Spatial Modeling of Land Use, Climate, and Environmental Consequences Active
USGS scientists have a long tradition of providing high-quality, consistent, and relevant land-cover data for the United States, using our archive of current and historical remote sensing data. Scientists at USGS EROS are using their experience in mapping land cover and their knowledge of land-cover change processes to temporally extend these databases beyond the dates of available remote sensing data. Using the EROS FOREcasting SCEnarios of Land-Cover (FORE-SCE) model, EROS scientists are modeling land-cover change both into the future, using scenario-based modeling approaches, and for "backcasting" land cover for historical periods. Modeled land-cover data, in combination with remote-sensing based land cover for historical and current time periods, are being used to assess the interactions among land use and climate with a variety of ecologically and societally relevant processes.
Statement of Problem: Land-use and land-cover modeling is a critical component for analysis and potential mitigation of the consequences of landscape change on ecological processes. Land managers and researchers require spatially and thematically consistent land-cover data to assess historical, current, and potential future interactions among land use, climate, and a host of ecologically and societally relevant processes. USGS provides historical and current land cover based on remote sensing databases, but only for a relatively short historical time period. Methodologies are needed to produce both historical and potential future land-cover maps that are consistent with remote sensing-based maps, facilitating long-term assessments of landscape, climate, and ecological interactions.
Why this Research is Important: Urban development, forestry, agriculture, mining, and other land uses can substantially alter the Earth's surface. Land use and the resultant change in land cover have important effects on ecological systems and processes. The use of current land-cover maps enables researchers and land managers to assess recent conditions and respond accordingly, based upon research and land management objectives. However, the availability of long-term historical land cover data and potential future land cover data enables researchers and land managers to move beyond a reactionary approach to an anticipatory approach. Historical records can be used to develop likely relationships between landscape change and the process of interest. That information can be used in conjunction with future scenarios of landscape change to visualize future outcomes and maximize societal, economic, or ecologic priorities, and to potentially mitigate any negative consequences before they even occur.
Objective(s): The objectives of this research are to develop state-of-the-art landscape modeling frameworks and apply them to problems of ecological, economic, and societal importance. We will:
- Continue development of the USGS's "FORE-SCE" model
- Investigate new modeling techniques, including continued improvements in our methodologies for mapping vegetation succession, fire and disturbance, and landscape response to climate change.
- Apply USGS land-cover models to produce spatially explicit, thematically detailed landscape maps / models that are consistent with widely used remote sensing-based land-cover data such as the National Land Cover Database (NLCD) or the Cropland Data Layer (CDL).
- Collaborate with USGS and other researchers on analyses of land-use and land-cover change effects on ecological and societal processes.
Methods: USGS EROS began development of a home-grown land-use and land-cover modeling framework in 2006. Work continues to improve the capabilities of the Forecasting Scenarios of Land-use Change (FORE-SCE) model, a model which has gained acceptance in the scientific literature, and has been applied in the United States to produce both historical "backcasts" and future forecasts of land-use and land-cover change. Our work focuses on the continued development of the FORE-SCE modeling framework, the integration of other modeling frameworks, and the development of new modeling frameworks that improve USGS' ability to map and model land-use and land-cover change.
Remote sensing provides an integral source of data for landscape modeling. Historical and current landscape information is used for scenario construction, model parameterization, and validation of model performance. However, land-cover modeling is inherently an interdisciplinary activity. We rely on elements of socioeconomics, geography, hydrology, climate, and other disciplines to both ensure the production of realistic and useful landscape projections, and in the application of the resultant modeled projections to address issues of societal importance. Because of the high level of uncertainty associated with predicting future developments in complex socio-environmental systems, a scenario framework is used that enables land managers to anticipate and adapt to a wide range of plausible future conditions.
Below are other science projects associated with this project.
Below are publications associated with this project.
The relative impacts of climate and land-use change on conterminous United States bird species from 2001 to 2075
Development of a generic auto-calibration package for regional ecological modeling and application in the Central Plains of the United States
Spatially explicit modeling of 1992-2100 land cover and forest stand age for the conterminous United States
Clarity versus complexity: land-use modeling as a practical tool for decision-makers
Land use and carbon dynamics in the southeastern United States from 1992 to 2050
A land-use and land-cover modeling strategy to support a national assessment of carbon stocks and fluxes
- Overview
USGS scientists have a long tradition of providing high-quality, consistent, and relevant land-cover data for the United States, using our archive of current and historical remote sensing data. Scientists at USGS EROS are using their experience in mapping land cover and their knowledge of land-cover change processes to temporally extend these databases beyond the dates of available remote sensing data. Using the EROS FOREcasting SCEnarios of Land-Cover (FORE-SCE) model, EROS scientists are modeling land-cover change both into the future, using scenario-based modeling approaches, and for "backcasting" land cover for historical periods. Modeled land-cover data, in combination with remote-sensing based land cover for historical and current time periods, are being used to assess the interactions among land use and climate with a variety of ecologically and societally relevant processes.
Statement of Problem: Land-use and land-cover modeling is a critical component for analysis and potential mitigation of the consequences of landscape change on ecological processes. Land managers and researchers require spatially and thematically consistent land-cover data to assess historical, current, and potential future interactions among land use, climate, and a host of ecologically and societally relevant processes. USGS provides historical and current land cover based on remote sensing databases, but only for a relatively short historical time period. Methodologies are needed to produce both historical and potential future land-cover maps that are consistent with remote sensing-based maps, facilitating long-term assessments of landscape, climate, and ecological interactions.
