USGS Science⌕ Search

SEARCH · USGS Science

Results for “Land Use and Land Cover”

Search indexed USGS publications on groundwater, aquifers, geologic maps, mineral resources and earthquakes. Explore source records by subject and place.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,009 records · Page 56Linked to original sources
USGS2025

Multiscale framework for assessing land cover change on barrier islands from extreme storms and restoration

Often found along the estuarine-marine interface, barrier islands and mainland coastal zones are shaped by tides, currents, extreme storms, and relative sea-level rise. These systems provide ecosystem services such as storm surge and wave attenuation, erosion protection to inland areas, habitat for fish and wildlife, recreation, and tourism. Given the importance of these ecosystems coupled with their dynamic nature, information on how these coastal systems are changing can help to inform natural resource management. Remote sensing advancements have led to an abundance of data for monitoring change in coastal settings. This study developed a multiscale framework that can provide trajectory information from screening-level analyses by using existing or custom moderate spatial resolution land cover maps. Using the north-central Gulf Coast as a case study, the trajectory of land cover area for barrier islands and mainland coastal zones was assessed using several geospatial data sets, including: (1) long-term moderate-resolution remote sensing products with an annual (or more frequent) temporal frequency; (2) a restoration database ( e.g. , beach/dune restoration, sediment placement, and dune enhancement); and (3) a tropical storm database. Due to the coarser spatial resolution of data sets used for screening-level analyses, detailed or application-specific analyses are often needed to reduce uncertainty in smaller changes that may not be captured. These may include land cover change analyses ( i.e. this study), periodic land cover maps with higher spatial resolution and more detailed land cover classes, or elevation-related analyses ( e.g. , dune change or inundation change). Using this framework, abrupt changes in land cover on Dauphin Island, Alabama, resulting from extreme storms were detected using moderate spatial resolution screening-level data, while restoration impact analyses may require higher resolution data. Further, land cover change analyses that incorporate change allocation provide robust information for understanding land cover change in dynamic coastal settings.

Alabama, Florida↗
USGS2015

The Southern Piedmont’s continued land-use evolution, 1973–2011

The southern Piedmont in the U.S. was an important farming region during the 19 th century, but by the end of the 20th century, agricultural land use had decreased substantially with forest becoming the majority land cover by the 1970s. Geographical literature has documented this change but has not concentrated on the region’s contemporary land uses. The Piedmont currently has three main types of land use and land cover changes: cyclic forestry, changes between forest and agriculture, and urbanization. The first and second groupings are reversible and land uses and land covers can change among them, but urbanization is normally a permanent change that increases in area through time. U.S. Geological Survey findings indicate that cyclic forestry of cutting (clearing) and regrowth dominated recent land change in the Piedmont. This paper explores the Piedmont’s current land uses and some of their driving forces.

Alabama, Georgia, North Carolina, South Carolina, ↗
USGS2019

Landsat: The cornerstone of global land imaging

Since 1972, the joint NASA/ U.S. Geological Survey Landsat series of Earth Observation satellites have provided an uninterrupted space-based data record of the Earth’s land surface to help advance scientific research towards the understanding of our planet and the environmental impact of its inhabitants. Early Landsat satellites offered a wealth of new data that improved mapping of remote areas and geologic features along with digital analysis of vegetation. The utility of Landsat’s spatial and spectral resolution has advanced its use for applications that benefit society such as global crop forecasting, forest monitoring, water use, carbon assessments, and the base for Google Maps. Landsat’s long-term data record provides an unrivaled resource for observing land cover and land-use change over a timescale of decades. The free and open Landsat data policy in 2008 was a paradigm shift for the world. Today, due to improved analytical and computing capabilities, the Landsat archive is poised to shift into a more real-time monitoring and understanding of the Earth.

