越南化天顺化省植被指数增强与木材量的相关性分析

IF 1 Q4 ECOLOGY Tropics Pub Date : 2016-03-01 DOI:10.3759/TROPICS.24.181
T. Pham, K. Yoshino, T. Nguyen
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引用次数: 2

摘要

发展中国家的REDD +需要估算森林碳储量和地上生物量。由于植被指数被认为与地上生物量或植被活力高度相关,因此遥感已被广泛用于利用卫星衍生的植被指数监测植被面积。然而,这些卫星衍生的植被指数是否适用于任何类型的森林,如不同物种的森林,仍然值得怀疑。研究野外调查获得的木材体积数据与MODIS EVI数据时间序列之间的关系,验证卫星遥感数据能否准确估算不同树种不同森林的地上生物量。本文给出了不同森林的相关性。我们的分析使用简单的线性回归说明了年木材量与年平均EVI之间的相关性。森林1的回归方程为Y = 249.02x + 37.474;r2 = 0.82;森林2的N = 22, Y = 668.3x-258.61;r2 = 0.80;N = 15, r2 = 0.0285;森林3混合种数大于7种,N = 15。这些不同的相关性与不同森林的物种组成密切相关。树木种类少的森林相关性高,树木种类多的森林相关性低。森林树种组成是利用遥感数据估算森林地上生物量的一个重要特征。
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Correlation analysis between Enhance Vegetation Index and Wood Volume in Thua Thien Hue Province, Vietnam
REDD + in developing countries needs to estimate forest carbon stocks and above ground biomass. Remote sensing has been widely used for monitoring of vegetated area using the satellite-derived vegetation index since vegetation indices are thought to have high correlation with above ground biomass or vigor of vegetation. However, these satellite-derived vegetation indices are still doubtful whether they are available for REDD + in any types of forests such as forests with different species. We studied the relationship between wood volume data obtained by field survey and the time series of MODIS EVI data to check whether the above ground biomass in different forests with different species could be accurately estimated from satellite remotely sensed data. This paper presents the different correlation for different forests. Our analysis illustrated the correlation between annual wood volume and annual average EVI using a simple linear regression. The regression equation for Forest 1 was Y = 249.02x + 37.474; R 2 = 0.82; N = 22 and for Forest 2 was Y = 668.3x-258.61; R 2 = 0.80; N = 15, and R 2 = 0.0285; N = 15 for forest 3 which mixed more than 7 species, respectively. These different correlations are strongly correlated with composition of species in different forests. The forests with a few tree species had high correlations, while the forest mixed with many species of trees had low correlation. The composition of tree species in forests is an important characteristic for estimating above ground biomass of forests using remote sensing data.
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来源期刊
Tropics
Tropics ECOLOGY-
CiteScore
1.40
自引率
0.00%
发文量
7
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