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Recent data and information system initiatives for remotely sensed measurements of the land surface

As part of the International Satellite Land Satellite Climatology Program (ISLSCP) Workshop on Remote Sensing of the Land Surface for Studies of Global Change, five invited presentations were given on recent data initiatives relevant to the ISLSCP community. The presentations are summarized in this paper along with some observations by the authors on data systems for the land sciences community. The invited presentations are by no means all inclusive but were selected as examples of current data activities, representing a range of topics associated with data for land sciences including: the generation of global and local scale data sets, the reworking of historical data sets, new data initiatives and some programmatic aspects of land data base development. This paper serves to provide information on these data initiatives and to air some of the issues concerning land science data systems that were raised at the meeting.

Remote Sensing of Environment↗

Small values in big data: The continuing need for appropriate metadata

Compiling data from disparate sources to address pressing ecological issues is increasingly common. Many ecological datasets contain left-censored data – observations below an analytical detection limit. Studies from single and typically small datasets show that common approaches for handling censored data — e.g., deletion or substituting fixed values — result in systematic biases. However, no studies have explored the degree to which the documentation and presence of censored data influence outcomes from large, multi-sourced datasets. We describe left-censored data in a lake water quality database assembled from 74 sources and illustrate the challenges of dealing with small values in big data, including detection limits that are absent, range widely, and show trends over time. We show that substitutions of censored data can also bias analyses using ‘big data’ datasets, that censored data can be effectively handled with modern quantitative approaches, but that such approaches rely on accurate metadata that describe treatment of censored data from each source.

Ecological Informatics↗

A working environment for digital planetary data processing and mapping using ISIS and GRASS GIS

Since the beginning of planetary exploration, mapping has been fundamental to summarize observations returned by scientific missions. Sensor-based mapping has been used to highlight specific features from the planetary surfaces by means of processing. Interpretative mapping makes use of instrumental observations to produce thematic maps that summarize observations of actual data into a specific theme. Geologic maps, for example, are thematic interpretative maps that focus on the representation of materials and processes and their relative timing. The advancements in technology of the last 30 years have allowed us to develop specialized systems where the mapping process can be made entirely in the digital domain. The spread of networked computers on a global scale allowed the rapid propagation of software and digital data such that every researcher can now access digital mapping facilities on his desktop. The efforts to maintain planetary missions data accessible to the scientific community have led to the creation of standardized digital archives that facilitate the access to different datasets by software capable of processing these data from the raw level to the map projected one. Geographic Information Systems (GIS) have been developed to optimize the storage, the analysis, and the retrieval of spatially referenced Earth based environmental geodata; since the last decade these computer programs have become popular among the planetary science community, and recent mission data start to be distributed in formats compatible with these systems. Among all the systems developed for the analysis of planetary and spatially referenced data, we have created a working environment combining two software suites that have similar characteristics in their modular design, their development history, their policy of distribution and their support system. The first, the Integrated Software for Imagers and Spectrometers (ISIS) developed by the United States Geological Survey, represents the state of the art for processing planetary remote sensing data, from the raw unprocessed state to the map projected product. The second, the Geographic Resources Analysis Support System (GRASS) is a Geographic Information System developed by an international team of developers, and one of the core projects promoted by the Open Source Geospatial Foundation (OSGeo). We have worked on enabling the combined use of these software systems throughout the set-up of a common user interface, the unification of the cartographic reference system nomenclature and the minimization of data conversion. Both software packages are distributed with free open source licenses, as well as the source code, scripts and configuration files hereafter presented. In this paper we describe our work done to merge these working environments into a common one, where the user benefits from functionalities of both systems without the need to switch or transfer data from one software suite to the other one. Thereafter we provide an example of its usage in the handling of planetary data and the crafting of a digital geologic map. ?? 2010 Elsevier Ltd. All rights reserved.