GIM International↗
USGS2018

Density of American black bears in New Mexico

Considering advances in noninvasive genetic sampling and spatially explicit capture–recapture (SECR) models, the New Mexico Department of Game and Fish sought to update their density estimates for American black bear ( Ursus americanus ) populations in New Mexico, USA, to aide in setting sustainable harvest limits. We estimated black bear density in the Sangre de Cristo, Sandia, and Sacramento Mountains, New Mexico, 2012–2014. We collected hair samples from black bears using hair traps and bear rubs and used a sex marker and a suite of microsatellite loci to individually genotype hair samples. We then estimated density in a SECR framework using sex, elevation, land cover type, and time to model heterogeneity in detection probability and the spatial scale over which detection probability declines. We sampled the populations using 554 hair traps and 117 bear rubs and collected 4,083 hair samples. We identified 725 (367 male, 358 female) individuals. Our density estimates varied from 16.5 bears/100 km 2 (95% CI = 11.6–23.5) in the southern Sacramento Mountains to 25.7 bears/100 km 2 (95% CI = 13.2–50.1) in the Sandia Mountains. Overall, detection probability at the activity center (g0) was low across all study areas and ranged from 0.00001 to 0.02. The low values of g0 were primarily a result of half of all hair samples for which genotypes were attempted failing to produce a complete genotype. We speculate that the low success we had genotyping hair samples was due to exceedingly high levels of ultraviolet (UV) radiation that degraded the DNA in the hair. Despite sampling difficulties, we were able to produce density estimates with levels of precision comparable to those estimated for black bears elsewhere in the United States.

New Mexico↗
USGS2010

Predictors of occurrence of the aquatic macrophyte Podostemum ceratophyllum in a southern Appalachian River

The aquatic macrophyte Podostemum ceratophyllum (Hornleaf Riverweed) commonly provides habitat for invertebrates and fishes in flowing-water portions of Piedmont and Appalachian streams in the eastern US. We quantified variation in percent cover by P. ceratophyllum in a 39-km reach of the Conasauga River, TN and GA, to test the hypothesis that cover decreased with increasing non-forest land use. We estimated percent P. ceratophyllum cover in quadrats (0.09 m 2 ) placed at random coordinates within 20 randomly selected shoals. We then used hierarchical logistic regression, in an information-theoretic framework, to evaluate relative support for models incorporating alternative combinations of microhabitat and shoal-level variables to predict the occurrence of high (≥50%) P. ceratophyllum cover. As expected, bed sediment size and measures of light availability (location in the center of the channel, canopy cover) were included in best-supported models and had similar estimated-effect sizes across models. Podostemum ceratophyllum cover declined with increasing watershed size (included in 8 of 13 models in the confidence set of models); however, this decrease in cover was not well predicted by variation in land use. Focused monitoring of temporal and spatial trends in status of P. ceratophyllum are important due to its biotic importance in fast-flowing waters and its potential sensitivity to landscape-level changes, such as declines in forested land cover and homogenization of benthic habitats.

Southeastern Naturalist↗
USGS2003

Raster dataset showing the probability of elevated concentrations of nitrate in ground water in Colorado, hydrogeomorphic regions and fertilizer use estimates included

