Hyperspectral imagery is a powerful tool for managing farmlands and forests, enhancing both efficiency and yield. Applications include precise crop monitoring for drought, stress, disease, nutrient levels, weeds, invasive species, and other crop-specific metrics. Using the unique spectral fingerprints of vegetation, ground coverage (acreage) can be estimated and allocated to specific crop or tree species. In forestry, hyperspectral data fused with lidar can assess pre-harvest conditions, estimate yield in board feet, and identify species mixtures. Additionally, recurring imagery collections allow for effective monitoring of replanting efforts over time.​