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Identification of season-dependent relationships between spectral vegetation indices and aboveground phytomass in alpine grassland by using field spectroscopy

机译:利用田间光谱法识别高寒草原光谱植被指数与地上植物的季节相关关系

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Halabuk A., Gerhátová K., Kohút F., Ponecová Z., Mojses M.: Identification of season-dependent relationships between spectral vegetation indices and aboveground phytomass in alpine grassland by using field spectroscopy. Ekológia (Bratislava), Vol. 32, No. 2, p. 186–196, 2013. Spectral characteristics of alpine grasslands across the vegetation season (from May to September) are presented. The results are based on three year field spectroscopy monitoring of acid, nutrient poor grasslands at Krá?ova ho?a research site, Low Tatras, Slovakia. Relationships between commonly used spectral vegetation indices (VIs) and field-based estimation of aboveground green phytomass (AG B) were analysed. Finally, season-dependent regression models were created in order to allow spatially extensive non-destructive monitoring of AG B. Spatial–temporal dynamics of background and standing litter markedly affect seasonal variations of relationships between VIs and AG B and predictability of the regression models. Because of a high proportion of litter during the whole season, this was a plant water–sensitive normalized difference water index (NDWI), which dominates as the predictive variable in the regression models across the whole season; except June, where chlorophyll absorption sensitive in normalized difference vegetation index (NDVI) performed the best (R~2 = 0.57; rel. RMSE = 34%). However, the accuracy of the models was quite low (May: R~2 = 0.45; rel. RMSE = 49%; July: R~2 = 0.47; rel. RMSE = 26%; August: R~2 = 0.13; rel. RMSE = 31%; September: R~2 = 0.53; rel. RMSE = 40%).
机译:Halabuk A.,GerhátováK.,KohútF.,PonecováZ.,Mojses M .:利用​​田间光谱法确定高山草原光谱植被指数与地上植物的关系。 Ekológia(布拉迪斯拉发),第32卷2期186-196,2013年。介绍了整个植被季节(5月至9月)的高寒草原光谱特征。这些结果是基于对斯洛伐克低塔特拉地区Kráovahoa研究地点的酸,营养不良的草原进行的三年现场光谱监测得出的。分析了常用的光谱植被指数(VIs)与基于地面的绿色植物气概(AG B)之间的关系。最后,创建了与季节有关的回归模型,以便对AG B进行空间广泛的非破坏性监测。背景和站立垫料的时空动态显着影响VI和AG B之间关系的季节性变化以及回归模型的可预测性。由于整个季节的凋落物比例很高,因此这是植物对水敏感的归一化差异水指数(NDWI),在整个季节的回归模型中占主导地位的是预测变量。除六月外,在归一化植被指数(NDVI)中对叶绿素吸收敏感的表现最好(R〜2 = 0.57;相对RMSE = 34%)。但是,模型的准确性非常低(5月:R〜2 = 0.45;相对RMSE = 49%; 7月:R〜2 = 0.47;相对RMSE = 26%; 8月:R〜2 = 0.13;相对RMSE = 31%; 9月:R〜2 = 0.53;相对RMSE = 40%)。

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