Scientific and Technical Aerospace Reports Volume 38 July 28, 2000

km x 1000 km). As with the nearly completed Amazon component of the Global Rain Forest Mapping project, SAR imagery, radar
image mosaics and SAR-derived texture image products will be available to the scientific community on the World Wide Web.
Image acquisition for this project has been completed and processing and image interpretation is underway at the Alaska SAR
Facility.
Author
Image Processing; Thematic Mapping; Rain Forests; Radar Imagery; North America
20000062933 Nature Conservancy, Arlington, VA USA
The Gulf Coastal Plain Ecosystem Partnership: Development of Conservation Strategies and Projects Final Report, 5 May
1998 - 4 May 2000
Compton, Vernon; May 2000; 274p; In English
Contract(s)/Grant(s): DAMD17-98-2-8015
Report No.(s): AD-A377316; No Copyright; Avail: CASI; A12, Hardcopy; A03, Microfiche
The Gulf Coastal Plain Ecosystem Partnership (GCPEP) is a unique collaboration among Eglin AFB, The Nature Conservancy
(TNC), Champion International Corporation, Blackwater River State Forest, Northwest Florida Water Management District
and National Forests in Alabama and Florida, who cooperate under the auspices of a 1996 multi party Memorandum of
Understanding. The partners manage more than 840,000 acres in one of the most important conservation landscapes in the Southeast.
of the 115 species of plants and animals and 29% natural communities identified by TNC as being targets for conservation
action in the 42 million acre Eastern Gulf Coastal Plain ecoregion, 37% of species and 38% of natural communities occur on
GCPEP lands, despite GCPEP being only 2% of the ecoregional land area. The GCPEP has undertaken a joint planning process,
including identifying site conservation targets and assessing the stresses and sources of stress. Eighteen total conservation targets
were identified, ranging from single species (e.g., red-cockaded woodpeckers) to large, matrix-forming ecosystem types, (e.g.,
longleaf pine matrix). Major threats to targets include residential development, incompatible fire, forestry and agricultural practices,
unstable management funding and roads/utility corridors. Cooperative conservation strategies were developed in the project’s
second phase.
DTIC
Gulfs; Coastal Ecology; Ecosystems
20000064524 Colorado Univ., Cooperative Inst. for Research in Environmental Sciences, Boulder, CO USA
Sources of Variability in Plant Canopy Hyperspectral Data in a Savanna Ecosystem
Asner, Gregory P., Colorado Univ., USA; Wessman, Carol A., Colorado Univ., USA; Bateson, C. Ann, Colorado Univ., USA; Summaries
of the Seventh JPL Airborne Earth Science Workshop January 12-16, 1998; Dec. 19, 1998; Volume 1, pp. 23-31; In English;
See also 20000064520; No Copyright; Avail: CASI; A02, Hardcopy; A04, Microfiche
The relative importance of the plant structural, biophysical, and biochemical attributes of vegetation that determine a hyperspectral
reflectance signal have not been well quantified. Vegetation reflectance is primarily a function of tissue optical properties
(leaf, woody stem, standing litter), canopy structural attributes (e.g. leaf and stem area), soil reflectance, illumination conditions,
and viewing geometry. Foliage and non-photosynthetic vegetation (NPV) affect the radiation field through their reflectance and
transmittance characteristics. Leaf optical properties are a function of leaf structure, water content, and the concentration of
biochemicals (e.g. lignin, cellulose, nitrogen). However, several studies have demonstrated that leaf-level variability in carbon
and nitrogen chemistry plays a small role in determining canopy reflectance characteristics in comparison to leaf water content
and leaf area index (LAI). In this paper, we use a combination of field and modeling techniques to quantify the relative contribution
of leaf, stem, and litter optical properties, and canopy and landscape structural attributes, to the hyperspectral reflectance characteristics
of a spatially complex savanna ecosystem. In contrast to recent studies focused on scaling within-leaf biochemical characteristics
to leaf and canopy scales, this study approaches the scaling problem from the observed variability in tissue optical
properties, then examines the importance of this tissue-level variability in comparison to canopy structural variability at landscape
scales using a plant canopy radiative transfer model.
Derived from text
Spectrum Analysis; Canopies (Vegetation); Leaf Area Index; Optical Properties; Mathematical Models; Remote Sensing
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