This dataset is one of eight datasets produced by this study. Four of the datasets predict the probability of detecting atrazine and(or) desethyl-atrazine (a breakdown product of atrazine) in ground water in Colorado; the other four predict the probability of detecting elevated concentrations of nitrate in ground water in Colorado. The four datasets that predict the probability of atrazine and(or) desethyl-atrazine (atrazine/DEA) are differentiated by whether or not they incorporated atrazine use and whether or not they incorporated hydrogeomorphic regions. The four datasets that predict the probability of elevated concentrations of nitrate are differentiated by whether or not they incorporated fertilizer use and whether or not they incorporated hydrogeomorphic regions. Each of the eight datasets has its own unique strengths and weaknesses. The user is cautioned to read Rupert (2003, Probability of detecting atrazine/desethyl-atrazine and elevated concentrations of nitrate in ground water in Colorado: U.S. Geological Survey Water-Resources Investigations Report 02-4269, 35 p., http://water.usgs.gov/pubs/wri/wri02-4269/) to determine if he(she) is using the most appropriate dataset for his(her) particular needs. This dataset specifically predicts the probability of detecting elevated concentrations of nitrate in ground water in Colorado with hydrogeomorphic regions and fertilizer use included. The following text was extracted from Rupert (2003). Draft Federal regulations may require that each State develop a State Pesticide Management Plan for the herbicides atrazine, alachlor, metolachlor, and simazine. Maps were developed that the State of Colorado could use to predict the probability of detecting atrazine/DEA in ground water in Colorado. These maps can be incorporated into the State Pesticide Management Plan and can help provide a sound hydrogeologic basis for atrazine management in Colorado. Maps showing the probability of detecting elevated nitrite plus nitrate as nitrogen (nitrate) concentrations in ground water in Colorado also were developed because nitrate is a contaminant of concern in many areas of Colorado. Maps showing the probability of detecting atrazine/DEA at or greater than concentrations of 0.1 microgram per liter and nitrate concentrations in ground water greater than 5 milligrams per liter were developed as follows: (1) Ground-water quality data were overlaid with anthropogenic and hydrogeologic data by using a geographic information system (GIS) to produce a dataset in which each well had corresponding data on atrazine use, fertilizer use, geology, hydrogeomorphic regions, land cover, precipitation, soils, and well construction. These data then were downloaded to a statistical software package for analysis by logistic regression. (2) Relations were observed between ground-water quality and the percentage of land-cover categories within circular regions (buffers) around wells. Several buffer sizes were evaluated; the buffer size that provided the strongest relation was selected for use in the logistic regression models. (3) Relations between concentrations of atrazine/DEA and nitrate in ground water and atrazine use, fertilizer use, geology, hydrogeomorphic regions, land cover, precipitation, soils, and well-construction data were evaluated, and several preliminary multivariate models with various combinations of independent variables were constructed. (4) The multivariate models that best predicted the presence of atrazine/DEA and elevated concentrations of nitrate in ground water were selected. (5) The accuracy of the multivariate models was confirmed by validating the models with an independent set of ground-water quality data. (6) The multivariate models were entered into a geographic information system and the probability GRIDS were constructed.

Open-File Report↗
USGS2003

Probability of detecting atrazine/desethyl-atrazine and elevated concentrations of nitrate in ground water in Colorado

Draft Federal regulations may require that each State develop a State Pesticide Management Plan for the herbicides atrazine, alachlor, metolachlor, and simazine. Maps were developed that the State of Colorado could use to predict the probability of detecting atrazine and desethyl-atrazine (a breakdown product of atrazine) in ground water in Colorado. These maps can be incorporated into the State Pesticide Management Plan and can help provide a sound hydrogeologic basis for atrazine management in Colorado. Maps showing the probability of detecting elevated nitrite plus nitrate as nitrogen (nitrate) concentrations in ground water in Colorado also were developed because nitrate is a contaminant of concern in many areas of Colorado. Maps showing the probability of detecting atrazine and(or) desethyl-atrazine (atrazine/DEA) at or greater than concentrations of 0.1 microgram per liter and nitrate concentrations in ground water greater than 5 milligrams per liter were developed as follows: (1) Ground-water quality data were overlaid with anthropogenic and hydrogeologic data using a geographic information system to produce a data set in which each well had corresponding data on atrazine use, fertilizer use, geology, hydrogeomorphic regions, land cover, precipitation, soils, and well construction. These data then were downloaded to a statistical software package for analysis by logistic regression. (2) Relations were observed between ground-water quality and the percentage of land-cover categories within circular regions (buffers) around wells. Several buffer sizes were evaluated; the buffer size that provided the strongest relation was selected for use in the logistic regression models. (3) Relations between concentrations of atrazine/DEA and nitrate in ground water and atrazine use, fertilizer use, geology, hydrogeomorphic regions, land cover, precipitation, soils, and well-construction data were evaluated, and several preliminary multivariate models with various combinations of independent variables were constructed. (4) The multivariate models that best predicted the presence of atrazine/DEA and elevated concentrations of nitrate in ground water were selected. (5) The accuracy of the multivariate models was confirmed by validating the models with an independent set of ground-water quality data. (6) The multivariate models were entered into a geographic information system and the probability maps were constructed.

