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At least 1,657 records · Page 92Linked to original sources

USGS2019

The Value of Data – The Qatar Geologic Mapping Project

The State of Qatar is in a period of rapid development, modernization, and population growth. One of the most important factors influencing the long-term success and sustainability of future development is a comprehensive understanding of the region’s geologic regime, geotechnical conditions, natural resources, and environmental constraints. To obtain this understanding, the Ministry of Municipality and Environment (MME) of the State of Qatar has undertaken the Qatar Geological Mapping Project (QGMP). The project was envisioned with the strategic foresight to compile and utilize existing and legacy subsurface data collected as part of its massive infrastructure and development projects as the foundation for developing modern scientific resources including geologic maps, digital thematic maps, and a 3-dimensional geological model of the Doha metropolitan area. Recently, the MME, in consultation with Gannett Fleming, Inc. (GF) and the United States Geological Survey (USGS) concluded the data collection and analysis phase (Phase I) of the two-phase QGMP. Phase I included: the development of a comprehensive geotechnical relational database populated with data digitized from more than 13,000 subsurface data logs; a detailed data quality analysis and distribution assessment; an extensive gap analysis and needs assessment; and careful design of the geologic mapping and subsurface investigation programs for the next phase of the project.

Conference Paper↗

USGS2024

Fine-resolution land cover mapping over large and mountainous areas for Lāna‘i, Hawaii using posterior probabilities, and expert knowledge

The task of accurately mapping species-specific vegetation cover in remote and topographically complex regions like those found in Hawaiʻi presents unique challenges. This study leverages a machine learning approach to accurately classify vegetation into fine species-specific classes across the island of Lāna‘i, Hawaii, offering a novel methodology for tackling such challenges. Utilizing high-resolution WordView-2 satellite imagery, a neural network classifier and a custom lidar-based geometric correction, we introduced two new approaches to refine our high-resolution land cover classifications. This included the implementation of prior-based adjustments to class posterior probabilities to enhance land cover classification accuracy. Moreover, we developed mixed hierarchical classification maps that use class posterior probabilities to identify, at the pixel level, the finest land cover class that meets a user-defined confidence threshold. The resulting high-resolution land cover map for Lāna‘i captures the rich diversity and distribution of native and invasive plant species with high overall accuracy, generally exceeding 95%, based on independent ground control data. The capacity to produce wall-to-wall species-level vegetation maps provides a new window into monitoring vegetation dynamics on Lāna‘i and similarly remote and topographically complex regions, and contributes to our broader understanding of ecosystem responses to invasive species, climatic changes, and land management practices such as erosion and sediment control planning. Our approach offers a blueprint for similar efforts in other complex and remote ecosystems.

Hawaii↗

USGS2015

Landscape prediction and mapping of game fish biomass, an ecosystem service of Michigan rivers

The increased integration of ecosystem service concepts into natural resource management places renewed emphasis on prediction and mapping of fish biomass as a major provisioning service of rivers. The goals of this study were to predict and map patterns of fish biomass as a proxy for the availability of catchable fish for anglers in rivers and to identify the strongest landscape constraints on fish productivity. We examined hypotheses about fish responses to total phosphorus (TP), as TP is a growth-limiting nutrient known to cause increases (subsidy response) and/or decreases (stress response) in fish biomass depending on its concentration and the species being considered. Boosted regression trees were used to define nonlinear functions that predicted the standing crops of Brook Trout Salvelinus fontinalis , Brown Trout Salmo trutta , Smallmouth Bass Micropterus dolomieu , panfishes (seven centrarchid species), and Walleye Sander vitreus by using landscape and modeled local-scale predictors. Fitted models were highly significant and explained 22–56% of the variation in validation data sets. Nonlinear and threshold responses were apparent for numerous predictors, including TP concentration, which had significant effects on all except the Walleye fishery. Brook Trout and Smallmouth Bass exhibited both subsidy and stress responses, panfish biomass exhibited a subsidy response only, and Brown Trout exhibited a stress response. Maps of reach-specific standing crop predictions showed patterns of predicted fish biomass that corresponded to spatial patterns in catchment area, water temperature, land cover, and nutrient availability. Maps illustrated predictions of higher trout biomass in coldwater streams draining glacial till in northern Michigan, higher Smallmouth Bass and panfish biomasses in warmwater systems of southern Michigan, and high Walleye biomass in large main-stem rivers throughout the state. Our results allow fisheries managers to examine the biomass potential of streams, describe geographic patterns of fisheries, explore possible nutrient management targets, and identify habitats that are candidates for species management.

