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

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At least 649 records · Page 36Linked to original sources
USGS2017

Ecology and space: A case study in mapping harmful invasive species

The establishment and invasion of non-native plant species have the ability to alter the composition of native species and functioning of ecological systems with financial costs resulting from mitigation and loss of ecological services. Spatially documenting invasions has applications for management and theory, but the utility of maps is challenged by availability and uncertainty of data, and the reliability of extrapolating mapped data in time and space. The extent and resolution of projections also impact the ability to inform invasive species science and management. Early invasive species maps were coarse-grained representations that underscored the phenomena, but had limited capacity to direct management aside from development of watch lists for priorities for prevention and containment. Integrating mapped data sets with fine-resolution environmental variables in the context of species-distribution models allows a description of species-environment relationships and an understanding of how, why, and where invasions may occur. As with maps, the extent and resolution of models impact the resulting insight. Models of cheatgrass ( Bromus tectorum ) across a variety of spatial scales and grain result in divergent species-environment relationships. New data can improve models and efficiently direct further inventories. Mapping can target areas of greater model uncertainty or the bounds of modeled distribution to efficiently refine models and maps. This iterative process results in dynamic, living maps capable of describing the ongoing process of species invasions.

Book chapter↗
USGS1992

Environmental benefits vs. costs of geologic mapping

Boone and Winnebago Counties, Illinois, U.S.A., were selected for this study, required by the Illinois State Senate, because mapping and environmental interpretations were completed there in 1981. Costs of geologic mapping in these counties in 1990 dollars were $290,000. Two estimates of costs of statewide mapping were made, one extrapolated from Boone and Winnebago Counties ($21 million), the other estimated on the basis of differences between the Boone/Winnebago program and proposed mapping program for the State of Illinois ($55 million). Benefits of geologic information come in the form of future avoided costs for environmental cleanup. Only the quantifiable data, available from a few sites, were included. Data collection, based on 55 personal interviews in Boone and Winnebago Counties, were grouped into four cumulative categories with increasing variability. Geologic maps alone cannot account for all avoided costs of future cleanup. Therefore, estimated benefits were reduced by 50, 75, and 90 percent in three scenarios. To account for delays in proper utilization of knowledge gained from a mapping program, a 10-yr delay in benefit realization was assumed. All benefits were converted to 1990 dollars. In benefit category 4, benefit-cost ratios for Boone/Winnebago Counties ranged between 5 and 55. Statewide projection of benefits was based on county areas and an aquifer contamination potential score for each county. Statewide benefit-cost ratio in benefit category 4 ranged from 1.2 to 14 ($21 million mapping costs) and from 0.5 to 5.4 ($55 million mapping costs). ?? 1992 Springer-Verlag New York Inc.

Environmental Geology and Water Sciences↗
USGS1985

Global geologic mapping of Mars: The western equatorial region

Global geologic mapping of Mars was originally accomplished following acquisition of orbital spacecraft images from the Mariner 9 mission. The mapping program represented a joint enterprise by the U.S. Geological Survey and other planetary scientists from universities in the United States and Europe. Many of the Mariner photographs had low resolution or poor albedo contrast caused by atmospheric haze and high-sun angles. Some of the early geologic maps reflect these deficiencies in their poor discrimination and subdivision of rock units. New geologic maps made from higher resolution and better quality Viking images also represent a cooperative effort, by geologists from the U.S. Geological Survey, Arizona State University, and the University of London. This second series of global maps consists of three parts: 1) western equatorial region, 2) eastern equatorial region, and 3) north and south polar regions. These maps, at 1:15 million scale, show more than 60 individual rock-stratigraphic units assigned to three Martian time-stratigraphic systems. The first completed map of the series covers the western equatorial region of Mars. Accompanying the map is a description of the sequence and distribution of major tectonic, volcanic, and fluvial episodes as recorded in the stratigraphic record. ?? 1985.