Colorado↗
USGS2012

Novel approach for computing photosynthetically active radiation for productivity modeling using remotely sensed images in the Great Plains, United States

Gross primary production (GPP) is a key indicator of ecosystem performance, and helps in many decision-making processes related to environment. We used the Eddy covariancelight use efficiency (EC-LUE) model for estimating GPP in the Great Plains, United States in order to evaluate the performance of this model. We developed a novel algorithm for computing the photosynthetically active radiation (PAR) based on net radiation. A strong correlation ( R 2 =0.94, N =24) was found between daily PAR and Landsat-based mid-day instantaneous net radiation. Though the Moderate Resolution Spectroradiometer (MODIS) based instantaneous net radiation was in better agreement ( R 2 =0.98, N =24) with the daily measured PAR, there was no statistical significant difference between Landsat based PAR and MODIS based PAR. The EC-LUE model validation also confirms the need to consider biological attributes (C 3 versus C 4 plants) for potential light use efficiency. A universal potential light use efficiency is unable to capture the spatial variation of GPP. It is necessary to use C 3 versus C 4 based land use/land cover map for using EC-LUE model for estimating spatiotemporal distribution of GPP.

Journal of Applied Remote Sensing↗
USGS2017

Simulations of hydrologic response in the Apalachicola-Chattahoochee-Flint River Basin, Southeastern United States

A suite of hydrologic models has been developed for the Apalachicola-Chattahoochee-Flint River Basin (ACFB) as part of the National Water Census, a U.S. Geological Survey research program that focuses on developing new water accounting tools and assessing water availability and use at the regional and national scales. Seven hydrologic models were developed using the Precipitation-Runoff Modeling System (PRMS), a deterministic, distributed-parameter, process-based system that simulates the effects of precipitation, temperature, land cover, and water use on basin hydrology. A coarse-resolution PRMS model was developed for the entire ACFB, and six fine-resolution PRMS models were developed for six subbasins of the ACFB. The coarse-resolution model was loosely coupled with a groundwater model to better assess the effects of water use on streamflow in the lower ACFB, a complex geologic setting with karst features. The PRMS coarse-resolution model was used to provide inputs of recharge to the groundwater model, which in turn provide simulations of groundwater flow that were aggregated with PRMS-based simulations of surface runoff and shallow-subsurface flow. Simulations without the effects of water use were developed for each model for at least the calendar years 1982–2012 with longer periods for the Potato Creek subbasin (1942–2012) and the Spring Creek subbasin (1952–2012). Water-use-affected flows were simulated for 2008–12. Water budget simulations showed heterogeneous distributions of precipitation, actual evapotranspiration, recharge, runoff, and storage change across the ACFB. Streamflow volume differences between no-water-use and water-use simulations were largest along the main stem of the Apalachicola and Chattahoochee River Basins, with streamflow percentage differences largest in the upper Chattahoochee and Flint River Basins and Spring Creek in the lower Flint River Basin. Water-use information at a shorter time step and a fully coupled simulation in the lower ACFB may further improve water availability estimates and hydrologic simulations in the basin.

Apalachicola-Chattahoochee-Flint River Basin↗
USGS2009

Vegetation classification and distribution mapping report: Mesa Verde National Park

