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At least 325 records · Page 18Linked to original sources
USGS1980

A survey of image processing developments in support of remote sensing

New algorithm developments for image processing (IP) will occur throughout the 1980's, resulting from evolution in computer hardware and sensors as well as continuing research. This report will describe the areas of algorithm development that are occurring in applications, research, and operational environments. Included is an overview of image processing activities at institutions which are generally regarded as leaders in IP algorithm development and implementation. Finally, this report addresses directions in IP algorithm development that are being proposed for the EROS Data Center (EDC). The major applications of IP at EDC are developed for use in the processing, analysis, and extraction of remote sensing information from Landsat and aircraft data (platforms).

Report↗
USGS2009

The emerging role of lidar remote sensing in coastal research and resource management

Knowledge of coastal elevation is an essential requirement for resource management and scientific research. Recognizing the vast potential of lidar remote sensing in coastal studies, this Special Issue includes a collection of articles intended to represent the state-of-the-art for lidar investigations of nearshore submerged and emergent ecosystems, coastal morphodynamics, and hazards due to sea-level rise and severe storms. Some current applications for lidar remote sensing described in this Special Issue include bluegreen wavelength lidar used for submarine coastal benthic environments such as coral reef ecosystems, airborne lidar used for shoreline mapping and coastal change detection, and temporal waveform-resolving lidar used for vegetation mapping.

Journal of Coastal Research↗
USGS2008

Technical Manual for the Geospatial Stream Flow Model (GeoSFM)

The monitoring of wide-area hydrologic events requires the use of geospatial and time series data available in near-real time. These data sets must be manipulated into information products that speak to the location and magnitude of the event. Scientists at the U.S. Geological Survey Earth Resources Observation and Science (USGS EROS) Center have implemented a hydrologic modeling system which consists of an operational data processing system and the Geospatial Stream Flow Model (GeoSFM). The data processing system generates daily forcing evapotranspiration and precipitation data from various remotely sensed and ground-based data sources. To allow for rapid implementation in data scarce environments, widely available terrain, soil, and land cover data sets are used for model setup and initial parameter estimation. GeoSFM performs geospatial preprocessing and postprocessing tasks as well as hydrologic modeling tasks within an ArcView GIS environment. The integration of GIS routines and time series processing routines is achieved seamlessly through the use of dynamically linked libraries (DLLs) embedded within Avenue scripts. GeoSFM is run operationally to identify and map wide-area streamflow anomalies. Daily model results including daily streamflow and soil water maps are disseminated through Internet map servers, flood hazard bulletins and other media.

Open-File Report↗
USGS2012

Novel approach for computing photosynthetically active radiation for productivity modeling using remotely sensed images in the Great Plains, United States

Gross primary production (GPP) is a key indicator of ecosystem performance, and helps in many decision-making processes related to environment. We used the Eddy covariancelight use efficiency (EC-LUE) model for estimating GPP in the Great Plains, United States in order to evaluate the performance of this model. We developed a novel algorithm for computing the photosynthetically active radiation (PAR) based on net radiation. A strong correlation ( R 2 =0.94, N =24) was found between daily PAR and Landsat-based mid-day instantaneous net radiation. Though the Moderate Resolution Spectroradiometer (MODIS) based instantaneous net radiation was in better agreement ( R 2 =0.98, N =24) with the daily measured PAR, there was no statistical significant difference between Landsat based PAR and MODIS based PAR. The EC-LUE model validation also confirms the need to consider biological attributes (C 3 versus C 4 plants) for potential light use efficiency. A universal potential light use efficiency is unable to capture the spatial variation of GPP. It is necessary to use C 3 versus C 4 based land use/land cover map for using EC-LUE model for estimating spatiotemporal distribution of GPP.

Journal of Applied Remote Sensing↗
USGS2019

Modeling long-term effects of fuel treatments on fuel loads and fire regimes in the Great Basin