Advances in Space Research↗
USGS2023

Rapid estimation of minimum depth-to-bedrock from lidar leveraging deep-learning-derived surficial material maps

Previously glaciated landscapes often share similar surficial characteristics, including large areas of exposed bedrock, blankets of till deposits, and alluvium-floored valleys. These materials play significant roles in geologic and hydrologic resources, geohazards, and landscape evolution; however, the vast extents of many previously glaciated landscapes have rendered comprehensive, detailed field mapping difficult. While recent advances in remote sensing have facilitated mapping of surficial materials and landforms, manual map creation has remained a time-intensive task. The development of convolutional neural networks (CNNs) for image classification has provided a new opportunity for rapid characterization of digital elevation models, thus enabling efficient mapping of surficial materials and landforms. We have developed a methodology that leverages existing geologic maps and high-resolution (1–3 m) lidar data to train a U-Net CNN to classify alluvium and exposed bedrock in previously glaciated regions. Coupled with U.S. Geological Survey-developed geomorphometry tools capable of approximating stream incision depths, these classifications can be used to estimate the minimum thicknesses of stream-proximal hillslope sediments in areas where streams have undergone minimal incision into bedrock. We validate this approach in the context of the Neversink River watershed, a subbasin of the Delaware River Basin and significant water source for New York City. Evaluation of deep learning model performance demonstrates substantial agreement with manually drawn maps of alluvium and exposed bedrock. Validation of the minimum sediment thickness map using borehole data and passive seismic measurements shows the greatest performance for shallow materials and decreased performance in deep sediments, as well as in areas where bedrock exposures were too small to be resolved by lidar. To resolve these issues and create more accurate surficial maps, we are training new CNNs with additional geologic data and exploring advanced approaches for estimating depths of stream incision.

Delaware, New Jersey, New York, Pennsylvania↗
USGS2016

Comparing orbiter and rover image-based mapping of an ancient sedimentary environment, Aeolis Palus, Gale crater, Mars

This study provides the first systematic comparison of orbital facies maps with detailed ground-based geology observations from the Mars Science Laboratory (MSL) Curiosity rover to examine the validity of geologic interpretations derived from orbital image data. Orbital facies maps were constructed for the Darwin, Cooperstown, and Kimberley waypoints visited by the Curiosity rover using High Resolution Imaging Science Experiment (HiRISE) images. These maps, which represent the most detailed orbital analysis of these areas to date, were compared with rover image-based geologic maps and stratigraphic columns derived from Curiosity’s Mast Camera (Mastcam) and Mars Hand Lens Imager (MAHLI). Results show that bedrock outcrops can generally be distinguished from unconsolidated surficial deposits in high-resolution orbital images and that orbital facies mapping can be used to recognize geologic contacts between well-exposed bedrock units. However, process-based interpretations derived from orbital image mapping are difficult to infer without known regional context or observable paleogeomorphic indicators, and layer-cake models of stratigraphy derived from orbital maps oversimplify depositional relationships as revealed from a rover perspective. This study also shows that fine-scale orbital image-based mapping of current and future Mars landing sites is essential for optimizing the efficiency and science return of rover surface operations.

Icarus↗
USGS2020

Mapping croplands of Europe, Middle East, Russia, and Central Asia using Landsat 30-m data, machine learning algorithms and Google Earth Engine

Accurate and timely information on croplands is important for environmental, food security, and policy studies. Spatially explicit cropland datasets are also required to derive information on crop type, crop yield, cropping intensity, as well as irrigated areas. Large area defined as continental to global cropland mapping is challenging due to differential manifestation of croplands, wide range of cultivation practices and limited reference data availability. This study presents the results of a cropland extent mapping of 64 Countriescovering large parts of Europe, Middle East, Russia and Central Asia. To cover such a vast area, roughly 160,000 Landsat scenes from 3,351 footprints between 2014 and 2016 were processed within the Google Earth Engine (GEE) cloud-platform. We used the pixel-based supervised Random Forest (RF) machine learning algorithm with a set of satellite data inputs capturing diverse spectral, temporal and topographical characteristics across twelve agroecological zones (AEZs). The reference data to train the classification model were collected from very high spatial resolution imagery (VHRI) and ancillary datasets. The result is a binary map showing cultivated/non-cultivated areas ca. 2015. The map produced an overall accuracy of 94 percent with roughly 14 percent omission and commission errors for the cropland class based on a large set of independent validation samples. The map suggests the entire study area has a total 546 million hectares (Mha) of croplands occupying 18 percent of the land area. Comparison between national cropland area estimates from United Nations Food and Agricultural Organizations (FAO) and those derived from this work also showed an R-square value of 0.95. For the entire Landsat-derived 30-m product the overall accuracy was 93.8% with cropland class providing producers accuracy of 86.5% (errors of omissions = 13.5%) and users accuracy of 85.7% (errors of commissions = 14.3%). This Landsat-derived 30-m cropland product (GFSAD30) provided 10-30% greater cropland areas compared to UN FAO in the 64 Countries. Finally, the map-to-map comparison between GFSAD30 with several other cropland products revealed that the best similarity matrix was with the 30m global land cover (GLC30) product providing an overall accuracy of 88.8 percent (Kappa 0.7) with producers cropland similarity of 89.2 percent (errors of omissions = 10.8%) and users cropland similarity of 81.8 percent (errors of commissions = 8.1%). GFSAD30 captured the missing croplands in GLC30 product around significantly irrigated agricultural areas in Germany and Belgium and rainfed agriculture in Italy. This study also established that the real strength of GFSAD30 product, compared to other products, were in: 1. Identifying precise location of croplands, and 2. Capturing fragmented croplands. The cropland extent map dataset is available through NASAs Land Processes Distributed Active Archive Center (LP DAAC) at https://doi.org/10.5067/MEaSUREs/GFSAD/GFSAD30EUCEARUMECE.001, while the training and reference data as well as visualization are available at the Global Croplands website.

