Mapping of forest water-stressed changes based on normalized difference water index (NDWI) during 1998-2018 using multi-temporal landsat data

Forests play an important role in ecosystem and its services by way of regulating the climate of the particular region. However, when the climate turns adverse changes begin to occur that cloud affect the status of the forest. There are several issues that are of global concern especially relating t...

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Bibliographic Details
Main Author: Isa, Alhaji Mustapha
Format: Thesis
Language:English
Published: 2019
Subjects:
Online Access:http://eprints.utm.my/id/eprint/96625/1/AlhajiMustaphaIsaMFABU2019.pdf.pdf
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Summary:Forests play an important role in ecosystem and its services by way of regulating the climate of the particular region. However, when the climate turns adverse changes begin to occur that cloud affect the status of the forest. There are several issues that are of global concern especially relating to the determination of the forest resources. Therefore this study maps the wetness of the Kota Tinggi forest reserve and vicinity using Landsat Multitemporal remote sensing image data. The specific objectives are :i) examine and analyse selective Normalized Difference Water Index (NDWI) method for humid tropic; and ii) map spatio-temporal pattern of NDWI in normal and extreme seasons. Multi-temporal images of three different epochs were used in this study, which include Landsat TM of 1998, 2008, and 2018. The normalize difference water indexes for each season was calculated and classified forest map of the study area was overlaid on the water indexes to find out the best wetness indexes within the period of the study as it relate with period of extreme climate condition such as La Nina and El Nino cases the result indicate that the hypothesis drawn H1: µ1= µ2 pc 0.05 and H2:µ1?µ2 pc>0.05. From the stated hypothesis, the result reveal that forest wetness has no relationship with the El Nino and La Nina, R2 = 0.0285 and 0.0942 respectively. This is due to normal rainfall which has insignificant impact to La Nina and El Nino occurrences, couple with some environment factors influencing the structure of the study area.