Demographic data are commonly represented by using a choropleth map, which aggregates the data to... more Demographic data are commonly represented by using a choropleth map, which aggregates the data to arbitrary areal units, causing inaccuracies associated with spatial analysis and distribution. In contrast, dasymetric mapping takes quantitative areal data and attempts to show the underlying statistical surface by breaking up the areal units into zones of relative homogeneity. This thesis applies the dasymetric mapping method to the 1990 U.S. Census blockgroup populations of Alameda County, California using the U.S. Geological Survey’s 1992 National Land Cover Data Set and other ancillary land-cover sources to redistribute the block-group populations into a 30-m grid based on categorical zones relative to population distribution. To test the accuracy of the dasymetric approach, census block populations were compared with the dasymetric mapping distributions; the results yield high correlation coefficients (between 0.80-0.88), indicating that the dasymetric mapping method produced more...
Remotely sensed imagery is increasingly used by emergency managers to monitor and map the impact ... more Remotely sensed imagery is increasingly used by emergency managers to monitor and map the impact of flood events to support preparedness, response, and critical decision making throughout the flood event lifecycle. To reduce latency in delivery of imagery-derived information, ensure consistent and reliably derived map products, and facilitate processing of an increasing volume of remote sensing data-streams, automated flood mapping workflows are needed. The U.S. Geological Survey is facilitating the development and integration of machine-learning algorithms in collaboration with NASA, National Geospatial Intelligence Agency (NGA), University of Alabama, and University of Illinois to create a workflow for rapidly generating improved flood-map products. A major bottleneck to the training of robust, generalizable machine learning algorithms for pattern recognition is a lack of training data that is representative across the landscape. To overcome this limitation for the training of alg...
Data were obtained to assess how forest type, hydrologic conditions and management strategies aff... more Data were obtained to assess how forest type, hydrologic conditions and management strategies affect GHG soil flux at the Great Dismal Swamp National Wildlife Refuge. The goal is to relate changes in GHG fluxes to shifts in refuge hydrologic management on forested peatlands. We identified nine study site locations, representing three mature vegetation communities [Atlantic White Cedar (desired community), tall pine pocosin (desired community), and red maple/black gum mixed (undesired community)] with typical water depth within each vegetation type. All measurements were replicated three times (3 vegetation types x 3 replicates = 9 sites total). We installed four flux chambers at each site to collect GHG fluxes from all nine sites. We measured CO2 and CH4 using a Los Gatos Research Ultra Portable Greenhouse Gas Analyzer and two-part 760 cm2 flux chambers (chamber base remained in situ; chamber top was placed on the bottom only when sampling). We checked the gas fluxes on a monthly ti...
In this study, we determined the carbon balance in the Great Dismal Swamp, a large forested peatl... more In this study, we determined the carbon balance in the Great Dismal Swamp, a large forested peatland in the southeastern USA, which has been drained for over two hundred years and now is being restored through hydrologic management. We modeled future net ecosystem carbon balance over 100 years (2012 to 2112) using in situ field observations paired with simulations of water-table depth. The three scenarios used in the model were baseline conditions, flooded/wet conditions, and drained/dry conditions, which represent a range of potential management actions and climate conditions at the Great Dismal Swamp. This U.S. Geological Survey Data Release provides the modeled output estimating the net ecosystem carbon balance, on an annual time-step, from 2012 through 2112, for each scenario. The U.S. Geological Survey modeling framework is referred to as the Land Use and Carbon Scenario Simulator (LUCAS), which uses a state-and-transition simulation model coupled with a carbon stock-flow model...
Abstract: Demographic data are commonly represented by using a choropleth map, which aggregates t... more Abstract: Demographic data are commonly represented by using a choropleth map, which aggregates the data to arbitrary areal units, causing inaccuracies associated with spatial analysis and distribution. In contrast, dasymetric mapping takes quantitative areal data and attempts to show the underlying statistical surface by breaking up the areal units into zones of relative homogeneity. This thesis applies the dasymetric mapping method to the 1990 U.S. Census block-group populations of Alameda County, California using the U.S. Geological Survey’s 1992 National Land Cover Data Set and other ancillary land-cover sources to redistribute the block-group populations into a 30-m grid based on categorical zones relative to population distribution. To test the accuracy of the dasymetric approach, census block populations were compared with the dasymetric mapping distributions; the results yield high correlation coefficients (between 0.80-0.88), indicating that the dasymetric mapping method pr...