ISPRS Journal of Photogrammetry and Remote Sensing↗
USGS2008

Mapping invasive wetland plants in the Hudson River National Estuarine Research Reserve using quickbird satellite imagery

The National Estuarine Research Reserve (NERR) program is a nationally coordinated research and monitoring program that identifies and tracks changes in ecological resources of representative estuarine ecosystems and coastal watersheds. In recent years, attention has focused on using high spatial and spectral resolution satellite imagery to map and monitor wetland plant communities in the NERRs, particularly invasive plant species. The utility of this technology for that purpose has yet to be assessed in detail. To that end, a specific high spatial resolution satellite imagery, QuickBird, was used to map plant communities and monitor invasive plants within the Hudson River NERR (HRNERR). The HRNERR contains four diverse tidal wetlands (Stockport Flats, Tivoli Bays, Iona Island, and Piermont), each with unique water chemistry (i.e., brackish, oligotrophic and fresh) and, consequently, unique assemblages of plant communities, including three invasive plants (Trapa natans, Phragmites australis, and Lythrum salicaria). A maximum-likelihood classification was used to produce 20-class land cover maps for each of the four marshes within the HRNERR. Conventional contingency tables and a fuzzy set analysis served as a basis for an accuracy assessment of these maps. The overall accuracies, as assessed by the contingency tables, were 73.6%, 68.4%, 67.9%, and 64.9% for Tivoli Bays, Stockport Flats, Piermont, and Iona Island, respectively. Fuzzy assessment tables lead to higher estimates of map accuracies of 83%, 75%, 76%, and 76%, respectively. In general, the open water/tidal channel class was the most accurately mapped class and Scirpus sp. was the least accurately mapped. These encouraging accuracies suggest that high-resolution satellite imagery offers significant potential for the mapping of invasive plant species in estuarine environments. ?? 2007 Elsevier Inc. All rights reserved.

Remote Sensing of Environment↗
USGS2015

Developing a 30-m grassland productivity estimation map for central Nebraska using 250-m MODIS and 30-m Landsat-8 observations

Accurately estimating aboveground vegetation biomass productivity is essential for local ecosystem assessment and best land management practice. Satellite-derived growing season time-integrated Normalized Difference Vegetation Index (GSN) has been used as a proxy for vegetation biomass productivity. A 250-m grassland biomass productivity map for the Greater Platte River Basin had been developed based on the relationship between Moderate Resolution Imaging Spectroradiometer (MODIS) GSN and Soil Survey Geographic (SSURGO) annual grassland productivity. However, the 250-m MODIS grassland biomass productivity map does not capture detailed ecological features (or patterns) and may result in only generalized estimation of the regional total productivity. Developing a high or moderate spatial resolution (e.g., 30-m) productivity map to better understand the regional detailed vegetation condition and ecosystem services is preferred. The 30-m Landsat data provide spatial detail for characterizing human-scale processes and have been successfully used for land cover and land change studies. The main goal of this study is to develop a 30-m grassland biomass productivity estimation map for central Nebraska, leveraging 250-m MODIS GSN and 30-m Landsat data. A rule-based piecewise regression GSN model based on MODIS and Landsat (r = 0.91) was developed, and a 30-m MODIS equivalent GSN map was generated. Finally, a 30-m grassland biomass productivity estimation map, which provides spatially detailed ecological features and conditions for central Nebraska, was produced. The resulting 30-m grassland productivity map was generally supported by the SSURGO biomass production map and will be useful for regional ecosystem study and local land management practices.