Michigan↗

USGS2002

Fuzzy logic merger of spectral and ecological information for improved montane forest mapping.

Environmental data are often utilized to guide interpretation of spectral information based on context, however, these are also important in deriving vegetation maps themselves, especially where ecological information can be mapped spatially. A vegetation classification procedure is presented which combines a classification of spectral data from Landsat‐5 Thematic Mapper (TM) and environmental data based on topography and fire history. These data were combined utilizing fuzzy logic where assignment of each pixel to a single vegetation category was derived comparing the partial membership of each vegetation category within spectral and environmental classes. Partial membership was assigned from canopy cover for forest types measured from field sampling. Initial classification of spectral and ecological data produced map accuracies of less than 50% due to overlap between spectrally similar vegetation and limited spatial precision for predicting local vegetation types solely from the ecological information. Combination of environmental data through fuzzy logic increased overall mapping accuracy (70%) in coniferous forest communities of northwestern Montana, USA.

Montana↗

USGS2005

Mapping impervious surface type and sub-pixel abundance using Hyperion hyperspectral imagery

Impervious surfaces have been identified as an important and quantifiable indicator of environmental degradation in urban settings. A number of research efforts have been directed at mapping impervious surface type using multispectral imagery. To date, however, no studies have compared equivalent techniques using multispectral and hyperspectral imagery to that end. In this study, data from NASA's 220‐channel Hyperion instrument were used to: a) delineate three types of impervious surface, and b) map sub‐pixel percent abundance for a study site near Washington, D.C., USA. The results were compared with the results of similar methods using same‐spatial‐resolution Landsat ETM+ data for mapping impervious surface type, and with the results of the U.S. Geological Survey's National Land Cover Data (NLCD) 2001 impervious surface data layer, which is derived from Landsat and high‐resolution Ikonos data. The accuracy of discriminating impervious surface type using Hyperion data was assessed at 88% versus Landsat at 59%. The sub‐pixel percent impervious map corresponded well with the NLCD 2001; impervious surface in the study area was calculated at 29.3% for NLCD 2001 and 28.4% for the Hyperion‐derived layer. The results suggest that fairly simple techniques using hyperspectral data are effective for quantifying impervious surface type, and that high‐spectral‐resolution imagery may be a good alternative to high‐spatial‐resolution data.

Geocarto International↗

USGS2023

Mapping high marsh and salt pannes/flats along the northern Gulf of Mexico coast

Coastal wetlands are predicted to undergo extensive transformation due to climate and land use change. Baseline maps of coastal wetlands can be used to help assess changes. Found in the upper portion of the estuarine zone, high marsh and salt pannes/flats provide ecosystem goods and services and are particularly important to fish and wildlife. We developed the first map of high marsh and salt pannes/flats along the northern Gulf of Mexico using regional models that included spectral indices related to greenness and wetness from optical satellite imagery, elevation data, irregularly flooded wetland probability information, and synthetic aperture radar backscatter. We found the greatest relative coverage of high marsh along the Texas coast (30% to 65%) and the Florida Panhandle (40%), whereas the greatest relative coverage of salt pannes/flats was along the lower Texas coast (74%) and the middle Texas coast (15%). As part of this effort, we also developed a map that highlighted irregularly flooded wetlands dominated by Juncus roemerianus (black needlerush) for part of the study area. Both maps had an overall accuracy of around 80%. Our results advance the understanding of estuarine marsh zonation and provide a baseline for assessing future transformations.

