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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 721 records · Page 40Linked to original sources
USGS1993

First results of a deep tow CHIRP sonar seafloor imaging system

The latest and most innovative technology has been applied towards the development of a full-ocean depth multi-sensor sonar system using linear swept-FM (Chirp) technology. The seafloor imaging system (SIS- 7000) described herein uses Chirp sidescan sonar to provide high resolution imagery at long range, and Chirp subbottom sonar to provide high resolution profiles in both the near bottom and deeper subbottom. The tow vehicle contains a suite of full-ocean depth instrumentation for measuring various oceanographic parameters and for monitoring vehicle status. Top side systems include a sonar display and data logging system as well as real-time sensor status display and tow vehicle control system. This paper will present an overview of this system, describe its technology and capabilities, and present some initial results.

Conference Paper↗
USGS2012

Seeing the light: the effects of particles, dissolved materials, and temperature on in situ measurements of DOM fluorescence in rivers and streams

Field-deployable sensors designed to continuously measure the fluorescence of colored dissolved organic matter (FDOM) in situ are of growing interest. However, the ability to make FDOM measurements that are comparable across sites and over time requires a clear understanding of how instrument characteristics and environmental conditions affect the measurements. In particular, the effects of water temperature and light attenuation by both colored dissolved material and suspended particles may be significant in settings such as rivers and streams. Using natural standard reference materials, we characterized the performance of four commercially-available FDOM sensors under controlled laboratory conditions over ranges of temperature, dissolved organic matter (DOM) concentrations, and turbidity that spanned typical environmental ranges. We also examined field data from several major rivers to assess how often attenuation artifacts or temperature effects might be important. We found that raw (uncorrected) FDOM values were strongly affected by the light attenuation that results from dissolved substances and suspended particles as well as by water temperature. Observed effects of light attenuation and temperature agreed well with theory. Our results show that correction of measured FDOM values to account for these effects is necessary and feasible over much of the range of temperature, DOM concentration, and turbidity commonly encountered in surface waters. In most cases, collecting high-quality FDOM measurements that are comparable through time and between sites will require concurrent measurements of temperature and turbidity, and periodic discrete sample collection for laboratory measurement of DOM.

Limnology and Oceanography: Methods↗
USGS2011

Hydrologic conditions and terrestrial laser scanning of post-firedebris flows in the San Gabriel Mountains, CA, U.S.A

To investigate rainfall-runoff conditions that generate post-wildfire debris flows, we instrumented and surveyed steep, small watersheds along the tectonically active front of the San Gabriel Mountains, California. Fortuitously, we recorded runoff-generated debris-flows triggered by one spatially restricted convective event with 28 mm of rainfall falling over 62 minutes. Our rain gages, nested hillslope overland-flow sensors and soil-moisture probes, as well as a time series of terrestrial laser scanning (TLS) revealed the effects of the storm. Hillslope overland-flow response, along two ~10-m long flow lines perpendicular to and originating from a drainage divide, displayed only a 10 to 20 minute delay from the onset of rainfall with accumulated totals of merely 5-10 mm. Depth-stratified soil-moisture probes displayed a greater time delay, roughly 20- 30 minutes, indicating that initial overland flow was Hortonian. Furthermore, a downstream channel-monitoring array recorded a pronounced discharge peak generated by the passage of a debris flow after 18 minutes of rainfall. At this time, only four of the eleven hillslope overland flow sensors confirmed the presence of surface-water flow. Repeat TLS and detailed field mapping using GPS document how patterns of rainsplash, overland-flow scour, and rilling contributed to the generation of metter-scale debris flows. In response to a single small storm, the debris flows deposited irregular levees and lobate terminal snouts on hillslopes and caused wide- spread erosion of the valley axis with ground surface lowering exceeding 1.5 m.

