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Assessing the Health of Akamkpa Forest Reserves in Southeastern Part of Nigeria Using Remote Sensing Techniques

机译:利用遥感技术评估尼日利亚东南部的Akamkpa森林储备健康

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Assessment of forest health is very vital because forests form the largest terrestrial ecosystems on earth. The greenness of vegetation is one of the essential factors used in evaluating the health of forest reserves. This study is aimed at assessing the health of fifteen forest reserves in Southeastern part of Nigeria using meteorological data and MOD13A1-derived Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI). Related portions of the monthly MOD13A1 data, derived for the years 2010, 2014, and 2018, were downloaded, and the monthly mean values of the vegetation indices (NDVI and EVI) were estimated for each of the forest reserves using the Spatial Analysis Module in ArcGIS software. The computed monthly mean values of NDVI range from 0.094 to 0.790 while that of EVI ranges from 0.11 to 0.624 and the rainfall data range from 0 to 780.2?mm/month within the period of study. Analyses of the correlation coefficients between monthly rainfall data and NDVI, monthly rainfall data and EVI, and that of NDVI and EVI range from ?0.827 to 0.584; ?0.715 to 0.914, and 0.598 to 0.980. The obtained results indicate that some of the forest reserves are moderately healthy while some areas are under great stress. We can conclude that satellite remote sensing is a veritable tool in the assessment, management, and monitoring of forest health especially where there is little or no terrestrially acquired forest inventory data.
机译:森林健康的评估非常重要,因为森林形成了地球上最大的地面生态系统。植被的绿色是用于评估森林储备健康的必要因素之一。本研究旨在评估尼日利亚东南部的十五林保护的健康,使用气象数据和Mod13A1衍生的归一化差异植被指数(NDVI)和增强植被指数(EVI)。下载了2010年2010年截至2010年的月度Mod13A1数据的相关部分,并且使用空间分析模块的每个森林储备估计了植被指数的月平均值(NDVI和EVI) ArcGIS软件。 NDVI的计算每月平均值为0.094至0.790,而EVI的速度范围为0.11至0.624,降雨数据范围为0至780.2?在学习期间/月份。每月降雨量数据和NDVI,每月降雨数据和EVI之间的相关系数分析,以及NDVI和EVI范围的Δ0.827至0.584; ?0.715至0.914,0.598至0.980。所获得的结果表明,一些森林储备是适度健康的,而某些地区受重音很大。我们可以得出结论,卫星遥感是评估,管理和监测森林健康的真正工具,特别是在很少或没有彻底收购的森林库存数据。

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