首页> 外文期刊>Indonesian Journal of Forestry Research >CARBON STOCK ASSESSMENT IN PINE FOREST OF KEDUNG BULUS SUB-WATERSHED (GOMBONG DISTRICT) USING REMOTE SENSING AND FOREST INVENTORY DATA
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CARBON STOCK ASSESSMENT IN PINE FOREST OF KEDUNG BULUS SUB-WATERSHED (GOMBONG DISTRICT) USING REMOTE SENSING AND FOREST INVENTORY DATA

机译:利用遥感和森林资源调查数据对甘榜子湿地(贡分区)松林中的碳储量进行评估

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Carbon stock in tree biomass can be quantified directly by cutting and weighing trees. It is assumed that 50% of the dry weight of biomass consists of carbon. This direct measurement is the most accurate method, however for large areas it is considered time consuming and costly. Remote sensing has been proven to be an important tool for mapping and monitoring carbon stock from landscape to global scale in order to support forest management and policy practices. The study aimed to (1) develop regression models for estimating carbon stock of pine forests using field measurement and remotely sensed data; and (2) quantify soil carbon stock under pine forests using field measurement. The study was conducted in Kedung Bulus sub-watershed, Gombong - Central Java. The derived data from Satellite Probatoire d'Observation de la Terre (SPOT) included spectral band 1, 2, 3, and 4, Normalized Differences Vegetation Index (NDVI), and Principle Component Analysis (PCA) images. These data were integrated with field measurement to develop models. Soil samples were collected by augering for every 20 cm until a depth of 100 cm. The potential of remote sensing to estimate carbon stock was shown by the strong correlation between multiple bands of SPOT (band 2 , 3; band 1, 2, 3; band 1, 3, 4; and band 1, 2, 3, 4) and carbon stock with r = 0.76, PCA (PC1, PC2, PC3) and carbon stock with r = 0.73. The role of pine forest to reduce CO2 in the atmosphere was demonstrated by the amount of carbon in the tree and the soil. Carbon stock in the tree biomass varied from 26 to 206 Mg C ha-1 and in the soil under pine forest ranged from 85 to 194 Mg C ha-1.
机译:树木生物量中的碳储量可以通过砍伐和称重树木直接进行量化。假设生物质干重的50%由碳组成。这种直接测量是最准确的方法,但是对于大面积区域,它被认为既耗时又昂贵。事实证明,遥感是测绘和监测从景观到全球范围的碳储量的重要工具,以支持森林管理和政策实践。这项研究旨在(1)利用野外测量和遥感数据建立回归模型,以估算松树林的碳储量; (2)使用野外测量量化松树林下的土壤碳储量。该研究在中爪哇省贡邦的Kedung Bulus子流域进行。卫星观测基地(SPOT)的派生数据包括光谱带1、2、3和4,归一化植被指数(NDVI)和主成分分析(PCA)图像。这些数据与现场测量结果集成在一起以开发模型。每20厘米凿孔收集土壤样品,直至深度达到100厘米。 SPOT的多个波段(波段2、3,波段1、2、3,波段1、3、4和波段1、2、3、4)之间的强相关性显示了遥感估计碳储量的潜力。 r = 0.76的碳库,PCA(PC1,PC2,PC3)和r = 0.73的碳库。树木和土壤中的碳含量证明了松树林对减少大气中二氧化碳的作用。树木生物量中的碳储量为26至206 Mg C ha-1,松林土壤中的碳储量为85至194 Mg C ha-1。

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