Monitoring of forest stand condition in Thailand
- Tropical; seasonal forest-
Haruo sawada, hideki saito
forestry and forest products research institute, Japan
P.O. box 16, tsukuba-norin, ibarakim, 305 Japan
Thongchai charuppat, jirawan charuppat, Suwit Ongsomwant
Royal forestry department, Thailand
surachai ratanasermping, chaowalit silapathong national research council of Thailand.
Abstract
The study aims to find and develop practical methodology on digital processing of satellite remote sensing data and other geographical information for observing and monitoring tropical seasonal forest area.
Around the Doi intanon, chiang mai, was selected as one of the study areas to develop forest type classification method and to delineate forest area affected by shifting cultivation.
The main methodologies of the study are (1) to make a forest type map of chiang Mai study area based on the normalized difference vegetation index (2) to establish the field check system for comparing ground measurements with the processed remote sensing data. The results are as follows: (1) The shifting one between evergreen forests and deciduous forests in 700m
and 800m was found by the four landsat images and checked by the field survey. (2) a field survey system was established among the researchers concerned to the project. The video system was found useful for recording field survey plot.
1. Introduction
IUFRO ( international union of forestry organization) published the "international guideline for forest monitoring" in 1994. the basic forest types which have been used by FAO for the "Forest resources assessment (1990)" are introduced in the Guideline as the minimum requirement for global monitoring in order to contribute international activities in forestry community.
Based on the idea of this Guideline, we could classify forests into several types in Thailand. The main forest types in Thailand are evergreen forest, mixed forest and deciduous forest, and
plantation and mangrove forest are found at specific areas. In northern Thailand, DDF (Dry Dipterocarp forest) are dominant in low altitude and evergreen trees are dominant at high altitude. MDF (Mixed Deciduous Forest) stands at the transitional one of these two forest types. Phonological changes of forests dcorrespond to the rainfall and the components of forest (forest stand condition) and it is clearly observed in DDF and MDF stands.
Satellite remote sensing technology are considered effective for monitoring these phonological aspects. The periodicity of observation is one of the main important characteristics of Satellite remote sensing. NOAA, Landsat, Spot, Mos and JERS are main satellites from which we can get earth observation images regularly.
The remote sensing community has used Normalized Difference Vegetation index (NDVI) of NOAA AVHRR data to monitor global vegetation conditions (Goward et al. 1991; Spanner et al. 1990; Tucker and choudhury 1987)). The index is sensitive to the quantity of active photosynthesizing biomass on the landscape (Burgan and Hartford 1993). Geographers have used NDVI data to develop a map that portrays vegetation patterns across the United States (Loveland et al. 1991).
This study aims to find and develop practical methodology on digital processing of satellite remote sensing data and other geographical information for observing and monitoring seasonal changes of tropical forest, which correspond to forest stand conditions.
Chiang Mai district were selected for this study. Forest development by shifting cultivation is widely being executed in Chiang Mai and multi-temporal TM data are considered useful to classify the forest, which correspond to forest stand conditions.