Why this Research is Important: Urban development, forestry, agriculture, mining, and other land uses can substantially alter the Earth's surface. Land use and the resultant change in land cover have important effects on ecological systems and processes. The use of current land-cover maps enables researchers and land managers to assess recent conditions and respond accordingly, based upon research and land management objectives. However, the availability of long-term historical land cover data and potential future land cover data enables researchers and land managers to move beyond a reactionary approach to an anticipatory approach. Historical records can be used to develop likely relationships between landscape change and the process of interest. That information can be used in conjunction with future scenarios of landscape change to visualize future outcomes and maximize societal, economic, or ecologic priorities, and to potentially mitigate any negative consequences before they even occur.
Objective(s): The objectives of this research are to develop state-of-the-art landscape modeling frameworks and apply them to problems of ecological, economic, and societal importance. We will:
- Continue development of the USGS's "FORE-SCE" model
- Investigate new modeling techniques, including continued improvements in our methodologies for mapping vegetation succession, fire and disturbance, and landscape response to climate change.
- Apply USGS land-cover models to produce spatially explicit, thematically detailed landscape maps / models that are consistent with widely used remote sensing-based land-cover data such as the National Land Cover Database (NLCD) or the Cropland Data Layer (CDL).
- Collaborate with USGS and other researchers on analyses of land-use and land-cover change effects on ecological and societal processes.
Methods: USGS EROS began development of a home-grown land-use and land-cover modeling framework in 2006. Work continues to improve the capabilities of the Forecasting Scenarios of Land-use Change (FORE-SCE) model, a model which has gained acceptance in the scientific literature, and has been applied in the United States to produce both historical "backcasts" and future forecasts of land-use and land-cover change. Our work focuses on the continued development of the FORE-SCE modeling framework, the integration of other modeling frameworks, and the development of new modeling frameworks that improve USGS' ability to map and model land-use and land-cover change.
Remote sensing provides an integral source of data for landscape modeling. Historical and current landscape information is used for scenario construction, model parameterization, and validation of model performance. However, land-cover modeling is inherently an interdisciplinary activity. We rely on elements of socioeconomics, geography, hydrology, climate, and other disciplines to both ensure the production of realistic and useful landscape projections, and in the application of the resultant modeled projections to address issues of societal importance. Because of the high level of uncertainty associated with predicting future developments in complex socio-environmental systems, a scenario framework is used that enables land managers to anticipate and adapt to a wide range of plausible future conditions.
- Science
Below are other science projects associated with this project.
- Publications
Below are publications associated with this project.
Filter Total Items: 18The relative impacts of climate and land-use change on conterminous United States bird species from 2001 to 2075
Species distribution models often use climate data to assess contemporary and/or future ranges for animal or plant species. Land use and land cover (LULC) data are important predictor variables for determining species range, yet are rarely used when modeling future distributions. In this study, maximum entropy modeling was used to construct species distribution maps for 50 North American bird specAuthorsTerry L. SohlDevelopment of a generic auto-calibration package for regional ecological modeling and application in the Central Plains of the United States
Process-oriented ecological models are frequently used for predicting potential impacts of global changes such as climate and land-cover changes, which can be useful for policy making. It is critical but challenging to automatically derive optimal parameter values at different scales, especially at regional scale, and validate the model performance. In this study, we developed an automatic calibraAuthorsYiping Wu, Shuguang Liu, Zhengpeng Li, Devendra Dahal, Claudia J. Young, Gail L. Schmidt, Jinxun Liu, Brian Davis, Terry L. Sohl, Jeremy M. Werner, Jennifer OedingSpatially explicit modeling of 1992-2100 land cover and forest stand age for the conterminous United States
Information on future land-use and land-cover (LULC) change is needed to analyze the impact of LULC change on ecological processes. The U.S. Geological Survey has produced spatially explicit, thematically detailed LULC projections for the conterminous United States. Four qualitative and quantitative scenarios of LULC change were developed, with characteristics consistent with the IntergovernmentalAuthorsTerry L. Sohl, Kristi Sayler, Michelle Bouchard, Ryan R. Reker, Aaron M. Friesz, Stacie L. Bennett, Benjamin M. Sleeter, Rachel R. Sleeter, Tamara S. Wilson, Christopher E. Soulard, Michelle Knuppe, Travis Van HofwegenClarity versus complexity: land-use modeling as a practical tool for decision-makers
The last decade has seen a remarkable increase in the number of modeling tools available to examine future land-use and land-cover (LULC) change. Integrated modeling frameworks, agent-based models, cellular automata approaches, and other modeling techniques have substantially improved the representation of complex LULC systems, with each method using a different strategy to address complexity. HowAuthorsTerry L. Sohl, Peter R. ClaggettLand use and carbon dynamics in the southeastern United States from 1992 to 2050
Land use and land cover change (LUCC) plays an important role in determining the spatial distribution, magnitude, and temporal change of terrestrial carbon sources and sinks. However, the impacts of LUCC are not well understood and quantified over large areas. The goal of this study was to quantify the spatial and temporal patterns of carbon dynamics in various terrestrial ecosystems in the southeAuthorsShuqing Zhao, Shuguang Liu, Terry L. Sohl, Claudia Young, Jeremy M. WernerA land-use and land-cover modeling strategy to support a national assessment of carbon stocks and fluxes
Changes in land use, land cover, disturbance regimes, and land management have considerable influence on carbon and greenhouse gas (GHG) fluxes within ecosystems. Through targeted land-use and land-management activities, ecosystems can be managed to enhance carbon sequestration and mitigate fluxes of other GHGs. National-scale, comprehensive analyses of carbon sequestration potential by ecosystemAuthorsTerry L. Sohl, Benjamin M. Sleeter, Zhi-Liang Zhu, Kristi Sayler, Stacie Bennett, Michelle Bouchard, Ryan R. Reker, Todd Hawbaker, Anne Wein, Shu-Guang Liu, Ronald Kanengieter, William Acevedo