Urban heat island (UHI) effect can be characterized by increasing surface and atmospheric temperature and decreasing
rainfall amount in urban area. This research detected the impact of urban land use changes to UHI effect in Taichung city
at Taiwan by temporal ASTER and MODIS satellite images and measured data from ground thermometer stations. From
spatially analyzed data output, the results showed a linear pattern between land use changes to UHI effect for study area.
The remote sensing technology has become the important information source in environment investigation, Moreover,
optical satellite images are the most important information source. Although the optical satellite images may provides
high resolution, multi-spectral images and better vision images than active satellite, the disadvantage is affected by the
atmospheric condition easily. In general, the cloud cover is the most common noise, may decrease the image information
abundantly and has impact on the environmental monitoring application seriously. According to the cloud imaging
model, add defilade manually with different reflection coefficient to simulate different thickness of cloud. Then utilize
GIS analytical method and cooperate with histogram calculation to extraction different reflection coefficients boundary.
In this research, we get the upper threshold limitation value for haze and lower threshold limitation value for thick heavy
cloud. So, we change the classification level from 2 ordinal levels into 3 qualitative levels. We change the thick and haze
cover classification into threshold limitation value heavy, haze and fuzzy could cover classification by using the
Formosat-2 satellite images. Make use of therefore way, can change the description yardstick into the quantitative
yardstick that is we change the ordinal scale into interval scale in the image of cloud cover efficiency.
Taipei Water Source Domain is established to protecting the water source which supplied approximately 5 million
populations in the large Taipei living area to avoid destroy and pollution. Therefore, land management of water source
domain becomes the key point to prevent these problems. Using the remote sensing technology to manage the land use
is the major target in this research. We employed Supervised Classifier to classify the land use and land cover type. We
utilize spatial analysis to investigate the current land use condition and employ post-classification comparison
algorithm for land use types' change analysis. The classification overall accuracy of 2006 is 95.60%. The result of
environmental change detection analysis of land use categories shows that vegetation goes through three period's
growth tendency. However, the change analysis through 1998 to 2006 points out the area near Hsin-Dian and Ping-Lin
had a magnitude change.