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Land use categorical changes, though not as numerous as one might suspect, vary by type within the three designated ecozones of the Corn Belt with the westernmost zone showing the most temporary change vis-a-vis the more permanent changes taking place in the eastern and central zones.
The U.S. Geological Survey (USGS) has a long heritage of leadership and innovation in land use and land cover mapping. The USGS Anderson system defined the principles for land use and land cover mapping that have been the model both nationally and internationally for more than 20 years. The Land Cover Characterization Program (LCCP) is founded on the premise that the Nation's needs for land cover and land use data are diverse and increasingly sophisticated. The range of projects, programs, and organizations that use land cover data to meet their planning, management, development, and assessment objectives has expanded significantly. The reasons for this are numerous, and include the improved capabilities provided by geographic information systems, better and more data-intensive analytic models, and increasing requirements for improved information for decision making. The overall goals of the LCCP are to: (1) identify the broad range of user requirements; (2) identify sources, develop procedures, and organize partners to deliver data and information to meet user requirements. The LCCP builds on the heritage and success of previous USGS land use and land cover programs and projects. It will be compatible with current concepts of government operations, the changing needs of the land use and land cover data users, and the technological tools with which the data are applied.
Urban growth and other land-use changes were examined in the Lower Rio Grande Valley and Alluvial Floodplain ecoregions in Texas, along the U.S.-Mexico border. The analysis focused on understanding the types and causes of land change as well as the recovery of natural land-cover types between years 2001 and 2011. The purpose was to develop improved capabilities for understanding land change dynamics in urbanizing ecoregions and to provide data for further analyses. The spatial data, including metadata, allows further exploration and characterization of changes affecting this dynamic region.
Overlay and index methods were derived for rating the unsaturated zone and watershed characteristics for use by the State of North Carolina in assessing more than 11,000 public water-supply wells and approximately 245 public surface-water intakes. The rating of the unsaturated zone and watershed characteristics represents a practical and effective means of assessing part of the inherent vulnerability of water supplies to potential contamination. Factors that influence the inherent vulnerability of the drinking water supply to potential contamination were selected and assigned ratings (on a scale of 1 to 10) to cover the possible range of values in North Carolina. These factors were assigned weights of 1, 2, or 3 to reflect their relative influence on the inherent vulnerability of the drinking water supply. The factor values were obtained from Geographic Information System data layers, and were transformed into grids having 60-meter by 60-meter cells, with each cell being assigned a value. Identification of factors, the development of ratings for each, and assignment of weights were based on (1) a literature search, which included examination of potential factors and their effects on the drinking water; and (2) consultation with experts in the science and engineering of hydrology, geology, forestry, agriculture, and water management. Factors selected for rating the inherent vulnerability of the unsaturated zone are vertical hydraulic conductance, land-surface slope, land cover, and land use. Vertical hydraulic conductance is a measure of the capacity of unsaturated material to transmit water. Land-surface slope influences whether precipitation runs off land surfaces or infiltrates into the subsurface. Land cover, the physical overlay of the land surface, influences the amount of precipitation that becomes overland flow or infiltrates into the subsurface. Land use describes activities that occur on the land surface and influence the potential generation of nonpoint-source contamination. Factors selected for rating the watershed characteristics upstream from surface-water intakes are average annual precipitation, land-surface slope, land cover, land use, and ground-water contribution. The average annual precipitation represents the mass of water that becomes available for transport in a watershed. Land-surface slope, land cover, and land use have similar influences in watersheds as those identified for the unsaturated zone. Ground-water contribution represents the part of streamflow that is derived from ground-water discharge.
