4 results for “Airborne remote sensing”

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Research ArticleOpen accessIn the keywordsIndividual Species Crown Mapping in Taman Rimba Ilmu, University Malaya Using Airborne Hyperspectral ImagingKamaruzaman JusoffProblem statement: Accurate, current and cost-effective individual standing tree data are required by forest management communities for use in forest inventory over large areas. Currently, most of the forest mapping process is done directly on the ground using many technique such as the bearing-distance and also the other technique that use the computer software as a support, such as Tree … …American Journal of Applied Sciences, Vol. 7, Issue 4 · 30 Apr 2010 · 7,816 accessesView PDF Cite

Research ArticleOpen accessIn the abstractA New Approach in Individual Tree Counting of Nyatoh (Palaquium spp.) Using an Airborne SpectroradiometerKamaruzaman JusoffProblem statement: In Malaysia inadequate data are available to make decisions regarding the sustainable management of Nyatoh (Palaquium spp.). Factual data and estimation of Nyatoh in the lowland dipterocarp forest resources are still lacking or, if available, are not complete, reliable or up to date. The collection and compilation of information and updating of existing data in near real time … …American Journal of Applied Sciences, Vol. 7, Issue 4 · 30 Apr 2010 · 7,955 accessesView PDF Cite

Research ArticleOpen accessIn the abstractHyperspectral Remote Sensing for Tropical Rain ForestKamaruzaman Jusoff, Kasawani IbrahimProblem statement: Sensing, mapping and monitoring the rain forest in forested regions of the world, particularly the tropics, has attracted a great deal of attention in recent years as deforestation and forest degradation account for up to 30% of anthropogenic carbon emissions and are now included in climate change negotiations. Approach: We reviewed the potential for air and spaceborne hyperspectral … …American Journal of Applied Sciences, Vol. 6, Issue 12 · 31 Dec 2009 · 8,576 accessesView PDF Cite

Research ArticleOpen accessAll words, across the recordThe Performance of Maximum Likelihood, Spectral Angle Mapper, Neural Network and Decision Tree Classifiers in Hyperspectral Image AnalysisHelmi Zulhaidi Mohd Shafri, Affendi Suhaili, Shattri MansorSeveral classification algorithms for pattern recognition had been tested in the mapping of tropical forest cover using airborne hyperspectral data. Results from the use of Maximum Likelihood (ML), Spectral Angle Mapper (SAM), Artificial Neural Network (ANN) and Decision Tree (DT) classifiers were compared and evaluated. It was found that ML performed the best followed by ANN, DT and SAM with … …Journal of Computer Science, Vol. 3, Issue 6 · 30 Jun 2007 · 142,381 accessesView PDF Cite