Remote Sensing for forestry applications In the tropical rain forest of Peninsular Malaysia
Yoshio Awaya, Itsuhito Ohnuki,
Harrrrruo Sawada, Osamu Nakakita
Forestry and forest products research institute of Japan
P.O. Box 16, Tsukuba Norin Kenkyudanchi-nai, Ibaraki, 305 Japan,
Khali Aziz b.Hamzah
Forest Research Institute Malaysia
Karung Berkunci 201, Kepong, 52109 Kuala Lumpur, Malaysia
Abstract
Remote sensing is an advantageous technology for forest resource management. Remote sensors send periodical image data, which can be used for various types of forest resource evaluation such as harvest monitoring and forest type classification. However clouds with tropical rain forests in the image data obstruct remote sensing. In the case of utilizing the visible and infrared radiometer, cloud free data might never be obtained from these areas and finding effective usages are now primary research topics.
This study concerns cutovers' detection and effective display techniques for displaying both original Landsat Thematic Mapper (TM) data and processed images, which show changes. As digital image processing has limited ability in accurately classifying forests both in the sun and shade and in accurately distinguishing cutovers from clouds, enhancement and display techniques for image interpretation are primary research themes in the tropics. Histogram normalization and Wall is enhancement was consecutively executed to provide contrast stretching in forests. TM channels 4,5 and 1 (TM 4,5,1) (red, green and blue in color respectively: RGB) made a very good combination for enhancing forest types and about 7 different types could be interpreted. Then principal component analysis (PCA) was executed to enhance images of cutovers using a combination of SPOT High Resolution Visible (HRV) and TH images, and normalized vegetation index (NVI) images of the HRV and TH respectively. Both results were adversely affected by clouds and their shadows, though the obtained with NVI had greatly enhanced cutover with reduced topographic effects. Compartment superimposed composites made it possible to precisely locate each forest cutover and they can effectively supplement the forest inventories on the ground.
Introduction
Forestry is one of the important industries of Malaysia and sustained timber harvesting is a major problem there. Forests are usually managed by the selective harvesting system. Forests are harvested every 30 or 55 years (MPI 1988) and their regeneration is a primary concern. "Harvesting has spread widely and it seems difficult to check exact harvested locations, extent of disturbance and growth. Due to poor accessibility and inadequate forest information, satellite remote sensing is a desired technology to be used in place of field checks (Wan Yusoff 1988)". However, since the appearance of clouds in combined NOAA Advanced Very High Resolution Radiometer (AVHRR) images using three weeks' data was reported by Malingreau (1986), it has been found that clouds obstruct practical remote sensing applications in the tropics. Since forest monitoring by digital image processing leads to numerous errors in the tropics producing interpretative photo products is a simple and practical way to utilize remote sensing data for forestry applications (Awaya et al. 1988).
As the topography of Peninsular Malaysia is very sleep, shadows may lead to misinterpretation, and also the varying sun elevations and azimuth angles of each image make complex mosaics of shadows in combined images. The objective of this paper is to determine how to reduce shadow effects and to enhance images of forest types and selectively harvested fporests in Malaysia by image enhancement techniques, i.e. histogram normalization, Wallis enhancement, NVI and PCA. Forest compartment boundaries are superimposed on the enhanced images to make it easy to interpret locations for forestry usage.
Study Area
The Ulu Selangor to Gombak area, which is adjacent to the north of Kuala Lumpur and covers an area of 25km by 25 km, was selected as a study area (Figure 1,2). The topography of the area various greatly. The western part is hilly with widespread oil palm and rubber plantations, and there are secondary forests in the north. The eastern part, which is from Batang Kali (Batang Kali, Serendah forest reserve and so on) to the Gentling Highlands (Ulu Gombak protoected forest, Ulu Gombak forest reserve), is mostly a steep mountainous area with elevations up to 1770 m above sea level and it is covered with forest.
The vertical distribution of the natural forests of Malaysia is shown in table 1 (Wyatt-Smith et al. 1963). Natural or primary forests including the Upper Dipterocarp Forest and Montane Forests are founded in the Genting Highlands and Ulu Gomak protected forest. Forests have been classified into eleven broad forest types by 19811-82' second global forest inventories organized by FAO (Wan Yusoff, 1988). According to the classification, forests are divided into two groups, based on elevations above and below 1000 m, i.e. unproductive and productive forests. They are further divided by stand volumes and species. Productive virgin forests were classified at the foot of the Genting Highlands by prescribed inventories. There are disturbed forests in the southeast of the study area, which have been harvested since 1988 and logged-over forests are common, though harvest years vary from the mid-70's up to present. Forests harvested prior to 1980situated in the south east and recently harvested forests in the east of the study area. Some forests have been converted forests in the east of the study area. Some forests have been converted into agriculture lands recently (Table 2, figure 2,5,8). Average timber volumes harvested in Batand Kali are about 15 tons (wet weight) par hectare.