Alabama, Florida, Louisiana, Mississippi, Texas↗

USGS1988

Developing of 10-year EEZ seafloor mapping and research program

Mapping and research on the seafloor adjacent to the United States has been a national effort involving elements of the Department of the Interior, the Department of Commerce, certain academic institutions, and private industry, the latter primarily for the exploration for oil and gas. These activities were accelerated by the USGS and NOAA in 1983, following the issuance of the EEZ (Exclusive Economic Zone) Proclamation by President Reagan. The intent of expanding the exploration already begun on the outer continental shelf (OCS) to the frontier of the EEZ is to determine the “characteristics”; and resource potential of this region. To coordinate this exploration , a Joint Office for Mapping and Research (JOMAR) has been established by the U.S. Geological Survey (in the Department of the Interior) and the National Oceanic and Atmospheric Administration (in the Department of Commerce). JOMAR's main purpose is to help direct and coordinate ongoing and planned seafloor related activities in the EEZ and prepare a 10 ‐ year plan for mapping and research . JOMAR recently hosted a national symposium to identify the major elements of this plan . A comprehensive mapping and research plan will provide the needed direction and guide this national challenge.

Marine Geodesy↗

USGS2022

Simulating burn severity maps at 30 meters in two forested regions in California

Climate change is altering wildfire behavior and vegetation regimes in California’s forested ecosystems. Present day fires are seeing an increase in high burn severity area and high severity patch size. The ability to predict future burn severity patterns would support better policy and land management decisions. Here we demonstrate a methodology to first, statistically estimate individual burn severity classes at 30 meters and second, cluster and smooth high severity patches onto a landscape. Our goal here was not to exactly replicate observed burn severity maps, but rather to utilize observed maps as one realization of a random process dependent on climate, topography, fire weather, and fuels, to inform creation of additional realizations through our simulation technique. We developed two sets of empirical models with two different vegetation datasets to test if coarse vegetation could accurately model for burn severity. While visual acuity can be used to assess the performance of our simulation process, we also employ the Ripley’s K function to compare spatial point processes at different scales to test if the simulation is capturing an appropriate amount of clustering. We utilize FRAGSTATS to obtain high severity patch metrics to test the contiguity of our high severity simulation. Ripley’s K function helped identify the number of clustering iterations and FRAGSTATS showed how different focal window sizes affected our ability to cluster high severity patches. High severity patch simulations was comparable between the coarse and fine resolution vegetation datasets. Improving our ability to simulate burn severity will help advance our understanding of the potential influence of land and fuels management on ecosystem-level response variables that are important for decision-makers. Simulated burn severity maps can support managing habitat and estimating risks of habitat loss, protecting infrastructure and homes, improving future wildfire emissions projections, and better mapping and planning for fuels treatment scenarios.

California↗

USGS2023

Maps of active layer thickness in northern Alaska by upscaling P-band polarimetric synthetic aperture radar retrievals

Extensive, detailed information on the spatial distribution of active layer thickness (ALT) in northern Alaska and how it evolves over time could greatly aid efforts to assess the effects of climate change on the region and also help to quantify greenhouse gas emissions generated due to permafrost thaw. For this reason, we have been developing high-resolution maps of ALT throughout northern Alaska. The maps are produced by upscaling from high-resolution swaths of estimated ALT retrieved from airborne P-band synthetic aperture radar (SAR) images collected for three different years. The upscaling was accomplished by using hundreds of thousands of randomly selected samples from the SAR-derived swaths of ALT to train a machine learning regression algorithm supported by numerous spatial data layers. In order to validate the maps, thousands of randomly selected samples of SAR-derived ALT were excluded from the training in order to serve as validation pixels; error performance calculations relative to these samples yielded root-mean-square errors (RMSEs) of 7.5–9.1 cm, with bias errors of magnitude under 0.1 cm. The maps were also compared to ALT measurements collected at a number of in situ test sites; error performance relative to the site measurements yielded RMSEs of approximately 11–12 cm and bias of 2.7–6.5 cm. These data are being used to investigate regional patterns and underlying physical controls affecting permafrost degradation in the tundra biome.

Environmental Research Letters↗

USGS2021

Mineral Mapping of the Battle Mountain District, Nevada, USA, Using AVIRIS-Classic and SpecTIR Inc. AisaFENIX 1K Imaging Spectrometer Datasets

Imaging spectroscopy (hyperspectral imaging) has been used to successfully map minerals at the outcrop, deposit, district, and regional scale. This contribution presents spectral-based mineral maps of the Battle Mountain mining district, Nevada, USA, generated using multi-scale airborne imaging and ground-based point spectrometers. Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and AisaFENIX 1K imaging spectrometer data were processed using Atmospheric and Topographic Correction (ATCOR-4) software with an empirical correction multiplier derived from field data. Data were used to generate spectral-based mineral maps with spatial resolutions of 13.5 and 1.8 m. A comparison of the various radiative transfer models used to convert radiance data to reflectance indicated that the ATCOR4 rugged model performed best for these datasets. These mineral maps were then used to spectrally characterize two potential porphyry mineral targets in the district.