Urban development and associated land cover and land use change alter the thermal, hydrological, and physical properties of the land surface. Assessments of surface urban heat island (UHI) usually focused on using remote sensing and land cover data to quantify UHI intensity and spatial distribution within a certain period. However, the mechanisms and complex interactions in landscape dynamics and land surface thermal features are still being assessed. In this study, we developed and implemented a novel approach to characterize landscape thermal conditions by focusing on UHI intensity and its spatiotemporal variation using the recently available time series of Landsat land surface temperature and land cover change products. We analyzed land surface temperature changes in urban and surrounding non-urban lands to quantify the UHI intensity and landscape thermal conditions in the Atlanta and Minneapolis metropolitan areas of the United States. Our results revealed that UHI intensities had averages of 3.4 °C and 3.3 °C in the Atlanta and Minneapolis metropolitan areas, respectively. The dominant land cover type in rural areas and urban imperviousness cover determines the UHI intensity. Increasing trends of 0.04 °C/year and 0.01 °C/year in UHI intensity between 1985 and 2018 were found in Atlanta and Minneapolis, respectively. The UHI intensity variations in 1985 and 2018 suggest that the magnitudes and temporal variations of UHI intensity averaged from all urban land cover classes are close to the UHI intensity estimated from the low intensity urban area only while the UHI intensities are more than 2 °C larger in medium to high and high intensity urban areas. The UHI intensities estimated from the maximum temperature that have statistically significant increasing trends suggest that the maximum temperature is a good element for measuring UHI effect. Urban land cover dynamics play an important role in controlling temporal variation of UHI and the UHI hotspots. Our findings support the scientific value of implementing the prototype approach as an objective framework to quantify and monitor UHI intensity at a large geographic extent.
This study examines long-term changes in Senegal's natural resources. We monitor and quantify land use and land cover changes occurring across Senegal using nearly 40 years of satellite imagery, aerial surveys, and fieldwork. We stratify Senegal into ecological regions and present land use and land cover trends for each region, followed by a national summary. Results aggregated to the national level show moderate change, with a modest decrease in savannas from 74 to 70 percent from 1965 to 2000, and an expansion of cropland from 17 to 21 percent. However, at the ecoregion scale, we observed rapid change in some and relative stability in others. One particular concern is the decline in Senegal's biodiverse forests. However, in the year 2000, Senegal's savannas, woodlands, and forests still cover more than two-thirds of the country, and the rate of agricultural expansion has slowed.
Model estimates of impervious area as a function of landcover area may be biased and imprecise because of errors in the land-cover classification. This investigation of the effects of land-cover misclassification on impervious surface models that use National Land Cover Data (NLCD) evaluates the consequences of adjusting land-cover within a watershed to reflect uncertainty assessment information. Model validation results indicate that using error-matrix information to adjust land-cover values used in impervious surface models does not substantially improve impervious surface predictions. Validation results indicate that the resolution of the landcover data (Level I and Level II) is more important in predicting impervious surface accurately than whether the land-cover data have been adjusted using information in the error matrix. Level I NLCD, adjusted for land-cover misclassification, is preferable to the other land-cover options for use in models of impervious surface. This result is tied to the lower classification error rates for the Level I NLCD. ?? 2007 American Society for Photogrammetry and Remote Sensing.
The U.S. Geological Survey, in cooperation with other government and private organizations, is producing a conterminous U.S. land-cover map using Landsat Thematic Mapper 30-meter data for the Federal regions designated by the U.S. Environmental Protection Agency. Accuracy assessment is to be conducted for each Federal region to estimate overall and class-specific accuracies. In Region 2, consisting of New York and New Jersey, the accuracy assessment was completed for 15 land-cover and land-use classes, using interpreted 1:40,000-scale aerial photographs as reference data. The methodology used for Region 2 features a two-stage, geographically stratified approach, with a general sample of all classes (1,033 sample sites), and a separate sample for rare classes (294 sample sites). A confidence index was recorded for each land-cover interpretation on the 1:40,000-scale aerial photography The estimated overall accuracy for Region 2 was 63 percent (standard error 1.4 percent) using all sample sites, and 75.2 percent (standard error 1.5 percent) using only reference sites with a high-confidence index. User's and producer's accuracies for the general sample and user's accuracy for the sample of rare classes, as well as variance for the estimated accuracy parameters, were also reported. Narrowly defined land-use classes and heterogeneous conditions of land cover are the major causes of misclassification errors. Recommendations for modifying the accuracy assessment methodology for use in the other nine Federal regions are provided.