The classification and distribution mapping of the vegetation of Mesa Verde National Park (MEVE) and surrounding environment was achieved through a multi-agency effort between 2004 and 2007. The National Park Service’s Southern Colorado Plateau Network facilitated the team that conducted the work, which comprised the U.S. Geological Survey’s Southwest Biological Science Center, Fort Collins Research Center, and Rocky Mountain Geographic Science Center; Northern Arizona University; Prescott College; and NatureServe. The project team described 47 plant communities for MEVE, 34 of which were described from quantitative classification based on f eld-relevé data collected in 1993 and 2004. The team derived 13 additional plant communities from field observations during the photointerpretation phase of the project. The National Vegetation Classification Standard served as a framework for classifying these plant communities to the alliance and association level. Eleven of the 47 plant communities were classified as “park specials;” that is, plant communities with insufficient data to describe them as new alliances or associations. The project team also developed a spatial vegetation map database representing MEVE, with three different map-class schemas: base, group, and management map classes. The base map classes represent the fi nest level of spatial detail. Initial polygons were developed using Definiens Professional (at the time of our use, this software was called eCognition), assisted by interpretation of 1:12,000 true-color digital orthophoto quarter quadrangles (DOQQs). These polygons (base map classes) were labeled using manual photo interpretation of the DOQQs and 1:12,000 true-color aerial photography. Field visits verified interpretation concepts. The vegetation map database includes 46 base map classes, which consist of associations, alliances, and park specials classified with quantitative analysis, additional associations and park specials noted during photointerpretation, and non-vegetated land cover, such as infrastructure, land use, and geological land cover. The base map classes consist of 5,007 polygons in the project area. A field-based accuracy assessment of the base map classes showed overall accuracy to be 43.5%. Seven map classes comprise 89.1% of the park vegetated land cover. The group map classes represent aggregations of the base map classes, approximating the group level of the National Vegetation Classification Standard, version 2 (Federal Geographic Data Committee 2007), and reflecting physiognomy and floristics. Terrestrial ecological systems, as described by NatureServe (Comer et al. 2003), were used as the fi rst approximation of the group level. The project team identified 14 group map classes for this project. The overall accuracy of the group map classes was determined using the same accuracy assessment data as for the base map classes. The overall accuracy of the group representation of vegetation was 80.3%. In consultation with park staff , the team developed management map classes, consisting of park-defined groupings of base map classes intended to represent a balance between maintaining required accuracy and providing a focus on vegetation of particular interest or import to park managers. The 23 management map classes had an overall accuracy of 73.3%. While the main products of this project are the vegetation classification and the vegetation map database, a number of ancillary digital geographic information system and database products were also produced that can be used independently or to augment the main products. These products include shapefiles of the locations of field-collected data and relational databases of field-collected data.

Mesa Verde National Park↗
USGS2022

Linkages between land-use change and groundwater management foster long-term resilience of water supply in California

Study Region We created a 270-m coupled model of land-use and groundwater conditions, LUCAS-W[ater], for California’s Central Coast. This groundwater-dependent region is undergoing a dramatic reorganization of groundwater management under California’s 2014 Sustainable Groundwater Management Act (SGMA). Study Focus Understanding land-use and land-cover change supports long-term sustainable water management. Anthropogenic water demand has depleted groundwater aquifers worldwide, while future water shortages will likely affect land-use change, creating system feedbacks. Our novel participatory approach fused changes in land-use and associated water use from county-scale data to local water agencies’ estimates of total sustainable supply, scaling up local hydro-geologic knowledge from heterogeneous aquifers and diverse management approaches to a regional level. We assessed five stakeholder-driven scenarios with the same historic rates of urban and agricultural land-use change, but different water and land-use management, analyzing how management strategies altered both the spatial pattern of development and subsequent water sustainability from 2001 to 2061. New Hydrological Insights for the Region Transformative strategies using demand-side interventions that coupled water availability to land-use more effectively achieved long-term sustainability than adaptive strategies using supply-side interventions to increase water supplies. Limiting water withdrawals within SGMA regulated basins resulted in leakage of development into unregulated basins, increasing groundwater pumping there. Protecting ecosystems, farmlands, and recharge areas from development reduced leakage into undeveloped basins without negatively affecting water sustainability.

California↗
USGS2004

Compilation of Data to Support Development of a Pesticide Management Plan by the Yankton Sioux Tribe, Charles Mix County, South Dakota