Conference Paper↗

Developing a national stream morphology data exchange: needs, challenges, and opportunities

Stream morphology data, primarily consisting of channel and foodplain geometry and bed material size measurements, historically have had a wide range of applications and uses including culvert/ bridge design, rainfall- runoff modeling, food inundation mapping (e.g., U.S. Federal Emergency Management Agency food insurance studies), climate change studies, channel stability/sediment source investigations, navigation studies, habitat assessments, and landscape change research. The need for stream morphology data in the United States, and thus the quantity of data collected, has grown substantially over the past 2 decades because of the expanded interests of resource management agencies in watershed management and restoration. The quantity of stream morphology data collected has also increased because of state-of-the-art technologies capable of rapidly collecting high-resolution data over large areas with heretofore unprecedented precision. Despite increasing needs for and the expanding quantity of stream morphology data, neither common reporting standards nor a central data archive exist for storing and serving these often large and spatially complex data sets. We are proposing an open- access data exchange for archiving and disseminating stream morphology data.

Eos, Transactions, American Geophysical Union↗

Cloud-native repositories for big scientific data

Scientific data have traditionally been distributed via downloads from data server to local computer. This way of working suffers from limitations as scientific datasets grow toward the petabyte scale. A “cloud-native data repository,” as defined in this article, offers several advantages over traditional data repositories—performance, reliability, cost-effectiveness, collaboration, reproducibility, creativity, downstream impacts, and access and inclusion. These objectives motivate a set of best practices for cloud-native data repositories: analysis-ready data, cloud-optimized (ARCO) formats, and loose coupling with data-proximate computing. The Pangeo Project has developed a prototype implementation of these principles by using open-source scientific Python tools. By providing an ARCO data catalog together with on-demand, scalable distributed computing, Pangeo enables users to process big data at rates exceeding 10 GB/s. Several challenges must be resolved in order to realize cloud computing’s full potential for scientific research, such as organizing funding, training users, and enforcing data privacy requirements.

Computing in Science and Engineering↗

Atmospheric correction at AERONET locations: A new science and validation data set

This paper describes an Aerosol Robotic Network (AERONET)-based Surface Reflectance Validation Network (ASRVN) and its data set of spectral surface bidirectional reflectance and albedo based on Moderate Resolution Imaging Spectroradiometer (MODIS) TERRA and AQUA data. The ASRVN is an operational data collection and processing system. It receives 50 ?? 50 km 2 ; subsets of MODIS level 1B (L1B) data from MODIS adaptive processing system and AERONET aerosol and water-vapor information. Then, it performs an atmospheric correction (AC) for about 100 AERONET sites based on accurate radiative-transfer theory with complex quality control of the input data. The ASRVN processing software consists of an L1B data gridding algorithm, a new cloud-mask (CM) algorithm based on a time-series analysis, and an AC algorithm using ancillary AERONET aerosol and water-vapor data. The AC is achieved by fitting the MODIS top-of-atmosphere measurements, accumulated for a 16-day interval, with theoretical reflectance parameterized in terms of the coefficients of the Li SparseRoss Thick (LSRT) model of the bidirectional reflectance factor (BRF). The ASRVN takes several steps to ensure high quality of results: 1) the filtering of opaque clouds by a CM algorithm; 2) the development of an aerosol filter to filter residual semitransparent and subpixel clouds, as well as cases with high inhomogeneity of aerosols in the processing area; 3) imposing the requirement of the consistency of the new solution with previously retrieved BRF and albedo; 4) rapid adjustment of the 16-day retrieval to the surface changes using the last day of measurements; and 5) development of a seasonal backup spectral BRF database to increase data coverage. The ASRVN provides a gapless or near-gapless coverage for the processing area. The gaps, caused by clouds, are filled most naturally with the latest solution for a given pixel. The ASRVN products include three parameters of the LSRT model (kL, kG, and kV), surface albedo, normalized BRF (computed for a standard viewing geometry, VZA = 0, SZA = 45??), and instantaneous BRF (or one-angle BRF value derived from the last day of MODIS measurement for specific viewing geometry) for the MODIS 500-m bands 17. The results are produced daily at a resolution of 1 km in gridded format. We also provide a cloud mask, a quality flag, and a browse bitmap image. The ASRVN data set, including 6 years of MODIS TERRA and 1.5 years of MODIS AQUA data, is available now as a standard MODIS product (MODASRVN) which can be accessed through the Level 1 and Atmosphere Archive and Distribution System website ( http://ladsweb.nascom.nasa.gov/data/search.html). It can be used for a wide range of applications including validation analysis and science research. ?? 2006 IEEE.

