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USGS2005

Comparison of constitutive flow resistance equations based on the Manning and Chezy equations applied to natural rivers

A set of conceptually derived in‐bank river discharge–estimating equations (models), based on the Manning and Chezy equations, are calibrated and validated using a database of 1037 discharge measurements in 103 rivers in the United States and New Zealand. The models are compared to a multiple regression model derived from the same data. The comparison demonstrates that in natural rivers, using an exponent on the slope variable of 0.33 rather than the traditional value of 0.5 reduces the variance associated with estimating flow resistance. Mean model uncertainty, assuming a constant value for the conductance coefficient, is less than 5% for a large number of estimates, and 67% of the estimates would be accurate within 50%. The models have potential application where site‐specific flow resistance information is not available and can be the basis for (1) a general approach to estimating discharge from remotely sensed hydraulic data, (2) comparison to slope‐area discharge estimates, and (3) large‐scale river modeling.

Water Resources Research↗

USGS2015

Valuing geospatial information: Using the contingent valuation method to estimate the economic benefits of Landsat satellite imagery

While the U.S. government does not charge for downloading Landsat images, the images have value to users. This paper demonstrates a method that can value Landsat and other imagery to users. A survey of downloaders of Landsat images found: (a) established US users have a mean value of $912 USD per scene; (b) new US users and users returning when imagery became free have a mean value of $367 USD per scene. Total US user benefits for the 2.38 million scenes downloaded is $1.8 billion USD. While these benefits indicate a high willingness-to-pay among many Landsat downloaders, it would be economically inefficient for the US government to charge for Landsat imagery. Charging a price of $100 USD a scene would result in an efficiency loss of $37.5 million a year. This economic information should be useful to policy-makers who must decide about the future of this and similar remote sensing programs.

Photogrammetric Engineering and Remote Sensing↗

USGS2001

Environmental studies of the World Trade Center area after the September 11, 2001 attack

This web site describes the results of an interdisciplinary environmental characterization of the World Trade Center (WTC) area after September 11, 2001. Information presented in this site was first made available to the World Trade Center emergency response teams on September 18, 2001 (Thermal hot spot information), and September 27, 2001 (maps and compositional results). The Airborne Visible / Infrared Imaging Spectrometer (AVIRIS), a hyperspectral remote sensing instrument, was flown by JPL/NASA over the World Trade Center (WTC) area on September 16, 18, 22, and 23, 2001 ( Link to the AVIRIS JPL data facility) . A 2-person USGS crew collected samples of dusts and airfall debris from more than 35 localities within a 1-km radius of the World trade Center site on the evenings of September 17 and 18, 2001. Two samples were collected of indoor locations that were presumably not affected by rainfall (there was a rainstorm on September 14). Two samples of material coating a steel beam in the WTC debris were also collected. The USGS ground crew also carried out on-the-ground reflectance spectroscopy measurements during daylight hours to field calibrate AVIRIS remote sensing data. Radiance calibration and rectification of the AVIRIS data were done at JPL/NASA. Surface reflectance calibration, spectral mapping, and interpretation were done at the USGS Imaging Spectroscopy Lab in Denver. The dust/debris and beam-insulation samples were analyzed for a variety of mineralogical and chemical parameters using Reflectance Spectroscopy (RS), Scanning Electron Microscopy (SEM), X-Ray Diffraction (XRD), chemical analysis, and chemical leach test techniques in U.S. Geological Survey laboratories in Denver, Colorado.

