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At least 1,009 records · Page 56Linked to original sources
USGS2016

Regional differences in upland forest to developed (urban) land cover conversions in the conterminous U.S., 1973–2011

In this U.S. Geological Survey study of forest land cover across the conterminous U.S. (CONUS), specific proportions and rates of forest conversion to developed (urban) land were assessed on an ecoregional basis. The study period was divided into six time intervals between 1973 and 2011. Forest land cover was the source of 40% or more of the new urban land in 35 of the 84 ecoregions located within the CONUS. In 11 of these ecoregions this threshold exceeded in every time interval. When the percent of change, forest to urban, was compared to the percent of forest in each ecoregion, 58 ecoregions had a greater percent of change and, in six of those, change occurred in every time interval. Annual rates of forest to urban land cover change of 0.2% or higher occurred in 12 ecoregions at least once and in one ecoregion in all intervals. There were three ecoregions where the above conditions were met for nearly every time interval. Even though only a small number of the ecoregions were heavily impacted by forest loss to urban development within the CONUS, the ecosystem services provided by undeveloped forest land cover need to be quantified more completely to better inform future regional land management.

Conterminous United States↗
USGS2024

A "Region-Specific Model Adaptation (RSMA)" based training data method in large-scale land cover mapping

An accurate and historical land cover monitoring dataset for Alaska could provide fundamental information for a range of studies, such as conservation habitats, biogeochemical cycles, and climate systems, in this distinctive region. This research addresses challenges associated with the extraction of training data for timely and accurate land cover classifications in Alaska over longer time periods (e.g., greater than 10 years). Specifically, we designed the “Region-Specific Model Adaptation (RSMA)” method for training data. The method integrates land cover information from the National Land Cover Database (NLCD), LANDFIRE’s Existing Vegetation Type (EVT), and the National Wetlands Inventory (NWI) and machine learning techniques to generate robust training samples based on the Anderson Level II classification legend. The assumption of the method is that spectral signatures vary across regions because of diverse land surface compositions; however, despite these variations, there are consistent, collective land cover characteristics that span the entire region. Building upon this assumption, this research utilized the classification power of deep learning algorithms and the generalization ability of RSMA to construct a model for the RSMA method. Additionally, we interpreted existing vegetation plot information for land cover labels as validation data to reduce inconsistency in the human interpretation. Our validation results indicate that the RSMA method improved the quality of the training data derived solely from the NLCD by approximately 30% for the overall accuracy. The validation assessment also demonstrates that the RSMA method can generate reliable training data on large scales in regions that lack sufficient reliable data.

Remote Sensing↗
USGS2010

Mapping irrigated lands at 250-m scale by merging MODIS data and National Agricultural Statistics

Accurate geospatial information on the extent of irrigated land improves our understanding of agricultural water use, local land surface processes, conservation or depletion of water resources, and components of the hydrologic budget. We have developed a method in a geospatial modeling framework that assimilates irrigation statistics with remotely sensed parameters describing vegetation growth conditions in areas with agricultural land cover to spatially identify irrigated lands at 250-m cell size across the conterminous United States for 2002. The geospatial model result, known as the Moderate Resolution Imaging Spectroradiometer (MODIS) Irrigated Agriculture Dataset (MIrAD-US), identified irrigated lands with reasonable accuracy in California and semiarid Great Plains states with overall accuracies of 92% and 75% and kappa statistics of 0.75 and 0.51, respectively. A quantitative accuracy assessment of MIrAD-US for the eastern region has not yet been conducted, and qualitative assessment shows that model improvements are needed for the humid eastern regions where the distinction in annual peak NDVI between irrigated and non-irrigated crops is minimal and county sizes are relatively small. This modeling approach enables consistent mapping of irrigated lands based upon USDA irrigation statistics and should lead to better understanding of spatial trends in irrigated lands across the conterminous United States. An improved version of the model with revised datasets is planned and will employ 2007 USDA irrigation statistics.

