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Displaying 596 - 600 of 661Interacting watershed size and landcover influences on habitat and biota of Lake Superior coastal wetlands
Coastal wetlands are important contributors to large-lake productivity and biodiversity and mediators of lake—watershed interactions. This study explores whether the size of the watershed in which coastal wetlands are embedded (a measure of strength of connection to the terrestrial landscape) influences their background condition and response to anthropogenic landuse.
Monitoring land cover change in the Lake Superior basin
Consistent, repeatable and broadly applicable land use, land cover data is needed across the Lake Superior basin to facilitate ecosystem condition assessment and trend analysis. Such a data set collected regularly through time could inform and focus field monitoring efforts, and help prioritize restoration and mitigation efforts. Unfortunately, few data sets exist that are bi-nationally consistent in time, classification method, or resolution.
Desertification in China's Horquin area: a multi-temporal land use change analysis
China's Horquin area in the northern farming–pastoral transition zone is undergoing rapid land degradation and rangeland modification that is impacting far broader areas as the source of material for dust storms. Multi-temporal Landsat images of the Horquin core area were used to generate a time series of land use covering about a 30-year period, 1975–2003. We show that the physical environment in Horquin deteriorated between 1975 and 2000, although this situation was more controlled after 2000.
integrated approach to assessing multiple stressors for coastal Lake Superior
Biological indicators can be used both to estimate ecological condition and to suggest plausible causes of ecosystem degradation across the U.S. Great Lakes coastal region. Here we use data on breeding bird, diatom, fish, invertebrate, and wetland plant communities to develop robust indicators of ecological condition of the U.S. Lake Superior coastal zone. Sites were selected as part of a larger, stratified random design for the entire U.S. Great Lakes coastal region, covering gradients of anthropogenic stress defined by over 200 stressor variables (e.g.
Coastal wetland vegetation classification with a Landsat Thematic Mapper image
Coastal wetland vegetation classification with remotely sensed data has attracted increased attention but remains a challenge. This paper explored a hybrid approach on a Landsat Thematic Mapper (TM) image for classifying coastal wetland vegetation classes. Linear spectral mixture analysis was used to unmix the TM image into four fraction images, which were used for classifying major land covers with a thresholding technique. The spectral signatures of each land cover were extracted separately and then classified into clusters with the unsupervised classification method.