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At least 73 records · Page 4Linked to original sources

Effects of contemporary land-use and land-cover change on the carbon balance of terrestrial ecosystems in the United States

Changes in land use and land cover (LULC) can have profound effects on terrestrial carbon dynamics, yet their effects on the global carbon budget remain uncertain. While land change impacts on ecosystem carbon dynamics have been the focus of numerous studies, few efforts have been based on observational data incorporating multiple ecosystem types spanning large geographic areas over long time horizons. In this study we use a variety of synoptic-scale remote sensing data to estimate the effect of LULC changes associated with urbanization, agricultural expansion and contraction, forest harvest, and wildfire on the carbon balance of terrestrial ecosystems (forest, grasslands, shrublands, and agriculture) in the conterminous United States (i.e. excluding Alaska and Hawaii) between 1973 and 2010. We estimate large net declines in the area of agriculture and forest, along with relatively small increases in grasslands and shrublands. The largest net change in any class was an estimated gain of 114 865 km 2 of developed lands, an average rate of 3282 km 2 yr −1 . On average, US ecosystems sequestered carbon at an annual rate of 254 Tg C yr −1 . In forest lands, the net sink declined by 35% over the study period, largely a result of land-use legacy, increasing disturbances, and reductions in forest area due to land use conversion. Uncertainty in LULC change data contributed to a ~16% margin of error in the annual carbon sink estimate prior to 1985 (approximately ±40 Tg C yr −1 ). Improvements in LULC and disturbance mapping starting in the mid-1980s reduced this uncertainty by ~50% after 1985. We conclude that changes in LULC are a critical component to understanding ecosystem carbon dynamics, and continued improvements in detection, quantification, and attribution of change have the potential to significantly reduce current uncertainties.

Environmental Research Letters

Global modeling of land water and energy balances. Part II: Land-characteristic contributions to spatial variability

Land water and energy balances vary around the globe because of variations in amount and temporal distribution of water and energy supplies and because of variations in land characteristics. The former control (water and energy supplies) explains much more variance in water and energy balances than the latter (land characteristics). A largely untested hypothesis underlying most global models of land water and energy balance is the assumption that parameter values based on estimated geographic distributions of soil and vegetation characteristics improve the performance of the models relative to the use of globally constant land parameters. This hypothesis is tested here through an evaluation of the improvement in performance of one land model associated with the introduction of geographic information on land characteristics. The capability of the model to reproduce annual runoff ratios of large river basins, with and without information on the global distribution of albedo, rooting depth, and stomatal resistance, is assessed. To allow a fair comparison, the model is calibrated in both cases by adjusting globally constant scale factors for snow-free albedo, non-water-stressed bulk stomatal resistance, and critical root density (which is used to determine effective root-zone depth). The test is made in stand-alone mode, that is, using prescribed radiative and atmospheric forcing. Model performance is evaluated by comparing modeled runoff ratios with observed runoff ratios for a set of basins where precipitation biases have been shown to be minimal. The withholding of information on global variations in these parameters leads to a significant degradation of the capability of the model to simulate the annual runoff ratio. An additional set of optimization experiments, in which the parameters are examined individually, reveals that the stomatal resistance is, by far, the parameter among these three whose spatial variations add the most predictive power to the model in stand-alone mode. Further single-parameter experiments with surface roughness length, available water capacity, thermal conductivity, and thermal diffusivity show very little sensitivity to estimated global variations in these parameters. Finally, it is found that even the constant-parameter model performance exceeds that of the Budyko and generalized Turc-Pike water-balance equations, suggesting that the model benefits also from information on the geographic variability of the temporal structure of forcing.

Journal of Hydrometeorology

The USGS Abandoned Mine Lands Initiative: Protecting and restoring the environment near abandoned mine lands

The Abandoned Mine Lands (AML) Initiative is part of a larger strategy of the U.S. Department of the Interior and the U.S. Department of Agriculture to clean up Federal lands contaminated by abandoned mines. Thousands of abandond hard-rock metal mines (such as gold, copper, lead, and zinc) have left a dual legacy across the Western United States. They reflect the historic development of the west, yet at the same time represent a possible threat to human health and local ecosystems. Abandoned Mine Lands (AML) are areas adjacent to or affected by abandoned mines. AML's often contain unmined mineral deposits, mine dumps (the ore and rock removed to get to the ore deposits), and tailings (the material left over from the ore processing) that contaminate the surrounding watershed and ecosystem. For example, streams near AML's can contain metals and (or) be so acidic that fish and aquatic insects cannot live in them. Many of these abandoned hard-rock mines are located on or adjacent to public lands administered by the Bureau of Land Management, National Park Service, and U.S. Forest Service. These federal land management agencies and the USGS are committed to mitigating the adverse effects that AML's can have on water quality and stream habitats. The USGS AML Initiative began in 1997 and will continue through 2001 in two pilot watersheds - the Boulder River basin in southwestern Montana and the upper Animas River basin in southwestern Colorado. The USGS is providing a wide range of scientific expertise to help land managers minimize and, where possible, eliminate the adverse environmental effects of AML's. USGS ecologists, geologists, water quality experts, hydrologists, geochemists, and mapping and digital data collection experts are collaborating to provide the scientific knowledge needed for an effective cleanup of AML's.