Estimating ecosystem carbon (C) balance relative to natural disturbances and land management stre... more Estimating ecosystem carbon (C) balance relative to natural disturbances and land management strengthens our understanding of the benefits and tradeoffs of carbon sequestration. We conducted a historic model simulation of net ecosystem C balance in the Great Dismal Swamp, VA. for the 30-year time period of 1985-2015. The historic simulation of annual carbon flux was calculated with the Land Use and Carbon Scenario Simulator (LUCAS) model. The LUCAS model utilizes a state-and-transition simulation model coupled with a carbon stock-flow accounting model to estimate net ecosystem C balance, and long term sequestration rates under various ecological conditions and management strategies. The historic model simulation uses age-structured forest growth curves for four forest species, C stock and flow rates for 8 pools and 14 fluxes, and known data for disturbance and management. The annualized results of C biomass are provided in this data release in the following categories: Growth, Heterotrophic Respiration (Rh), Net Ecosystem Production (NEP), Net Biome Production (NBP), Below-ground Biomass (BGB) Stock, Above-ground Biomass (AGB) Stock, AGB Carbon Loss from Fire, BGB Carbon Loss from Fire, Deadwood Carbon Loss from Management, and Total Carbon Loss. The table also includes the area (annually) of each forest type in hectares: Atlantic white cedar Area (hectares); Cypress-gum Area (hectares); Maple-gum Area (hectares); Pond pine Area (hectares). Net ecosystem production for the Great Dismal Swamp (~ 54,000 ha), from 1985 to 2015 was estimated to be a net sink of 0.97 Tg C. When the hurricane and six historic fire events were modeled, the Great Dismal Swamp became a net source of 0.89 Tg C. The cumulative above and belowground C loss estimated from the South One in 2008 and Lateral West fire in 2011 totaled 1.70 Tg C, while management activities removed an additional 0.01 Tg C. The C loss in below-ground biomass alone totaled 1.38 Tg C, with the balance (0.31 Tg C) coming from above-ground biomass and detritus. The LUC [...]
Hazard preparedness has become a critical issue for local populations who are potentially vulnera... more Hazard preparedness has become a critical issue for local populations who are potentially vulnerable to natural disasters. Essential to preparedness planning is determining where people are likely to be located, which varies from day to night. The fundamental approaches to geographic scale and cartographic representation are an integral aspect of how population distribution is represented over space. Using a dasymetric mapping technique, residential populations are estimated by interpolating the census block values to 10 m pixels based on parcellevel land use and density. To determine daytime population estimates, a quantitative employee database gives x,y point locations of each business and exact numbers of how many people are employed within a coastal community. From census records, we can estimate the number of people who are leaving their residences during the daytime to go to work outside of a tsunami hazard zone.
Abstract The Great Dismal Swamp National Wildlife Refuge (GDS) is a forested peatland that provid... more Abstract The Great Dismal Swamp National Wildlife Refuge (GDS) is a forested peatland that provides a number of ecosystem services including carbon (C) sequestration. We modeled and analyzed the potential capacity of the GDS to sequester C under four management scenarios: no management, no management with catastrophic fire, current management, and increased management. The analysis uses the Land Use and Carbon Scenario Simulator developed for the GDS to estimate net ecosystem C balance. The model simulates net C gains and losses on an annual time-step from 2013 through 2062 which is converted to carbon dioxide equivalent (CO2-eq) and monetized using the Interagency Working Group's Social Cost of Carbon. Our analysis incorporates compounded uncertainty including variation in ecological processes, temporal and spatial heterogeneity, and uncertainty in the discount rate. The no management scenario results in 2.4 million tons of CO2 emissions with a Net Present Value (NPV) under a 3% discount rate of −$67 million. No management with catastrophic fires emits 6.5 million tons of CO2 with an NPV of −$232 million. Current management avoids 9.9 million tons of emissions (via sequestration) with an NPV of $326 million. Increased management avoids 16.5 million tons of emissions with an NPV of $524 million.