New York↗

USGS1996

Geologic Map of the Cascade Head Area, Northwestern Oregon Coast Range (Neskiwin, Nestucca Bay, Hebo, and Dolph 7.5 minute Quadrangles)

The geology of the Cascade Head area bridges the geology in the Tillamook Highlands to the north (Wells and others, 1994; 1995) with that of the Newport Embayment on the south (Snavely and others, 1976 a,b,c). The four 7.5-minute quadrangles (Neskowin, Nestucca Bay, Hebo, and Dolph) which comprise the Cascade Head area include significant stratigraphic, structural, and igneous data that are essential in unraveling the geology of the northern and central part of the Oregon Coast Range and of the adjacent continental shelf Earlier studies (Snavely and Vokes, 1949) were of a broad reconnaissance nature because of limited access in this rugged, densely forested part of the Siuslaw National Forest. Also, numerous thick sills of late middle Eocene diabase and middle Miocene basalt mask the Eocene stratigraphic relationships. Previous mapping was hampered by a lack of precise biostratigraphic data. However, recent advances in biostratigraphy and radiometric age dating and geochemistry have provided the necessary tools to decipher stratigraphic and structural relationships in the Eocene sedimentary and volcanic rock sequences (W.W. Rau, personal communication, 1978 to 1988; Bukry and Snavely, 1988). Many important stratigraphic and igneous relationships are displayed within the Casacde Head area: (1) turbidite sandstone of the middle Eocene Tyee Formation, which is widespread in the central and southern part of the Oregon Coast Range (Snavely and others, 1964), was not deposited in the western part of the Cascade Head, and is of limited extent north of the map area (Wells and others, 1994); (2) the late middle Eocene Yamhill Formation, which crops out along the west and east flank of the Oregon Coast Range, overlaps older strata and overlies an erosional unconformity on the lower Eocene Siletz River Volcanics (Snavely and others, 1990; 1991); (3) thick sills of late middle Eocene diabase (43 Ma) are widespread in the Cascade Head area and also form much of the eastern flank of the Tillamook Highlands (Wells and others, 1994), but are rare south of the map area; (4) Cascade Head is the northernmost eruptive center of late Eocene alkalic basalts--85 km north of the eruptive center of correlative alkalic flows of the Yachats Basalt in the Newport Embayment (Snavely and Vokes, 1949; Snavely and others, 1990; Barnes and Barnes, 1992; Davis and others, 1995); (5) early Oligocene (33 Ma) sills and dikes of nepheline syenite and camptonite present in the Newport Embayment (Snavely and Wagner, 1961) are not found in the Cascade Head area; (6) extensive middle Oligocene (30 Ma) granophyric gabbro sills that are widespread in the central part of the Oregon Coast Range (Snavely and Wagner, 1961; MacLeod, 1969) are not present in the Cascade Head area. The Cascade Head area is the last segment of the Oregon Coast to receive detailed geologic mapping. Increased logging operations in the 1970's and 1980's created numerous new roadcut exposures and access to exposures in stream beds. More importantly, microfossil biostratigraphic control, available since 1970, based upon foraminifer determinations by W.W. Rau and nannofossil determinations by David Bukry provided critical information on stratigraphic succession as well as on depositional environments of the deep water (bathyal) siltstone units present in much of the Cascade Head area. These paleontologic data also permitted correlations with other sedimentary sequences mapped in the Newport Embayment and in the Tillamook Highlands as well as in western Washington. New 7.5-minute topographic maps and aerial photographs which became available in the late 1980's provided detailed topography which can be related to the distribution of thick sills and broad landslide areas, as well as a precise geographic relationship of geologic observations in this densely forested and brush-covered terrain. New geographic information systems (GIS) technology has produced a digitized color map of the Cascade Head area that combines the four 7.5-minute quadrangles that previously were open-filed as separate black and white 7.5-minute quadrangles (Snavely and others, 1990; 1990a; 1991; 1993). The tectonic framework and stratigraphic architecture presented on the map of the Cascade Head area was obtained by classic geologic field methods. This information could have been obtained only through detailed observation and sampling along stream beds, road cuts, and outcrops. Remote sensing techniques were of minor help in unraveling the geology in this poorly exposed and complex terrain, a terrain that characterizes much of the Oregon and Washington Coast Ranges.

