Land cover/land use change studies are predicated on reliable ontologies for vegetation classification and categorization. Classifications of land cover and land use, and land cover change have been useful for documenting forest loss, urbanization, and habitat conversion. However, the current global land cover data products are insufficient for arid grasslands for two reasons. First, current classification products have poor performance in arid systems and are extremely unreliable, particularly for distinguishing between cropland and grassland. Second, these classifications are discrete characterizations of dynamic systems and do not provide any information about grassland degradation, or relative condition; rather grassland is classified as a singular static state. Combined, these limitations mean that our ability to discern any information about change in grasslands with current mapping approaches is extremely limited. This symposium will bring together researchers engaged with remote sensing, land cover change detection, and spatial modeling of grasslands, and seeks to challenge the participants to re-imagine the process of mapping of grasslands on regional and global scales. The idea for this project comes from a need for a more useful and accurate portrayal of grassland dynamics in a spatial context. The goal is to spark new research that will create an entirely new system of characterizing and tracking grassland area and status that will be useful for arid systems research and land use/land cover change detection as well as monitoring and management of rangelands.
2016 Annual Meeting
Asheville, NC | April 3-7, 2016