Nevada↗

USGS2017

Estimating floodwater depths from flood inundation maps and topography

Information on flood inundation extent is important for understanding societal exposure, water storage volumes, flood wave attenuation, future flood hazard, and other variables. A number of organizations now provide flood inundation maps based on satellite remote sensing. These data products can efficiently and accurately provide the areal extent of a flood event, but do not provide floodwater depth, an important attribute for first responders and damage assessment. Here we present a new methodology and a GIS-based tool, the Floodwater Depth Estimation Tool (FwDET), for estimating floodwater depth based solely on an inundation map and a digital elevation model (DEM). We compare the FwDET results against water depth maps derived from hydraulic simulation of two flood events, a large-scale event for which we use medium resolution input layer (10 m) and a small-scale event for which we use a high-resolution (LiDAR; 1 m) input. Further testing is performed for two inundation maps with a number of challenging features that include a narrow valley, a large reservoir, and an urban setting. The results show FwDET can accurately calculate floodwater depth for diverse flooding scenarios but also leads to considerable bias in locations where the inundation extent does not align well with the DEM. In these locations, manual adjustment or higher spatial resolution input is required.

Journal of the American Water Resources Associatio↗

USGS2022

DSWEmod - The production of high-frequency surface water map composites from daily MODIS images

Optical satellite imagery is commonly used for monitoring surface water dynamics, but clouds and cloud shadows present challenges in assembling complete water time series. To test whether the daily revisit rate of Moderate Resolution Imaging Spectroradiometer (MODIS) satellite imagery can reduce cloud obstruction and improve high-frequency surface water mapping, we compared map results derived from Landsat (30-m) and MODIS (250-m) data across the state of California for 2003–2019. We adapted the Dynamic Surface Water Extent (DSWE) model in Google Earth Engine to generate surface water map composites from MODIS imagery every 5, 10, 15, and 30 days, and compared products to monthly Landsat-based DSWE maps. Results for DSWEmod (DSWE MODIS) in California suggest that more than 5% data loss (cloud obstruction, etc.) was present in only 2% of the 15-day time series, as compared to 32% of the monthly Landsat DSWE time series. The five-day DSWEmod composites averaged 8.4% obscuration in the winter months. Area estimates derived from cloud-filtered MODIS and Landsat monthly products have the highest linear correlations compared to streamgage discharge records, suggesting that monthly scale analyses best explain the relationship between surface water area and general streamflow dynamics. Shorter-interval DSWEmod products have lower correlations but utility for understanding the timing of surface water peaks and past flood events.

Journal of the American Water Resources Associatio↗

USGS2017

Integrating future scenario‐based crop expansion and crop conditions to map switchgrass biofuel potential in eastern Nebraska, USA

Switchgrass ( Panicum virgatum ) has been evaluated as one potential source for cellulosic biofuel feedstocks. Planting switchgrass in marginal croplands and waterway buffers can reduce soil erosion, improve water quality, and improve regional ecosystem services (i.e. it serves as a potential carbon sink). In previous studies, we mapped high risk marginal croplands and highly erodible cropland buffers that are potentially suitable for switchgrass development, which would improve ecosystem services and minimally impact food production. In this study, we advance our previous study results and integrate future crop expansion information to develop a switchgrass biofuel potential ensemble map for current and future croplands in eastern Nebraska. The switchgrass biomass productivity and carbon benefits (i.e. NEP: net ecosystem production) for the identified biofuel potential ensemble areas were quantified. The future scenario‐based (‘A1B’) land use and land cover map for 2050, the US Geological Survey crop type and Compound Topographic Index (CTI) maps, and long‐term (1981–2010) averaged annual precipitation data were used to identify future crop expansion regions that are suitable for switchgrass development. Results show that 2528 km 2 of future crop expansion regions (~3.6% of the study area) are potentially suitable for switchgrass development. The total estimated biofuel potential ensemble area (including cropland buffers, marginal croplands, and future crop expansion regions) is 4232 km 2 (~6% of the study area), potentially producing 3.52 million metric tons of switchgrass biomass per year. Converting biofuel ensemble regions to switchgrass leads to potential carbon sinks (the total NEP for biofuel potential areas is 0.45 million metric tons C) and is environmentally sustainable. Results from this study improve our understanding of environmental conditions and ecosystem services of current and future cropland systems in eastern Nebraska and provide useful information to land managers to make land use decisions regarding switchgrass development.