Remote Sensing↗
USGS2016

Evaluation of the initial thematic output from a continuous change-detection algorithm for use in automated operational land-change mapping by the U.S. Geological Survey

The U.S. Geological Survey (USGS) has begun the development of operational, 30-m resolution annual thematic land cover data to meet the needs of a variety of land cover data users. The Continuous Change Detection and Classification (CCDC) algorithm is being evaluated as the likely methodology following early trials. Data for training and testing of CCDC thematic maps have been provided by the USGS Land Cover Trends (LC Trends) project, which offers sample-based, manually classified thematic land cover data at 2755 probabilistically located sample blocks across the conterminous United States. These samples represent a high quality, well distributed source of data to train the Random Forest classifier invoked by CCDC. We evaluated the suitability of LC Trends data to train the classifier by assessing the agreement of annual land cover maps output from CCDC with output from the LC Trends project within 14 Landsat path/row locations across the conterminous United States. We used a small subset of circa 2000 data from the LC Trends project to train the classifier, reserving the remaining Trends data from 2000, and incorporating LC Trends data from 1992, to evaluate measures of agreement across time, space, and thematic classes, and to characterize disagreement. Overall agreement ranged from 75% to 98% across the path/rows, and results were largely consistent across time. Land cover types that were well represented in the training data tended to have higher rates of agreement between LC Trends and CCDC outputs. Characteristics of disagreement are being used to improve the use of LC Trends data as a continued source of training information for operational production of annual land cover maps.

Remote Sensing↗
USGS2019

Synergistic interaction of climate and land-use drivers alter the function of North American, Prairie-pothole Wetlands

Prairie-pothole wetlands provide the critical habitat necessary for supporting North American migratory waterfowl populations. However, climate and land-use change threaten the sustainability of these wetland ecosystems. Very few experiments and analyses have been designed to investigate the relative impacts of climate and land-use change drivers, as well as the antagonistic or synergistic interactions among these drivers on ecosystem processes. Prairie-pothole wetland water budgets are highly dependent on atmospheric inputs and especially surface runoff, which makes them especially susceptible to changes in climate and land use. Here, we present the history of prairie-pothole climate and land-use change research and address the following research questions: 1) What are the relative effects of climate and land-use change on the sustainability of prairie-pothole wetlands? and 2) Do the effects of climate and land-use change interact differently under different climatic conditions? To address these research questions, we modeled 25 wetland basins (1949–2018) and measured the response of the lowest wetland in the watershed to wetland drainage and climate variability. We found that during an extremely wet period (1993–2000) wetland drainage decreased the time at which the lowest wetland reached its spill point by four years, resulting in 10 times the amount of water spilling out of the watershed towards local stream networks. By quantifying the relative effects of both climate and land-use drivers on wetland ecosystems our findings can help managers cope with uncertainties about flooding risks and provide insight into how to manage wetlands to restore functionality

Sustainability↗
USGS2021

An assessment of vertical land movement to support coastal hazards planning in Washington state

The sea and land change elevation spatially and temporally from a multitude of processes, so it is necessary to constrain the movement of both to evaluate how coastlines will evolve and how those evolving coastlines will impact the natural and built environment over time. We combine land movement observations from global navigation satellite systems (GNSSs), leveling of geodetic monuments, and tide gauge records with a tectonic model of the Cascadia subduction zone to constrain absolute rates of vertical land movement in coastal Washington. We infer rates of vertical land movement in areas lacking direct observations by interpolating high-quality land movement observations and a discretely sampled interseismic locking model. Here we present a model of absolute vertical land movement that is combined with sea level rise estimates to inform local relative sea level projections on a community-scale. The most rapid vertical uplift (~3.5 mm/year) of the land is found across the northwest Olympic Peninsula, which currently outpaces sea level rise. Conversely, some areas, including a stretch of the northern Pacific Ocean coast from La Push to Kalaloch and the southern Puget Sound, are found to be subsiding at 0.5–1.0 mm/year, exacerbating the rate of relative sea level rise and thereby increasing the vulnerability of coastal communities.