The principal motivation for this study is that sagebrush-steppe ecosystems are undergoing significant state changes, and land managers are challenged with optimizing their resources for both short- and long-term use. Yet, limited knowledge is available regarding how the sagebrush-steppe will respond to environmental changes related to precipitation and temperature regimes, and disturbance such as fire. Furthermore, there is a lack of understanding on how fuels reduction and other fuel management activities will impact these ecosystems over the long-term. We addressed these challenges by adapting and testing a vegetation dynamics model, the Ecosystem Demography v2.2 model (EDv2.2), for the sagebrush-steppe. Vegetation dynamics models can provide estimations of ecosystem productivity in their natural and disturbance states, and thus serve as a tool to understand and predict potential changes in various processes and properties of vegetation communities. Yet, there is no vegetation dynamics model that is well-developed for the sagebrush-steppe, and thus significant effort is needed to test EDv2.2 for its application. As part of our efforts to develop the EDv2.2 model into a useful tool for the sagebrush-steppe, we developed a sagebrush plant functional type (PFT) as part of this study, and then performed sensitivity analyses, model calibration, and finally model evaluation. Furthermore, we developed several model scenarios under natural (undisturbed) and disturbed (fire) environments. We compared our model outputs with ground-based data (field and eddy covariance) and remote sensing observations. The results of our project include a sagebrush PFT that can be used in both future EDv2.2 modeling efforts and other vegetation dynamic models. Our results from the model sensitivity analysis indicate that specific leaf area (SLA), stomatal slope (STO_S), cuticular conductance (CUT_C), and carboxylase rate constant (VM0) are sensitive parameters to vegetation productivity in the model (based on gross primary production, GPP), and future modeling efforts will benefit from both lab and field studies of these parameters and sensitivity analyses. Through calibration, we found that the EDv2.2 model estimates of GPP were modeled well at our lowest elevation field site in Reynolds Creek Experimental Watershed (RCEW), which is dominated by Wyoming big sagebrush. On the contrary, we found poorer results at higher elevation site shrub sites. These sites are characterized by either low sagebrush or mountain big sagebrush, and have more forb cover than the low elevation site. In this project we also implemented the fire model in EDv2.2 to explore how shrub and C3 grasses respond to fire by analyzing post-fire GPP. We ran both point and regional model runs with fire introduced. In most fire scenarios, fire substantially reduced shrub GPP and it took several decades for shrub GPP to return to pre-fire conditions. Grass GPP responded more quickly in post-fire conditions. While these processes are representative of what other studies have found, significant efforts to improve the fire processes in EDv2.2 are needed. For example, nuances associated with the fire subroutine in the model (running periodic fire events versus instantaneous fires and fire intensity) will need to be expanded. Another significant contribution to our knowledge gap is that additional PFTs to represent the sagebrush-steppe (e.g. annual grasses such cheatgrass) are needed for EDv2.2. Regardless, this project made significant advances in PFT development and model testing. Moreover, the EDv2.2 provides a useful framework to conceptualize vegetation dynamics, project future conditions, and consider fire as a disturbance. With additional parameterizations, PFTs, and fire routines, EDv2.2 will evolve as a tool for which to better understand future ecosystem dynamics of the sagebrush-steppe.

Idaho↗
USGS2015

High-resolution remote sensing of water quality in the San Francisco Bay-Delta Estuary

The San Francisco Bay–Delta Estuary watershed is a major source of freshwater for California and a profoundly human-impacted environment. The water quality monitoring that is critical to the management of this important water resource and ecosystem relies primarily on a system of fixed water-quality monitoring stations, but the limited spatial coverage often hinders understanding. Here, we show how the latest technology in visible/near-infrared imaging spectroscopy can facilitate water quality monitoring in this highly dynamic and heterogeneous system by enabling simultaneous depictions of several water quality indicators at very high spatial resolution. The airborne portable remote imaging spectrometer (PRISM) was used to derive high-spatial-resolution (2.6 × 2.6 m) distributions of turbidity, and dissolved organic carbon (DOC) and chlorophyll-a concentrations in a wetland-influenced region of this estuary. A filter-passing methylmercury vs DOC relationship was also developed using in situ samples and enabled the high-spatial-resolution depiction of surface methylmercury concentrations in this area. The results illustrate how high-resolution imaging spectroscopy can inform management and policy development in important inland and estuarine water bodies by facilitating the detection of point- and nonpoint-source pollution, and by providing data to help assess the complex impacts of wetland restoration and climate change on water quality and ecosystem productivity.