The U.S. Environmental Protection Agency is working with the Yankton Sioux Tribe to develop a pesticide management plan to reduce potential for contamination of ground water that may result from the use of registered pesticides. The purpose of this study was to compile technical information to support development of a pesticide management plan by the Yankton Sioux Tribe for the area within the Yankton Sioux Reservation, Charles Mix County, South Dakota. Five pesticides (alachlor, atrazine, cyanazine, metolachlor, and simazine) were selected by the U.S. Environmental Protection Agency for the management plan approach because they had been identified as probable or possible human carcinogens and they often had been associated with ground-water contamination in many areas and at high concentrations. This report provides a compilation of data to support development of a pesticide management plan. Available data sets are summarized in the text of this report, and actual data sets are provided in one Compact Disk?Read-Only Memory that is included with the report. The compact disk contains data sets pertinent to the development of a pesticide management plan. Pesticide use for the study area is described using information from state and national databases. Within South Dakota, pesticides commonly are applied to corn and soybean crops, which are the primary row crops grown in the study area. Water-quality analyses for pesticides are summarized for several surface-water sites. Pesticide concentrations in most samples were found to be below minimum reporting levels. Topographic data are presented in the form of 30-meter digital elevation model grids and delineation of drainage basins. Geohydrologic data are provided for the surficial deposits and the bedrock units. A high-resolution (30-by-30 meters) land-cover and land-use database is provided and summarized in a tabular format. More than 91 percent of the study area is used for row crops, pasture, or hay, and almost 6 percent of the study area is covered by water or wetlands. Average monthly and yearly precipitation data are summarized in a tabular format. Irrigation information associated with permitted and licensed diversion points is provided. A composite of aerial photographs of Charles Mix County is provided. This report also describes and summarizes the data sets and files, and how the data are relevant to development of a pesticide management plan.

Open-File Report↗
USGS2015

Can orchards help connect Mediterranean ecosystems? Animal movement data alter conservation priorities

As natural habitats become fragmented by human activities, animals must increasingly move through human-dominated systems, particularly agricultural landscapes. Mapping areas important for animal movement has therefore become a key part of conservation planning. Models of landscape connectivity are often parameterized using expert opinion and seldom distinguish between the risks and barriers presented by different crop types. Recent research, however, suggests different crop types, such as row crops and orchards, differ in the degree to which they facilitate or impede species movements. Like many mammalian carnivores, bobcats ( Lynx rufus ) are sensitive to fragmentation and loss of connectivity between habitat patches. We investigated how distinguishing between different agricultural land covers might change conclusions about the relative conservation importance of different land uses in a Mediterranean ecosystem. Bobcats moved relatively quickly in row crops but relatively slowly in orchards, at rates similar to those in natural habitats of woodlands and scrub. We found that parameterizing a connectivity model using empirical data on bobcat movements in agricultural lands and other land covers, instead of parameterizing the model using habitat suitability indices based on expert opinion, altered locations of predicted animal movement routes. These results emphasize that differentiating between types of agriculture can alter conservation planning outcomes.

California↗
USGS2019

Relationships between regional coastal land cover distributions and elevation reveal data uncertainty in a sea-level rise impacts model

Understanding land loss or resilience in response to sea-level rise (SLR) requires spatially extensive and continuous datasets to capture landscape variability. We investigate sensitivity and skill of a model that predicts dynamic response likelihood to SLR across the northeastern U.S. by exploring several data inputs and outcomes. Using elevation and land cover datasets, we determine where data error is likely, quantify its effect on predictions, and evaluate its influence on prediction confidence. Results show data error is concentrated in low-lying areas with little impact on prediction skill, as the inherent correlation between the datasets can be exploited to reduce data uncertainty using Bayesian inference. This suggests the approach may be extended to regions with limited data availability and/or poor quality. Furthermore, we verify that model sensitivity in these first-order landscape change assessments is well-matched to larger coastal process uncertainties, for which process-based models are important complements to further reduce uncertainty.

Earth Surface Dynamics↗
USGS1997

Effects of carbon dioxide variations in the unsaturated zone on water chemistry in a glacial-outwash aquifer