Digital land-cover data are among the most popular data sources used in ecological research and natural resource management. However, processes for accurate land-cover classification over large regions are still evolving. We identified inconsistencies in the National Land Cover Dataset 1992, the most current and available representation of land cover for the conterminous United States. We also report means to address these inconsistencies in a bird-habitat model. We used a Geographic Information System (GIS) to position a regular grid (or lattice) over the upper midwestern United States and summarized the proportion of individual land covers in each cell within the lattice. These proportions were then mapped back onto the lattice, and the resultant lattice was compared to satellite paths, state borders, and regional map classification units. We observed mapping inconsistencies at the borders between mapping regions, states, and Thematic Mapper (TM) mapping paths in the upper midwestern United States, particularly related to grass I and-herbaceous, emergent-herbaceous wetland, and small-grain land covers. We attributed these discrepancies to differences in image dates between mapping regions, suboptimal image dates for distinguishing certain land-cover types, lack of suitable ancillary data for improving discrimination for rare land covers, and possibly differences among image interpreters. To overcome these inconsistencies for the purpose of modeling regional populations of birds, we combined grassland-herbaceous and pasture-hay land-cover classes and excluded the use of emergent-herbaceous and small-grain land covers. We recommend that users of digital land-cover data conduct similar assessments for other regions before using these data for habitat evaluation. Further, caution is advised in using these data in the analysis of regional land-cover change because it is not likely that future digital land-cover maps will repeat the same problems, thus resulting in biased estimates of change.
Increased demands for cleaner burning energy, coupled with the relatively recent technological advances in accessing unconventional hydrocarbon-rich geologic formations, have led to an intense effort to find and extract natural gas from various underground sources around the country. One of these sources, the Marcellus Shale, located in the Allegheny Plateau, is currently undergoing extensive drilling and production. The technology used to extract gas in the Marcellus Shale is known as hydraulic fracturing and has garnered much attention because of its use of large amounts of fresh water, its use of proprietary fluids for the hydraulic-fracturing process, its potential to release contaminants into the environment, and its potential effect on water resources. Nonetheless, development of natural gas extraction wells in the Marcellus Shale is only part of the overall natural gas story in this area of Pennsylvania. Conventional natural gas wells, which sometimes use the same technique, are commonly located in the same general area as the Marcellus Shale and are frequently developed in clusters across the landscape. The combined effects of these two natural gas extraction methods create potentially serious patterns of disturbance on the landscape. This document quantifies the landscape changes and consequences of natural gas extraction for Bedford, Blair, Cambria, Centre, Clearfield, Clinton, Columbia, Huntingdon, and Luzerne Counties in Pennsylvania between 2004 and 2010. Patterns of landscape disturbance related to natural gas extraction activities were collected and digitized using National Agriculture Imagery Program (NAIP) imagery for 2004, 2005/2006, 2008, and 2010. The disturbance patterns were then used to measure changes in land cover and land use using the National Land Cover Database (NLCD) of 2001. A series of landscape metrics is also used to quantify these changes and is included in this publication. In this region, natural gas development disturbed approximately 943 hectares of land in which forest sustained three times the amount of disturbance as agricultural land. One-quarter of that total disturbance was from Marcellus natural gas development.
