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rlhe stucly was originally designed to assess vegetation diversity in Borneo's tropical rain forest with ecological consequence that can be retrieved from Landsat erM+. "le were particularly interested in recognitien of spectral pattern of land cover for developing land cover and forest degradation mapping by visual analysis of satellite imagery in Sabah, Malaysia. In addition unsupervised, supervised classification, band ratio of TM4, TM41TM5, and TM2!TM7, and pattern decernposition analysis were tested to evaluate the interpretation. iVe proposed a reliable method of forest degradation mapping in Sabah from land cover map incorporated with their spectral pattern. Dense forest was found clearly discriminated from water and soil by using visual interpretation a d pattern deeomposition analysis, particularly in channel 3, 4, and 5. Hewever, it was difficult to discriminate spectral pattern of non-forest through decomposition analysis. Logged-over forest was found dominant in the study area (36%), followed by plantatien (21%), and only about 17% covered with natural dense forest, It is estimated that approximately 76% of the forest in Sabah, have been threatened with forest degradation. Iteywortts: spectral pattern, land coverfuse, Landsat Ei'M+, forest degradation. INTRODUCTION Borneo Island, next to the Arriazon of Brazil, is the secend largest ropical rain forest ecosystem in the world. It has the mest species-rich communities known anywhere else on earth and perferms important envirenment and landscape functien ovHTTEMoRE, 1975). However, the vegetation biodiversity oi Borneo tropical forest has been peorly studied and understood although it is subject to be intensive converting for timber 'iGraduate School of Agricultural and life Sciences, the University of lbkyo, 1-1-1 Yayoi Bunkyo-ku, Tbkyo 113-8657, Japan. e-mail/ darmawan@affrc.go.jp '" Forestrv and Forest Produets Research Institute, 1 Matsunosato, Tsukuba-si, Ibaraki 305-8687, Japan.e-mail:rslsaite@ffpri.aifrc.go.jp '3 Centre for Ecological Research, }fyoto University, 509-3 Ohtsuka, Kamitanakami Hirano-cho, Ohtsu, Shiga 520-2113, Japan. e-mail: kitayama@ecology. kyoto-u.ac.jp extraction, agriculture, mining and settlemenL lherefore, study of characteristic ef land cover is important source for understanding the vegetation biodiversity Availability of ]and cover information is a prerequisite for understanding the global change process and will enhance our capability to predict land use and vegetation pattern and global ferest environment (forest fire, degradation forest etc,) for forest management strategles. Recently several image classification techniques have been developed to map land cover and forest degradation (I2xNGFoRD and BELL, 1997; Sm.MABuKuRo et al., 1998). In general, rnethods to extract land cover/use from remotely sensed data can be summarized as: Visual Analysis CXUX) (LILLEsANT) and lhEFER, 1987; HoMmo, 1991), Multivariate Spectral Analysis (MSA) (pt(A/rllER, 1987; SMITH, 1999), Spectral Mixture 1inalysis (SMA) (ADAM et al,, 1986; rllioMpKINs et al., 1997), and Data Integration (e.g, CoNiww, 1997) , The rnost famous technique to extract information from satellite irnagery that still preserves the highest information on vegetation is the Normalized Difference Vegetation Index

journal of forest planning

Recognition of Spectral Pattern Characteristic of Land Cover for Assisting Visual Interpretation of Landsat ETM&lt;sup&gt;+&lt;/sup&gt;: A Forest Degradation Mapping in Tropical Rain Forest of Sabah, Malaysia