California↗
USGS2020

Soil moisture product validation good practices protocol, version 1.0

The Global Climate Observing System (GCOS) included soil moisture in the list of Essential Climate Variables (ECVs) to express its important role in Earth’s water, energy and carbon cycle. Soil moisture has a major impact on agriculture, land surface hydrology, weather, and climate forecasting. This document is a community-based effort to provide recommendations on good practices for the validation of global to regional soil moisture products. Definitions are given and metrics to adequately describe the quality of soil moisture products are presented. Spaceborne active and passive microwave sensors are listed with their characteristics, and the typical soil moisture retrieval methods are explained, including dielectric mixing models and optical methods. Spatial scaling, root zone soil moisture estimation, and operational implementations are addressed, as these issues continue to gain more and more importance. Standard and advanced in situ measurement techniques are described as well as sensor calibration, spatial representativity, sampling strategies, and the benefit of airborne campaigns.The community has agreed upon the utilization of the International Soil Moisture Network (ISMN) as the main online repository for in situ soil moisture measurements. Different validation methods such as ground-based validation, satellite product intercomparison, and time series analyses are presented. We provide strategies to evaluate the long-term quality of soil moisture products, and give advice on how to handle typical temporal and spatial-scale mismatches and how to effectively report validation results. Moreover, the benefit of blind tests is discussed to gain objective validation results. We encourage data providers, scientists and practitioners to use this Soil Moisture Product Validation Good Practices Protocol to provide, analyze, and improve high quality Earth Observation results.

Report↗
USGS2013

Large scale snow water status monitoring: Comparison of different snow water products in the upper Colorado basins

We illustrate the ability to monitor the status of snow water content over large areas by using a spatially distributed snow accumulation and ablation model that uses data from a weather forecast model in the upper Colorado Basin. The model was forced with precipitation fields from the National Weather Service (NWS) Multi-sensor Precipitation Estimator (MPE) and the Tropical Rainfall Measuring Mission (TRMM) data-sets; remaining meteorological model input data were from NOAA's Global Forecast System (GFS) model output fields. The simulated snow water equivalent (SWE) was compared to SWEs from the Snow Data Assimilation System (SNODAS) and SNOwpack TELemetry system (SNOTEL) over a region of the western US that covers parts of the upper Colorado Basin. We also compared the SWE product estimated from the special sensor microwave imager (SSM/I) and scanning multichannel microwave radiometer (SMMR) to the SNODAS and SNOTEL SWE data-sets. Agreement between the spatial distributions of the simulated SWE with MPE data was high with both SNODAS and SNOTEL. Model-simulated SWE with TRMM precipitation and SWE estimated from the passive microwave imagery were not significantly correlated spatially with either SNODAS or the SNOTEL SWE. Average basin-wide SWE simulated with the MPE and the TRMM data were highly correlated with both SNODAS ( r = 0.94 and r = 0.64; d.f. = 14 – d.f. = degrees of freedom) and SNOTEL ( r = 0.93 and r = 0.68; d.f. = 14). The SWE estimated from the passive microwave imagery was significantly correlated with the SNODAS SWE ( r = 0.55, d.f. = 9, p = 0.05) but was not significantly correlated with the SNOTEL-reported SWE values ( r = 0.45, d.f. = 9, p = 0.05).The results indicate the applicability of the snow energy balance model for monitoring snow water content at regional scales when coupled with meteorological data of acceptable quality. The two snow water contents from the microwave imagery (SMMR and SSM/I) and the Utah Energy Balance forced with the TRMM precipitation data were found to be unreliable sources for mapping SWE in the study area; both data sets lacked discernible variability of snow water content between sites as seen in the SNOTEL and SNODAS SWE data. This study will contribute to better understanding the adequacy of data from weather forecast models, TRMM, and microwave imagery for monitoring status of the snow water content.

