TITLE:
Assessing Change of Lamto Reserve Area Based on the MODIS Time Series Data and Bioclimatic Factors Using BFAST Algorithms
AUTHORS:
Christian Jonathan Anoma Kouassi, Dilawar Khan, Lutumba Suika Achille, James Kehinde Omifolaji, Mikouendanandi Mouendo Rahmat Brice Espoire, Kebin Zhang, Xiaohui Yang
KEYWORDS:
Assessing, Break, Change Detection, Land Cover, Climate Extreme, Vegetation Vulnerability
JOURNAL NAME:
American Journal of Plant Sciences,
Vol.13 No.4,
April
29,
2022
ABSTRACT: Lamto Reserve area is a savannah landscape
threatened by periodic drought, and
anthropogenic activities leading to natural ecological imbalance. The ecological
support services of the landscape had been significantly impacted by the grassland ecosystem. The Breaks for Additive
Season and Trend Algorithms have been implemented in R to analyze the land
cover/land use dynamic in relation to
the climatic driver of Lamto forest from 2000 to 2020. We examine the
vegetation state breaks using vegetation phenological patterns, and several
time series including the Normalized Difference Vegetation Index and the
Enhanced Vegetation Index, were studied utilizing Breaks for Additive Season
and Trend. The findings indicate that the phenological changes in the
vegetation in 2020 resulted from an increased temperature from (27.7°C)
to (32.17°C), and a decrease in precipitation (71.75 millimeters). The analysis of variance ANOVA of the non-parametric
Mann-Kendall test reveals a strong correlation
between Precipitation/Evapotranspiration Grass (p mperature/Evapotranspiration
Grass (p in vegetation detected by the Breaks for Additive Season and Trend
Algorithms were caused by temperature extremes and reduced rainfall.