IEEE Transactions on Geoscience and Remote Sensing↗

A procedure for radiometric recalibration of Landsat 5 TM reflective-band data

From the Landsat program's inception in 1972 to the present, the Earth science user community has been benefiting from a historical record of remotely sensed data. The multispectral data from the Landsat 5 (L5) Thematic Mapper (TM) sensor provide the backbone for this extensive archive. Historically, the radiometric calibration procedure for the L5 TM imagery used the detectors' response to the internal calibrator (IC) on a scene-by-scene basis to determine the gain and offset for each detector. The IC system degraded with time, causing radiometric calibration errors up to 20%. In May 2003, the L5 TM data processed and distributed by the U.S. Geological Survey (USGS) Earth Resources Observation and Science Center through the National Landsat Archive Production System (NLAPS) were updated to use a lifetime lookup-table (LUT) gain model to radiometrically calibrate TM data instead of using scene-specific IC gains. Further modification of the gain model was performed in 2007. The L5 TM data processed using IC prior to the calibration update do not benefit from the recent calibration revisions. A procedure has been developed to give users the ability to recalibrate their existing level-1 products. The best recalibration results are obtained if the work-order report that was included in the original standard data product delivery is available. However, if users do not have the original work-order report, the IC trends can be used for recalibration. The IC trends were generated using the radiometric gain trends recorded in the NLAPS database. This paper provides the details of the recalibration procedure for the following: 1) data processed using IC where users have the work-order file; 2) data processed using IC where users do not have the work-order file; 3) data processed using prelaunch calibration parameters; and 4) data processed using the previous version of the LUT (e.g., LUT03) that was released before April 2, 2007.

IEEE Transactions on Geoscience and Remote Sensing↗

Safari Science: Assessing the reliability of citizen science data for wildlife surveys

Protected areas are the cornerstone of global conservation, yet financial support for basic monitoring infrastructure is lacking in 60% of them. Citizen science holds potential to address these shortcomings in wildlife monitoring, particularly for resource-limited conservation initiatives in developing countries – if we can account for the reliability of data produced by volunteer citizen scientists (VCS). This study tests the reliability of VCS data vs. data produced by trained ecologists, presenting a hierarchical framework for integrating diverse datasets to assess extra variability from VCS data. Our results show that while VCS data are likely to be overdispersed for our system, the overdispersion varies widely by species. We contend that citizen science methods, within the context of East African drylands, may be more appropriate for species with large body sizes, which are relatively rare, or those that form small herds. VCS perceptions of the charisma of a species may also influence their enthusiasm for recording it. Tailored programme design (such as incentives for VCS) may mitigate the biases in citizen science data and improve overall participation. However, the cost of designing and implementing high-quality citizen science programmes may be prohibitive for the small protected areas that would most benefit from these approaches. Synthesis and applications . As citizen science methods continue to gain momentum, it is critical that managers remain cautious in their implementation of these programmes while working to ensure methods match data purpose. Context-specific tests of citizen science data quality can improve programme implementation, and separate data models should be used when volunteer citizen scientists' variability differs from trained ecologists' data. Partnerships across protected areas and between protected areas and other conservation institutions could help to cover the costs of citizen science programme design and implementation.

Journal of Applied Ecology↗

The Coastal Carbon Library and Atlas: Open source soil data and tools supporting blue carbon research and policy