Colorado, Utah, Wyoming↗
USGS2016

Geometric quality assessment of lidar data based on swath overlap

This paper provides guidelines on quantifying the relative horizontal and vertical errors observed between conjugate features in the overlapping regions of lidar data. The quantification of these errors is important because their presence quantifies the geometric quality of the data. A data set can be said to have good geometric quality if measurements of identical features, regardless of their position or orientation, yield identical results. Good geometric quality indicates that the data are produced using sensor models that are working as they are mathematically designed, and data acquisition processes are not introducing any unforeseen distortion in the data. High geometric quality also leads to high geolocation accuracy of the data when the data acquisition process includes coupling the sensor with geopositioning systems. Current specifications (e.g. Heidemann 2014) do not provide adequate means to quantitatively measure these errors, even though they are required to be reported. Current accuracy measurement and reporting practices followed in the industry and as recommended by data specification documents also potentially underestimate the inter-swath errors, including the presence of systematic errors in lidar data. Hence they pose a risk to the user in terms of data acceptance (i.e. a higher potential for Type II error indicating risk of accepting potentially unsuitable data). For example, if the overlap area is too small or if the sampled locations are close to the center of overlap, or if the errors are sampled in flat regions when there are residual pitch errors in the data, the resultant Root Mean Square Differences (RMSD) can still be small. To avoid this, the following are suggested to be used as criteria for defining the inter-swath quality of data: a) Median Discrepancy Angle b) Mean and RMSD of Horizontal Errors using DQM measured on sloping surfaces c) RMSD for sampled locations from flat areas (defined as areas with less than 5 degrees of slope) It is suggested that 4000-5000 points are uniformly sampled in the overlapping regions of the point cloud, and depending on the surface roughness, to measure the discrepancy between swaths. Care must be taken to sample only areas of single return points only. Point-to-Plane distance based data quality measures are determined for each sample point. These measurements are used to determine the above mentioned parameters. This paper details the measurements and analysis of measurements required to determine these metrics, i.e. Discrepancy Angle, Mean and RMSD of errors in flat regions and horizontal errors obtained using measurements extracted from sloping regions (slope greater than 10 degrees). The research is a result of an ad-hoc joint working group of the US Geological Survey and the American Society for Photogrammetry and Remote Sensing (ASPRS) Airborne Lidar Committee.

Conference Paper↗
USGS2018

The potential of high-frequency profiling to assess vertical and seasonal patterns of phytoplankton dynamics in lakes: An extension of the Plankton Ecology Group (PEG) model

The use of high-frequency sensors on profiling buoys to investigate physical, chemical, and biological processes in lakes is increasing rapidly. Profiling buoys with automated winches and sensors that collect high-frequency chlorophyll fluorescence (ChlF) profiles in 11 lakes in the Global Lake Ecological Observatory Network (GLEON) allowed the study of the vertical and temporal distribution of ChlF, including the formation of subsurface chlorophyll maxima (SSCM). The effectiveness of 3 methods for sampling phytoplankton distributions in lakes, including (1) manual profiles, (2) single-depth buoys, and (3) profiling buoys were assessed. High-frequency ChlF surface data and profiles were compared to predictions from the Plankton Ecology Group (PEG) model. The depth-integrated ChlF dynamics measured by the profiling buoy data revealed a greater complexity that neither conventional sampling nor the generalized PEG model captured. Conventional sampling techniques would have missed SSCM in 7 of 11 study lakes. Although surface-only ChlF data underestimated average water column ChlF, at times by nearly 2-fold in 4 of the lakes, overall there was a remarkable similarity between surface and mean water column data. Contrary to the PEG model’s proposed negligible role for physical control of phytoplankton during the growing season, thermal structure and light availability were closely associated with ChlF seasonal depth distribution. Thus, an extension of the PEG model is proposed, with a new conceptual framework that explicitly includes physical metrics to better predict SSCM formation in lakes and highlight when profiling buoys are especially informative.

Inland Waters↗
USGS2016

How can present and future satellite missions support scientific studies that address ocean acidification?

