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Biomass Estimation of Gwangneung Catchment Area with Landsat ETM+ Image

机译:利用Landsat ETM +图像估算光陵流域的生物量

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Spatial information on forest biomass is an important factor to evaluate the capability of forest as a carbon sequestrator and is a core independent variable required to drive models which describe ecological processes such as carbon budget, hydrological budget, and energy flow. The objective of this study is to understand the relationship between satellite image and field data, and to quantitatively estimate and map the spatial distribution of forest biomass. Landsat Enhanced Thematic Mapper (ETM+)derived vegetation indices and field survey data were applied to estimate the biomass distribution of mountainous forest located in Gwangneung Experimental Forest (230 ha). Field survey data collected from the ground plots were used as the dependent variable, forest biomass, while satellite image reflectance data (Band 1~5 and Band 7), Normalized Difference Vegetation Index (NDVI), Soil-Adjusted Vegetation Index (SAVI), and RVI (Ratio Vegetation Index) were used as the independent variables. The mean and total biomass of Gwangneung catchment area were estimated to be about 229.5 ton/ha and 52.8 x 10~3 tons respectively. Regression analysis revealed significant relationships between the measured biomass and Landsat derived variables in both of deciduousforest (R2 = 0.76, p < 0.05) and coniferous forest (R2 = 0.75, p < 0.05). However, there still exist many uncertainties in the estimation of forest ecosystem parameters based on vegetation remote sensing. Developing remote sensing techniques with adequate filed survey data over a long period are expected to increase the estimation accuracy of spatial information of the forest ecosystem.
机译:有关森林生物量的空间信息是评估森林作为碳固存者的能力的重要因素,并且是驱动描述生态过程(例如碳预算,水文预算和能流)的模型所需的核心自变量。这项研究的目的是了解卫星图像和野外数据之间的关系,并定量估计和绘制森林生物量的空间分布。利用Landsat增强型专题测绘仪(ETM +)得出的植被指数和野外调查数据来估算位于广陵试验林(230公顷)的山区森林的生物量分布。从地面样地收集的实地调查数据用作因变量森林生物量,而卫星图像反射率数据(波段1〜5和波段7),归一化植被指数(NDVI),土壤调整植被指数(SAVI),和RVI(植被比指数)用作自变量。估计光陵流域的平均生物量和总生物量分别为229.5吨/公顷和52.8 x 10〜3吨。回归分析表明,在落叶林(R2 = 0.76,p <0.05)和针叶林(R2 = 0.75,p <0.05)中,测得的生物量与Landsat衍生变量之间存在显着关系。然而,基于植被遥感的森林生态系统参数估计仍存在许多不确定性。期望在很长一段时间内开发具有充足归档调查数据的遥感技术,以提高森林生态系统空间信息的估计准确性。

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