Forestry

Abstract

Remote sensing has numerous applications in forestry. Older, historical applications relied primarily on interpretation of aerial photography for forest inventories. More recently, newer airborne and spaceborne active and passive sensors have greatly expanded the utility of remote sensing in forestry. Examples include lidar, which can provide forest structural parameters such as tree height, crown volume, and stand biomass at accuracies that are equal to, or exceed, ground-based measures. Regional to global estimates of changes in forest cover have also been made possible by remote sensing, providing critical measures of changes in carbon stocks and fluxes needed to better understand human environmental impacts and better manage resources. Several operational remote sensing products contribute to improved assessment of fire danger, fire management, fire severity, and postfire recovery.