Space-based observations offer unique capabilities for studying spatial and temporal dynamics of the upper ocean inorganic carbon cycle and, in turn, supporting research tied to ocean acidification (OA). Satellite sensors measuring sea surface temperature, color, salinity, wind, waves, currents, and sea level enable a fuller understanding of a range of physical, chemical, and biological phenomena that drive regional OA dynamics as well as the potentially varied impacts of carbon cycle change on a broad range of ecosystems. Here, we update and expand on previous work that addresses the benefits of space-based assets for OA and carbonate system studies. Carbonate chemistry and the key processes controlling surface ocean OA variability are reviewed. Synthesis of present satellite data streams and their utility in this arena are discussed, as are opportunities on the horizon for using new satellite sensors with increased spectral, temporal, and/or spatial resolution. We outline applications that include the ability to track the biochemically dynamic nature of water masses, to map coral reefs at higher resolution, to discern functional phytoplankton groups and their relationships to acid perturbations, and to track processes that contribute to acid variation near the land-ocean interface.

Oceanography↗
USGS2017

Acoustic doppler velocimeter backscatter for quantification of suspended sediment concentration in South San Francisco Bay

A data set was acquired on a shallow mudflat in south San Francisco Bay that featured simultaneous, co-located optical and acoustic sensors for subsequent estimation of suspended sediment concentrations (SSC). The optical turbidity sensor output was converted to SSC via an empirical relation derived at a nearby site using bottle sample estimates of SSC. The acoustic data was obtained using an acoustic Doppler velocimeter. Backscatter and noise were combined to develop another empirical relation between the optical estimates of SSC and the relative backscatter from the acoustic velocimeter. The optical and acoustic approaches both reproduced similar general trends in the data and have merit. Some seasonal variation in the dataset was evident, with the two methods differing by greater or lesser amounts depending on which portion of the record was examined. It is hypothesized that this is the result of flocculation, affecting the two signals by different degrees, and that the significance or mechanism of the flocculation has some seasonal variability. In the earlier portion of the record (March), there is a clear difference that appears in the acoustic approach between ebb and flood periods, and this is not evident later in the record (May). The acoustic method has promise but it appears that characteristics of flocs that form and break apart may need to be accounted for to improve the power of the method. This may also be true of the optical method: both methods involve assuming that the sediment characteristics (size, size distribution, and shape) are constant

California↗
USGS1982

USGS aerial resolution targets.

It is necessary to measure the achievable resolution of any airborne sensor that is to be used for metric purposes. Laboratory calibration facilities may be inadequate or inappropriate for determining the resolution of non-photographic sensors such as optical-mechanical scanners, television imaging tubes, and linear arrays. However, large target arrays imaged in the field can be used in testing such systems. The USGS has constructed an array of resolution targets in order to permit field testing of a variety of airborne sensing systems. The target array permits any interested organization with an airborne sensing system to accurately determine the operational resolution of its system. -from Author

Photogrammetric Engineering and Remote Sensing↗
USGS1991

Use of electronic microprocessor-based instrumentation by the U.S. geological survey for hydrologic data collection

The U.S. Geological Survey is acquiring a new generation of field computers and communications software to support hydrologic data-collection at field locations. The new computer hardware and software mark the beginning of the Survey's transition from the use of electromechanical devices and paper tapes to electronic microprocessor-based instrumentation. Software is being developed for these microprocessors to facilitate the collection, conversion, and entry of data into the Survey's National Water Information System. The new automated data-collection process features several microprocessor-controlled sensors connected to a serial digital multidrop line operated by an electronic data recorder. Data are acquired from the sensors in response to instructions programmed into the data recorder by the user through small portable lap-top or hand-held computers. The portable computers, called personal field computers, also are used to extract data from the electronic recorders for transport by courier to the office computers. The Survey's alternative to manual or courier retrieval is the use of microprocessor-based remote telemetry stations. Plans have been developed to enhance the Survey's use of the Geostationary Operational Environmental Satellite telemetry by replacing the present network of direct-readout ground stations with less expensive units. Plans also provide for computer software that will support other forms of telemetry such as telephone or land-based radio.

