Disturbance is a critical ecological process in forested systems, and disturbance maps are important for understanding forest dynamics. Landsat data are a key remote sensing dataset for monitoring forest disturbance and there recently has been major growth in the development of disturbance mapping algorithms.
In light of Earth's changing climate and growing human population, there is an urgent need to improve monitoring of natural and anthropogenic disturbanceswhich effect forests' ability to sequester carbon and provide other ecosystem services.
When characterizing the processes that shape ecosystems, ecologists increasingly use the unique perspective offered by repeat observations of remotely sensed imagery. However, the concept of change embodied in much of the traditional remote-sensing literature was primarily limited to capturing large or extreme changes occurring in natural systems, omitting many more subtle processes of interest to ecologists.
Vegetation structure quantified by light detection and ranging (LiDAR) can improve understanding of wildlife occupancy and species-richness patterns. However, there is often a time lag between the collection of LiDAR data and wildlife data.
With earth's surface temperature and human population both on the rise a new emphasis has been placed on monitoring changes to forested ecosystems the world over. In the United States the U.S. Forest Service Forest Inventory and Analysis (FIA) program monitors the forested land base with field data collected over a permanent network of sample plots. Although these plots are visited repeatedly through time there are large temporal gaps (e.g.
Using remotely-sensed metrics to identify regions containing high animal diversity and/or specific animal species or guilds can help prioritize forest management and conservation objectives across actively managed landscapes. We predicted avian species richness in two mixed conifer forests, Moscow Mountain and Slate Creek, containing different management contexts and located in north-central Idaho.
In western conifer-dominated forests where the abundance of old-growth stands is decreasing, species such as the Brown Creeper (Certhia americana) may be useful as indicator species for monitoring the health of old-growth systems because they are strongly associated with habitat characteristics associated with old growth and are especially sensitive to forest management.
The critical role of forests in the global carbon cycle is well known, but significant uncertainties remain about the specific role of disturbance, in part because of the challenge of incorporating spatial and temporal detail in the characterization of disturbance processes.
Disturbance events strongly affect the composition, structure, and function of forest ecosystems; however, existing US land management inventories were not designed to monitor disturbance. To begin addressing this gap, the North American Forest Dynamics (NAFD) project has examined a geographic sample of 50 Landsat satellite image time series to assess trends in forest disturbance across the conterminous United States for 1985-2005.
Tree canopy cover is a fundamental component of the landscape, and the amount of cover influences fire behavior, air pollution mitigation, and carbon storage. As such, efforts to empirically model percent tree canopy cover across the United States are a critical area of research. The 2001 national-scale canopy cover modeling and mapping effort was completed in 2006, and here we present results from a pilot study for a 2011 product.