Detection of deforestation and forest fragmentation in forest reserve Ulu Muda, Kedah by using : spot data imagery / Muhammad Hazim Hazairin

Deforestation is one of the commonly issue that occur in Malaysia whether it is legal or illegal logging activity. The deforestation give an impact to the animal and plant in the forest by having the animal loss their habitat, effecting water catchment and losing of valuable tree species. As of for...

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Bibliographic Details
Main Author: Hazairin, Muhammad Hazim
Format: Thesis
Language:English
Published: 2018
Subjects:
Online Access:http://ir.uitm.edu.my/id/eprint/21759/1/TD_MUHAMMAD%20HAZIM%20HAZAIRIN%20AP%20R%2018_5.pdf
http://ir.uitm.edu.my/id/eprint/21759/
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Institution: Universiti Teknologi Mara
Language: English
Description
Summary:Deforestation is one of the commonly issue that occur in Malaysia whether it is legal or illegal logging activity. The deforestation give an impact to the animal and plant in the forest by having the animal loss their habitat, effecting water catchment and losing of valuable tree species. As of for this research project, the aim and purpose of the project is firstly for the aim is to analyse the forest cover changes using SPOT data imagery and as for the purpose is to detect the deforestation, detection of forest fragmentation and to analyse the rate of forest loss in Forest Reserve Ulu Muda, Kedah. The problem that having in Ulu Muda forest is the forest management do not update the information more efficiency and consistent. The require data use to make a detection based from the objective are three SPOT data with different year which is 2006, 2011 and 2016. These three data was achieved from the MRSA (Malaysian Remote Sensing Agency). The method used to process the data is pixel classification on classifying the feature that consist on land cover such as forest, non-forest, water and logging trail. Next is performing the landscape fragmentation tool based from the pixel classification output to extract the information of types of fragmentation which is patch, edge, perforated and core forest. Lastly, perform the Normalised Difference Vegetation Index (NDVI) for verification with pixel classification and then analyse the area of forest and calculate the rate of forest loss in between year 2006 and 2016. As for conclusion, the output result in the project is the table of accuracy assessment, bar graph for the forest fragmentation detect in the Ulu Muda Forest, Kedah and lastly the table of forest loss rate that occur in the Ulu Muda forest.