Browsing by Subject "Inventory"

Now showing 1 - 9 of 9
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    Downtown Saint Paul Retail/Commercial Inventory
    (2004) Schaffer, Brian
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    East Seventh: A Cosmopolitan Corridor
    (2001) Daniel, Thomas
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    Municipal Housing Policy in Minnesota.
    (Center for Urban and Regional Affairs, University of Minnesota; School of Public Affairs; and Office of Local and Urban Affairs, 1977) CURA
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    The Restaurant GHG Guidelines: An Operational Greenhouse Gas Emissions Accounting Protocol for Restaurants
    (2016-05) Messier, Joseph
    This thesis proposes the Restaurant GHG Guideline, a holistic protocol, to document and assess the greenhouse gas emissions generated by processes that occur both directly and indirectly in the operation of a restaurant. Existing greenhouse gas (GHG) accounting protocols either have a narrow focus on emissions from processes that occur directly on the site of the building and indirectly as a result of purchased energy consumption on site or offer only general guidance for identifying emissions sources throughout organizations’ supply chains. For restaurant operations, many offsite processes are necessary to produce goods or services that are critical to their economic success, and therefore carry much weight in management decisions. By including emissions sources throughout a restaurant’s supply chain, this guideline identifies significant hot-spot emissions sources. It provides calculation methods for identifying GHG emissions generated at the scale of individual components, creating a more effective inventory for operators to develop targeted reduction initiatives. Historic operational data from a test case restaurant is used to illustrate how the specificity of the tool can help restaurant operators identify GHG emissions hot-spots at the level of individual components. By utilizing this guideline to identify these emission sources, restaurant operators can then create targeted reduction strategies.
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    Spatial Assessment of Boreal Forest Carbon
    (2015-06) Kristensen, Terje
    The ability to accurately map and monitor forest carbon (C) has gained global attention as countries seek to comply with international agreements to mitigate climate change. However, attaining precise estimates of forest C storage is challenging due to the inherent heterogeneity occurring across different scales. To develop cost-effective sampling protocols, there is a need for more unbiased estimates of the current C stock, its distribution among forest compartments and its variability across different scales. As a contribution to this work, this dissertation used high-resolution field measurements of C collected from different forest compartments across a boreal forest stand in South East Norway. In the first paper, we combined the use of airborne scanning light detection and ranging (lidar) systems with fine-scale spatial C data relating to vegetation and the soil surface to describe and contrast the size and spatial distribution of C pools across the forest. We found that predictor variables from lidar derived metrics delivered precise models of above and belowground tree C, which comprised the largest of the measured C pool in our study. We also found evidence that lidar canopy data correlated well with the variation in field layer C stock. By using topographical models from lidar ground returns we were able to establish a strong correlation between lidar data and the organic layer C stock at a stand level. In the search for an effective tool to measure and monitor forest C pools, we found the capabilities of lidar to map forest C encouraging. In the second paper, we used a geostatistical approach to analyze the fine-scale heterogeneity of the soil organic layer (forest floor) C storage. Our results showed that the C stocks were highly variable within each plot, with spatial autocorrelation distances < 3 m. Further, we established that a minimum of 20 to 25 inventory samples is needed to determine the organic layer C stock with a precision of �0.5 kg C m-2 in inventory plots of ~2000 m2. In the third paper, we investigated how the short-range spatial variability of organic layer C affects sampling strategies aiming to monitor and detect changes in the C stock. We found that sample repeatability rapidly declines with sample separation distance, and the a priori sample sizes needed to detect a change a fixed change in the organic layer C stock vary by a factor of ~4 over 15 to 125 cm separation distance. Unless care is taken by the surveyor to ensure spatial sampling precision, substantially larger samples sizes, or longer time intervals between baseline sampling and revisit are required to detect a change. In the final paper, we utilized the nested sampling protocol to investigate the spatial variability of organic layer C across different scales and incorporated inventory expenses in the development of a cost-optimal sampling approach. Because precise estimates are costly to obtain, it is of great interest for surveyors to develop cost-efficient sampling protocols aimed at maximizing the spatial coverage, while minimizing the estimate variance. We found that the majority of the estimate variance is confined within small subplots (100 m2) of the forest (25 km2), emphasizing the importance of considering the short-range variability when conducting a large-scale inventory. Further, this chapter demonstrated how optimal allocation of sampling units (plot, subplot and sample) is not only a function of the variance component within that dimension, but also changes with the sampling unit costs and the acceptable margin of error. We found that the costs of conducting an organic layer C inventory could be reduced by more than 60% by increasing the inventory uncertainty from �0.25 Mg C ha-1 to �0.5 Mg C ha-1. Finally, we established that sampling costs can be reduced with as much 80% by conducting a double sampling procedure that utilizes the correlation between organic layer C stock (r = 0.79 to 0.85) and measurements of layer thickness.
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    Twin Cities Conversions. The Complete Inventory: 1970-1980.
    (Center for Urban and Regional Affairs, University of Minnesota., 1981) Pinkerton, Milo
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    Wetland Inventory and Classification for Carlton and South St. Louis Counties : Final Report and Deliverables
    (University of Minnesota Duluth, 2008-12-31) Host, George E; Meysembourg, Paul
    Accurate maps of the type and locations of wetlands are critical for land use planning, particularly for watersheds undergoing rapid develoment or facing increased development pressure. The important role wetlands play in maintaining habitat, water quality and surface and ground-water protection is well documented, but cun*ent information on the types, sizes, and locations of wetlands is difficult to obtain. As coastal environments come under increased pressure from development, this infonnation is essential for zoning, buildout scenarios and numerous other planning objectives. Within the Coastal Program boundary, however，up-to-date information on wetland type and distribution is sparse, outdated, or lacking for many watersheds. While the National Wetland Inventory is the most extensive and commonly used inventory, the limitations with respect to spatial and classification accuracy are well-recogiiized. Over several iterations, we have systematically been mapping wetlands within high- gi*owth areas of the Minnesota's Lake Superior Coastal Program. The objective of the current proposal is to use recent MN DNR aerial photography and other spatial data to delineate and characterize wetlands for the southwestern portion the Coastal Program area. These includes approximately tliree townships in Carlton County and watershed extensions into St. Louis County (Figure 1). Our primary end products are digital maps of classified wetlands and with associated data tables, which are here provided to the Lake Superior Coastal Program for distribution to decision makers and the general public. Wetland maps are delivered in two fomiats. As part of this final report to the MN DNR, we have included a DVD that contains the rectified raw imagery, inteipreted wetland in GIS fonnat, and metadata for the data layers. We have also created, as part of the CoastalGIS website at the Natural Resources Research Institute, downloadable and online versions of the interpreted wetlands. The download versions are delivered in ESRI shapefile fonnat, with associated metadata. We also provide an interactive version using the Arc Internet Map Server, which allows maps to be viewed and manipulated over the Internet with a standard web brower. The NOAA-funded CoastalGIS web site was established in March 2002 to sei*ve as a clearinghouse for spatial data relevant to the Coastal Program. The site currently contains a wide range of data sets on natural resources and infrastructure，and is designed to assist local decision makers and the general public in land use planning. The CoastalGIS web site can be accessed at: http://www. nrri. umn. edu/Coastal GIS