Demographic data are commonly represented by using a choropleth map, which aggregates the data to... more Demographic data are commonly represented by using a choropleth map, which aggregates the data to arbitrary areal units, causing inaccuracies associated with spatial analysis and distribution. In contrast, dasymetric mapping takes quantitative areal data and attempts to show the underlying statistical surface by breaking up the areal units into zones of relative homogeneity. This thesis applies the dasymetric mapping method to the 1990 U.S. Census block-group populations of Alameda County, California using the U.S. Geological Survey's 1992 National Land Cover Data Set and other ancillary land-cover sources to redistribute the block-group populations into a 30-m grid based on categorical zones relative to population distribution. To test the accuracy of the dasymetric approach, census block populations were compared with the dasymetric mapping distributions; the results yield high correlation coefficients (between 0.80-0.88), indicating that the dasymetric mapping method produced...
For more information on the USGS-the Federal source for science about the Earth, its natural and ... more For more information on the USGS-the Federal source for science about the Earth, its natural and living resources, natural hazards, and the environment-visit http://www.usgs.gov or call 1-888-ASK-USGS
Spatially-explicit state-and-transition simulation models of land use and land cover (LULC) incre... more Spatially-explicit state-and-transition simulation models of land use and land cover (LULC) increase our ability to assess regional landscape characteristics and associated carbon dynamics across multiple scenarios. By characterizing appropriate spatial attributes such as forest age and land-use distribution, a state-and-transition model can more effectively simulate the pattern and spread of LULC changes. This manuscript describes the methods and input parameters of the Land Use and Carbon Scenario Simulator (LUCAS), a customized state-and-transition simulation model utilized to assess the relative impacts of LULC on carbon stocks for the conterminous U.S. The methods and input parameters are spatially explicit and describe initial conditions (strata, state classes and forest age), spatial multipliers, and carbon stock density. Initial conditions were derived from harmonization of multi-temporal data characterizing changes in land use as well as land cover. Harmonization combines numerous national-level datasets through a cell-based data fusion process to generate maps of primary LULC categories. Forest age was parameterized using data from the North American Carbon Program and spatially-explicit maps showing the locations of past disturbances (i.e. wildfire and harvest). Spatial multipliers were developed to spatially constrain the location of future LULC transitions. Based on distance-decay theory, maps were generated to guide the placement of changes related to forest harvest, agricultural intensification/extensification, and urbanization. We analyze the spatially-explicit input parameters with a sensitivity analysis, by showing how LUCAS responds to variations in the model input. This manuscript uses Mediterranean California as a regional subset to highlight local to regional aspects of land change, which demonstrates the utility of LUCAS at many scales and applications.
Socio-environmental vulnerable populations are often unrepresented in land-use planning yet have ... more Socio-environmental vulnerable populations are often unrepresented in land-use planning yet have great potential for loss when exposed to changes in ecosystem services. Administrative boundaries, cultural differences, and language barriers increase the disassociation between land-use management and marginalized populations living in the U.S.eMexico borderlands. This paper describes the development of a Modified Socio-Environmental Vulnerability Index (M-SEVI), using determinants from binational census and neighborhood data that describe levels of education, access to resources, migratory status, housing, and number of dependents, to provide a simplified snapshot of the region's populace that can be used in binational planning efforts. We apply this index at the SCW, located on the border between Arizona, USA and Sonora, Mexico. For comparison, the Soil and Water Assessment Tool is concurrently applied to assess the provision of erosion-and flood control services over a 9-year period. We describe how this coupling of data can form the base for an ecosystem services assessment across political boundaries that can be used by land-use planners. Results reveal potential disparities in environmental risks and burdens throughout the binational watershed in residential districts surrounding and between urban centers. The M-SEVI can be used as an important first step in addressing environmental justice for binational decision-making.
