Browsing by Subject "Tree canopy"

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    2015 Twin Cities Metropolitan Area Urban Tree Canopy Assessment
    (2017-01-03) Knight, Joe F; Rampi, Lian P; Host, Trevor K; jknight@umn.edu; Knight, Joseph, F
    A high-resolution (1-meter) tree canopy assessment was completed for the Twin Cities Metropolitan Area. Mapping of existing and potential tree canopy is critical for urban tree management at the landscape level. This classification was created from combined 2015 aerial imagery, LIDAR data, and ancillary thematic layers. These data sets were integrated using an Object-Based Image Analysis (OBIA) approach through multi-resolution image segmentation and an iterative set of classification commands in the form of customized rulesets. eCognition® Developer was used to develop the rulesets and produce raster classification products for TCMA. The results were evaluated using randomly placed and independent verified assessment points. The classification product was analyzed at regional scales to compare distributions of tree canopy spatially and at different resolutions. The combination of spectral data and LiDAR through an OBIA method helped to improve the overall accuracy results providing more aesthetically pleasing maps of tree canopy with highly accurate results.
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    Quantifying solids and nutrient recovered through street sweeping in a suburban watershed
    (2015-04) Kalinosky, Paula Marie
    Solids that collect on street surfaces are comprised of varying proportions of inorganic particles ranging in size from silt and clays to gravels, vegetative and other organic material, trash, and a host of pollutants deposited from surface runoff and atmospheric sources (ex. car exhaust). This material has alternatively been called `street dust' `street dirt', `street dirt', `road sediments', `street particulate matter' or `SPaM', `urban particulate matter', or simply referred to as `gross solids'. Whatever name it goes by, it is a significant source of pollution to urban stormwater and one mean of limiting this source is street sweeping. The coarse organic component of street particulate matter (leaves, grass clippings, and other vegetative matter) is not well characterized in existing street sweeping literature. Coarse organic debris that enters storm sewers can accumulate in catch basins and pipes, or be transported into streams, lakes, and rivers, releasing nutrients along the way as it decomposes. The primary objectives of the study were to quantify the influence of tree canopy (a source of organic debris), season, and street sweeping frequency on the quantity of solids and nutrients recovered from streets through street sweeping. We measured the total solids and nutrient loads (TP, TN, TOC) recovered in 392 street sweeping operations over a 2-year period in residential areas of Prior Lake, MN. Coarse organic material was separated from finer, soil-like material through dry sieving followed by density separation (floating the material retained on the sieve in a water bath). Chemical analysis (total phosphorus, TP, total nitrogen, TN, total organic carbon, TOC, % moisture, and % organic matter, %OM) was carried out on each fraction. Coarse organic material made up 15% of the total dry weight of swept material collected during the study, but 36% of the TP and 71% of the TN. Percent overhead tree canopy cover was a significant predictor of average recoverable loads of coarse organic material and associated nutrients in all months of the year. Sweeping frequency was a significant predictor of total recoverable loads in several months of the year. Seasonal influences were apparent in both fractions of sweepings. The loading intensity (kg/curb-meter) of fines was greatest in the early spring immediately following snow melt and the loading intensity of coarse organic matter was greatest in October during fall leaf litter drop. Fresh coarse organics recovered during May had a significantly higher leaching potential than coarse organics collected at other times of the year.Regression analysis was used to develop predictive metrics for planning sweeping operations. The regressions predict the average expected solids and nutrient recovery by month, sweeping frequency, and tree canopy cover. Metrics for tracking total phosphorus (TP) and total nitrogen (TN) recovery based on the mass of sweepings collected were also developed based on study findings.