Arizona, California, Colorado, Idaho, Montana, New

Lake Michigan Diversion Accounting land cover change estimation by use of the National Land Cover Dataset and raingage network partitioning analysis

The U.S. Army Corps of Engineers (USACE), Chicago District, is responsible for monitoring and computation of the quantity of Lake Michigan water diverted by the State of Illinois. As part of this effort, the USACE uses the Hydrological Simulation Program–FORTRAN (HSPF) with measured meteorological data inputs to estimate runoff from the Lake Michigan diversion special contributing areas (SCAs), the North Branch Chicago River above Niles and the Little Calumet River above South Holland gaged basins, and the Lower Des Plaines and the Calumet ungaged that historically drained to Lake Michigan. These simulated runoffs are used for estimating the total runoff component from the diverted Lake Michigan watershed, which is accountable to the total diversion by the State of Illinois. The runoff is simulated from three interpreted land cover types in the HSPF models: impervious, grass, and forest. The three land cover data types currently in use were derived from aerial photographs acquired in the early 1990s. This study used the National Land Cover Dataset (NLCD) and developed an automated process for determining the area of the three land cover types, thereby allowing faster updating of future models, and for evaluating land cover changes by use of historical NLCD datasets. The study also carried out a raingage partitioning analysis so that the segmentation of land cover and rainfall in each modeled unit is directly applicable to the HSPF modeling. Historical and existing impervious, grass, and forest land acreages partitioned by percentages covered by two sets of raingages for the Lake Michigan diversion SCAs, gaged basins, and ungaged basins are presented.

Illinois

Land-cover sampling designs, data-collection procedures, and land-cover data for the Central Nebraska Basins, 1993-94

Within the U.S. Geological Survey's National Water-Quality Assessment (NAWQA) Program, land-cover data are used in characterizing drainage areas upstream from surface-water sampling sites and areas selected for spatially distributed ground-water sampling. During the period of time when the initial 20 NAWQA study study-unit investigations were evaluating existing land-cover data, a Prototype 190 Conterminous U.S. land Cover Characteristics Data Set was produced by the Survey's EROS Data Center in Sioux Falls, South Dakota. As part of the Central Nebraska Basins (CNB) study-unit investigation, a method was developed to estimate the areal extent of the principal land-cover types within selected seasonally distinct land-cover (SDLC) regions defined in the 1990 prototype data set. This report describes the sampling designs and methods used to collect land-cover data in the CNB study unit. Data collected at 309 sampling sites during the summers of 1993 and 1994 are presented and statistically summarized. Eleven land-cover categories were quantified, including major field crops and broad noncropland cover types.

Open-File Report

Digital elevation data as an aid to land use and land cover classification

Elevation data is generally associated with topographic maps and expressed by contours and spot elevations. However, elevation data is also essential to the proper classification of land use and land cover by remote sensing techniques. Absolute elevation governs various types of vegetative growth as does the degree and direction of slope. However, the effect of terrain aspect (slope and direction) on reflectance is of even greater significance. The angular relationship of a surface to the sun can significantly effect the radiometric response. For flat areas this effect is contract but she slopes are involved they must be considered if automated classification is to be applied. To overcome the terrain aspect effect, rating of multi-spectral responses is used in an attempt to eliminate the terrain aspect. However, this is only partially effective and when the terrain aspect controls group cover it is of little or no value. The proper solution to the aspect problem is to obtain and utilize suitable digital elevation data in conjunction with remote sensor response. The relationship of the aspect to the response can be developed by theory of empirical test and when properly applied can neutralize the aspect response. Then the classification of land use and land cover can proceed without the unwanted radiometric anomalies of terrain aspect. In relatively well mapped areas such as the United States and Europe, digital data can be developed from topographic maps or from the stereo aerial photographic movie. For poorer mapped areas (which involved most of the world's land areas), a satellite designed to obtain stereo data offers the best hope for a digital elevation database. Such a satellite, known as Mapsat, has been defined by the U.S. Geological Survey. Utilizing modern solid state technology, there is no reason why such stereo data cannot be acquired simultaneously with the multispectral response, thus simplifying the overall problem of land use and land cover classification.

Pecora VII Symposium

Inventory of land use and land cover of the Puget Sound region using Landsat digital data

Landsat multispectral scanner digital data from four bands were analyzed using computers to produce land use and land cover information of the Puget Sound region, Wash., for use by agencies in that area. The data were first geographically registered to map coordinates. This registration enabled samples of known land cover types to be digitized from the maps. Samples of the same land cover were grouped together and then subdivided by cluster analysis into spectrally similar classes. Spectral categories were associated with specific land cover classes and used to determine spectral signatures for classification of the entire region. Reclustering and reclassification techniques were developed and then employed to minimize certain classification errors. The classified data were displayed in color using a film recorder. This color image was enlarged photographically to a 1:100000 scale to match new base maps of the region. Although the result resembles a conventional polygonal land use and land cover map, certain image-like qualities remain and yield additional information about the landscape.

Washington