Demographic data are commonly represented by using a choropleth map, which aggregates the data to... more Demographic data are commonly represented by using a choropleth map, which aggregates the data to arbitrary areal units, causing inaccuracies associated with spatial analysis and distribution. In contrast, dasymetric mapping takes quantitative areal data and attempts to show the underlying statistical surface by breaking up the areal units into zones of relative homogeneity. This thesis applies the dasymetric mapping method
The Great Plains of the United States has undergone extensive land-use and land-cover change in t... more The Great Plains of the United States has undergone extensive land-use and land-cover change in the past 150 years, with much of the once vast native grasslands and wetlands converted to agricultural crops, and much of the unbroken prairie now heavily grazed. Future land-use change in the region could have dramatic impacts on ecological resources and processes. A scenario-based modeling framework is needed to support the analysis of potential land-use change in an uncertain future, and to mitigate potentially negative future impacts on ecosystem processes. We developed a scenario-based modeling framework to analyze potential future land-use change in the Great Plains. A unique scenario construction process, using an integrated modeling framework, historical data, workshops, and expert knowledge, was used to develop quantitative demand for future land-use change for four IPCC scenarios at the ecoregion level. The FORE-SCE model ingested the scenario information and produced spatially explicit land-use maps for the region at relatively fine spatial and thematic resolutions. Spatial modeling of the four scenarios provided spatial patterns of land-use change consistent with underlying assumptions and processes associated with each scenario. Economically oriented scenarios were characterized by significant loss of natural land covers and expansion of agricultural and urban land uses. Environmentally oriented scenarios experienced modest declines in natural land covers to slight increases. Model results were assessed for quantity and allocation disagreement between each scenario pair. In conjunction with the U.S. Geological Survey’s Biological Carbon Sequestration project, the scenario-based modeling framework used for the Great Plains is now being applied to the entire United States.
Demographic data are commonly represented by using a choropleth map, which aggregates the data to... more Demographic data are commonly represented by using a choropleth map, which aggregates the data to arbitrary areal units, causing inaccuracies associated with spatial analysis and distribution. In contrast, dasymetric mapping takes quantitative areal data and attempts to show the underlying statistical surface by breaking up the areal units into zones of relative homogeneity. This thesis applies the dasymetric mapping method to the 1990 U.S. Census blockgroup populations of Alameda County, California using the U.S. Geological Survey’s 1992 National Land Cover Data Set and other ancillary land-cover sources to redistribute the block-group populations into a 30-m grid based on categorical zones relative to population distribution. To test the accuracy of the dasymetric approach, census block populations were compared with the dasymetric mapping distributions; the results yield high correlation coefficients (between 0.80-0.88), indicating that the dasymetric mapping method produced more...
Remotely sensed imagery is increasingly used by emergency managers to monitor and map the impact ... more Remotely sensed imagery is increasingly used by emergency managers to monitor and map the impact of flood events to support preparedness, response, and critical decision making throughout the flood event lifecycle. To reduce latency in delivery of imagery-derived information, ensure consistent and reliably derived map products, and facilitate processing of an increasing volume of remote sensing data-streams, automated flood mapping workflows are needed. The U.S. Geological Survey is facilitating the development and integration of machine-learning algorithms in collaboration with NASA, National Geospatial Intelligence Agency (NGA), University of Alabama, and University of Illinois to create a workflow for rapidly generating improved flood-map products. A major bottleneck to the training of robust, generalizable machine learning algorithms for pattern recognition is a lack of training data that is representative across the landscape. To overcome this limitation for the training of alg...
