Improving Species Spectral Discrimination Using Derivatives Spectra For Mapping of Tropical Forest From Airborne Hyperspectral Imagery Affendi Bin Suhaili PhD Candidate [GS14198] Faculty of Forestry Universiti Putra Malaysia UPM Serdang, Selangor. affendi.suhaili@gmail.com Helmi Z.M Shafri N.A Ainuddin A.G. Awg Noor I.Faridah Hanum ABSTRACT Forest resource maps were traditionally prepared from forest inventories involving aerial photography and fieldwork, however with the advent of technology, remote sensing from satellite platforms offers an alternative and economic tool for forest mapping. With the development of hyperspectral sensors, forest species discrimination and mapping could be improved as the fine spectral resolutions inherent in this system allows the identification of small differences in the similar spectral responses between forest species. There are however some problems associated with the use of this technology, namely associated with the high dimensionality of the data set that results in redundancy and the also the detection of small absorption features presence in the plant spectra. By using derivative spectra, subtle spectral features between different tree species could be detected from a limited number of bands and the overlapping absorption characteristics from these similar plant responses are resolved which might not be possible from analysis of the original spectrum. This study evaluates the discriminative capabilities in terms of the spectral separability among tropical tree species and on classification accuracy when using the derivative spectra for mapping an old growth forest plot in the Forest Research Institute of Malaysia (FRIM), Kepong, Selangor. Results showed that the separability (JM distance measure) of crown spectra from 16 species of trees commonly found in the Malaysian tropical forest were higher and classification accuracy (Max-Likelihood algorithm) improved to 70.15% when using the derivative data set. From this study it is concluded that hyperspectral data obtained from the airborne imaging spectrometer (AISA) could discriminate between tree species of the tropical forest and the use of derivative spectroscopy as an image enhancement technique could improve species discrimination and classification accuracy. This has provided a potential for application of the hyperspectral imaging system for mapping of the tropical forest at an operational level. INTRODUCTION Forests have long been regarded as a national treasure in Malaysia. With the current depletion of forested areas around the world, it is important that we manage these renewable resources in a sustainable manner and in order to formulate and excise efficient forest management policies and practices, it is important to have the maximum information about the forest cover. Forest resource maps were traditionally prepared from forest inventories involving aerial photography and fieldwork, however with the advent of technology, remote sensing from satellite platforms offers an alternative and economic tool for forest mapping. The tropical rainforest is much known for its high species composition and the current use of broad band multispectral sensors would not be effective to distinguish the small spectral differences of the forest canopies due to the similar spectral signature between the tree species. With the development of hyperspectral sensors, forest species discrimination and mapping could be improved as the fine spectral resolutions inherent in this system allows the identification of small differences in the similar spectral responses between forest species. There are however some problems associated with the use of this technology, namely associated with the high dimensionality of the data set that results in redundancy and the also the detection of small absorption features presence in the plant spectra. Operational application of the hyperspectral sensors for mapping of forest canopies are also subjected to varying illumination conditions and background effects. One method which is commonly employed to resolve or enhance the absorption features that might be masked by interfering background absorption is by the use of derivative spectrometry (Curran et al.,1990 ; Filella and Penuelas, 1994). Spectral derivatives also aid in suppressing the continuum caused by other leaf biochemicals (such as lignin and secondary pigments) and canopy background effects (Elvidge, 1990). By using derivative spectra, subtle spectral features between different tree species could be detected from a limited number of bands and the overlapping absorption characteristics from these similar plant responses are resolved which might not be possible from analysis of the original spectrum.
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