Nebraska↗
USGS2002

A reconnaissance method for delineation of tracts for regional-scale mineral-resource assessment based on geologic-map data

The U.S. Geological Survey (USGS) is proposing to conduct a global mineral-resource assessment using geologic maps, significant deposits, and exploration history as minimal data requirements. Using a geologic map and locations of significant pluton-related deposits, the pluton-related-deposit tract maps from the USGS national mineral-resource assessment have been reproduced with GIS-based analysis and modeling techniques. Agreement, kappa, and Jaccard's C correlation statistics between the expert USGS and calculated tract maps of 87%, 40%, and 28%, respectively, have been achieved using a combination of weights-of-evidence and weighted logistic regression methods. Between the experts' and calculated maps, the ranking of states measured by total permissive area correlates at 84%. The disagreement between the experts and calculated results can be explained primarily by tracts defined by geophysical evidence not considered in the calculations, generalization of tracts by the experts, differences in map scales, and the experts' inclusion of large tracts that are arguably not permissive. This analysis shows that tracts for regional mineral-resource assessment approximating those delineated by USGS experts can be calculated using weights of evidence and weighted logistic regression, a geologic map, and the location of significant deposits. Weights of evidence and weighted logistic regression applied to a global geologic map could provide quickly a useful reconnaissance definition of tracts for mineral assessment that is tied to the data and is reproducible.

Natural Resources Research↗
USGS2001

Mapping wildland fuels for fire management across multiple scales: integrating remote sensing, GIS, and biophysical modeling

Fuel maps are essential for computing spatial fire hazard and risk and simulating fire growth and intensity across a landscape. However, fuel mapping is an extremely difficult and complex process requiring expertise in remotely sensed image classification, fire behavior, fuels modeling, ecology, and geographical information systems (GIS). This paper first presents the challenges of mapping fuels: canopy concealment, fuelbed complexity, fuel type diversity, fuel variability, and fuel model generalization. Then, four approaches to mapping fuels are discussed with examples provided from the literature: (1) field reconnaissance; (2) direct mapping methods; (3) indirect mapping methods; and (4) gradient modeling. A fuel mapping method is proposed that uses current remote sensing and image processing technology. Future fuel mapping needs are also discussed which include better field data and fuel models, accurate GIS reference layers, improved satellite imagery, and comprehensive ecosystem models.

International Journal of Wildland Fire↗
USGS2013

Overcoming the momentum of anachronism: American geologic mapping in a twenty-first-century world

The practice of geologic mapping is undergoing conceptual and methodological transformation. Profound changes in digital technology in the past 10 yr have potential to impact all aspects of geologic mapping. The future of geologic mapping as a relevant scientific enterprise depends on widespread adoption of new technology and ideas about the collection, meaning, and utility of geologic map data. It is critical that the geologic community redefine the primary elements of the traditional paper geologic map and improve the integration of the practice of making maps in the field and office with the new ways to record, manage, share, and visualize their underlying data. A modern digital geologic mapping model will enhance scientific discovery, meet elevated expectations of modern geologic map users, and accommodate inevitable future changes in technology.

