- Related Research Areas
- Carbon Cycle & Ecosystems
Investigation is needed to identify the ICESat-II measurement characteristics that are necessary for detecting vegetation change and disturbance. Using Landsat imagery, existing landcover maps, and other geospatial data layers it is possible to identify areas of change and then to link this information with the three-dimensional vegetation structure data that can be derived from a lidar waveform (e.g. ICESat-I data). This structural information is critical for quantifying stand parameters that are affected by change. To optimize this data collection it is important to determine the footprint size and sampling density needed to capture change. This is expected to vary depending on the vegetation type that has changed, the type of change, and change magnitude. One approach is the use of seasonality as a change surrogate using ICESat-I data. This approach is expected to be especially useful for identifying subtle, but critical changes like disease. Another approach is to compare before and after waveforms in known areas of change, such as plantations. To extend the temporal range in which to experiment with change metrics and to identify footprint size and sampling issues we plan to incorporate LVIS (Laser Vegetation Imaging System) waveform data. The goal is to identify metrics or characteristics in the waveform (e.g. amplitude, shape) that will help discriminate among change types and/or magnitudes. The SDT member will be supported by staff from the US Forest Service and the US Geological Survey, currently involved in the LANDFIRE project, who have considerable expertise in remote sensing (including waveform lidar), ecology, geography, computer science, and signal processing. LANDFIRE produces consistent vegetation and fire fuels maps for the United States at 30-m resolution, and is developing change detection methods, using various data sources. The results of this effort can help to guide definition of mission requirements to detect change in forested areas.
Project PI: Birgit Peterson/USGS EROS Center
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