Oregon↗

USGS2021

The effects of urban land cover dynamics on urban heat Island intensity and temporal trends

Assessments of surface urban heat island (UHI) have focused on using remote sensing and land cover data to quantify UHI intensity and spatial distribution within a certain time period by including land cover information. In this study, we implemented a prototype approach to characterize the spatiotemporal variations of UHI using time series of Landsat land surface temperature products and annual land change information. We analyzed UHI distribution and change in Sioux Falls, South Dakota, in the north-central United States and found that the mean UHI intensity in the region was as large as 2.2°C during the period 1986–2017 with an increasing trend of 0.02°C per year within the area with a 5-km non-urban extent. The UHI intensity associated with high intensity urban land cover usually is stronger than with low intensity urban land cover. We evaluated the impact of different non-urban reference extents on UHI variation using different non-urban buffers. The result also suggests that the overall temporal trends of UHI intensity are almost the same when using a 5-km or 10-km non-urban buffer surrounding the urban core. The prototype approach provides a framework to consistently quantify UHI and monitor its change to a large geographic extent.

South Dakota↗

USGS2024

Water-level changes impact angler effort in a large lake: Implications for climate change

Climate change is expected to influence aquatic habitats and associated fish populations, yet we know little about the impact on recreational anglers. Our goal was to explore whether interannual fluctuations in waterbody surface area and other explanatory variables could be used as indicators of changes in angler fishing effort. Our approach leveraged a combination of remotely sensed waterbody surface area, environmental and fish population data, and onsite angler survey monitoring data for Devils Lake, North Dakota, USA during the open-water fishing period (May 1st to August 31st) for 9 years (1992–2021). The information was used to develop a dynamic waterbody size-angler effort model. Changes in waterbody surface area reliably predicted changes in angler effort (r 2 = 0.60). Increases in waterbody surface area led to increases in angler effort, and decreases in waterbody surface area led to decreases in angler effort. Our findings show promise that remotely sensed fluctuations in waterbody surface area could be used as an indicator of interannual angler effort dynamics. Dynamic waterbody size-angler effort models could provide managers the ability to predict changes in angler effort via climate-related hydrological cycles that affect the size and distribution of waterbodies on the landscape.

North Dakota↗

USGS2024

Hyperspectral Image Transects during Transient Events in Rivers (HITTER): Framework development and application to a tracer experiment on the Missouri River, USA

Rivers convey a broad range of materials, such as sediment, nutrients, and contaminants. Much of this transport can occur during or immediately after an episodic, pulsed event like a flood or an oil spill. Understanding the flow processes that influence the motion of these substances is important for managing water resources and conserving aquatic ecosystems. This study introduces a new remote sensing framework for characterizing dynamic phenomena at the scale of a channel cross-section: Hyperspectral Image Transects during Transient Events in Rivers (HITTER). We present a workflow that uses repeated hyperspectral scan lines acquired from a hovering uncrewed aircraft system (UAS) to quantify how a water attribute of interest varies laterally across the river and evolves over time. Data from a tracer experiment on the Missouri River are used to illustrate the components of the end-to-end processing chain we used to quantify the passage of a visible dye. The framework is intended to be flexible and could be applied in a number of different contexts. The results of this initial proof-of-concept investigation suggest that HITTER could potentially provide insight regarding the dispersion of a range of materials in rivers, which would facilitate ecological and geomorphic studies and help inform management.

Remote Sensing↗

USGS2026

Evaluating approximations of river channel shape using a national cross section database

Many hydrologic applications require basic information on the size and shape of river channels, but measuring cross section (XS) geometry in the field or via remote sensing can be costly and often provides only partial coverage. Given these challenges, we capitalized upon an existing data set of 46,971 XS from gaging stations to evaluate various approximations of channel shape. After screening and pre-processing these data, we fit four model types to each XS, including a new approach that involves Stacking PDFs (probability density functions) to Approximate River Channel Shapes (SPARCS). This framework produced depth estimates that closely matched field measurements, with typical cross-sectional area errors <1 % and a median R 2 of 0.77 for comparison of observed and predicted depths. SPARCS model parameters can be interpreted in terms of channel characteristics: mean depth, asymmetry, bar convexity, and flatness of the bed. The model performed well for the XS included in the database, which was biased toward straight, uniform channels conducive to operational streamflow measurement. Neither model parameters nor accuracy were dependent on discharge. We also assessed the potential of SPARCS to fill in measurement gaps and found that although the model can help, the accuracy of inferred depths decreased as the observable fraction of the channel decreased. An important limitation of SPARCS is that mid-channel bars or multi-threaded morphologies cannot be produced. Graphical tools can help visualize how model parameters affect simulated river forms. SPARCS could facilitate satellite-based discharge estimation by providing prior information on channel shape.