Increased demands for cleaner burning energy, coupled with the relatively recent technological advances in accessing hydrocarbon-rich geologic formations, have led to an intense effort to find and extract unconventional natural gas from various underground sources around the country. One of these sources, the Marcellus Shale, located in the Allegheny Plateau, is currently undergoing extensive drilling and production. The technology used to extract gas in the Marcellus Shale is known as hydraulic fracturing and has garnered much attention because of its use of large amounts of fresh water, its use of proprietary fluids for the hydraulic-fracturing process, its potential to release contaminants into the environment, and its potential effect on water resources. Nonetheless, development of natural gas extraction wells in the Marcellus Shale is only part of the overall natural gas story in this area of Pennsylvania. Conventional natural gas wells, which sometimes use the same technique for extraction, are commonly located in the same general area as the Marcellus Shale and are frequently developed in clusters across the landscape. The combined effects of these two natural gas extraction methods create potentially serious patterns of disturbance on the landscape. This document quantifies the landscape changes and consequences of natural gas extraction for Cameron, Clarion, Elk, Forest, Jefferson, McKean, Potter, and Warren Counties in Pennsylvania between 2004 and 2010. Patterns of landscape disturbance related to natural gas extraction activities were collected and digitized using National Agriculture Imagery Program (NAIP) imagery for 2004, 2005/2006, 2008, and 2010. The disturbance patterns were then used to measure changes in land cover and land use using the National Land Cover Database (NLCD) of 2001. A series of landscape metrics is also used to quantify these changes and is included in this publication. In this region, natural gas and oil development disturbed approximately 5,255 hectares (ha) (conventional, 2,400 ha; Marcellus, 357 ha; and oil, 1,883 ha) of land of which 3,507 ha were forested land and 610 ha were agricultural land. Eighty percent of that total disturbance was from conventional natural gas and oil development.
The advancement of geographic science in the area of land surface status and trends and land cover change is at the core of the current geographic scientific research of the U.S. Geological Survey (USGS) (McMahon and others, 2005). Perhaps the least developed or articulated aspects of USGS land change science have been the identification and analysis of the ecological consequences of land cover change. Changes in land use and land cover significantly affect the ability of ecosystems to provide essential ecological goods and services, which, in turn, affect the economic, public health, and social benefits that these ecosystems provide. One of the great scientific challenges for geographic science is to understand and calibrate the effects of land use and land cover change and the complex interaction between human and biotic systems at a variety of natural, geographic, and political scales. Understanding the dynamics of land surface change requires an increased understanding of the complex nature of human-environmental systems and will require a suite of scientific tools that include traditional geographic data and analysis methods, such as remote sensing and geographic information systems (GIS), as well as innovative approaches to understanding the dynamics of complex systems. One such approach that has gained much recent scientific attention is the landscape indicator, or landscape assessment, approach, which has been developed with the emergence of the science of landscape ecology.
Since the adoption of a Regional Development Plan in 1975, the Atlanta Regional Commission has investigated methods for monitoring regional development patterns in a periodic, efficient manner. A promising approach appears to be the use of Landsat satellite data. In cooperation with the Earth Resources Observation Systems (EROS) Data Center, the commission used machine processing of digital temporal overlays of Landsat data collected in 1972, 1974 and 1976 to detect land use and land cover changes in the Atlanta metropolitan area. Results of the analysis revealed the conversion of forested and open space areas to residential, commercial and industrial land use in the urban-rural fringe zone from 1972 to 1974 and from 1974 to 1976. The study indicated that a land use and land cover change-detection program may be used to revise small-area forecasts of land use, population and employment made by planning models.