California↗
USGS2023

Monitoring long-term changes of urban surface temperature using time-series land cover and remote sensing data across 50 major cities in the United States

The increase of developed land changes the Earth’s ecosystems and, in doing so, impacts the natural environment and further affects the services it provides to humans. Urban growth and associated land cover transitions alter the thermal and physical properties of the land surface, resulting in surface temperature change in urban areas. In this study, we integrated both land cover and surface temperature information to characterize surface temperature spatiotemporal variations using the recently available time series of Landsat land surface temperature and annual land change products. We analyzed over thirty-year trends of land surface temperature (LST) in urban and surrounding non-urban lands. We found that the transitions of different land cover types to urban affected urban LST trends differently, and further impacted the temporal trend of urban heat island intensity.

continental United States↗
USGS2025

Offsetting the noise: A framework for applying phenological offset corrections in remotely sensed burn severity assessments

Background Phenological correction of pre- and post-fire imagery is used to improve remotely sensed burn severity evaluations. Unburned offset values standardize greenness between image pairs; however, efficacy across diverse scenarios remains underexplored. Aims We evaluated the impact of phenological offset correction methods to support analyst decision-making across fire-prone environments. Methods We generated burn severity spectral index values for a dataset of Composite Burn Index (CBI) field plots across the conterminous US. The effectiveness of offset corrections was tested across image selection techniques, spectral indices, offset generation methods and burn perimeter sources. We assessed the influence of offset corrections on the modeled relationship with CBI, agreement between burn severity thresholds and potential bias. Key results Applying offset corrections consistently improved the modeled relationship with CBI by addressing extreme outlier severity values. However, automated offset corrections had the potential to introduce bias, systematically lowering severity values and reducing correspondence with observed burn severity categories. Conclusions Offset corrections offer benefits but also present trade-offs to accurately representing remotely sensed burn severity. Implications The utility of offset corrections depends on the environment, methods and scale of analysis. We propose a decision-tree framework for analysts to consider when employing offset corrections given their study scope.

conterminous United States↗
USGS2024

Restoration monitoring metric framework: Integrating innovative remote-sensing technologies: Comparisons between field and remotely sensed vegetation surveys of restored forested and grassland sites in Ohio

Restoration monitoring is generally perceived as costly and time-consuming, yet the concept of universal restoration monitoring metrics is trending for evaluation of restoration performance across spatial scales, project boundaries, and jurisdictions. Natural Resource Damage Assessment and Restoration (NRDAR) practitioners seek to restore natural resources injured by oil spills or hazardous substance releases into the environment. Therefore, a multiagency team [US Army Engineer Research and Development Center (ERDC), US Department of the Interior (DOI), and US Department of Energy (DOE)] developed and field-tested a multitiered monitoring framework, illustrating a range of field and remote-sensing techniques and methodologies. The restoration monitoring framework and field demonstration offer a unique methodology to acquire and evaluate simultaneously collected, multiscale/multiplatform data. The result of this research provides new insights to (1) assist planning, implementing, and monitoring restoration progress and effectiveness; and (2) apply common monitoring methods, endpoints, and metrics to other types of ecosystem restoration initiatives. Although the aim was to inform monitoring and management of areas that had been injured, these methods could also be used to inform restoration monitoring practices in a broader context, benefiting environmental stewardship missions of all project partners.

Final Technical Report↗
USGS2019

Radiometric calibration of a non-imaging airborne spectrometer to measure the Greenland ice sheet surface

Methods to radiometrically calibrate a non-imaging airborne visible-to-shortwave infrared (VSWIR) spectrometer to measure the Greenland ice sheet surface are presented. Airborne VSWIR measurement performance for bright Greenland ice and dark bare rock/soil targets is compared against the MODerate resolution atmospheric TRANsmission (MODTRAN ® ) radiative transfer code (version 6.0), and a coincident Landsat 8 Operational Land Imager (OLI) acquisition on 29 July 2015 during an in-flight radiometric calibration experiment. Airborne remote sensing flights were carried out in northwestern Greenland in preparation for the Ice, Cloud, and land Elevation Satellite 2 (ICESat-2) laser altimeter mission. A total of nine science flights were conducted over the Greenland ice sheet, sea ice, and open-ocean water. The campaign's primary purpose was to correlate green laser pulse penetration into snow and ice with spectroscopic-derived surface properties. An experimental airborne instrument configuration that included a nadir-viewing (looking downward at the surface) non-imaging Analytical Spectral Devices (ASD) Inc. spectrometer that measured upwelling VSWIR (0.35 to 2.5 µ m) spectral radiance ( W m - 2 sr - 1 µ m - 1 "> W m − 2 sr − 1 µ m − 1 ) in the two-color Slope Imaging Multi-polarization Photon-Counting Lidar's (SIMPL) ground instantaneous field of view, and a zenith-viewing (looking upward at the sky) ASD spectrometer that measured VSWIR spectral irradiance (W m −2 nm −1 ) was flown. National Institute of Standards and Technology (NIST) traceable radiometric calibration procedures for laboratory, in-flight, and field environments are described in detail to achieve a targeted VSWIR measurement requirement of within 5 % to support calibration/validation efforts and remote sensing algorithm development. Our MODTRAN predictions for the 29 July flight line over dark and bright targets indicate that the airborne nadir-viewing spectrometer spectral radiance measurement uncertainty was between 0.6 % and 4.7 % for VSWIR wavelengths (0.4 to 2.0 µ m) with atmospheric transmittance greater than 80 %. MODTRAN predictions for Landsat 8 OLI relative spectral response functions suggest that OLI is measuring 6 % to 16 % more top-of-atmosphere (TOA) spectral radiance from the Greenland ice sheet surface than was predicted using apparent reflectance spectra from the nadir-viewing spectrometer. While more investigation is required to convert airborne VSWIR spectral radiance into atmospherically corrected airborne surface reflectance, it is expected that airborne science flight data products will contribute to spectroscopic determination of Greenland ice sheet surface optical properties to improve understanding of their potential influence on ICESat-2 measurements.

