The research is to explore the utility of multisensor remote sensing data to survey and map the tropical forest vegetation distribution.Those multisensor remote sensing materials are: （1） Spot-1 XS 16-Feb-1988; （2） Landsat-5 TM 02-Feb-1988; （3） Landsat-1 MSS 02-Mar-1973; （4） aerial panchromatic black and white photographs Mar-1989.The satellite remote sensing data were processed through histogram equalization

principal components analysis and maximum likelihood classification

by using a IIS model 75 with S-600 software

linked to a micro-VAX as host compu ter. The tropical forest vegetation classification system for surveying and mapping with remote sensing is developed.According to tropical forest vegetation classification system

the remote sensing images were interpreted before some field sampling of remote sensing images were conducted. The method of analysis that combined the image feacture with the forest ecological law was used in this interpretation. The details of interest for this research were forest vegetation type

so the boundaries delineated by tracing details on a transparency superimpsed on the spot XS or Landsat TM composites. But the satellite images can not be used for the classification of all forest vegetation types. This is he reason t hat aerial photographs of special sites were used in this research.After interpretation

all details of relevant forest vegetation types from satellite images were transferred to base map （scale 1:200

000 and 1:50

000） for making the forest vegetation map of xishuangbanna Prefecture and nature reserves. The Preliminary map accuracy is 38%

by some field verification. The forest vegetation maps was completed and printed.The research both provides the important basic data for protection and management of the tropical forest vegetation in Xishuangbanna and reveals that remote sensing technique especially multisensor remote sensing method is an economic and efficient technique for surveying and mapping the tropical forest vegetation.