Data were obtained to assess how forest type, hydrologic conditions and management strategies aff... more Data were obtained to assess how forest type, hydrologic conditions and management strategies affect GHG soil flux at the Great Dismal Swamp National Wildlife Refuge. The goal is to relate changes in GHG fluxes to shifts in refuge hydrologic management on forested peatlands. We identified nine study site locations, representing three mature vegetation communities [Atlantic White Cedar (desired community), tall pine pocosin (desired community), and red maple/black gum mixed (undesired community)] with typical water depth within each vegetation type. All measurements were replicated three times (3 vegetation types x 3 replicates = 9 sites total). We installed four flux chambers at each site to collect GHG fluxes from all nine sites. We measured CO2 and CH4 using a Los Gatos Research Ultra Portable Greenhouse Gas Analyzer and two-part 760 cm2 flux chambers (chamber base remained in situ; chamber top was placed on the bottom only when sampling). We checked the gas fluxes on a monthly ti...
In this study, we determined the carbon balance in the Great Dismal Swamp, a large forested peatl... more In this study, we determined the carbon balance in the Great Dismal Swamp, a large forested peatland in the southeastern USA, which has been drained for over two hundred years and now is being restored through hydrologic management. We modeled future net ecosystem carbon balance over 100 years (2012 to 2112) using in situ field observations paired with simulations of water-table depth. The three scenarios used in the model were baseline conditions, flooded/wet conditions, and drained/dry conditions, which represent a range of potential management actions and climate conditions at the Great Dismal Swamp. This U.S. Geological Survey Data Release provides the modeled output estimating the net ecosystem carbon balance, on an annual time-step, from 2012 through 2112, for each scenario. The U.S. Geological Survey modeling framework is referred to as the Land Use and Carbon Scenario Simulator (LUCAS), which uses a state-and-transition simulation model coupled with a carbon stock-flow model...
Abstract: Demographic data are commonly represented by using a choropleth map, which aggregates t... more Abstract: Demographic data are commonly represented by using a choropleth map, which aggregates the data to arbitrary areal units, causing inaccuracies associated with spatial analysis and distribution. In contrast, dasymetric mapping takes quantitative areal data and attempts to show the underlying statistical surface by breaking up the areal units into zones of relative homogeneity. This thesis applies the dasymetric mapping method to the 1990 U.S. Census block-group populations of Alameda County, California using the U.S. Geological Survey’s 1992 National Land Cover Data Set and other ancillary land-cover sources to redistribute the block-group populations into a 30-m grid based on categorical zones relative to population distribution. To test the accuracy of the dasymetric approach, census block populations were compared with the dasymetric mapping distributions; the results yield high correlation coefficients (between 0.80-0.88), indicating that the dasymetric mapping method pr...
Estimating ecosystem carbon (C) balance relative to natural disturbances and land management stre... more Estimating ecosystem carbon (C) balance relative to natural disturbances and land management strengthens our understanding of the benefits and tradeoffs of carbon sequestration. We conducted a historic model simulation of net ecosystem C balance in the Great Dismal Swamp, VA. for the 30-year time period of 1985-2015. The historic simulation of annual carbon flux was calculated with the Land Use and Carbon Scenario Simulator (LUCAS) model. The LUCAS model utilizes a state-and-transition simulation model coupled with a carbon stock-flow accounting model to estimate net ecosystem C balance, and long term sequestration rates under various ecological conditions and management strategies. The historic model simulation uses age-structured forest growth curves for four forest species, C stock and flow rates for 8 pools and 14 fluxes, and known data for disturbance and management. The annualized results of C biomass are provided in this data release in the following categories: Growth, Heterotrophic Respiration (Rh), Net Ecosystem Production (NEP), Net Biome Production (NBP), Below-ground Biomass (BGB) Stock, Above-ground Biomass (AGB) Stock, AGB Carbon Loss from Fire, BGB Carbon Loss from Fire, Deadwood Carbon Loss from Management, and Total Carbon Loss. The table also includes the area (annually) of each forest type in hectares: Atlantic white cedar Area (hectares); Cypress-gum Area (hectares); Maple-gum Area (hectares); Pond pine Area (hectares). Net ecosystem production for the Great Dismal Swamp (~ 54,000 ha), from 1985 to 2015 was estimated to be a net sink of 0.97 Tg C. When the hurricane and six historic fire events were modeled, the Great Dismal Swamp became a net source of 0.89 Tg C. The cumulative above and belowground C loss estimated from the South One in 2008 and Lateral West fire in 2011 totaled 1.70 Tg C, while management activities removed an additional 0.01 Tg C. The C loss in below-ground biomass alone totaled 1.38 Tg C, with the balance (0.31 Tg C) coming from above-ground biomass and detritus. The LUC [...]