The research site at Otis Air Base, Cape Cod, Massachusetts, has been developed for hydrogeological and geochemical studies of sewage-effluent contaminated groundwater since 1982. Research of hydrologic properties, transport, and chemical and biological processes is ongoing, but the origin of background water chemistry has not been determined. The principal geochemical process giving rise to the observed background water chemistry is CO2-controlled hydrolysis of Na feldspar. Geochemical modeling demonstrated that CO2 sources could vary over the project area. Analyses of unsaturated zone gases showed variations in CO2 which were dependent on land use and vegetative cover in the area of groundwater recharge. Measurements of CO2 in unsaturated-zone gases showed that concentrations of total inorganic C in recharge water should range from about 0.035 to 1.0 mmoles/L in the vicinity of Otis Air Base. Flux of CO2 from the unsaturated zone varied for a principal land uses, ranging from 86 gC/m2/yr for low vegetated areas to 1630 gC/m2/yr for a golf course. Carbon dioxide flux from woodlands was 220 gC/m2/yr, lower than reported fluxes of 500 to 600 gC/m2/yr for woodlands in a similar climate. Carbon dioxide flux from grassy areas was 540 gC/m2/yr, higher than reported fluxes of 230 to 490 gC/m2/yr for grasslands in a similar climate.

Applied Geochemistry↗
USGS2002

Development of a stream habitat index for the Northern Lakes and Forest Ecoregions

Physical habitat was quantified in 105 randomly selected streams across the Northern Lakes and Forests Ecoregion during 1998 and 1999 to develop a stream habitat index for the region. Physical habitat measures (106) were classified into four groups: substrate, instream cover, riparian zone–land use, and geomorphology–hydrology. Variable reduction procedures yielded seven variables: sinuosity, percent of substrate gravel or larger, percent substrate as detritus or muck, percent of bank with forested cover, amount of bank erosion, number of large logs per 100 m, and mean length of pools. Streams were separated by a gradient value of 3 m/km (low N = 70; high N = 35) and assigned to model and test data sets. For low-gradient streams in the model data set, the seven habitat variables explained 47% of the variation in index of biotic integrity (IBI) scores. To produce the habitat index, the coefficients in the regression were used to weight each of the seven variables. For low-gradient streams in the test data set, the habitat index explained 20% of the variation in IBI scores. A habitat index could not be developed for high-gradient sites, probably due to the low number of sites. Comparison of habitat to IBI scores provides resource managers with a method to evaluate the contribution of habitat quality to the IBI score.

Michigan, Minnesota, Wisconsin↗
USGS2006

The USGS Land Cover Institute

The U.S. Geological Survey (USGS) Land Cover Institute (LCI) is located at the Center for Earth Resources Observation and Science (EROS) in Sioux Falls, South Dakota. It provides a focal point for advancing USGS land cover studies and applications. Satellite images and other remotely sensed data play an important role in this research. Land Cover scientists investigate new ways to use satellite images and other data to map land cover. They assess national and global land cover characteristics and monitor how - and how rapidly - land cover changes. They also study the economic impacts of land cover as well as its effects on water quality, the spread of invasive species, habitats and biodiversity, climate variability, and other environmental factors.

Fact Sheet↗
USGS2008

Seasonal temperature responses to land-use change in the western United States

In the western United States, more than 79 000??km2 has been converted to irrigated agriculture and urban areas. These changes have the potential to alter surface temperature by modifying the energy budget at the land-atmosphere interface. This study reports the seasonally varying temperature responses of four regional climate models (RCMs) - RSM, RegCM3, MM5-CLM3, and DRCM - to conversion of potential natural vegetation to modern land-cover and land-use over a 1-year period. Three of the RCMs supplemented soil moisture, producing large decreases in the August mean (- 1.4 to - 3.1????C) and maximum (- 2.9 to - 6.1????C) 2-m air temperatures where natural vegetation was converted to irrigated agriculture. Conversion to irrigated agriculture also resulted in large increases in relative humidity (9% to 36% absolute change). Modeled changes in the August minimum 2-m air temperature were not as pronounced or consistent across the models. Converting natural vegetation to urban land-cover produced less pronounced temperature effects in all models, with the magnitude of the effect dependent upon the preexisting vegetation type and urban parameterizations. Overall, the RCM results indicate that the temperature impacts of land-use change are most pronounced during the summer months, when surface heating is strongest and differences in surface soil moisture between irrigated land and natural vegetation are largest. ?? 2007 Elsevier B.V. All rights reserved.

Global and Planetary Change↗