Atmospheric Measurement Techniques↗
USGS2012

A remote-sensing, GIS-based approach to identify, characterize, and model spawning habitat for fall-run chum salmon in a sub-arctic, glacially fed river

At northern limits of a species’ distribution, fish habitat requirements are often linked to thermal preferences, and the presence of overwintering habitat. However, logistical challenges and hydrologic processes typical of glacial systems could compromize the identification of these habitats, particularly in large river environments. Our goal was to identify and characterize spawning habitat for fall-run chum salmon Oncorhynchus keta and model habitat selection from spatial distributions of tagged individuals in the Tanana River, Alaska using an approach that combined ground surveys with remote sensing. Models included braiding, sinuosity, ice-free water surface area (indicating groundwater influence), and persistent ice-free water (i.e., consistent presence of ice-free water for a 12-year period according to satellite imagery). Candidate models containing persistent ice-free water were selected as most likely, highlighting the utility of remote sensing for monitoring and identifying salmon habitat in remote areas. A combination of ground and remote surveys revealed spatial and temporal thermal characteristics of these habitats that could have strong biological implications. Persistent ice-free sites identified using synthetic aperture radar appear to serve as core areas for spawning fall chum salmon, and the importance of stability through time suggests a legacy of successful reproductive effort for this homing species. These features would not be captured with a one-visit traditional survey but rather required remote-sensing monitoring of the sites through time.

Transactions of the American Fisheries Society↗
USGS2023

A 1.2 billion pixel human-labeled dataset for data-driven classification of coastal environments

The world’s coastlines are spatially highly variable, coupled-human-natural systems that comprise a nested hierarchy of component landforms, ecosystems, and human interventions, each interacting over a range of space and time scales. Understanding and predicting coastline dynamics necessitates frequent observation from imaging sensors on remote sensing platforms. Machine Learning models that carry out supervised (i.e., human-guided) pixel-based classification, or image segmentation, have transformative applications in spatio-temporal mapping of dynamic environments, including transient coastal landforms, sediments, habitats, waterbodies, and water flows. However, these models require large and well-documented training and testing datasets consisting of labeled imagery. We describe “Coast Train,” a multi-labeler dataset of orthomosaic and satellite images of coastal environments and corresponding labels. These data include imagery that are diverse in space and time, and contain 1.2 billion labeled pixels, representing over 3.6 million hectares. We use a human-in-the-loop tool especially designed for rapid and reproducible Earth surface image segmentation. Our approach permits image labeling by multiple labelers, in turn enabling quantification of pixel-level agreement over individual and collections of images.