Hazard preparedness has become a critical issue for local populations who are potentially vulnera... more Hazard preparedness has become a critical issue for local populations who are potentially vulnerable to natural disasters. Essential to preparedness planning is determining where people are likely to be located, which varies from day to night. The fundamental approaches to geographic scale and cartographic representation are an integral aspect of how population distribution is represented over space. Using a dasymetric mapping technique, residential populations are estimated by interpolating the census block values to 10 m pixels based on parcellevel land use and density. To determine daytime population estimates, a quantitative employee database gives x,y point locations of each business and exact numbers of how many people are employed within a coastal community. From census records, we can estimate the number of people who are leaving their residences during the daytime to go to work outside of a tsunami hazard zone.
Abstract The Great Dismal Swamp National Wildlife Refuge (GDS) is a forested peatland that provid... more Abstract The Great Dismal Swamp National Wildlife Refuge (GDS) is a forested peatland that provides a number of ecosystem services including carbon (C) sequestration. We modeled and analyzed the potential capacity of the GDS to sequester C under four management scenarios: no management, no management with catastrophic fire, current management, and increased management. The analysis uses the Land Use and Carbon Scenario Simulator developed for the GDS to estimate net ecosystem C balance. The model simulates net C gains and losses on an annual time-step from 2013 through 2062 which is converted to carbon dioxide equivalent (CO2-eq) and monetized using the Interagency Working Group's Social Cost of Carbon. Our analysis incorporates compounded uncertainty including variation in ecological processes, temporal and spatial heterogeneity, and uncertainty in the discount rate. The no management scenario results in 2.4 million tons of CO2 emissions with a Net Present Value (NPV) under a 3% discount rate of −$67 million. No management with catastrophic fires emits 6.5 million tons of CO2 with an NPV of −$232 million. Current management avoids 9.9 million tons of emissions (via sequestration) with an NPV of $326 million. Increased management avoids 16.5 million tons of emissions with an NPV of $524 million.
Demographic data are commonly represented by using a choropleth map, which aggregates the data to... more Demographic data are commonly represented by using a choropleth map, which aggregates the data to arbitrary areal units, causing inaccuracies associated with spatial analysis and distribution. In contrast, dasymetric mapping takes quantitative areal data and attempts to show the underlying statistical surface by breaking up the areal units into zones of relative homogeneity. This thesis applies the dasymetric mapping method to the 1990 U.S. Census block-group populations of Alameda County, California using the U.S. Geological Survey's 1992 National Land Cover Data Set and other ancillary land-cover sources to redistribute the block-group populations into a 30-m grid based on categorical zones relative to population distribution. To test the accuracy of the dasymetric approach, census block populations were compared with the dasymetric mapping distributions; the results yield high correlation coefficients (between 0.80-0.88), indicating that the dasymetric mapping method produced...
