Analyzing degradation of Southern Mau forest using GIS and remote sensing
Abstract
Forest Canopy density is a major factor in evaluation of forest status and is an important
indicator ofpossible management interventions. Forest canopy cover, also known as
canopy coverage or crown cover, is defined as the proportion of the forest floor covered
by the vertical projection of the tree crowns. Conventional remote sensing methods assess
the forest status based on qualitative data analysis. Forest Canopy Density Model is one
ofthe useful methods to detect and estimate the canopy density over large area in a time
and cost effective manner. This model requires very less ground truths, just for accuracy
check.
The main aim of the project isto assess the viability of using GTSand remote sensing in
analyzing the forest depletion. Mainly to assess the effectiveness of analyzing forest
cover with emphasis on Southern Mau forest.
Landsat maps 4 to 5 Thematic Mapper ™ and Enhanced Thematic Mapper (+ETM) with
a mid resolution of30 meters was selected, the maps were acquired from an authorized
site (http://glovis.usgs.gov) this was due to its easy access and its swath width of 150km
which covered the whole area.
Satellite images from the 28th Jan 1986,2ilt Jan 2000 and so" Jan 2010 were used and
analyzed using the World Reference Systems (WRS) index path 169 row 060.
There were five main steps inthe methodology of southern Mau canopy analysis which
involve image pre-processing and land cover classification using Erdas software. A post
classification was carried out using arcGTSand land cover detection and analysis using
Erdas. Final maps and tables were done using arcGTSand Ms Excel.
The results indicate that the percentage depletion from 1986-2000 is about 7.55% and
32.71 between 1986 and 2010.
Tnconclusion GTSand remote sensing are important tools in assessing the depletion of
forests. Further assessment indicates that application of the GTSand remote sensing can
be used in forest management and monitoring systems.
Publisher
School of Computing and Informatics
Description
MSc