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Land Cover Mapping in Jeli Using Selected Classification Algorithms


Citation

Syaza Sholimin (2013) Land Cover Mapping in Jeli Using Selected Classification Algorithms. Undergraduate Final Project Report thesis, Faculty of Earth Sciences. (Submitted)

Abstract

Land cover describes the landscape of Earth surface include either series types of vegetation,naturally or planted,or even man-made constructions on land surface.Land cover whether like urban,bare soil, vegetation, water, or others is necessarily to be described on it presence. f o determine the existence of land cover at area,integration remote sensing and Geographical Information System (GIS) could he used- though the fact that Jeli land cover might filled with forest,but still there are lots more different 13„c, of land cover which covered the land surface of Jell. In order to get better understanding in terms of which algorithms best used in land cover mapping, this re.;car•h \\a, conducted with the useful help of remote sensing technology. This research satellite imagery of Landsat 5 Thematic Mapper (TM) for 1010 to map land cover type's present within Jell. Selected classification algorithms are employed to run the classification process and hereby class all the possible land cover types within Jell. This research focused on comparing which are the best selected classification algorithms in producing land cover map with reference to the confusion matrix and kappa statistic. The best classification algorithm found and appointed in this research is Maximum Likelihood Classification (MLC). MLC recorded the highest result for overall accuracy and kappa statistic compared to other two techniques which were 89.6987% for its accuracy and 0.8775 for kappa statistic. Besides, this technique is best determined and identified to give precise picture of land cover within Jeli as being compared with the Kelantan Land Cover Topograhic Map of 2008. As a conclusion. the best selected algorithm for land cover map can be determined and the use of remote sensing technology for land cover map is able to efficiently be generated.

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Additional Metadata

Item Type: Undergraduate Final Project Report
Collection Type: Final Year Project
Date: 2013
Call Number: SEN13030
Supervisor: Dr. Ibrahim Busu
Programme: Natural Resources
Institution: Faculty of Earth Sciences
Faculty/Centre/Office: Faculty of Earth Sciences
URI: http://discol.umk.edu.my/id/eprint/6061
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