In this paper the progress of research on remotely sensing grassland is comprehensively reviewed through examination of the most recent international literature. First, the feasibility of using remotely sensed data to study grassland is discussed on the basis of its unique spectral reflectance. The most useful spectral bands for the monitoring and assessment of grassland resources are identified next. The common method of studying grassland through the use of vegetation index and other indices is assessed for their effectiveness. The applications of remote sensing in grassland studies, including monitoring and mapping of grassland cover, estimation of biomass, and degradation, are reviewed next. Of these applications, the most challenging is quantitative analysis of grassland resources. This paper then concentrates on the recent trends in remote sensing of grassland. They include use of videography and other air-borne high-resolution image data, digital image analysis, and GIS. It is anticipated that as remote sensing of grassland evolves from simple monitoring and assessment to dynamic modeling, GIS will play an increasingly important role in integrating diverse data into a common database to generate accurate results. The introduction of GIS will make remote sensing of grassland resources more predictive in nature.