Washington↗
USGS2010

A spatial resolution threshold of land cover in estimating terrestrial carbon sequestration in four counties in Georgia and Alabama, USA

Changes in carbon density (i.e., carbon stock per unit area) and land cover greatly affect carbon sequestration. Previous studies have shown that land cover change detection strongly depends on spatial scale. However, the influence of the spatial resolution of land cover change information on the estimated terrestrial carbon sequestration is not known. Here, we quantified and evaluated the impact of land cover change databases at various spatial resolutions (250 m, 500 m, 1 km, 2 km, and 4 km) on the magnitude and spatial patterns of regional carbon sequestration in four counties in Georgia and Alabama using the General Ensemble biogeochemical Modeling System (GEMS). Results indicated a threshold of 1 km in the land cover change databases and in the estimated regional terrestrial carbon sequestration. Beyond this threshold, significant biases occurred in the estimation of terrestrial carbon sequestration, its interannual variability, and spatial patterns. In addition, the overriding impact of interannual climate variability on the temporal change of regional carbon sequestration was unrealistically overshadowed by the impact of land cover change beyond the threshold. The implications of these findings directly challenge current continental- to global-scale carbon modeling efforts relying on information at coarse spatial resolution without incorporating fine-scale land cover dynamics.

Alabama;Georgia↗
USGS2016

Setting priorities for private land conservation in fire-prone landscapes: Are fire risk reduction and biodiversity conservation competing or compatible objectives?

Although wildfire plays an important role in maintaining biodiversity in many ecosystems, fire management to protect human assets is often carried out by different agencies than those tasked for conserving biodiversity. In fact, fire risk reduction and biodiversity conservation are often viewed as competing objectives. Here we explored the role of management through private land conservation and asked whether we could identify private land acquisition strategies that fulfill the mutual objectives of biodiversity conservation and fire risk reduction, or whether the maximization of one objective comes at a detriment to the other. Using a fixed budget and number of homes slated for development, we simulated 20 years of housing growth under alternative conservation selection strategies, and then projected the mean risk of fires destroying structures and the area and configuration of important habitat types in San Diego County, California, USA. We found clear differences in both fire risk projections and biodiversity impacts based on the way conservation lands are prioritized for selection, but these differences were split between two distinct groupings. If no conservation lands were purchased, or if purchases were prioritized based on cost or likelihood of development, both the projected fire risk and biodiversity impacts were much higher than if conservation lands were purchased in areas with high fire hazard or high species richness. Thus, conserving land focused on either of the two objectives resulted in nearly equivalent mutual benefits for both. These benefits not only resulted from preventing development in sensitive areas, but they were also due to the different housing patterns and arrangements that occurred as development was displaced from those areas. Although biodiversity conflicts may still arise using other fire management strategies, this study shows that mutual objectives can be attained through land-use planning in this region. These results likely generalize to any place where high species richness overlaps with hazardous wildland vegetation.

California↗
USGS1977

Urban and regional land use change detected by using Landsat data

The Atlanta Regional Commission and the Earth Resources Observation Systems Data Center participated in a demonstration of the use of Landsat digital data to detect land use change in the Atlanta, Ga., area. Temporal overlays combining Landsat band-5 data from October 1972 and 1974 were made by using the General Electric Image 100 system. The 1972 data were divided by the 1974 data, and low ratios indicate areas where land use and land cover had changed. These low ratios were classified into a land-use-change theme. A classification based on the use of the four bands of the multispectral scanner data, taken in 1974, yielded six land use categories: (1) Commercial-industrial-multifamily, (2) single-family residential, (3) cleared land, (4) open space, (5) forested land, and (6) water. These six 1974 categories and the change theme were combined to determine changes between 1972 and 1974.