A study of the water resources of the unconsolidated groundwater system of the Chamokane Creek basin was conducted to determine the hydrogeologic framework, interactions of shallow and deep parts of the groundwater system with each other and the surface-water system, changes in land use and land cover, and water-use estimates. Chamokane Creek basin is a 179 mi2 area that borders and partially overlaps the Spokane Indian Reservation in southern Stevens County in northeastern Washington State. Aquifers within the Chamokane Creek basin are part of a sequence of glaciofluvial and glaciolacustrine sediment that may reach total thicknesses of about 600 ft. In 1979, most of the water rights in the Chamokane Creek basin were adjudicated by the United States District Court requiring regulation in favor of the Spokane Tribe of Indians' senior water right. The Spokane Tribe, the State of Washington, and the United States are concerned about the effects of additional groundwater development within the basin on Chamokane Creek. Information provided by this study will be used to evaluate the effects of potential increases in groundwater withdrawals on groundwater and surface-water resources within the basin. The hydrogeologic framework consists of six hydrogeologic units: The Upper outwash aquifer, the Landslide Unit, the Valley Confining Unit, the Lower Aquifer, the Basalt Unit, and the Bedrock Unit. The Upper outwash aquifer occurs along the valley floors of the study area and consists of sand, gravel, cobbles, boulders, with minor silt and (or) clay interbeds in places. The Lower aquifer is a confined aquifer consisting of sand and gravel that occurs at depth below the Valley confining unit. Median horizontal hydraulic conductivity values for the Upper outwash aquifer, Valley confining unit, Lower aquifer, and Basalt unit were estimated to be 540, 10, 19, and 3.7 ft/d, respectively. Many low-flow stream discharge measurements at sites on Chamokane Creek and its tributaries were at or near zero flow. The most notable exception is where Chamokane Creek is supported by discharge of large springs from the Upper outwash aquifer in the southern part of the basin. Most high-flow measurements indicated gains in streamflow (groundwater discharging to the stream). Large streamflow losses, however, were recorded near the north end of Walkers Prairie where streamflow directly recharges the Upper outwash aquifer. The similarity in seasonal water-level fluctuations in the Upper outwash aquifer and the Lower aquifer indicate that these systems may be fairly well connected. Land use and land cover change analysis indicates that Chamokane Creek basin has been dominated by forests with some pasture and agricultural lands with sparse residential development from the 1980s to present. Loss in forest cover represents the largest change in land cover in the basin between 1987 and 2009. This appears to be mostly due to forestry activities, especially in the northern part of the basin. Since 1987, more than 18,000 acres of evergreen forest have been logged and are at various stages of regrowth. Estimated average annual total groundwater pumpage in the basin increased from 224 million gallons per year (Mgal/yr) in 1980 to 1,330 Mgal/yr in 2007. The largest withdrawals during 2007 were to supply two fish hatcheries, with a combined total annual pumpage of about 1,150 Mgal. Annual groundwater pumpage values from 1980 through 2007 for the study area ranged from 21.1 to 28.9 Mgal/yr for domestic wells and 0.38 to 23.7 Mgal/yr for public supply. An approximate water budget for a typical year in the Chamokane Creek basin indicates that 19.6 in. of precipitation are balanced by 4.7 in. of streamflow discharge from the basin, and 14.9 in. of evapotranspiration.
Increased demands for cleaner burning energy, coupled with the relatively recent technological advances in accessing unconventional hydrocarbon-rich geologic formations, led to an intense effort to find and extract natural gas from various underground sources around the country. One of these sources, the Marcellus Shale, located in the Allegheny Plateau, is undergoing extensive drilling and production. The technology used to extract gas in the Marcellus Shale is known as hydraulic fracturing and has garnered much attention because of its use of large amounts of fresh water, its use of proprietary fluids for the hydraulic-fracturing process, its potential to release contaminants into the environment, and its potential effect on water resources. Nonetheless, development of natural gas extraction wells in the Marcellus Shale is only part of the overall natural gas story in the area of Pennsylvania. Coalbed methane, which is sometimes extracted using the same technique, is often located in the same general area as the Marcellus Shale and is frequently developed in clusters across the landscape. The combined effects of these two natural gas extraction methods create potentially serious patterns of disturbance on the landscape. This document quantifies the landscape changes and consequences of natural gas extraction for Bradford County and Washington County, Pennsylvania, between 2004 and 2010. Patterns of landscape disturbance related to natural gas extraction activities were collected and digitized using National Agriculture Imagery Program (NAIP) imagery for 2004, 2005/2006, 2008, and 2010. The disturbance patterns were then used to measure changes in land cover and land use using the National Land Cover Database (NLCD) of 2001. A series of landscape metrics is used to quantify these changes and are included in this publication.