Water Resources Research↗

USGS1973

Remote sensing and photogrammetric studies: Part C: comparison between photogrammetric and bistatic-radar slope-frequency distributions

Stereoscopic photographs taken by the metric and panoramic cameras can be used to obtain information on the roughness and slope-frequency distributions of lunar surfaces (see appendix to this part). Bistatic radar on board Apollo 14, 15, and 16 spacecraft may also be used to obtain information on lunar surface roughness at two wavelengths—13 cm (S-band) and 116 cm (VHF).

Book chapter↗

USGS2007

Estimating Water Storage Capacity of Existing and Potentially Restorable Wetland Depressions in a Subbasin of the Red River of the North

Executive Summary Concern over flooding along rivers in the Prairie Pothole Region has stimulated interest in developing spatially distributed hydrologic models to simulate the effects of wetland water storage on peak river flows. Such models require spatial data on the storage volume and interception area of existing and restorable wetlands in the watershed of interest. In most cases, information on these model inputs is lacking because resolution of existing topographic maps is inadequate to estimate volume and areas of existing and restorable wetlands. Consequently, most studies have relied on wetland area to volume or interception area relationships to estimate wetland basin storage characteristics by using available surface area data obtained as a product from remotely sensed data (e.g., National Wetlands Inventory). Though application of areal input data to estimate volume and interception areas is widely used, a drawback is that there is little information available to provide guidance regarding the application, limitations, and biases associated with such approaches. Another limitation of previous modeling efforts is that water stored by wetlands within a watershed is treated as a simple lump storage component that is filled prior to routing overflow to a pour point or gaging station. This approach does not account for dynamic wetland processes that influence water stored in prairie wetlands. Further, most models have not considered the influence of human-induced hydrologic changes, such as land use, that greatly influence quantity of surface water inputs and, ultimately, the rate that a wetland basin fills and spills. The goals of this study were to (1) develop and improve methodologies for estimating and spatially depicting wetland storage volumes and interceptions areas and (2) develop models and approaches for estimating/simulating the water storage capacity of potentially restorable and existing wetlands under various restoration, land use, and climatic scenarios. To address these goals, we developed models and approaches to spatially represent storage volumes and interception areas of existing and potentially restorable wetlands in the upper Mustinka subbasin within Grant County, Minn. We then developed and applied a model to simulate wetland water storage increases that would result from restoring 25 and 50 percent of the farmed and drained wetlands in the upper Mustinka subbasin. The model simulations were performed during the growing season (May-October) for relatively wet (1993; 0.79 m of precipitation) and dry (1987; 0.40 m of precipitation) years. Results from the simulations indicated that the 25 percent restoration scenario would increase water storage by 21-24 percent and that a 50 percent scenario would increase storage by 34-38 percent. Additionally, we estimated that wetlands in the subbasin have potential to store 11.57-20.98 percent of the total precipitation that fell over the entire subbasin area (52,758 ha). Our simulation results indicated that there is considerable potential to enhance water storage in the subbasin; however, evaluation and calibration of the model is necessary before simulation results can be applied to management and planning decisions. In this report we present guidance for the development and application of models (e.g., surface area-volume predictive models, hydrology simulation model) to simulate wetland water storage to provide a basis from which to understand and predict the effects of natural or human-induced hydrologic alterations. In developing these approaches, we tried to use simple and widely available input data to simulate wetland hydrology and predict wetland water storage for a specific precipitation event or a series of events. Further, the hydrology simulation model accounted for land use and soil type, which influence surface water inputs to wetlands. Although information presented in this report is specific to the Mustinka subbasin, the approaches