GSA Special Papers↗
USGS2016

A multiagency and multijurisdictional approach to mapping the glacial deposits of the Great Lakes region in three dimensions

The Great Lakes Geologic Mapping Coalition (GLGMC), consisting of state geological surveys from all eight Great Lakes states, the Ontario Geological Survey, and the U.S. Geological Survey, was conceived out of a societal need for unbiased and scientifically defensible geologic information on the shallow subsurface, particularly the delineation, interpretation, and viability of groundwater resources. Only a small percentage (<10%) of the region had been mapped in the subsurface, and there was recognition that no single agency had the financial, intellectual, or physical resources to conduct such a massive geologic mapping effort at a detailed scale over a wide jurisdiction. The GLGMC provides a strategy for generating financial and stakeholder support for three-dimensional (3-D) geologic mapping, pooling of physical and personnel resources, and sharing of mapping and technological expertise to characterize the thick cover of glacial sediments. Since its inception in 1997, the GLGMC partners have conducted detailed surficial and 3-D geologic mapping within all jurisdictions, and concurrent significant scientific advancements have been made to increase understanding of the history and framework of geologic processes. More importantly, scientific information has been provided to public policymakers in understandable formats, emphasis has been placed on training early-career scientists in new mapping techniques and emerging technologies, and a successful model has been developed of state/provincial and federal collaboration focused on geologic mapping, as evidenced by this program's unprecedented and long-term successful experiment of 10 geological surveys working together to address common issues.

GSA Special Papers↗
USGS2000

Development of Maximum Considered Earthquake Ground Motion Maps

The 1997 NEHRP Recommended Provisions for Seismic Regulations for New Buildings use a design procedure that is based on spectral response acceleration rather than the traditional peak ground acceleration, peak ground velocity, or zone factors. The spectral response accelerations are obtained from maps prepared following the recommendations of the Building Seismic Safety Council's (BSSC) Seismic Design Procedures Group (SDPG). The SDPG-recommended maps, the Maximum Considered Earthquake (MCE) Ground Motion Maps, are based on the U.S. Geological Survey (USGS) probabilistic hazard maps with additional modifications incorporating deterministic ground motions in selected areas and the application of engineering judgement. The MCE ground motion maps included with the 1997 NEHRP Provisions also serve as the basis for the ground motion maps used in the seismic design portions of the 2000 International Building Code and the 2000 International Residential Code . Additionally the design maps prepared for the 1997 NEHRP Provisions , combined with selected USGS probabilistic maps, are used with the 1997 NEHRP Guidelines for the Seismic Rehabilitation of Buildings .

Earthquake Spectra↗
USGS2007

Lateral spread hazard mapping of the northern Salt Lake Valley, Utah, for a M7.0 scenario earthquake

This paper describes the methodology used to develop a lateral spread-displacement hazard map for northern Salt Lake Valley, Utah, using a scenario M7.0 earthquake occurring on the Salt Lake City segment of the Wasatch fault. The mapping effort is supported by a substantial amount of geotechnical, geologic, and topographic data compiled for the Salt Lake Valley, Utah. ArcGIS?? routines created for the mapping project then input this information to perform site-specific lateral spread analyses using methods developed by Bartlett and Youd (1992) and Youd et al. (2002) at individual borehole locations. The distributions of predicted lateral spread displacements from the boreholes located spatially within a geologic unit were subsequently used to map the hazard for that particular unit. The mapped displacement zones consist of low hazard (0-0.1 m), moderate hazard (0.1-0.3 m), high hazard (0.3-1.0 m), and very high hazard (> 1.0 m). As expected, the produced map shows the highest hazard in the alluvial deposits at the center of the valley and in sandy deposits close to the fault. This mapping effort is currently being applied to the southern part of the Salt Lake Valley, Utah, and probabilistic maps are being developed for the entire valley. ?? 2007, Earthquake Engineering Research Institute.

Earthquake Spectra↗
USGS2010

Seismic hazard mapping of California considering site effects

In this paper, we have combined the U.S. Geological Survey's National Seismic Hazard Maps model with the California geologic map showing 17 generalized geologic units that can be defined by their VS30. We regrouped these units into seven VS30 values and calculated a probabilistic seismic hazard map for the entire state for each VS30 value. By merging seismic hazard maps based on the seven different V S30 values, a suite of seismic hazard maps was computed for 0.2 and 1.0 s spectral ordinates at 2% probability of exceedance (PE) in 50 years. The improved hazards maps explicitly incorporate the site effects and their spatial variability on ground motion estimates. The spectral acceleration (SA) at 1.0 s map of seismic shaking potential for California has now been published as California Geological Survey Map Sheet 48.