Quantifying carbon fluxes into and out of coastal soils is critical to meeting greenhouse gas reduction and coastal resiliency goals. Numerous ‘blue carbon’ studies have generated, or benefitted from, synthetic datasets. However, the community those efforts inspired does not have a centralized, standardized database of disaggregated data used to estimate carbon stocks and fluxes. In this paper, we describe a data structure designed to standardize data reporting, maximize reuse, and maintain a chain of credit from synthesis to original source. We introduce version 1.0.0. of the Coastal Carbon Library, a global database of 6723 soil profiles representing blue carbon-storing systems including marshes, mangroves, tidal freshwater forests, and seagrasses. We also present the Coastal Carbon Atlas, an R-shiny application that can be used to visualize, query, and download portions of the Coastal Carbon Library. The majority (4815) of entries in the database can be used for carbon stock assessments without the need for interpolating missing soil variables, 533 are available for estimating carbon burial rate, and 326 are useful for fitting dynamic soil formation models. Organic matter density significantly varied by habitat with tidal freshwater forests having the highest density, and seagrasses having the lowest. Future work could involve expansion of the synthesis to include more deep stock assessments, increasing the representation of data outside of the U.S., and increasing the amount of data available for mangroves and seagrasses, especially carbon burial rate data. We present proposed best practices for blue carbon data including an emphasis on disaggregation, data publication, dataset documentation, and use of standardized vocabulary and templates whenever appropriate. To conclude, the Coastal Carbon Library and Atlas serve as a general example of a grassroots F.A.I.R. (Findable, Accessible, Interoperable, and Reusable) data effort demonstrating how data producers can coordinate to develop tools relevant to policy and decision-making.

Global Change Biology↗

A terracing operator for physical property mapping with potential field data

The terracing operator works iteratively on gravity or magnetic data, using the sense of the measured field's local curvature, to produce a field comprised of uniform domains separated by abrupt domain boundaries. The result is crudely proportional to a physical-property function defined in one (profile case) or two (map case) horizontal dimensions. This result can be extended to a physical-property model if its behavior in the third (vertical) dimension is defined, either arbitrarily or on the basis of the local geologic situation. The terracing algorithm is computationally fast and appropriate to use with very large digital data sets. Where gravity and magnetic data are both available, terracing provides an effective means by which the two data sets can be compared directly. Results of the terracing operation somewhat resemble those of conventional susceptibility (or density) mapping. In contrast with conventional susceptibility mapping, however, the terraced function is a true step function, which cannot be depicted by means of contour lines. Magnetic or gravity fields calculated from the physical-property model do not, in general, produce an exact fit to the observed data. By intent, the terraced map is more closely analogous to a geologic map in that domains are separated by hard-edged domain boundaries and minor within-domain variation is neglected. The terracing operator was applied separately to aeromagnetic and gravity data from a 136 km X 123 km area in eastern Kansas. Results provide a reasonably good physical representation of both the gravity and the aeromagnetic data. Superposition of the results from the two data sets shows many areas of agreement that can be referenced to geologic features within the buried Precambrian crystalline basement. The emerging picture of basement geology is much better resolved than that obtained either from the scanty available drill data or from interpretation of the geophysical data by inspection.

Geophysics↗

Integrating Breeding Bird Survey and demographic data to estimate Wood Duck population size in the Atlantic Flyway

The U.S. Fish and Wildlife Service (USFWS) uses data from the North American Breeding Bird Survey (BBS) to assist in monitoring and management of some migratory birds. However, BBS analyses provide indices of population change rather than estimates of population size, precluding their use in developing abundance-based objectives and limiting applicability to harvest management. Wood Ducks ( Aix sponsa ) are important harvested birds in the Atlantic Flyway (AF) that are difficult to detect during aerial surveys because they prefer forested habitat. We integrated Wood Duck count data from a ground-plot survey in the northeastern U.S. with AF-wide BBS, banding, parts collection, and harvest data to derive estimates of population size for the AF. Overlapping results between the smaller-scale intensive ground-plot survey and the BBS in the northeastern U.S. provided a means for scaling BBS indices to the breeding population size estimates. We applied these scaling factors to BBS results for portions of the AF lacking intensive surveys. Banding data provided estimates of annual survival and harvest rates; the latter, when combined with parts-collection data, provided estimates of recruitment. We used the harvest data to estimate fall population size. Our estimates of breeding population size and variability from the integrated population model (N̄ = 0.99 million, SD = 0.04) were similar to estimates of breeding population size based solely on data from the AF ground-plot surveys and the BBS (N̄ = 1.01 million, SD = 0.04) from 1998 to 2015. Integrating BBS data with other data provided reliable population size estimates for Wood Ducks at a scale useful for harvest and habitat management in the AF, and allowed us to derive estimates of important demographic parameters (e.g., seasonal survival rates, sex ratio) that were not directly informed by data.