Open-File Report↗

USGS2012

Regional scale impacts of Tamarix leaf beetles ( Diorhabda carinulata ) on the water availability of western U.S. rivers as determined by multi-scale remote sensing methods

Tamarix leaf beetles ( Diorhabda carinulata ) have been widely released on western U.S. rivers to control introduced shrubs in the genus Tamarix . Part of the motivation to control Tamarix is to salvage water for human use. Information is needed on the impact of beetles on Tamarix seasonal leaf production and subsequent water use overwide areas andmultiple cycles of annual defoliation.Herewe combine ground data with high resolution phenocam imagery and moderate resolution (Landsat) and coarser resolution (MODIS) satellite imagery to test the effects of beetles on Tamarix evapotranspiration (ET) and leaf phenology at sites on six western rivers. Satellite imagery covered the period 2000 to 2010 which encompassed years before and after beetle release at each study site. Phenocam images showed that beetles reduced green leaf cover of individual canopies by about 30% during a 6-8 week period in summer, but plants produced new leaves after beetles became dormant in August, and over three years no net reduction in peak summer leaf production was noted. ETwas estimated by vegetation index methods, and both Landsat and MODIS analyses showed that beetles reduced ET markedly in the first year of defoliation, but ET recovered in subsequent years. Over all six sites, ET decreased by 14% to 15% by Landsat and MODIS estimates, respectively. However, resultswere variable among sites, ranging fromno apparent effect on ET to substantial reduction in ET. Baseline ET rates before defoliation were low, 394 mmyr -1 by Landsat and 314 mm yr -1 by MODIS estimates (20-25% of potential ET), further constraining the amount of water that could be salvaged. Beetle- Tamarix interactions are in their early stage of development on this continent and it is too soon to predict the eventual extent towhich Tamarix populationswill be reduced. The utility of remote sensing methods for monitoring defoliation was constrained by the small area covered by each phenocamimage, the low temporal resolution of Landsat, and the lowspatial resolution ofMODIS imagery. Even combined image sets did not adequately reveal the details of the defoliation process, and remote sensing data should be combined with ground observations to develop operational monitoring protocols.

Colorado;Nevada;Utah;Wyoming↗

USGS2022

Multi-species inference of exotic annual and native perennial grasses in rangelands of the western United States using Harmonized Landsat and Sentinel-2 data

The invasion of exotic annual grass (EAG), e.g., cheatgrass ( Bromus tectorum ) and medusahead ( Taeniatherum caput-medusae ), into rangeland ecosystems of the western United States is a broad-scale problem that affects wildlife habitats, increases wildfire frequency, and adds to land management costs. However, identifying individual species of EAG abundance from remote sensing, particularly at early stages of invasion or growth, can be problematic because of overlapping controls and similar phenological characteristics among native and other exotic vegetation. Subsequently, refining and developing tools capable of quantifying the abundance and phenology of annual and perennial grass species would be beneficial to help inform conservation and management efforts at local to regional scales. Here, we deploy an enhanced version of the U.S. Geological Survey Rangeland Exotic Plant Monitoring System to develop timely and accurate maps of annual (2016–2020) and intra-annual (May 2021 and July 2021) abundances of exotic annual and perennial grass species throughout the rangelands of the western United States. This monitoring system leverages field observations and remote-sensing data with artificial intelligence/machine learning to rapidly produce annual and early season estimates of species abundances at a 30-m spatial resolution. We introduce a fully automated and multi-task deep-learning framework to simultaneously predict and generate weekly, near-seamless composites of Harmonized Landsat Sentinel-2 spectral data. These data, along with auxiliary datasets and time series metrics, are incorporated into an ensemble of independent XGBoost models. This study demonstrates that inclusion of the Normalized Difference Vegetation Index and Normalized Difference Wetness Index time-series data generated from our deep-learning framework enables near real-time and accurate mapping of EAG (Median Absolute Error (MdAE): 3.22, 2.72, and 0.02; and correlation coefficient (r): 0.82, 0.81, and 0.73; respectively for EAG, cheatgrass, and medusahead) and native perennial grass abundance (MdAE: 2.51, r:0.72 for Sandberg bluegrass ( Poa secunda )). Our approach and the resulting data provide insights into rangeland grass dynamics, which will be useful for applications, such as fire and drought monitoring, habitat suitability mapping, as well as land-cover and land-change modelling. Spatially explicit, timely, and accurate species-specific abundance datasets provide invaluable information to land managers.