Georgia↗
USGS1987

Producing Alaska interim land cover maps from Landsat digital and ancillary data

In 1985, the U.S. Geological Survey initiated a research program to produce 1:250,000-scale land cover maps of Alaska using digital Landsat multispectral scanner data and ancillary data and to evaluate the potential of establishing a statewide land cover mapping program using this approach. The geometrically corrected and resampled Landsat pixel data are registered to a Universal Transverse Mercator (UTM) projection, along with arc-second digital elevation model data used as an aid in the final computer classification. Areas summaries of the land cover classes are extracted by merging the Landsat digital classification files with the U.S. Bureau of Land Management's Public Land Survey digital file. Registration of the digital land cover data is verified and control points are identified so that a laser plotter can products screened film separate for printing the classification data at map scale directly from the digital file. The final land cover classification is retained both as a color map at 1:250,000 scale registered to the U.S. Geological Survey base map, with area summaries by township and range on the reverse, and as a digital file where it may be used as a category in a geographic information system.

Alaska↗
USGS1994

Tamarisk control on public lands in the desert of southern California: two case studies

As a land manager, the Federal Government faces enormous challenges from exotic pest invasions and associated changes to the structure and stability of native ecosystems (Bureau of Land Management, 1988). On public lands administered by the Bureau of Land Management (BLM) alone, it is estimated that almost three million hectares are occupied by invasive exotic plant species (weeds). Assuming an annual rate of invasion of 14 percent, 930 hectares of BLM-administered land are infested everyday by weeds (Jerry Asher, personal communication). When one considers the fact that BLM administers only about one-third of the public land in the United States (The Keystone Center, 1991), the magnitude of the problem assumes staggering proportions. The scenario described in the quote above portrays only some of the problems associated with the spread of the exotic plant tamarisk, a species on the California Exotic Pest Plant Council’s list of exotic pest plants of greatest concern (California Exotic Pest Plant Council, 1993). In this paper we review the threats posed by tamarisk invasion and proliferation and examine the traits that make the plant such a successful competitor. In addition, we highlight two tamarisk control efforts conducted by the Bureau of Land Management in the southern California desert.

California↗
USGS2015

Regulating services as measures of ecological resilience on DoD lands

Knowledge of the capacity and flow of ecosystem services can help DoD land managers make decisions that enhance cost-effectiveness, minimize environmental damage, and maximize resources available for military missions. We demonstrated a methodology to quantify and map selected regulating services (RS), which helps land managers envision tradeoffs. Our objectives were to 1) estimate current capacity of and demand for selected RS within DoD lands, 2) examine the effects of future DoD land management and climate changes on the capacity and flow of these RS, and 3) project how land-use and climate changes in nearby lands affect future demand for RS. Our approach incorporates widely accepted models and equations, remote sensing, GIS analysis, and stakeholder involvement. Required data include land cover/use, soil type, precipitation, and air temperature. We integrated data into the a) Surface Curve Number Method and b) Revised Universal Soil Loss Equation to estimate capacity of sediment, nitrogen (N) and surface-water regulation. Capacities and flows of RS vary greatly across landscapes and are likely to vary as climate changes or development occurs. Analyses of RS capacity and flow can help managers and planners prioritize actions in the context of best management practices and compatible use buffers. Staff surveys indicated that our approach was informative and easy to use. Implementation may be most limited by on-installation personnel time.

Report↗
USGS2010

The use of scenario analysis to assess water ecosystem services in response to future land use change in the Willamette River Basin, Oregon