The Condor↗

Capturing, preserving and digitizing legacy seismic data from the Montserrat Volcano Observatory analog seismic network, July 1995 – December 2004

An eruption of the Soufrière Hills Volcano (SHV) on the eastern Caribbean island of Montserrat began on 18 July 1995 and continued until February 2010. Within nine days of the eruption onset, an existing four‐station analog seismic network (ASN) was expanded to 10 sites. Telemetered data from this network were recorded, processed, and archived locally using a system developed by scientists from the U.S. Geological Survey (USGS) Volcano Disaster Assistance Program (VDAP). In October 1996, a digital seismic network (DSN) was deployed with the ability to capture larger amplitude signals across a broader frequency range. These two networks operated in parallel until December 2004, with separate telemetry and acquisition systems (analysis systems were merged in March 2001). Although the DSN provided better quality data for research, the ASN featured superior real‐time monitoring tools and captured valuable data including the only seismic data from the first 15 months of the eruption. These successes of the ASN have been rather overlooked. This article documents the evolution of the ASN, the VDAP system, the original data captured, and the recovery and conversion of more than 230,000 seismic events from legacy SUDS, Hypo71, and Seislog formats into Seisan database with waveform data in miniSEED format. No digital catalog existed for these events, but students at the University of South Florida have classified two-thirds of the 40,000 events that were captured between July 1995 and October 1996. Locations and magnitudes were recovered for ~10,000 of these events. Real-time seismic amplitude measurement, seismic spectral amplitude measurement, and tiltmeter data were also captured. The result is that the ASN seismic dataset is now more discoverable, accessible, and reusable, in accordance with FAIR data principles. These efforts could catalyze new research on the 1995–2010 SHV eruption. Furthermore, many observatories have data in these same legacy data formats and might benefit from procedures and codes documented here.

Soufrière Hills Volcano↗

A data management life-cycle

Documented, reliable, and accessible data and information are essential building blocks supporting scientific research and applications that enhance society's knowledge base (fig. 1). The U.S. Geological Survey (USGS), a leading provider of science data, information, and knowledge, is uniquely positioned to integrate science and natural resource information to address societal needs. The USGS Central Energy Resources Team (USGS-CERT) provides critical information and knowledge on the quantity, quality, and distribution of the Nation's and the world's oil, gas, and coal resources. By using a life-cycle model, the USGS-CERT Data Management Project is developing an integrated data management system to (1) promote access to energy data and information, (2) increase data documentation, and (3) streamline product delivery to the public, scientists, and decision makers. The project incorporates web-based technology, data cataloging systems, data processing routines, and metadata documentation tools to improve data access, enhance data consistency, and increase office efficiency

Fact Sheet↗

Geographic Information for Analysis of Highway Runoff-Quality Data on a National or Regional Scale in the Conterminous United States

Spatial data are important for interpretation of water-quality information on a regional or national scale. Geographic information systems (GIS) facilitate interpretation and integration of spatial data. The geographic information and data compiled for the conterminous United States during the National Highway Runoff Water-Quality Data and Methodology Synthesis project is described in this document, which also includes information on the structure, file types, and the geographic information in the data files. This 'geodata' directory contains two subdirectories, labeled 'gisdata' and 'gisimage.' The 'gisdata' directory contains ArcInfo coverages, ArcInfo export files, shapefiles (used in ArcView), Spatial Data Transfer Standard Topological Vector Profile format files, and meta files in subdirectories organized by file type. The 'gisimage' directory contains the GIS data in common image-file formats. The spatial geodata includes two rain-zone region maps and a map of national ecosystems originally published by the U.S. Environmental Protection Agency; regional estimates of mean annual streamflow, and water hardness published by the Federal Highway Administration; and mean monthly temperature, mean annual precipitation, and mean monthly snowfall modified from data published by the National Climatic Data Center and made available to the public by the Oregon Climate Service at Oregon State University. These GIS files were compiled for qualitative spatial analysis of available data on a national and(or) regional scale and therefore should be considered as qualitative representations, not precise geographic location information.