Conference Paper↗
USGS2012

Chapter 7: The hydrothermal diamond anvil cell (HDAC) for Raman spectroscopic studies of geological fluids at high pressures and temperatures

In this chapter, we describe the hydrothermal diamond-anvil cell (HDAC), which is specifically designed for experiments on systems with aqueous fluids to temperatures up to ~1000ºC and pressures up to a few GPa to tens of GPa. This cell permits optical observation of the sample and the in situ determination of properties by ‘photon-in photon-out’ techniques such as Raman spectroscopy. Several methods for pressure measurement are discussed in detail including the Raman spectroscopic pressure sensors a-quartz, berlinite, zircon, cubic boron nitride (c-BN), and 13 C-diamond, the fluorescence sensors ruby (α-Al 2 O 3 :Cr 3+ ), Sm:YAG (Y 3 Al 5 O 12 :Sm 3+ ) and SrB 4 O 7 :Sm 2+ , and measurements of phase-transition temperatures. Furthermore, we give an overview of published Raman spectroscopic studies of geological fluids to high pressures and temperatures, in which diamond anvil cells were applied.

Book chapter↗
USGS2011

Hyperspectral remote sensing of vegetation and agricultural crops: Knowledge gain and knowledge gap after 40 years of research

The focus of this chapter was to summarize the advances made over last 40+ years, as reported in various chapters of this book, in understanding, modeling, and mapping terrestrial vegetation using hyperspectral remote sensing (or imaging spectroscopy) using sensors that are ground-based, truck-mounted, airborne, and spaceborne. As we have seen in various chapters of this book and synthesized in this chapter, the advances made include: (a) significantly improved characterization and modeling of a wide array of biophysical and biochemical properties of vegetation, (b) ability to discriminate plant species and vegetation types with high degree of accuracies (c) reducing uncertainties in determining net primary productivity or carbon assessments from terrestrial vegetation, (d) improved crop productivity and water productivity models, (b), (e) ability to access stress resulting from causes such as management practices, pests and disease, water deficit or excess; , and (f) establishing more sensitive wavebands and indices to detect plant water\moisture content. The advent of spaceborne hyperspectral sensors (e.g., NASA’s Hyperion, ESA’s PROBA, and upcoming NASA’s HyspIRI) and numerous methods and techniques espoused in this book to overcome Hughes phenomenon or data redundancy when handling large volumes of hyperspectral data have generated tremendous interest in advancing our hyperspectral applications knowledge base over larger spatial extent such as region, nation, continent, and globe.

Book chapter↗
USGS1969

Surveying the earth's resources from space

During the past 4 years, scientists of the Geological Survey, in cooperation with NASA, have been investigating the feasibility and practicality of using remote-sensor data collected during conventional aircraft flights. This work is aimed at developing techniques for gathering facts about the earth's natural resources from satellites carrying sophisticated remote-sensing instruments. These experiments have vividly demonstrated our ability to study and assess natural resources from remotely-sensored data. Discussion of a few of these experiments will illustrate this point.

TRW Space Log↗
USGS1970

ERTS-A satellite imagery

The first satellite designed to survey the Earth's resources is scheduled to be launched in 1972. This satellite, known as ERTS-A, will telemeter frames of imagery each covering 100-nautical-mile squares of the Earth. Except for the internal anomalies in the sensor system, the imagery, after being properly scaled, rectified, and controlled, may be considered an orthographic view of the Earth and used as a planimetric photomap. The accuracy of this photomap will be limited, principally by the geometric fidelity of the sensor system rather than by external effects, such as relief displacement, which restrict the direct cartographic use of the conventional aerial photograph. ERST-A is not designed as a topographic mapping satellite but does have real potential' for thematic mapping particularly in areas now covered by topographic maps.