Predicting species distributions at scales of regions to continents is often necessary, as large-scale phenomena influence the distributions of spatially structured populations. Land use and land cover are important large-scale drivers of species distributions, and landscapes are known to create species occurrence thresholds, where small changes in a landscape characteristic results in abrupt changes in occurrence. The value of the landscape characteristic at which this change occurs is referred to as a change point. We present a hierarchical Bayesian threshold model (HBTM) that allows for estimating spatially varying parameters, including change points. Our model also allows for modeling estimated parameters in an effort to understand large-scale drivers of variability in land use and land cover on species occurrence thresholds. We use range-wide detection/nondetection data for the eastern brook trout ( Salvelinus fontinalis ), a stream-dwelling salmonid, to illustrate our HBTM for estimating and modeling spatially varying threshold parameters in species occurrence. We parameterized the model for investigating thresholds in landscape predictor variables that are measured as proportions, and which are therefore restricted to values between 0 and 1. Our HBTM estimated spatially varying thresholds in brook trout occurrence for both the proportion agricultural and urban land uses. There was relatively little spatial variation in change point estimates, although there was spatial variability in the overall shape of the threshold response and associated uncertainty. In addition, regional mean stream water temperature was correlated to the change point parameters for the proportion of urban land use, with the change point value increasing with increasing mean stream water temperature. We present a framework for quantify macrosystem variability in spatially varying threshold model parameters in relation to important large-scale drivers such as land use and land cover. Although the model presented is a logistic HBTM, it can easily be extended to accommodate other statistical distributions for modeling species richness or abundance.
Increased demands for cleaner burning energy, coupled with the relatively recent technological advances in accessing unconventional hydrocarbon-rich geologic formations, have led to an intense effort to find and extract natural gas from various underground sources around the country. One of these sources, the Marcellus Shale, located in the Allegheny Plateau, is currently undergoing extensive drilling and production. The technology used to extract gas in the Marcellus shale is known as hydraulic fracturing and has garnered much attention because of its use of large amounts of fresh water, its use of proprietary fluids for the hydraulic-fracturing process, its potential to release contaminants into the environment, and its potential effect on water resources. Nonetheless, development of natural gas extraction wells in the Marcellus Shale is only part of the overall natural gas story in the area of Pennsylvania. Coalbed methane, which is sometimes extracted using the same technique, is commonly located in the same general area as the Marcellus Shale and is frequently developed in clusters across the landscape. The combined effects of these two natural gas extraction methods create potentially serious patterns of disturbance on the landscape. This document quantifies the landscape changes and consequences of natural gas extraction for Greene County and Tioga County in Pennsylvania between 2004 and 2010. Patterns of landscape disturbance related to natural gas extraction activities were collected and digitized using National Agriculture Imagery Program (NAIP) imagery for 2004, 2005/2006, 2008, and 2010. The disturbance patterns were then used to measure changes in land cover and land use using the National Land Cover Database (NLCD) of 2001. A series of landscape metrics are also used to quantify these changes and are included in this publication.
Increased demands for cleaner burning energy, coupled with the relatively recent technological advances in accessing unconventional hydrocarbon-rich geologic formations, have led to an intense effort to find and extract natural gas from various underground sources around the country. One of these sources, the Marcellus Shale, located in the Allegheny Plateau, is currently undergoing extensive drilling and production. The technology used to extract gas in the Marcellus Shale is known as hydraulic fracturing and has garnered much attention because of its use of large amounts of fresh water, its use of proprietary fluids for the hydraulic-fracturing process, its potential to release contaminants into the environment, and its potential effect on water resources. Nonetheless, development of natural gas extraction wells in the Marcellus Shale is only part of the overall natural gas story in this area of Pennsylvania. Coalbed methane, which is sometimes extracted using the same technique, is commonly located in the same general area as the Marcellus Shale and is frequently developed in clusters of wells across the landscape. The combined effects of these two natural gas extraction methods create potentially serious patterns of disturbance on the landscape. This document quantifies the landscape changes and consequences of natural gas extraction for Allegheny County and Susquehanna County in Pennsylvania between 2004 and 2010. Patterns of landscape disturbance related to natural gas extraction activities were collected and digitized using National Agriculture Imagery Program (NAIP) imagery for 2004, 2005/2006, 2008, and 2010. The disturbance patterns were then used to measure changes in land cover and land use using the National Land Cover Database (NLCD) of 2001. A series of landscape metrics is also used to quantify these changes and is included in this publication.