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Detroit Lakes, MN, United States

Beck M.W.,University of Minnesota | Vondracek B.,U.S. Geological Survey | Hatch L.K.,University of Minnesota | Vinje J.,4583 County Hwy 19
ISPRS Journal of Photogrammetry and Remote Sensing

Lake resources can be negatively affected by environmental stressors originating from multiple sources and different spatial scales. Shoreline development, in particular, can negatively affect lake resources through decline in habitat quality, physical disturbance, and impacts on fisheries. The development of remote sensing techniques that efficiently characterize shoreline development in a regional context could greatly improve management approaches for protecting and restoring lake resources. The goal of this study was to develop an approach using high-resolution aerial photographs to quantify and assess docks as indicators of shoreline development. First, we describe a dock analysis workflow that can be used to quantify the spatial extent of docks using aerial images. Our approach incorporates pixel-based classifiers with object-based techniques to effectively analyze high-resolution digital imagery. Second, we apply the analysis workflow to quantify docks for 4261 lakes managed by the Minnesota Department of Natural Resources. Overall accuracy of the analysis results was 98.4% (87.7% based on K^) after manual post-processing. The analysis workflow was also 74% more efficient than the time required for manual digitization of docks. These analyses have immediate relevance for resource planning in Minnesota, whereas the dock analysis workflow could be used to quantify shoreline development in other regions with comparable imagery. These data can also be used to better understand the effects of shoreline development on aquatic resources and to evaluate the effects of shoreline development relative to other stressors. © 2013 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS). Source

Dustin D.L.,4583 County Hwy 19 | Jacobson P.C.,603 1st St West
Lake and Reservoir Management

Land use along lakeshores impacts littoral habitat. We used raster-based land use and land cover datasets as well as a statewide dock polygon dataset to assess the development status of lake shoreland on 150 Minnesota lakes. A dataset containing dock polygons identified using a semiautomated process performed best statewide. An older raster dataset that classified rural development based on the presence of buildings performed better than a recent dataset based on dominant land cover. We classified points along the shore as developed or undeveloped using proximity to a development indicator: either a raster cell with a developed land use or a dock point. We compared classifications derived from GIS data to actual development, which was defined by the presence of a manually identified dock on aerial photos, and used total operating characteristic (TOC) analysis to evaluate the performance of each dataset. All 3 datasets classified development better than random chance. The dock dataset performed best, and its results were consistent statewide, while the raster datasets' performance varied among ecoregions. Researchers should be aware that the prevalence of the condition being classified has a large impact on some commonly used metrics, such as accuracy and positive predictive value. The costs and tradeoffs of different types of error (false alarms or missed detections) will vary in different situations and should be explicitly considered when deciding how and when to use classification systems like these. © 2015 Copyright by the North American Lake Management Society. Source

Valley R.D.,Navico Inc | Johnson M.B.,Navico Inc | Dustin D.L.,4583 County Hwy 19 | Jones K.D.,University of Florida | And 2 more authors.
Journal of Aquatic Plant Management

Many ecosystem goods and services are derived from aquatic plant-dominated environments and the abundance and composition of aquatic plant communities affects habitat, recreation, angling, aesthetics, and commerce. We describe standardized hydroacoustic methodology that complements species composition surveys and generates comprehensive aquatic plant abundance data with little additional assessment or analysis effort than is already put forth for species surveys. Using data from 22 lakes across the United States, collected by biologists with varying levels of expertise, we compare hydroacoustically derived biovolume with two other semiquantitative measures of whole-lake abundance (frequency of occurrence and "rake fullness"). Although we documented some significant correlations between hydroacoustically derived biovolume and frequency and rake fullness, frequency or rake fullness was difficult to interpret biologically on a lakewide scale. We also describe a dominance index that incorporates both species composition and vegetation biovolume to evaluate the degree that a species dominates a local assemblage. We found that the extent of aquatic plant growth and invasive dominance was related to lake productivity with highest biovolume and dominance occurring in mesotrophic to eutrophic study lakes. Using both empirical and simulated data, we also found no significant differences between dominance calculated from a simple metric that gives equal weight to all species at a survey site and a metric that incorporated rake fullness for each species. Source

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