western United States↗

USGS2019

A space-time geostatistical model for probabilistic estimation of harmful algal bloom biomass and areal extent

Harmful algal blooms (HABs) have been increasing in intensity across many waterbodies worldwide, including the western basin of Lake Erie. Substantial efforts have been made to track these blooms using in situ sampling and remote sensing. However, such measurements do not fully capture HAB spatial and temporal dynamics due to the limitations of discrete shipboard sampling over large areas and the effects of clouds and winds on remote sensing estimates. To address these limitations, we develop a space-time geostatistical modeling framework to improve estimates of HAB timing, extent, and intensity using five independent sets of chlorophyll a (chl-a) data sampled from June to October, 2008 to 2017. Based on the Bayesian information criterion for model selection, trend variables explain bloom northerly and easterly expansion from Maumee Bay, wind effects over depth, and variability among sampling methods. Cross validation results indicate the model can estimate daily, location-specific chl-a concentrations with reasonable accuracy (R2 = 55%) between monitoring cruises. Conditional simulations provide probabilistic estimates of algal biomass and surface areal extent, which are compared to remote sensing estimates. The simulations also provide, for the first time, comprehensive estimates of overall bloom biomass based on depth-integrated concentrations, with quantified uncertainties. These estimates enhance our understanding of HAB variability and can inform HAB monitoring network design, predictive modeling, and management.

Lake Erie↗

USGS2016

Forecasting tidal marsh elevation and habitat change through fusion of Earth observations and a process model

Reducing uncertainty in data inputs at relevant spatial scales can improve tidal marsh forecasting models, and their usefulness in coastal climate change adaptation decisions. The Marsh Equilibrium Model (MEM), a one-dimensional mechanistic elevation model, incorporates feedbacks of organic and inorganic inputs to project elevations under sea-level rise scenarios. We tested the feasibility of deriving two key MEM inputs—average annual suspended sediment concentration (SSC) and aboveground peak biomass—from remote sensing data in order to apply MEM across a broader geographic region. We analyzed the precision and representativeness (spatial distribution) of these remote sensing inputs to improve understanding of our study region, a brackish tidal marsh in San Francisco Bay, and to test the applicable spatial extent for coastal modeling. We compared biomass and SSC models derived from Landsat 8, DigitalGlobe WorldView-2, and hyperspectral airborne imagery. Landsat 8-derived inputs were evaluated in a MEM sensitivity analysis. Biomass models were comparable although peak biomass from Landsat 8 best matched field-measured values. The Portable Remote Imaging Spectrometer SSC model was most accurate, although a Landsat 8 time series provided annual average SSC estimates. Landsat 8-measured peak biomass values were randomly distributed, and annual average SSC (30 mg/L) was well represented in the main channels (IQR: 29–32 mg/L), illustrating the suitability of these inputs across the model domain. Trend response surface analysis identified significant diversion between field and remote sensing-based model runs at 60 yr due to model sensitivity at the marsh edge (80–140 cm NAVD88), although at 100 yr, elevation forecasts differed less than 10 cm across 97% of the marsh surface (150–200 cm NAVD88). Results demonstrate the utility of Landsat 8 for landscape-scale tidal marsh elevation projections due to its comparable performance with the other sensors, temporal frequency, and cost. Integration of remote sensing data with MEM should advance regional projections of marsh vegetation change by better parameterizing MEM inputs spatially. Improving information for coastal modeling will support planning for ecosystem services, including habitat, carbon storage, and flood protection.