For more information on the USGS-the Federal source for science about the Earth, its natural and ... more For more information on the USGS-the Federal source for science about the Earth, its natural and living resources, natural hazards, and the environment-visit http://www.usgs.gov or call 1-888-ASK-USGS
Spatially-explicit state-and-transition simulation models of land use and land cover (LULC) incre... more Spatially-explicit state-and-transition simulation models of land use and land cover (LULC) increase our ability to assess regional landscape characteristics and associated carbon dynamics across multiple scenarios. By characterizing appropriate spatial attributes such as forest age and land-use distribution, a state-and-transition model can more effectively simulate the pattern and spread of LULC changes. This manuscript describes the methods and input parameters of the Land Use and Carbon Scenario Simulator (LUCAS), a customized state-and-transition simulation model utilized to assess the relative impacts of LULC on carbon stocks for the conterminous U.S. The methods and input parameters are spatially explicit and describe initial conditions (strata, state classes and forest age), spatial multipliers, and carbon stock density. Initial conditions were derived from harmonization of multi-temporal data characterizing changes in land use as well as land cover. Harmonization combines numerous national-level datasets through a cell-based data fusion process to generate maps of primary LULC categories. Forest age was parameterized using data from the North American Carbon Program and spatially-explicit maps showing the locations of past disturbances (i.e. wildfire and harvest). Spatial multipliers were developed to spatially constrain the location of future LULC transitions. Based on distance-decay theory, maps were generated to guide the placement of changes related to forest harvest, agricultural intensification/extensification, and urbanization. We analyze the spatially-explicit input parameters with a sensitivity analysis, by showing how LUCAS responds to variations in the model input. This manuscript uses Mediterranean California as a regional subset to highlight local to regional aspects of land change, which demonstrates the utility of LUCAS at many scales and applications.
Socio-environmental vulnerable populations are often unrepresented in land-use planning yet have ... more Socio-environmental vulnerable populations are often unrepresented in land-use planning yet have great potential for loss when exposed to changes in ecosystem services. Administrative boundaries, cultural differences, and language barriers increase the disassociation between land-use management and marginalized populations living in the U.S.eMexico borderlands. This paper describes the development of a Modified Socio-Environmental Vulnerability Index (M-SEVI), using determinants from binational census and neighborhood data that describe levels of education, access to resources, migratory status, housing, and number of dependents, to provide a simplified snapshot of the region's populace that can be used in binational planning efforts. We apply this index at the SCW, located on the border between Arizona, USA and Sonora, Mexico. For comparison, the Soil and Water Assessment Tool is concurrently applied to assess the provision of erosion-and flood control services over a 9-year period. We describe how this coupling of data can form the base for an ecosystem services assessment across political boundaries that can be used by land-use planners. Results reveal potential disparities in environmental risks and burdens throughout the binational watershed in residential districts surrounding and between urban centers. The M-SEVI can be used as an important first step in addressing environmental justice for binational decision-making.
Demographic data are commonly represented by using a choropleth map, which aggregates the data to... more Demographic data are commonly represented by using a choropleth map, which aggregates the data to arbitrary areal units, causing inaccuracies associated with spatial analysis and distribution. In contrast, dasymetric mapping takes quantitative areal data and attempts to show the underlying statistical surface by breaking up the areal units into zones of relative homogeneity. This thesis applies the dasymetric mapping method
The Great Plains of the United States has undergone extensive land-use and land-cover change in t... more The Great Plains of the United States has undergone extensive land-use and land-cover change in the past 150 years, with much of the once vast native grasslands and wetlands converted to agricultural crops, and much of the unbroken prairie now heavily grazed. Future land-use change in the region could have dramatic impacts on ecological resources and processes. A scenario-based modeling framework is needed to support the analysis of potential land-use change in an uncertain future, and to mitigate potentially negative future impacts on ecosystem processes. We developed a scenario-based modeling framework to analyze potential future land-use change in the Great Plains. A unique scenario construction process, using an integrated modeling framework, historical data, workshops, and expert knowledge, was used to develop quantitative demand for future land-use change for four IPCC scenarios at the ecoregion level. The FORE-SCE model ingested the scenario information and produced spatially explicit land-use maps for the region at relatively fine spatial and thematic resolutions. Spatial modeling of the four scenarios provided spatial patterns of land-use change consistent with underlying assumptions and processes associated with each scenario. Economically oriented scenarios were characterized by significant loss of natural land covers and expansion of agricultural and urban land uses. Environmentally oriented scenarios experienced modest declines in natural land covers to slight increases. Model results were assessed for quantity and allocation disagreement between each scenario pair. In conjunction with the U.S. Geological Survey’s Biological Carbon Sequestration project, the scenario-based modeling framework used for the Great Plains is now being applied to the entire United States.
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Papers by Rachel Sleeter