Scientific Data↗
USGS2018

Mapping and measuring aeolian sand dunes with photogrammetry and LiDAR from unmanned aerial vehicles (UAV) and multispectral satellite imagery on the Paria Plateau, AZ, USA

The Paria Plateau is a potentially important but relatively unstudied aeolian sand source area in the Grand Canyon region of Arizona, USA. This study used unmanned aerial vehicle(UAV) - based LiDAR and structure-from-motion (SfM) photogrammetry to produce high-resolution topographic models of aeolian dunes on the plateau. We combined the dune topography data with a high-resolution satellite image maximum likelihood classification (producer's accuracy = 87.2%) to quantify potential aeolian sand source areas across the 958 km 2 plateau. We mapped all the unvegetated active aeolian dunes on the plateau and estimate they contain 24 Tg of sand, and could, therefore, be a proportionately important regional sand source considering the annual sand loads of the downwind Paria River at its confluence with the Colorado River are generally <1 Tg. The results and data from this study could be useful for future investigations that wish to explicitly link aeolian sand on the Paria Plateau to downwind sediment dynamics in the region. The methodology for UAV and satellite remote sensing that we demonstrate could be applied to quantify sand at large geographic extents in other aeolian environments around the world.

Arizona↗
USGS2005

Methods for synthesis of some jarosites

Experimental procedures in this report summarize attempts to synthesize potassium-, hydronium-, sodium-, and mixed-composition (hydronium-bearing) jarosites. After experimentation, some acceptable combinations of chemical and physical factors were found to routinely synthesize chemically different jarosites, which were used as part of a characterization study of some natural and synthetic jarosites. Jarosite is a sulfate mineral that is common in geologic settings where iron sulfide minerals such as pyrite or marcasite are subject to oxidative weathering. The presence of jarosite is a hallmark of acidic conditions. Jarosite forms as a secondary mineral in weathered sulfidic ores, coal mine wastes, on oxidizing mine wastes, and in streams affected by acid mine drainage. Jarosite also forms in acid-sulfate soils, as an alteration product of sulfidic shales, and in hydrothermal environments. Because of its important role in earth surface processes, the USGS is conducting mineralogical, geochemical, and remote sensing studies to characterize natural jarosites and to elucidate its stability range and conditions of formation. The presence of jarosite is not limited to the Earth. The recent identification of jarosite in the rocks at the Meridiani Planum on Mars has given planetary geologists reason to think that jarosite may be evidence of relict lacustrine (lake systems) or hydrothermal (water enriched magma emanations) systems on the Martian surface. USGS scientists are currently developing jarosite detection systems that can be placed on orbiting spectrometers. One day these systems may guide Mars landers to sites abundant in jarosite, sites most likely to have sheltered ancient Martian life.

Techniques and Methods↗
USGS2023

Artisanal mining river dredge detection using SAR: A method comparison

Challenges exist in monitoring artisanal and small-scale mining (ASM) activities, given their dynamic and often informal nature. ASM takes form through various techniques and scales, including riverine dredging, which often targets the abundant alluvial gold deposits in South America. Remote sensing offers a solution to improve data collection, regulation, and monitoring of the more mobile and elusive ASM activities and their impacts. Mapping ASM riverine dredges using Synthetic Aperture Radar (SAR) is one of the application areas least explored. Three semi-automated detection approaches using Sentinel-1 SAR are compared on their ability to identify dredges with minimal false positives. The methods are: (i) Search for Unidentified Maritime Objects (SUMO), an established method for large ocean ship detection; and two techniques specifically developed for riverine environments that are introduced in this paper: (ii) a local detection method; and (iii) a global threshold method. A visual interpretation of SAR data with the inclusion of optical high-resolution data are used to generate a validation dataset. Results show it is possible to semi-automatically detect riverine dredge using SAR and that a local detection method provides the best balance between sensitivity and precision and has the lowest risk of error. Future improvements may consider further automation, more discriminatory variables, and analyzing the methods in different environments and at higher spatial resolutions.

Remote Sensing↗
USGS2007

Climate Change Research at USGS Center for Earth Resources Observation and Science (EROS)

Research and development projects at EROS apply unique resources to support the USGS mission of developing understanding, monitoring, and modeling of climate variability and change and their human, physical, and biological impacts. Remote sensing resources, both new and archived, form the core of our ability to determine changes in the state or condition of the Earth’s surface and its dynamic landscape and ecosystem processes. This rich resource provides powerful biophysical information for local to global areas. Archival data form the basis for assessing human and climate impacts on the land surface, trends of land use, and an understanding of climate and management impacts. Biophysical information from satellite data is assimilated into quantitative models that allow all disciplines of the USGS to understand impacts on ecosystem processes. Major processes and problems we address include: carbon fluxes, hydrological processes, albedo changes and regional climates, mangroves and wetland protection of coastal environments, natural and manmade hazards (e.g., fire and drought), ecosystem change and succession, land use and land cover change, and more. The integration of remote sensing, modeling, and multidisciplinary approaches fosters international scientific leadership across all disciplines for the USGS.