California↗

USGS2011

Land use and habitat conditions across the southwestern Wyoming sagebrush steppe: development impacts, management effectiveness and the distribution of invasive plants

For the past several years, USGS has taken a multi-faceted approach to investigating the condition and trends in sagebrush steppe ecosystems. This recent effort builds upon decades of work in semi-arid ecosystems providing a specific, applied focus on the cumulative impacts of expanding human activities across these landscapes. Here, we discuss several on-going projects contributing to these efforts: (1) mapping and monitoring the distribution and condition of shrub steppe communities with local detail at a regional scale, (2) assessing the relationships between specific, land-use features (for example, roads, transmission lines, industrial pads) and invasive plants, including their potential (environmentally defined) distribution across the region, and (3) monitoring the effects of habitat treatments on the ecosystem, including wildlife use and invasive plant abundance. This research is focused on the northern sagebrush steppe, primarily in Wyoming, but also extending into Montana, Colorado, Utah and Idaho. The study area includes a range of sagebrush types (including, Artemisia tridentata ssp. tridentata, Artemisia tridentata ssp. wyomingensis, Artemisia tridentata ssp. vaseyana, Artemisia nova) and other semi-arid shrubland types (for example, Sarcobatus vermiculatus, Atriplex confertifolia, Atriplex gardneri), impacted by extensive interface between steppe ecosystems and industrial energy activities resulting in a revealing multiple-variable analysis. We use a combination of remote sensing (AWiFS (1 Any reference to platforms, data sources, equipment, software, patented or trade-marked methods is for information purposes only. It does not represent endorsement of the U.S.D.I., U.S.G.S. or the authors), Landsat and Quickbird platforms), Geographic Information System (GIS) design and data management, and field-based, replicated sampling to generate multiple scales of data representing the distribution of shrub communities for the habitat inventory. Invasive plant sampling focused on the interaction between human infrastructure and weedy plant distributions in southwestern Wyoming, while also capturing spatial variability associated with growing conditions and management across the region. In a separate but linked study, we also sampled native and invasive composition of recent and historic habitat treatments. Here, we summarize findings of this ongoing work, highlighting patterns and relationships between vegetation (native and invasive), land cover, landform, and land-use patterns in the sagebrush steppe.

Wyoming↗

USGS1976

Integration of geological remote-sensing techniques in subsurface analysis

Geological remote sensing is defined as the study of the Earth utilizing electromagnetic radiation which is either reflected or emitted from its surface in wavelengths ranging from 0.3 micrometre to 3 metres. The natural surface of the Earth is composed of a diversified combination of surface cover types, and geologists must understand the characteristics of surface cover types to successfully evaluate remotely-sensed data. In some areas landscape surface cover changes throughout the year, and analysis of imagery acquired at different times of year can yield additional geological information. Integration of different scales of analysis allows landscape features to be effectively interpreted. Interpretation of the static elements displayed on imagery is referred to as an image interpretation. Image interpretation is dependent upon: (1) the geologist's understanding of the fundamental aspects of image formation, and (2.) his ability to detect, delineate, and classify image radiometric data; recognize radiometric patterns; and identify landscape surface characteristics as expressed on imagery. A geologic interpretation integrates surface characteristics of the landscape with subsurface geologic relationships. Development of a geologic interpretation from imagery is dependent upon: (1) the geologist's ability to interpret geomorphic processes from their static surface expression as landscape characteristics on imagery, (2) his ability to conceptualize the dynamic processes responsible for the evolution 6f interpreted geologic relationships (his ability to develop geologic models). The integration of geologic remote-sensing techniques in subsurface analysis is illustrated by development of an exploration model for ground water in the Tucson area of Arizona, and by the development of an exploration model for mineralization in southwest Idaho.

