Application of a Multispectral SPOT Image for Land Use Classification in Sampean Watershed

Authors

  • Januar Fery Irawan Research Center of Water Resource Development, Research Insitute, University of Jember. Jl. Kalimantan No. 37, Kampus - Tegalboto, Jember 68121
  • . Indarto Research Center of Water Resource Development, Research Insitute, University of Jember. Jl. Kalimantan No. 37, Kampus - Tegalboto, Jember 68121

DOI:

https://doi.org/10.5400/jts.2011.v16i2.176-181

Keywords:

Classification, supervised, Sampean watershed, SPOT Image, unsupervised

Abstract

This article described the process of land use classification at Sampean Watershed. The research was conducted in Sampean watershed to calculate the land use area using a multispectral SPOT image. Two SPOT image scenes were used to identify and classify the main nomenclature of land use. The research applied level 2A of SPOT image raw data which were obtained during 2004. Research methodology consisted of geometric correction of Image; image enhancement using high sharpen filter; un-supervised classification and supervised classification. The classification algorithm used the maximum likelihood in which pixels was classified based on their spectral signature. Several
training areas were identified to define the region area. Supervised classification could classified 9 class of land uses, the classification of land use consist of irrigated paddy field (56.05%), rain fed paddy field (0.89%), forest (10.75%), urban area (8.69%), plantation (4.22%), barren land (11.19%), river (0.05%), cropland (7.98%), and bushes (0.19%). The overall classification accuracy was 84.21%. This work will be useful for hydrological modelling and management planning of the Watershed.

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Published

2013-07-10

How to Cite

Irawan, J. F., & Indarto, . (2013). Application of a Multispectral SPOT Image for Land Use Classification in Sampean Watershed. JOURNAL OF TROPICAL SOILS, 16(2), 176–181. https://doi.org/10.5400/jts.2011.v16i2.176-181

Issue

Vol. 16 No. 2: May 2011

Section

Articles

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