Human pressures on the natural resources of the United States have resulted in many unintended changes in our ecosystems, e.g., loss of biodiversity, habitat degradation, increases in the number of endangered species, and increases in contamination and water pollution. Environmental managers are concerned about broad-scale changes in land use and landscape pattern and their cumulative impact on hydrologic and ecological processes that affect stream conditions. The type of land use and land cover has direct consequences for most ecosystem services, including water quantity and water quality, erosion control, and biodiversity. As human pressure continues to increase, ecosystem services worldwide are projected to suffer continued loss and degradation, thus reducing the capacity of ecosystems to provide essential goods and services that contribute to human well-being (MEA 2005). The ability to assess, report, and forecast the life support functions of ecosystems is absolutely critical to our capacity to make informed decisions which will maintain the sustainable nature of our environmental services and secure these resources into the future. This study presents an integrated approach to identify areas with potential water quality problems as a result of land cover change projected by stakeholders within a moderately large river basin in the Pacific Northwest (USA). A process-based hydrologic watershed model was used to examine the contribution of land use/land cover to sediment yield, and nitrate and phosphorous loadings, and identify subwatersheds within the Willamette River basin that would be most affected in the year 2050 relative to three possible future scenarios which include inherent differences related to conservation, existing planning trends, and open development. Thus, the objective of this study was to evaluate the effects of alternative future scenarios that describe varying degrees of urban development and human use on hydrological response related to water quality. Results of this study suggest that the amount of forest along streams and agriculture consistently explained a high percentage of variation in nutrients. The AGWA-SWAT model was used to simulate change in sediment yield, nitrate and phosphorus transported with surface runoff for the three future scenarios. With regard to nitrate, the greatest increase was associated with subwatersheds with agricultural land use and urban areas. Although the model predicted some improvement in basin headwaters for all scenarios, nitrate loadings are expected to decrease under the conservation scenario. The largest decrease was observed in the Coast Range. With regard to phosphorous loadings, the lowest reduction was observed in subwatersheds draining predominantly forest areas. The greatest increase was observed under the open development scenario in subwatersheds with agricultural land use. Urbanization and agriculture are presumed to be the major environmental stressors affecting watershed condition of the Willamette River Basin.

Oregon↗
USGS2009

A case study of carbon fluxes from land change in the Southwest Brazilian Amazon

Worldwide, land change is responsible for one-fifth of anthropogenic carbon emissions. In Brazil, three-quarters of carbon emissions originate from land change. This study represents a municipal-scale study of carbon fluxes from vegetation in Rio Branco, Brazil. Land-cover maps of pasture, forest, and secondary growth from 1993, 1996, 1999, and 2003 were produced using an unsupervised classification method (overall accuracy = 89%). Carbon fluxes from land change over the decade of imagery were estimated from transitions between land-cover categories for each time interval. This article presents new methods for estimating emissions reductions from carbon stored in the vegetation that replaces forests (e.g., pasture) and sequestration by new (>10–15 years) forests, which reduced gross emissions by 16, 15, and 22% for the period of 1993–1996, 1996–1999, and 1999–2003, respectively. The methods used in the analysis are broadly applicable and provide a comprehensive characterization of regional-scale carbon fluxes from land change.

Southwest Brazilian Amazon Rainforest↗
USGS2022

Analyzing the effects of land cover change on the water balance for case study watersheds in different forested ecosystems in the USA

We analyzed impacts of interannual disturbance on the water balance of watersheds in different forested ecosystem case studies across the United States from 1985 to 2016 using a remotely sensed long-term land cover monitoring record (U.S. Geological Survey Land Change Monitoring, Assessment, and Projection (LCMAP) Collection 1.0 Science products), gridded precipitation and evaporation data, and streamgaging data using paired watersheds (high and low disturbance). LCMAP products were used to quantify the timing and degree of interannual disturbance and to gain a better understanding of how land cover change affects the water balance of disturbed watersheds. In this paper, we present how LCMAP science products can be used to improve knowledge for hydrologic modeling, climate research, and forest management. Anthropogenic influences (e.g., dams and irrigation diversions) often minimize the impacts of land cover change on water balance dynamics when compared to interannual fluctuations of hydroclimatic events (e.g., drought and flooding). Our findings show that each watershed exhibits a complex suite of influences involving climate variables and other factors that affect each of their water balances differently when land cover change occurs. In this study, forests within arid to semi-arid climates experience greater water balance effects from land cover change than watersheds where water is less limited.

