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Terry L. Sohl

Publications and source records attributed to Terry L. Sohl.

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Land-use and land-cover scenarios and spatial modeling at the regional scale

Land-use and land-cover (LULC) change has altered a large part of the earth's surface. Scenarios of potential future LULC change are required in order to better manage potential impacts on biodiversity, carbon fluxes, climate change, hydrology, and many other ecological processes. The U.S. Geological Survey is analyzing potential future LULC change in the United States, using an approach based on scenario construction and spatially explicit modeling. Similar modeling techniques are being used to produce historical LULC maps from 1940 to present. With the combination of backcast and forecast LULC data, the USGS is providing consistent LULC data for historical, current, and future time frames to support a variety of research applications.

Fact Sheet

Future scenarios of land-use and land-cover change in the United States--the Marine West Coast Forests Ecoregion

Detecting, quantifying, and projecting historical and future changes in land use and land cover (LULC) has emerged as a core research area for the U.S. Geological Survey (USGS). Changes in LULC are important drivers of changes to biogeochemical cycles, the exchange of energy between the Earth’s surface and atmosphere, biodiversity, water quality, and climate change. To quantify the rates of recent historical LULC change, the USGS Land Cover Trends project recently completed a unique ecoregion-based assessment of late 20th century LULC change for the western United States. To characterize present LULC, the USGS and partners have created the National Land Cover Database (NLCD) for the years 1992, 2001, and 2006. Both Land Cover Trends and NLCD projects continue to evolve in an effort to better characterize historical and present LULC conditions and are the foundation of the data presented in this report. Projecting future changes in LULC requires an understanding of the rates and patterns of change, the major driving forces, and the socioeconomic and biophysical determinants and capacities of regions. The data presented in this report is the result of an effort by USGS scientists to downscale the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emission Scenarios (SRES) to ecoregions of the conterminous United States as part of the USGS Biological Carbon Sequestration Assessment. The USGS biological carbon assessment was mandated by Section 712 of the Energy Independence and Security Act of 2007. As part of the legislative mandate, the USGS is required to publish a methodology describing, in detail, the approach to be used for the assessment. The development of future LULC scenarios is described in chapter 3.2 and appendix A. Spatial modeling is described in chapter 3.3.2 and appendix B and in Sohl and others (2011). In this report, we briefly summarize the major components and methods used to downscale IPCC-SRES scenarios to ecoregions of the conterminous United States, followed by a description of the Marine West Coast Forests Ecoregion, and lastly a description of the data being published as part of this report.

California;Oregon;Washington

Coast Range Ecoregion: Chapter 1 in Status and trends of land change in the Western United States--1973 to 2000

The Coast Range Ecoregion, which covers approximately 57,338 km 2 (22,138 mi 2 ), is a thin, linear ecoregion along the Pacific Coast, stretching roughly 1,300 km from the Olympic Peninsula, in northwest Washington, to an area south of San Francisco, California (fig. 1) (Omernik, 1987; U.S. Environmental Protection Agency, 1997). It is bounded on the east by the Puget Lowland, the Willamette Valley, the Klamath Mountains, and the Southern and Central California Chaparral and Oak Woodlands Ecoregions. Almost the entire Coast Range Ecoregion lies within 100 km of the coast. Topography is highly variable, with coastal mountain ranges and valleys ranging from sea level to over 1,000 m in elevation (fig. 2). A maritime climate, along with high topographic relief, results in substantial, but regionally variable, amounts of rainfall, ranging from 130 cm to more than 350 cm per year. The favorable climate of the Coast Range Ecoregion has supported forests of Sitka spruce ( Picea sitchensis ) along its northern coast and coast redwoods ( Sequoia sempervirens ) along its southern coast, as well as Douglas-fir ( Pseudotsuga menziesii ), western red cedar ( Thuja plicata ), and western hemlock ( Tsuga heterophylla ) inland (Omernik, 1987). Today, however, much of the forest is heavily managed for logging (fig. 3), although the ecoregion still supports some of the largest remaining areas of old-growth forest in the Pacific Northwest. Agriculture is a minor component of the landscape, present locally in flat lands and valleys near the coast. Urban development is minimal; Eureka, California, is the only urban center in the ecoregion, with a population of over 26,000 (U.S. Census Bureau, 2000).

