Landscape Analysis and Characterization to Support Regional Environmental Assessment
Landscape characterization is an essential component for determining the status and trends in the condition of ecological resources. The amount and spatial arrangement of land cover types are related to ecological processes and the effect a specific stress(s) may have on the resources in a region. LACRA is a cooperative effort between KARS and EPA Region VII's Regional Environmental Monitoring and Assessment Program (R-EMAP) that seeks to establish empirical relationships between regional landscapes and fisheries health while developing landscape metrics for use in other regional environmental assessments.
R-EMAP is a key component of EPA's Office of Research and Development (ORD) Environmental Monitoring and Assessment Program (EMAP), a research program that focuses on the development and utilization of ecological monitoring as a critical part of environmental management and assessment for regional environmental issues. The EPA Region VII R-EMAP study concentrates on the condition of fisheries resources in the states of Missouri, Kansas, and Nebraska. Preliminary evidence from fish tissue studies has suggested that fisheries resources in these states have been adversely impacted by chemical pollutants. The Region VII R-EMAP study focuses on the following questions: (1) What is the status of the health of fisheries in Region VII? (2) What associations exist between selected landscape indicators of natural and anthropogenic stresses and indicators of fisheries health?
LACRA is examining the suitability of existing sources of regional land use/land cover data sets for landscape characterization. These data differ in their age, source data (i.e., aerial or satellite), method of compilation (i.e., manual or digital), attribute resolution, and spatial resolution. It also is looking at the use of vegetation indices (VIs) derived from digital satellite data. Vegetation indices are highly indicative of vegetation properties (e.g., leaf area, green biomass) and work done by KARS has shown VIs better explain variation in stream water chemistry than area statistics for land use/land cover. In addition, a VI time-series using multiple dates of VI imagery over the course of a growing season is being constructed to characterize and assess the dynamic nature of land cover.