California↗
USGS2018

Global Earthquake Model (GEM) Risk Map

The Global Earthquake Risk Map (v2018.1) comprises four global maps. The main map presents the geographic distribution of average annual loss (USD) normalized by the average construction costs of the respective country (USD/m2 due to ground shaking in the residential, commercial and industrial building stock, considering contents, structural and non-structural components. The normalized metric allows a direct comparison of the risk between countries with widely different construction costs. It does not consider the effects of tsunamis, liquefaction, landslides, and fires following earthquakes. The loss estimates are from direct physical damage to buildings due to shaking, and thus damage to infrastructure or indirect losses due to business interruption are not included. The Global Earthquake Hazard Map depicts the geographic distribution of the Peak Ground Acceleration (PGA) with a 10% probability of being exceeded in 50 years, computed for reference rock conditions (shear wave velocity of 760-800 m/s). The Global Exposure Map depicts the geographic distribution of residential, commercial and industrial buildings. The Global Seismic Fatalities Map depicts an estimate of average annual human losses due to earthquake-induced structural collapse of buildings. The results for human losses do not consider indirect fatalities such as those from post­ earthquake epidemics. The average annual losses and number of buildings are presented on a hexagonal grid, with a spacing of 0.30 x 0.34 decimal degrees (approximately 1,000 km2 at the equator). The average annual losses were computed using the event-based calculator of the OpenQuake engine, an open-source software for seismic hazard and risk analysis developed by the GEM Foundation. The seismic hazard, exposure and vulnerability models employed in these calculations were provided by national institutions, or developed within the scope of regional programs or bilateral collaborations. These global maps and the underlying databases are based on best available and publicly accessible datasets and models. Due to possible limitations in the model, regions portrayed with low risk may experience potentially damaging earthquakes. The GEM Risk Map is intended to be a dynamic product, which will be updated when new datasets and models become available. Updated versions of the hazard, exposure, and average annual losses will be released on a regular basis. Additional metrics for each country can be explored at globalquakemodel.org/gem.

Report↗
USGS2015

Vegetation burn severity mapping using Landsat-8 and WorldView-2

We used remotely sensed data from the Landsat-8 and WorldView-2 satellites to estimate vegetation burn severity of the Creek Fire on the San Carlos Apache Reservation, where wildfire occurrences affect the Tribe's crucial livestock and logging industries. Accurate pre- and post-fire canopy maps at high (0.5-meter) resolution were created from World- View-2 data to generate canopy loss maps, and multiple indices from pre- and post-fire Landsat-8 images were used to evaluate vegetation burn severity. Normalized difference vegetation index based vegetation burn severity map had the highest correlation coefficients with canopy loss map from WorldView-2. Two distinct approaches - canopy loss mapping from WorldView-2 and spectral index differencing from Landsat-8 - agreed well with the field-based burn severity estimates and are both effective for vegetation burn severity mapping. Canopy loss maps created with WorldView-2 imagery add to a short list of accurate vegetation burn severity mapping techniques that can help guide effective management of forest resources on the San Carlos Apache Reservation, and the broader fire-prone regions of the Southwest.

Photogrammetric Engineering and Remote Sensing↗
USGS2003

To the National Map and beyond

Scientific understanding, technology, and social, economic, and environmental conditions have driven a rapidly changing demand for geographic information, both digital and analog. For more than a decade, the U.S. Geological Survey (USGS) has been developing innovative partnerships with other government agencies and private industry to produce and distribute geographic information efficiently; increase activities in remote sensing to ensure ongoing monitoring of the land surface; and develop new understanding of the causes and consequences of land surface change. These activities are now contributing to a more robust set of geographic information called The National Map (TNM). The National Map is designed to provide an up-to-date, seamless, horizontally and vertically integrated set of basic digital geographic data, a frequent monitoring of changes on the land surface, and an understanding of the condition of the Earth's surface and many of the processes that shape it. The USGS has reorganized its National Mapping Program into three programs to address the continuum of scientific activities-describing (mapping), monitoring, understanding, modeling, and predicting. The Cooperative Topographic Mapping Program focuses primarily on the mapping and revision aspects of TNM. The National Map also includes results from the Land Remote Sensing and Geographic Analysis and Monitoring Programs that provide continual updates, new insights, and analytical tools. The National Map is valuable as a framework for current research, management, and operational activities. It also provides a critical framework for the development of distributed, spatially enabled decision support systems.

Cartography and Geographic Information Science↗