This paper presents a systematic approach to utilize multi-temporal remote sensing images and spatial analysis for the detection, investigation, and long-term monitoring of landslide hazards in Taiwan. Rigorous orthorectification of satellite images are achieved by correction of sensor orbits and backward projections with ground control points of digital elevation models. Individual images are also radiometrically corrected according to sensor calibration factors. In addition, multi-temporal images are further normalized based on pseudo-invariant features identified from the images. Probable landslides are automatically detected with a change-detection procedure that combines NDVI filtering and Change-Vector Analysis. A spatial analysis system is also developed to further edit and analyze detected landslides and to produce landslide maps and other helpful outputs such as field-investigation forms and statistical reports. The developed landslide detection and monitoring system was applied to a study of large-scale landslide mapping and analysis in southern Taiwan and to the long-term monitoring of landslides in the watershed of Shimen Reservoir in northern Taiwan. Both application examples indicate that the proposed approach is viable. It can detect landslides effectively and with high accuracy. The data produced with the developed spatial analysis system are also helpful for hazard investigation, reconstruction, and mitigation.