Remote Sensing, with its unique characteristics of multi-spatial, multi-temporal, and multi-spectral resolutions, provides a tool to conduct vegetation study. Remotely sensed data are available in spatial resolution from less than one meter to over a kilometer. The revisit time for a certain study area can be from one day to around one month. Satellite imagery provides information from visible wavelength region to near infrared, middle infrared, thermal infrared, and microwave wavelength regions. Remotely sensed data, as one important data source and with low cost comparing with in-situ measurement, have been used on urban planning, yield prediction, hazard estimation, land use land cover classification, global climate change, and many more. In this paper, two examples of using remotely sensed data to capture information of vegetation from large scale to small scale will be briefly described.