Nebraska↗

USGS2018

Mapping cropland waterway buffers for switchgrass development in the eastern Great Plains, USA

Switchgrass ( Panicum virgatum L.), a highly productive perennial grass, has been recommended as one potential source for cellulosic biofuel feedstocks. Previous studies indicate that planting perennial grasses (e.g., switchgrass) in high‐topographic‐relief cropland waterway buffers can improve local environmental conditions and sustainability. The main advantages of this land management practice include (i) reducing soil erosion and improving water quality because switchgrass requires less tillage, fertilizers, and pesticides; and (ii) improving regional ecosystem services (e.g., improving water infiltration, minimizing drought and flood impacts on production, and serving as carbon sinks). In this study, we mapped high‐topographic‐relief cropland waterway buffers with high switchgrass productivity potential that may be suitable for switchgrass development in the eastern Great Plains (EGP). The US Geological Survey (USGS) Compound Topographic Index map, National Land Cover Database 2011, USGS irrigation map, and a switchgrass biomass productivity map derived from a previous study were used to identify the switchgrass potential areas. Results show that about 16 342 km 2 ( c . 1.3% of the total study area) of cropland waterway buffers in the EGP are potentially suitable for switchgrass development. The total annual estimated switchgrass biomass production for these suitable areas is approximately 15 million metric tons. Results from this study provide useful information on EGP areas with good cellulosic switchgrass biomass production potential and synergistic substantial potential for improvement of ecosystem services.

Great Plains↗

USGS2006

Use of plume mapping data to estimate chlorinated solvent mass loss

Results from a plume mapping study from November 2000 through February 2001 in the sand-and-gravel surficial aquifer at Dover Air Force Base, Delaware, were used to assess the occurrence and extent of chlorinated solvent mass loss by calculating mass fluxes across two transverse cross sections and by observing changes in concentration ratios and mole fractions along a longitudinal cross section through the core of the plume. The plume mapping investigation was conducted to determine the spatial distribution of chlorinated solvents migrating from former waste disposal sites. Vertical contaminant concentration profiles were obtained with a direct-push drill rig and multilevel piezometers. These samples were supplemented with additional ground water samples collected with a minipiezometer from the bed of a perennial stream downgradient of the source areas. Results from the field program show that the plume, consisting mainly of tetrachloroethylene (PCE), trichloroethene (TCE), and cis-1,2-dichloroethene (cis-1,2-DCE), was approximately 670 m in length and 120 m in width, extended across much of the 9- to 18-m thickness of the surficial aquifer, and discharged to the stream in some areas. The analyses of the plume mapping data show that losses of the parent compounds, PCE and TCE, were negligible downgradient of the source. In contrast, losses of cis-1,2-DCE, a daughter compound, were observed in this plume. These losses very likely resulted from biodegradation, but the specific reaction mechanism could not be identified. This study demonstrates that plume mapping data can be used to estimate the occurrence and extent of chlorinated solvent mass loss from biodegradation and assess the effectiveness of natural attenuation as a remedial measure.

Ground Water Monitoring and Remediation↗

USGS2001

High-resolution aeromagnetic data, a new tool for mapping intrabasinal faults: Example from the Albuquerque basin, New Mexico

High-resolution aeromagnetic surveys flown over the Albuquerque basin, New Mexico, demonstrate that aeromagnetic methods can successfully map concealed and poorly exposed faults in sediment-filled basins. This is the first known use of aeromagnetic data as an aid to surficial mapping and hydrogeologic studies in a basin. Aeromagnetic maps show detailed fault patterns within the basin fill that revise the structural view of the basin. Concealed faults are more numerous and more closely spaced than expected. The Hubbell Springs fault is the central splay of three generally north-striking fault splays that can be traced for nearly 50 km. The splays converge on the north and may represent the southern extension of the Tijeras fault, contradicting the proposed southwest extension of the Tijeras fault across the basin. In profile view, the linear aeromagnetic anomalies associated with faults show a variety of signatures. One signature has potential for mapping fault-controlled sedimentation in the subsurface because it identifies increases in magnetic, likely coarse-grained, material in the hanging walls of faults.