Photogrammetric Engineering↗
USGS1985

New horizons in remote sensing for forest and range resource management

Forest and range resource scientists were among the first to recognize the potential of aircraft and satellite remote sensing for management of timber, forage, water, and wildlife resource. Today, data from a variety of sensor systems are being put to practical use for inventorying, monitoring, and assessing forest and range resources. In the future, improved sensor systems providing new kinds of data will be available. Likewise, new types of data handling and processing systems can be anticipated. Among the new or anticipated aircraft and satellite systems and/or data are National High-Altitude Photograph II, U. S. Geological Survey-acquired Side-Looking Airborne Radar, the Landsat thematic mapper, the National Oceanic Resolution Radiometer, the French Systeme Probatoire d'Observation de la Terre (SPOT) satellite, the European Space Agency Earth Resources Satellite, the National Aeronautics and Space Administration Large Format Camera and Shuttle Imaging Radar (SIR-A, -B, and -C), and a variety of other systems in existence or planned by the Soviets, Japanese, Canadians, Chinese, Brazilians, Indonesians, and other. Application examples are presented that illustrate uses of 1-kilometer-resolution AVHRR data, 80-meter Landsat multispectral scanner data, 30-meter Landsat thematic mapper data, and 10-meter SPOT-simulator data. These examples address fire fuel monitoring, land cover mapping, rangeland assessment, and soils landscape mapping.

Conference Paper↗
USGS2014

Experimental design and quality assurance: in situ fluorescence instrumentation

Both instrument design and capabilities of fluorescence spectroscopy have greatly advanced over the last several decades. Advancements include solid-state excitation sources, integration of fiber optic technology, highly sensitive multichannel detectors, rapid-scan monochromators, sensitive spectral correction techniques, and improve data manipulation software (Christian et al., 1981, Lochmuller and Saavedra, 1986; Cabniss and Shuman, 1987; Lakowicz, 2006; Hudson et al., 2007). The cumulative effect of these improvements have pushed the limits and expanded the application of fluorescence techniques to numerous scientific research fields. One of the more powerful advancements is the ability to obtain in situ fluorescence measurements of natural waters (Moore, 1994). The development of submersible fluorescence instruments has been made possible by component miniaturization and power reduction including advances in light sources technologies (light-emitting diodes, xenon lamps, ultraviolet [UV] lasers) and the compatible integration of new optical instruments with various sampling platforms (Twardowski et at., 2005 and references therein). The development of robust field sensors skirt the need for cumbersome and or time-consuming filtration techniques, the potential artifacts associated with sample storage, and coarse sampling designs by increasing spatiotemporal resolution (Chen, 1999; Robinson and Glenn, 1999). The ability to obtain rapid, high-quality, highly sensitive measurements over steep gradients has revolutionized investigations of dissolved organic matter (DOM) optical properties, thereby enabling researchers to address novel biogeochemical questions regarding colored or chromophoric DOM (CDOM). This chapter is dedicated to the origin, design, calibration, and use of in situ field fluorometers. It will serve as a review of considerations to be accounted for during the operation of fluorescence field sensors and call attention to areas of concern when making this type of measurement. Attention is also given to ways in which in-water fluorescence measurements have revolutionized biogeochemical studies of CDOM and how those measurements can be used in conjunction with remotely sense satellite data to understand better the biogeochemistry of DOM in aquatic environments.

Book chapter↗
USGS2011

Developing climate data records and essential climate variables from landsat data

The series of Landsat missions has compiled the longest record of satellite observation of the Earth’s land surface, extending for more than 38 years for most areas of the globe. Landsat data are particularly important as long term climate data records because the scale of observation is sufficient to differentiate between natural and human drivers of land cover change. The USGS has established consistent radiometric calibration across the Landsat TM and ETM+ sensors, and have extended the calibration back to the earlier MSS sensors. The USGS is developing capabilities to create fundamental climate data records (FCDRs), thematic climate data records (TCDRs), and essential climate variables (ECVs) from the Landsat data archive. Two high priority TCDRs were identified: surface reflectance and land surface temperature because they have direct application or are required as input to the generation of ECVs. We will focus development on a few of the terrestrial ECVs that have a high potential for being derived from Landsat data, that include land cover, albedo, fire disturbance, surface water, snow and ice, and leaf area index (LAI). We are collaborating with scientists who have demonstrated successful algorithm development and application of these science products to develop a framework of processing capabilities to support research projects and land management applications, along with an independent strategy for product validation. Our goal is to scale the creation and validation of these products from specific sites in the conterminous U.S. and Alaska, for extension to continental and global scales.

Conference Paper↗