Open-File Report↗

USGS1988

Water-resources activities of the U.S. Geological Survey in Texas– Fiscal year 1987

The U.S. Geological Survey (USGS) was established by an act of Congress on March 3, 1879, to provide a permanent Federal agency to conduct the systematic and scientific classification of the public lands and to examine the geological structure, mineral resources, and products of national domain. An integral part of that original mission includes publishing and disseminating the earth science information needed to understand, to plan the use of, and to manage the Nation's energy, land, mineral, and water resources. Since 1879, the research and fact-finding role of the USGS has grown and been modified to meet the changing needs of the Nation it serves. As part of that evolution, the USGS has become the Federal Government's largest earthscience research agency, the Nation's largest civilian mapmaking agency, the primary source of data on the Nation's surface- and ground-water resources, and the employer of the largest number of professional earth scientists. Today's programs serve a diversity of needs and users. Programs include: Conducting detailed assessments of the energy and mineral potential of the Nation's land and offshore areas. Investigating and issuing warnings of earthquakes, volcanic eruptions, landslides, and other geologic and hydrologic hazards. Conducting research on the geologic structure of the Nation. Studying the geologic features, structure, processes, and history of the other planets of our solar system. Conducting topographic surveys of the Nation and preparing topographic and thematic maps and related cartographic products. Developing and producing digital cartographic data bases and products. Collecting data on a routine basis to determine the quantity, quality, and use of surface and ground water. Conducting water-resources appraisals in order to describe the consequences of alternative plans for developing land and water resources. Conducting research in hydraulics and hydrology and coordinating all Federal water-data acquisition. Using remotely sensed data to develop new cartographic, geologic, and hydrologic research techniques for natural resources planning and management. Providing earth-science information through an extensive publications program and a network of public access points. Along with its continuing commitment to meet the growing and changing earthscience information needs of the Nation, the USGS remains dedicated to its original mission to collect, analyze, interpret, publish, and disseminate information about the natural resources of the Nation providing "earth science in the public service."

Texas↗

USGS1985

Water-resources activities of the U.S. Geological Survey in Texas; fiscal years 1982-84

The U.S. Geological Survey (USGS) was established by an act of Congress on March 3, 1879, to provide a permanent Federal agency to conduct the systematic and scientific classification of the public lands, and examination of the geological structure, mineral resources, and products of national domain. An integral part of that original mission includes publishing and disseminating the earth-science information needed to understand, to plan the use of, and to manage the Nation's energy, land, mineral, and water resources. Since 1879, the research and fact-finding role of the USGS has grown and been modified to meet the changing needs of the Nation it serves. As part of that evolution, the USGS has become the Federal Government's largest earth-science research agency, the Nation's largest civilian mapmaking agency, the primary source of data on the Nation's surface- and ground-water resources, and the employer of the largest number of professional earth scientists. Today's programs serve a diversity of needs and users. Programs include: Conducting detailed assessments of the energy and mineral potential of the Nation's land and offshore areas. Investigating and issuing warnings of earthquakes, volcanic eruptions, landslides, and other geologic and hydrologic hazards. Conducting research on the geologic structure of the Nation. Studying the geologic features, structure, processes, and history of the other planets of our solar system. Conducting topographic surveys of the Nation and preparing topographic and thematic maps and related cartographic products. Developing and producing digital cartographic data bases and products. Collecting data on a routine basis to determine the quantity, quality, and use of surface and ground water. Conducting water-resources appraisals in order to describe the consequences of alternative plans for developing land and water resources. Conducting research in hydraulics and hydrology and coordinating all Federal water-data acquisition. Using remotely sensed data to develop new cartographic, geologic, and hydrologic research techniques for natural resources planning and management. Providing earth-science information through an extensive publications program and a network of public access points. Along with its continuing commitment to meet the growing and changing earthscience information needs of the Nation, the USGS remains dedicated to its original mission to collect, analyze, interpret, publish, and disseminate information about the natural resources of the Nation providing "earth science in the public service."

Open-File Report↗