New Mexico↗

USGS2008

Shallow landslide hazard map of Seattle, Washington

Landslides, particularly debris flows, have long been a significant cause of damage and destruction to people and property in the Puget Sound region. Following the years of 1996 and 1997, the Federal Emergency Management Agency designated Seattle as a “Project Impact” city with the goal of encouraging the city to become more disaster resistant to landslides and other natural hazards. A major recommendation of the Project Impact council was that the city and the U.S. Geological Survey collaborate to produce a landslide hazard map. An exceptional data set archived by the city containing more than 100 yr of landslide data from severe storm events allowed comparison of actual landslide locations with those predicted by slope-stability modeling. We used an infinite-slope analysis, which models slope segments as rigid friction blocks, to estimate the susceptibility of slopes to debris flows, which are water-laden slurries that can form from shallow failures of soil and weathered bedrock and can travel at high velocities down steep slopes. Data used for the analysis consisted of a digital slope map derived from recent light detection and ranging (LiDAR) imagery of Seattle, recent digital geologic mapping of the city, and shear-strength test data for the geologic units found in the surrounding area. The combination of these data layers within a geographic information system (GIS) platform allowed us to create a shallow landslide hazard map for Seattle.

Washington↗

USGS2010

Geologic map of Lake Mead and surrounding regions, southern Nevada, southwestern Utah, and northwestern Arizona

Regional stratigraphic units and structural features of the Lake Mead region are presented as a 1:250,000 scale map, and as a Geographic Information System database. The map, which was compiled from existing geologic maps of various scales, depicts geologic units, bedding and foliation attitudes, faults and folds. Units and structural features were generalized to highlight the regional stratigraphic and tectonic aspects of the geology of the Lake Mead region. This map was prepared in support of the papers presented in this volume, Special Paper 463, as well as to facilitate future investigations in the region. Stratigraphic units exposed within the area record 1800 million years of geologic history and include Proterozoic crystalline rocks, Paleozoic and Mesozoic sedimentary rocks, Mesozoic plutonic rocks, Cenozoic volcanic and intrusive rocks, sedimentary rocks and surficial deposits. Following passive margin sedimentation in the Paleozoic and Mesozoic, late Mesozoic (Sevier) thrusting and Late Cretaceous and early Tertiary compression produced major folding, reverse faulting, and thrust faulting in the Basin and Range, and resulted in regional uplift and monoclinal folding in the Colorado Plateau. Cenozoic extensional deformation, accompanied by sedimentation and volcanism, resulted in large-magnitude high- and low-angle normal faulting and strike-slip faulting in the Basin and Range; on the Colorado Plateau, extension produced north-trending high-angle normal faults. The latest history includes integration of the Colorado River system, dissection, development of alluvial fans, extensive pediment surfaces, and young faulting. Stratigraphic units exposed within the area record 1800 million years of geologic history and include Proterozoic crystalline rocks, Paleozoic and Mesozoic sedimentary rocks, Mesozoic plutonic rocks, Cenozoic volcanic and intrusive rocks, sedimentary rocks and surfi cial deposits. Following passive margin sedimentation in the Paleozoic and Mesozoic, late Mesozoic (Sevier) thrusting and Late Cretaceous and early Tertiary compression produced major folding, reverse faulting, and thrust faulting in the Basin and Range, and resulted in regional uplift and monoclinal folding in the Colorado Plateau. Cenozoic extensional deformation, accompanied by sedimentation and volcanism, resulted in large-magnitude high- and low-angle normal faulting and strike-slip faulting in the Basin and Range; on the Colorado Plateau, extension produced north-trending high-angle normal faults. The latest history includes integration of the Colorado River system, dissection, development of alluvial fans, extensive pediment surfaces, and young faulting.

Arizona, Nevada, Utah↗