California;Oregon;Washington

Federal land management, carbon sequestration, and climate change in the Southeastern U.S.: a case study with fort benning

Land use activities can have a major impact on the temporal trendsandspatialpatternsofregionalland-atmosphereexchange of carbon. Federal lands generally have substantially different land management strategies from surrounding areas, and the carbon consequences have rarely been quantified and assessed. Using the Fort Benning Installation as a case study, we used the General Ensemble biogeochemical Modeling System (GEMS) to simulate and compare ecosystem carbon sequestration between the U.S. Army's Fort Benning and surrounding areas from 1992 to 2050. Our results indicate that the military installation sequestered more carbon than surrounding areas from 1992 to 2007 (76.7 vs 18.5 g C m -2 yr -1 ), and is projected to continue sequestering more carbon from 2008 to 2050 (75.7 vs 25.6 g C m -2 yr -1 ), mostly because of the proactive management approaches adopted on military training lands. Our results suggest that federal lands might play a positive and important role in sequestering and conserving atmospheric carbon because some anthropogenic disturbances (e.g., urbanization, forest harvesting, and agriculture) can be minimized or prevented on federal lands

Georgia

Addressing foundational elements of regional land-use change forecasting

Regional land-use models must address several foundational elements, including understanding geographic setting, establishing regional land-use histories, modeling process and representing drivers of change, representing local land-use patterns, managing issues of scale and complexity, and development of scenarios. Key difficulties include managing an array of biophysical and socioeconomic processes across multiple spatial and temporal scales, and acquiring and utilizing empirical data to support the analysis of those processes. The Southeastern and Pacific Northwest regions of the United States, two heavily forested regions with significant forest industries, are examined in the context of these foundational elements. Geographic setting fundamentally affects both the primary land cover (forest) in the two regions, and the structure and form of land use (forestry). Land-use histories of the regions can be used to parameterize land-use models, validate model performance, and explore land-use scenarios. Drivers of change in the two regions are many and varied, with issues of scale and complexity posing significant challenges. Careful scenario development can be used to simplify process-based land-use models, and can improve our ability to address specific research questions. The successful modeling of land-use change in these two areas requires integration of both top-down and bottom-up drivers of change, using scenario frameworks to both guide and simplify the modeling process. Modular approaches, with utilization and integration of existing process models, allow regional land-use modelers the opportunity to better represent primary drivers of land-use change. However, availability of data to represent driving forces remains a primary obstacle.

Landscape Ecology

The FORE-SCE model: a practical approach for projecting land cover change using scenario-based modeling

A wide variety of ecological applications require spatially explicit, historic, current, and projected land use and land cover data. The U.S. Land Cover Trends project is analyzing contemporary (1973–2000) land-cover change in the conterminous United States. The newly developed FORE-SCE model used Land Cover Trends data and theoretical, statistical, and deterministic modeling techniques to project future land cover change through 2020 for multiple plausible scenarios. Projected proportions of future land use were initially developed, and then sited on the lands with the highest potential for supporting that land use and land cover using a statistically based stochastic allocation procedure. Three scenarios of 2020 land cover were mapped for the western Great Plains in the US. The model provided realistic, high-resolution, scenario-based land-cover products suitable for multiple applications, including studies of climate and weather variability, carbon dynamics, and regional hydrology.

Journal of Land Use Science

The characteristics and interpretability of land surface change and implications for project design

The need for comprehensive, accurate information on land-cover change has never been greater. While remotely sensed imagery affords the opportunity to provide information on land-cover change over large geographic expanses at a relatively low cost, the characteristics of land-surface change bring into question the suitability of many commonly used methodologies. Algorithm-based methodologies to detect change generally cannot provide the same level of accuracy as the analyses done by human interpreters. Results from the Land Cover Trends project, a cooperative venture that includes the U.S. Geological Survey, Environmental Protection Agency, and National Aeronautics and Space Administration, have shown that land-cover conversion is a relatively rare event, occurs locally in small patches, varies geographically and temporally, and is spectrally ambiguous. Based on these characteristics of change and the type of information required, manual interpretation was selected as the primary means of detecting change in the Land Cover Trends project. Mixtures of algorithm-based detection and manual interpretation may often prove to be the most feasible and appropriate design for change-detection applications. Serious examination of the expected characteristics and measurability of change must be considered during the design and implementation phase of any change analysis project.

Photogrammetric Engineering and Remote Sensing

Statistical sampling to characterize recent United States land-cover change

The U.S. Geological Survey, in conjunction with the U.S. Environmental Protection Agency, is conducting a study focused on developing methods for estimating changes in land-cover and landscape pattern for the conterminous United States from 1973 to 2000. Eleven land-cover and land-use classes are interpreted from Landsat imagery for five sampling dates. Because of the high cost and potential effect of classification error associated with developing change estimates from wall-to-wall land-cover maps, a probability sampling approach is employed. The basic sampling unit is a 20 x 20 km area, and land cover is obtained for each 60 x 60 m pixel within the sampling unit. The sampling design is stratified based on ecoregions, and land-cover change estimates are constructed for each stratum. The sampling design and analyses are documented, and estimates of change accompanied by standard errors are presented to demonstrate the methodology. Analyses of the completed strata suggest that the sampling unit should be reduced to a 10 x 10 km block, and poststratified estimation and regression estimation are viable options to improve precision of estimated change. ?? 2003 Elsevier Inc. All rights reserved.

