Based on the introduction of remote sensing techniques and method as normal optical satellite remote sensing imagery, InSAR, LIDAR and etc, this paper reviews the newly application and development of remote sensing for landslide study. From each of the landslide risk assessment 5 phases: basic topographical data acquisition and extraction, landslide inventory and mapping, monitoring and landslide diagnostic factors mapping and element at risk mapping, this paper states the RS techniques offer a solid technique infrastructure, and exploits its potential development for landslide risk assessment. From the role of RS in landslide study, interpretability, causative condition that influence landslide identification, accuracy assessment and RS data source selection, the author states and discuss some questionable and arguable aspects，and as well presents that: ① the mainly use of remote sensing for landslide study is data and information acquisition and update; ② the interpretability of landslides from remote sensing images depends in the first place on the spatial resolution of the images in relation to the size of the features which are characterizing the slope movement and which can be recognized or identified. The following aspects are key features for recognizing landslides from remote sensing images: temporal resolution, the existing contrast between the slope movement and its background, the ability of stereo imagery acquisition and the interpretability is also influenced by the interpretation method，professional experience of the interpreter;③ the integration of remote sensing imagery，GIS spatial analysis and 3d visualization can enhance the landslide recognition and mapping efficiency and accuracy; ④ the accuracy assessment of landslide interpreted from remote sensing imagery should be objectively assessed from valid, misidentification, omission aspects according to the specific interpretability of the image; ⑤ as for remote sensing data selection for landslide risk assessment, which should follow sufficient is best for the specific application and take costeffective into account.