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High Spatial Resolution Land Cover Mapping Using Remotely Sensed Image

Author

Listed:
  • H. S. Lim
  • M. Z. MatJafri
  • K. Abdullah

Abstract

Land cover classification from remotely sensed data is an important topic in remote sensing applications. This paper present an economical analysis of land covers in Mebok Estuary, Penang, Malaysia. This study investigated the potential of using digital camera for land cover mapping Mebok Estuary, Penang, Malaysia. Airborne digital imagery has proved to be an effective tool for land cover studies. A Kodak camera, model DC290, was used to capture images from an elevation of 2438.4 meter on board Cessna 172Q. The use of digital camera as a sensor to capture digital images is cheaper and economical compared to the use of other airborne sensor. This technique overcomes the problem of the difficulty in obtaining cloud-free scenes in the Equatorial region from a satellite platform. Supervised classification techniques were used in the classification analysis. Supervised classification technique (Parallelepiped with Maximum Likelihood as tie breaker classifier, PML, Maximum Likelihood, ML, Minimum Distance-to-Mean, MDM, and Parallelepiped, P) was applied to the digital camera spectral bands (red, green and blue) to extract the thematic information from the acquired scenes. The best supervised classifier was chosen based on the highest overall accuracy and Kappa statistic. The accuracy of the classified images was validated using a reference data set. The study revealed that the Parallelepiped with Maximum Likelihood as tie breaker classifier produced superior result and achieved a high degree of accuracy. The classified land cover map was geometrically corrected to provide a geocode map. The results produced by this study indicated that land cover features could be clearly identified and classified into a land cover map. This study suggested that the land cover types of Mebok Estuary, Penang, Malaysia can be accurately mapped.

Suggested Citation

  • H. S. Lim & M. Z. MatJafri & K. Abdullah, 2009. "High Spatial Resolution Land Cover Mapping Using Remotely Sensed Image," Modern Applied Science, Canadian Center of Science and Education, vol. 3(5), pages 1-82, May.
  • Handle: RePEc:ibn:masjnl:v:3:y:2009:i:5:p:82
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    More about this item

    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

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