Cluster analysis also reported nearly identical results between methods, with over 98% of watersheds assigned to the same group for three of the four methods. Spearman ranks were nearly identical between methods for all four metrics. Paired t-test results showed significant differences between methods for three of the four metrics. Each metric was calculated using vector and raster methods and estimated values were compared using a paired t-test, Spearman rank correlation and cluster analysis. We examined four GIS-based measurements of environmental quality in approximately 1000 watersheds in the state of Maryland and Washington, D.C. This conversion error has been widely studied, but the impact on environmental decision making has not been addressed. Raster processes are more commonly used because they can be significantly faster computationally than vector, but error is introduced in converting vector data to raster. Most of these measurements can be calculated using either raster or vector data formats and processing methods. GIS-based measurements that combine native raster and native vector data are commonly used to assess environmental quality. Relative to the GRPA Goal 2 multiyear plan, this research is intended to "provide tools to assess and diagnose impairment in aquatic systems and the sources of associated stressors." Relative to the Goal 4 Multiyear Plan this research is intended to (1) provide states and tribes with an ability to assess the condition of waterbodies in a scientifically defensible and representative way, while allowing for aggregation and assessment of trends at multiple scales, (2) assist Federal, State and Local managers in diagnosing the probable cause and forecasting future conditions in a scientifically defensible manner to protect and restore ecosystems, and (3) provide Federal, State and Local managers with a scientifically defensible way to assess current and future ecological conditions, and probable causes of impairments, and a way to evaluate alternative future management scenarios. ![]() This research directly supports long-term goals established in ORDs multiyear plans related to GPRA Goal 2 (Water) and GPRA Goal 4 (Healthy Communities and Ecosystems), although funding for this task comes from Goal 4. ![]() Quantify relationships between landscape metrics generated from wall-to-wall spatial data and (1) specific parameters related to water resource conditions in different environmental settings across the US, including but not limited to nutrients, sediment, and benthic communities, and (2) multi-species habitat suitability ĭevelop and validate multivariate models based on quantification studies ĭevelop GIS/model assessment protocols and tools to characterize risk of nutrient and sediment TMDL exceedence Ĭomplete an initial draft (potentially web based) of a national landscape condition assessment. The primary objectives of this research are to:ĭevelop methodologies so that landscape indicator values generated from different sensors on different dates (but in the same areas) are comparable differences in metric values result from landscape changes and not differences in the sensors
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