Land↗
USGS2019

Partitioning global change: Assessing the relative importance of changes in climate and land cover for changes in avian distribution

Understanding the relative impact of climate change and land cover change on changes in avian distribution has implications for the future course of avian distributions and appropriate management strategies. Due to the dynamic nature of climate change, our goal was to investigate the processes that shape species distributions, rather than the current distributional patterns. To this end, we analyzed changes in the distribution of Eastern Wood Pewees (Contopus virens) and Red-eyed Vireos (Vireo olivaceus) from 1997 to 2012 using Breeding Bird Survey data and dynamic correlated-detection occupancy models. We estimated the local colonization and extinction rates of these species in relation to changes in climate (hours of extreme temperature) and changes in land cover (amount of nesting habitat). We fit six nested models to partition the deviance explained by spatial and temporal components of land cover and climate. We isolated the temporal components of environmental variables because this is the essence of global change. For both species, model fit was significantly improved when we modeled vital rates as a function of spatial variation in climate and land cover. Model fit only improved insignificantly when we added temporal variation in climate and land cover to the model. Temporal variation in climate explained more deviance than temporal variation in land cover, although both combined only explained 20% (Eastern Wood Pewee) and 6% (Red-eyed Vireo) of temporal variation in vital rates. Our results showing a significant correlation between initial occupancy and environmental covariates are consistent with biological expectation and previous studies. Our results estimating a weak correlation between vital rates and temporal changes in covariates indicate that we have yet to identify the most relevant components of global change changing the distributions of these species and, more significantly, that spatially significant covariates are not necessarily driving temporal shifts in avian distributions.

Ecology and Evolution↗
USGS1987

Stratification of a cityscape using census and land use variables for inventory of building materials

A cityscape (or any landscape) can be stratified into environmental units using multiple variables of information. For the purposes of sampling building materials, census and land use variables were used to identify similar strata. In the Metropolitan Statistical Area of a cityscape, the census tract is the smallest unit for which census data are summarized and digitized boundaries are available. For purposes of this analysis, census data on total population, total number of housing units, and number of singleunit dwellings were aggregated into variables of persons per square kilometer and proportion of housing units in single-unit dwellings. The level 2 categories of the U.S. Geological Survey's land use and land cover data base were aggregated into variables of proportion of residential land with buildings, proportion of nonresidential land with buildings, and proportion of open land. The cityscape was stratified, from these variables, into environmental strata of Urban Central Business District, Urban Livelihood Industrial Commercial, Urban Multi-Family Residential, Urban Single Family Residential, Non-Urban Suburbanizing, and Non-Urban Rural. The New England region was chosen as a region with commonality of building materials, and a procedure developed for trial classification of census tracts into one of the strata. Final stratification was performed by discriminant analysis using the trial classification and prior probabilities as weights. The procedure was applied to several cities, and the results analyzed by correlation analysis from a field sample of building materials. The methodology developed for stratification of a cityscape using multiple variables has application to many other types of environmental studies, including forest inventory, hydrologic unit management, waste disposal, transportation studies, and other urban studies. Multivariate analysis techniques have recently been used for urban stratification in England. ?? 1987 Annals of Regional Science.

The Annals of Regional Science↗
USGS2003

Assessing water quality at large geographic scales: Relations among land use, water physicochemistry, riparian condition, and fish community structure

Data collected from 172 sites in 20 major river basins between 1993 and 1995 as part of the US Geological Survey's National Water-Quality Assessment Program were analyzed to assess relations among basinwide land use (agriculture, forest, urban, range), water physicochemistry, riparian condition, and fish community structure. A multimetric approach was used to develop regionally referenced indices of fish community and riparian condition. Across large geographic areas, decreased riparian condition was associated with water-quality constituents indicative of nonpoint source inputs-total nitrogen and suspended sediment and basin-wide urban land use. Decreased fish community condition was associated with increases in total dissolved solids and rangeland use and decreases in riparian condition and agricultural land use. Fish community condition was relatively high even in areas where agricultural land use was relatively high (>50% of the basin). Although agricultural land use can have deleterious effects on fish communities, the results of this study suggest that other factors also may be important, including practices that regulate the delivery of nutrients, suspended sediments, and total dissolved solids into streams. Across large geographic scales, measures of water physicochemistry may be better indicators of fish community condition than basinwide land use. Whereas numerous studies have indicated that riparian restorations are successful in specific cases, this analysis suggests the universal importance of riparian zones to the maintenance and restoration of diverse fish communities in streams.

Environmental Management↗