Remote Sensing of Environment

Land use and land cover change in the North Central Appalachians ecoregion

The North Central Appalachians ecoregion, spanning northern Pennsylvania and southern New York, has a long history of land use and land cover change. Turn-of-the-century logging dramatically altered the natural landscape of the ecoregion, but subsequent regeneration returned the ecoregion to a forest dominated condition. To understand contemporary land use and land cover changes, the U.S. Geological Survey with NASA and the U.S. Environmental Protection Agency used a random sample of satellite remotely sensed data for 1973, 1980, 1986, 1992, and 2000 to estimate the rates and assess the primary drivers of change in the North Central Appalachians. The overall change was 6.2%. The 1973-1980 period had the lowest rate of change (1.5%); the highest rate (2.9%) occurred during the 1992-2000 period. The primary conversions were deforestation through harvesting and natural disturbance (i.e., tornados) followed by regeneration, and conversion of forests to mining and urban lands. The primary drivers of the change included changes in access, energy and forest prices, and attitudes toward the environment.

Pennsylvania Geographer

A strategy for estimating the rates of recent United States land-cover changes

Information on the rates of land-use and land-cover change is important in addressing issues ranging from the health of aquatic resources to climate change. Unfortunately, there is a paucity of information on land-use and land-cover change except at very local levels. We describe a strategy for estimating land-cover change across the conterminous United States over the past 30 years. Change rates are estimated for 84 ecoregions using a sampling procedure and five dates of Landsat imagery. We have applied this methodology to six eastern U.S. ecoregions. Results show very high rates of change in the Plains ecoregions, high to moderate rates in the Piedmont ecoregions, and moderate to low rates in the Appalachian ecoregions. This indicates that ecoregions are appropriate strata for capturing unique patterns of land-cover change. The results of the study are being applied as we undertake the mapping of the rest of the conterminous United States.

Photogrammetric Engineering and Remote Sensing

The land cover trends project: A strategy for monitoring land cover change at a national scale

Policy-makers and scientists often require comprehensive data on the types and rates of land use and land cover change at a variety of scales. However, there is generally a lack of local, regional, and national land use and land cover data of sufficient reliability and temporal and geographic detail for providing accurate estimates of landscape change. The U.S. Geological Survey's EROS Data Center and the Landscape Ecology Branch of the U.S. Environmental Protection Agency are collaborating on a four-year research project to document the types, distributions, rates, drivers, and consequences of land cover change for the conterminous United States over the past 30 years. The project is using an ecoregion framework as a geographic stratifier. Both regional and national characteristics of change are determined by sampling land cover change for each of 84 ecoregions using five selected epochs of data from the nearly 30-year record of Landsat 1-7 data. Three types of land cover variables are being mapped or derived: (1) general land cover type; (2) landscape biophysical properties; and (3) landscape pattern. Assessments of the drivers and consequences of change within each ecoregion are then prepared. A pilot phase focusing on the analysis of five selected ecoregions is well underway and will be completed by the end of 2000. Methodologies established during the pilot phase will then be applied to the remaining ecoregions.

Conference Paper

Regional land cover characterization using Landsat thematic mapper data and ancillary data sources

As part of the activities of the Multi-Resolution Land Characteristics (MRLC) Interagency Consortium, an intermediate-scale land cover data set is being generated for the conterminous United States. This effort is being conducted on a region-by-region basis using U.S. Standard Federal Regions. To date, land cover data sets have been generated for Federal Regions 3 (Pennsylvania, West Virginia, Virginia, Maryland, and Delaware) and 2 (New York and New Jersey). Classification work is currently under way in Federal Region 4 (the southeastern United States), and land cover mapping activities have been started in Federal Regions 5 (the Great Lakes region) and 1 (New England). It is anticipated that a land cover data set for the conterminous United States will be completed by the end of 1999. A standard land cover classification legend is used, which is analogous to and compatible with other classification schemes. The primary MRLC regional classification scheme contains 23 land cover classes. The primary source of data for the project is the Landsat thematic mapper (TM) sensor. For each region, TM scenes representing both leaf-on and leaf-off conditions are acquired, preprocessed, and georeferenced to MRLC specifications. Mosaicked data are clustered using unsupervised classification, and individual clusters are labeled using aerial photographs. Individual clusters that represent more than one land cover unit are split using spatial modeling with multiple ancillary spatial data layers (most notably, digital elevation model, population, land use and land cover, and wetlands information). This approach yields regional land cover information suitable for a wide array of applications, including landscape metric analyses, land management, land cover change studies, and nutrient and pesticide runoff modeling.