Fact Sheet↗
USGS2001

Satellite images for land cover monitoring - Navigating through the maze

Policy makers, managers, scientists and the public can view the changing environment using satellite images. More than 60 Earth observing satellites are collecting images of the Earth's surface. Remote sensing satellite systems for land cover assessment are operated by a growing number of countries including India, the United States, Japan, France, Canada and Russia. The focus of this publication is satellite systems for land cover monitoring. On the reverse is a table that compares a selection of these systems, whose data are globally available in a form suitable for land cover analysis. We hope the information presented will help you assess the utility of remotely sensed image to meet your needs.

Report↗
USGS2000

Hydrogeology of the regional aquifer near Flagstaff, Arizona, 1994-97

Sandstones, siltstones, and limestones that are Pennsylvanian to Permian in age underlie the southern part of the Colorado Plateau near Flagstaff, Arizona, and contain a complex regional aquifer that has become increasingly important as a source of water for domestic, municipal, and recreational uses. Ground-water flow in the regional aquifer is poorly understood in this area because (1) depth of the aquifer limits exploratory drilling and testing and (2) the geologic structure increases the complexity of the aquifer characteristics and the ground-water flow system. Four methods were used to improve the understanding of the hydrogeology of the regional aquifer near Flagstaff. • Remote-sensing techniques and geologic mapping provided data to identify many structural features that indicate a more complex structural environment and history than previously realized. • Data from surface-geophysical techniques that included ground-penetrating radar, seismic reflection and seismic refraction, and square-array resistivity, verified that some of the geologic structures expressed at land surface propagate deep into the subsurface and through the principal water-bearing zones of the regional aquifer at near-vertical angles. • A well and spring inventory, borehole-geophysical methods, and well and aquifer tests provided additional information relating aquifer and ground-water flow characteristics to geologic structure. • Water-chemistry data, which included major ion, nutrient, trace-element, and radioactive and stable-isotope analyses, provided an independent means of verifying the hydrogeologic characteristics of the aquifer and were used to determine recharge and discharge areas, groundwater movement, and ground-water age. Ground-water recharge occurs throughout the area but is greatest at higher altitudes where precipitation is greater and in areas where heavily fractured rock units of the aquifer are exposed. The estimated annual average recharge to the regional aquifer in the study area is about 290,000 acre-feet. Ground water flows laterally and vertically through pore spaces in the rock and along faults and other fractures from high-altitude areas in the southern part of the study area to regional drains north of the study area along the Little Colorado and Colorado Rivers, and to drains south of the study area along Oak Creek and the Verde Valley. Ground-water discharge in these areas—about 400,000 acre-feet per year—exceeds the annual recharge to the aquifer in the Flagstaff area, but ground water from areas outside the study area contributes to this discharge as well. The saturated thickness of the regional aquifer averages about 1,200 feet, and the amount of water in storage could be as much as 4,800,000 acrefeet, or about 10 percent of the total volume of the aquifer. The quality of water in the regional aquifer in terms of dissolved-solids concentrations is good for most uses throughout the area. Dissolvedsolids concentrations generally are less than 500 milligrams per liter. Water in the regional aquifer is primarily a calcium magnesium bicarbonate type. In some areas near the Rio de Flag, the water has significant nitrate and chloride components, which indicate direct recharge in these areas from the Rio de Flag. Oxygen and deuterium data indicate a common recharge source for water in the aquifer and that some sites receive recharge from surface waters where evaporation has occurred. Estimated carbon-14 ages and tritium activities indicate ground-water ages from less than 200 years in the Lake Mary area to more than 5,000 years in the Wupatki area. The regional aquifer is heterogeneous and anisotrophic and has a complex ground-water flow system. The most productive water-bearing material tends to be fine- to medium-grained sandstones, and ground-water flow and potential well yields are related to geologic structure. Fracturing associated with structural deformation increases recharge locally and also increases the potential for high well yields. Surface-geophysical techniques provided information on the orientation of high-angle, deep-seated structure in the saturated zone. Borehole-geophysical data identified horizontal to near-horizontal fractures as significant components of the fracture-flow system not apparent in the surface-geophysical data. Structural features that strike northwest appear to be areas that have the greatest potential for high well yields. A north-northeastward-striking structure may be just as promising, but additional data are needed to verify this relation.

Arizona↗