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Mukesh, Kumar, 2009. Geospatial monitoring and evaluation of UNESCO world heritage forest areas in the Tropics . Second cycle, A1E. Umeå: SLU, Dept. of Forest Resource Management



This Study aimed at providing a better understanding for monitoring the status, change and threats to UNESCO world heritage areas that are present in the tropical forest. Three change detection techniques were tested using Landsat images for detecting area of changes in the region of the Rio Platano biosphere reserve, a tropical rain forest in Honduras. The change detection techniques considered were image differencing, post classification analysis using supervised classification and vegetation index differencing (NDVI differencing).

Two Landsat scenes recorded on 28th January 1986 and 18th December 2002 were downloaded from USGS. Images were geometrically and radiometrically corrected and the three change detection techniques were tested. Change maps obtained from each technique were visually interpreted. In order to determine the accuracy of each change maps random points were generated using systematic sampling. For each random point, change/no change were separately evaluated by using high resolution data (Google earth data) through a confusion matrix method. Image differencing for band 2 was found to be the most accurate followed by supervised classification and NDVI. Image differencing using band 3 was found to be less accurate than supervised and NDVI differencing. Supervised classification was selected for calculating area statistics inside and outside the UNESCO protected boundary because of the advantage of indicating the nature of changes. The study revealed two important changes which are clear-cut and some changes (regrowth). Clear-cut have been found to be much higher outside than the inside the protected boundary of UNESCO world heritage forested site.

Main title:Geospatial monitoring and evaluation of UNESCO world heritage forest areas in the Tropics
Authors:Mukesh, Kumar
Supervisor:Egberth, Mikael
Examiner:Olsson, Håkan
Series:Arbetsrapport / Sveriges lantbruksuniversitet, Institutionen för skoglig resurshushållning och geomatik
Volume/Sequential designation:253
Year of Publication:2009
Level and depth descriptor:Second cycle, A1E
Student's programme affiliation:None
Supervising department:(S) > Dept. of Forest Resource Management
Keywords:NDVI, Landsat, Image differencing, supervised
Permanent URL:
Subject. Use of subject categories until 2023-04-30.:Forestry - General aspects
Surveying methods
Deposited On:26 Feb 2010 08:34
Metadata Last Modified:20 Apr 2012 14:11

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