Environmental Monitoring and Assessment

North American landscape characterization project: The production of a continental scale three-decade Landsat data set

The North American Landscape Characterization (NALC) project is a component of the National Aeronautics and Space Administration (NASA) Landsat Pathfinder program. Pathfinder projects are focused on the investigation of global change utilizing current remote sensing technologies. The NALC project is a cooperative effort between the U. S. Environmental Protection Agency (EPA), the U.S. Geological Survey (USGS), and NASA to make Landsat data available to the widest possible user community for scientific research and general public interest. The NALC project is principally funded by the EPA Office of Research and Development and the USGS's Earth Resources Observation Systems (EROS) Data Center (EDC). The objectives of the NALC project are to produce standardized remote sensing data sets, develop standardized analysis methods, and derive standardized land cover change products for a large portion of the North American continent (the conterminous United States and Mexico) (Lunetta and Sturdevant, 1993). The standard product is the NALC “triplicate”;, consisting of co‐registered Landsat multispectral scanner data for the years 1973, 1986, and 1991 (plus or minus one year), plus co‐registered 3 arcsecond digital terrain elevation data. Processing began with the 1986 scene, which was precision corrected (with full terrain correction) to a 60 meter Universal Transverse Mercator base. Automated cross‐correlation procedures were used to co‐register the 1970's and 1990's data to the 1980's base, and independent verifications of registration quality were performed on all triplicate components. The pertinent metadata were compiled in a relational database, which includes WRS2 path/rows, scene ID's, image dates, solar azimuth and elevation, verification RMSE's, and the number of verification control points. NALC triplicate data sets are being used for a number of applications, including the analysis of urbanization patterns, dynamics of climatic fluctuations, deforestation studies, and vegetation classification and mapping. These data are being distributed through the Earth Observing System Data and Information System (EOSDIS) Information Management System (IMS) at a cost of $15(U.S.) for each triplicate.

Geocarto International

Regional characterization of land cover using multiple sources of data

Many organizations require accurate intermediate-scale land-cover information for many applications, including modeling nutrient and pesticide runoff, understanding spatial patterns of biodiversity, land-use planning, and policy development. While many techniques have been successfully used to classify land cover in relatively small regions, there are substantial obstacles in applying these methods to large, multiscene regions. The purpose of this study was to generate and evaluate a large region land-cover classification product using a multiple-layer land-characteristics database approach. To derive land-cover information, mosaicked Landsat thematic mapper (TM) scenes were analyzed in conjunction with digital elevation data (and derived slope, aspect, and shaded relief), population census information, Defense Meteorological Satellite Program city lights data, prior land-use and land-cover data, digital line graph data, and National Wetlands Inventory data. Both leaf-on and leaf-off TM data sets were analyzed. The study area was U.S. Federal Region III, which includes the states of Pennsylvania, Virginia, Maryland, Delaware, and West Virginia. The general procedure involved (1) generating mosaics of multiple scenes of leaves-on TM data using histogram equalization methods; (2) clustering mosaics into 100 spectral classes using unsupervised classification; (3) interpreting and labeling spectral classes into approximately 15 land-cover categories (analogous to Anderson Level 1 and 2 classes) using aerial photographs; (4) developing decision-making rules and models using from one to several ancillary data layers to resolve confusion in spectral classes that represented two or more targeted land-cover categories; and (5) incorporating data from other sources (for example, leaf-off TM data and National Wetlands Inventory data) to yield a final land-cover product. Although standard accuracy assessments were not done, a series of consistency checks using available sources of land-cover information were conducted to evaluate the effectiveness of this approach for generating accurate land-cover information for large regions.

Photogrammetric Engineering and Remote Sensing

Regional land cover characterization using multiple sources of intermediate-scale data

Many United States federal agencies need accurate, intermediate scaled, land cover information. While many techniques and approaches have been successfully used to classify land cover in relatively small regions, there are substantial problems in applying these techniques to large multi-scene regions. An evaluation was conducted of the multiple layer land characteristics data base approach for generating large area land cover information. Mosaicked leaves-on Landsat thematic mapper scenes were used in conjunction with leaves-off thematic mapper data, digital elevation (and derived slope, aspect and shaded relief) data, population census information, defense meteorological satellite program "city lights" data, land use and land cover data, digital line graph data, and national wetlands inventory data to derive land cover information. This approach was evaluated for Region III of the United States Environmental Protection Agency (middle Atlantic states).

Conference Paper