Research Article AssessingtheHealthofAkamkpaForestReservesinSoutheastern Part of Nigeria Using Remote Sensing Techniques Elijah S. Ebinne, Ojima I. Apeh , Raphael I. Ndukwu, and Edebo J. Abah Department of Geoinformatics & Surveying, University of Nigeria, Enugu Campus, Enugu, Nigeria Correspondence should be addressed to Ojima I. Apeh; ojima.apeh@unn.edu.ng Received 18 November 2019; Revised 10 June 2020; Accepted 20 June 2020; Published 27 July 2020 Academic Editor: Nikolaos D. Hasanagas Copyright © 2020 Elijah S. Ebinne et al. is is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Assessment of forest health is very vital because forests form the largest terrestrial ecosystems on earth. e greenness of vegetation is one of the essential factors used in evaluating the health of forest reserves. is 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. e 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. e 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. 1. Introduction Forest health in Cross River State (a State in Southeastern Nigeria) is threatened by so many factors such as colonial nationalization and commodification of the forest estate, agricultural practices, government plantations and defor- estation, uncontrolled extraction of nontimber forest products (NTFPs), highway construction and mining of solid minerals, dereservation of large portions of some government forest reserves, and foresters and resistance to decentralized forest management [1]. Forest health is a condition of forest ecosystem that sustains their complexity while providing for human needs [2]. Healthy forests, which could be assessed and monitored by many forest health indicators, are needed for aesthetical pleasure, satisfaction of human needs, and maintenance of sustainable ecosystem. It is unarguable that the indicators of forest health obtained from forest inventory programs are more accurate but their acquisition is time-consuming, laborious, and cost- intensive. To worsen the matter, there is paucity of long- standing and standardized forest health inventory programs in the study area, thereby necessitating the use of remote sensing techniques to assess the health of the forest reserves in Cross River State following the outcry by [1] and the reports from United Nations Programme [3, 4]. is lack of terrestrially acquired forest inventory data makes it im- possible to integrate satellite remote sensing techniques with past inventory data in assessing the health of these forest reserves under study in contrary to what is obtainable in some other studies [5–7]. e Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) derived from MODIS (moderate resolution imaging spectroradiometer) coupled with meteorological data have been severally used to determine the greenness (which is an indicator of healthy condition) of vegetation in many lo- calities [8–13]. Hindawi International Journal of Forestry Research Volume 2020, Article ID 8739864, 15 pages https://doi.org/10.1155/2020/8739864