree. AGB and TWV obtained from non-anthropized plots presented linear relation with VIs (R2 = 0.82 and 0.74, respectively) and, on the other hand, presented nonlinear relation when plots were affected by anthropogenic disturbances or were not stratified. This finding helps improving estimates by stratifying plots into their anthropization degree, mainly in the Brazilian Savanna biome undergoing anthropogenic disturbances.

摘要 既往基于遥感（RS）开展生物变量建模的相关研究，均未将人为干扰作为相关影响因子纳入考量。本研究旨在利用陆地卫星5号专题制图仪（LANDSAT 5 TM）获取的植被指数（VI），对巴西稀树草原生物群系的地上生物量（AGB）与总木材蓄积量（TWV）进行建模。研究依托巴西米纳斯吉拉斯州境内641个狭义塞拉多（cerrado sensu stricto）野外样地，采用多元线性回归（MLR）与随机森林（RF）两种算法，对比两种建模方案：非分层建模，以及按样地人为干扰程度进行分层建模。结果表明，未受人为干扰样地的AGB与TWV均与植被指数呈线性相关关系（决定系数R²分别为0.82与0.74）；反之，当样地受人为干扰或未进行分层处理时，二者则呈非线性相关关系。本研究证实，通过按人为干扰程度对样地进行分层可有效提升估算精度，该结论对正遭受人为干扰的巴西稀树草原生物群系尤为适用。