Open-File Report↗

Seismic reflection and refraction data acquired in Canada Basin, Northwind Ridge and Northwind Basin, Arctic Ocean in 1988, 1992 and 1993

Seismic reflection and refraction data were collected in generally ice-covered waters of the Canada Basin and the eastern part of the Chukchi Continental Borderland of the Amerasia Basin, Arctic Ocean, during the late summers of 1988, 1992, and 1993. The data were acquired from a Polar class icebreaker, the U.S. Coast Guard Cutter Polar Star, using a seismic reflection system designed by the U.S. Geological Survey (USGS). The northernmost data extend to 78? 48' N latitude. In 1988, 155 km of reflection data were acquired with a prototype system consisting of a single 195 cubic inch air gun seismic source and a two-channel hydrophone streamer with a 150-m active section. In 1992 and 1993, 500 and 1,900 km, respectively, of seismic reflection profile data were acquired with an improved six air gun, 674 to 1303 cubic inch tuned seismic source array and the same two-channel streamer. In 1993, a 12-channel streamer with a 150-m active section was used to record five of the reflection lines and one line was acquired using a three air gun, 3,000 cubic inch source. All data were recorded with a DFS-V digital seismic recorder. Processed sections feature high quality vertical incidence images to more than 6 km of sub-bottom penetration in the Canada Basin. Refraction data were acquired with U.S. Navy sonobuoys recorded simultaneously with the seismic reflection profiles. In 1988 eight refraction profiles were recorded with the single air gun, and in 1992 and 1993 a total of 47 refraction profiles were recorded with the six air gun array. The sonobuoy refraction records, with offsets up to 35 km, provide acoustic velocity information to complement the short-offset reflection data. The report includes trackline maps showing the location of the data, as well as both digital data files (SEG-Y) and images of all of the profiles.

Open-File Report↗

The National Assessment of Shoreline Change: A GIS compilation of vector cliff edges and associated cliff erosion data for the California coast

The U.S. Geological Survey has generated a comprehensive data clearinghouse of digital vector cliff edges and associated rates of cliff retreat along the open-ocean California coast. These data, which are presented herein, were compiled as part of the U.S. Geological Survey's National Assessment of Shoreline Change Project. Cliff erosion is a chronic problem along many coastlines of the United States. As coastal populations continue to grow and community infrastructures are threatened by erosion, there is increased demand for accurate information including rates and trends of coastal cliff retreat. There is also a critical need for these data to be consistent from one region to another. One objective of this work is to a develop standard, repeatable methodology for mapping and analyzing cliff edge retreat so that periodic, systematic, and internally consistent updates of cliff edge position and associated rates of erosion can be made at a national scale. This data compilation for open-ocean cliff edges for the California coast is a separate, yet related study to Hapke and others, 2006 documenting shoreline change along sandy shorelines of the California coast, which is itself one in a series that includes the Gulf of Mexico and the Southeast Atlantic coast (Morton and others, 2004; Morton and Miller, 2005). Future reports and data compilations will include coverage of the Northeast U.S., the Great Lakes, Hawaii and Alaska. Cliff edge change is determined by comparing the positions of one historical cliff edge digitized from maps with a modern cliff edge derived from topographic LIDAR (light detection and ranging) surveys. Historical cliff edges for the California coast represent the 1920s-1930s time-period; the most recent cliff edge was delineated using data collected between 1998 and 2002. End-point rate calculations were used to evaluate rates of erosion between the two cliff edges. Please refer to our full report on cliff edge erosion along the California coastline at http://pubs.usgs.gov/of/2007/1133/ for additional information regarding methods and results (Hapke and others, 2007). Data in this report are organized into downloadable layers by region (Northern, Central and Southern California) and are provided as vector datasets with accompanying metadata. Vector cliff edges may represent a compilation of data from one or more sources and the sources used are included in the dataset metadata. This project employs the Environmental Systems Research Institute's (ESRI) ArcGIS as it's Geographic Information System (GIS) mapping tool and contains several data layers (shapefiles) that are used to create a geographic view of the California coast. The vector data form a basemap comprising polygon and line themes that include a U.S. coastline (1:80,000), U.S. cities, and state boundaries.

California↗

Compilation of water-resources data for Montana, water year 2006

The U.S. Geological Survey, Montana Water Science Center, in cooperation with other Federal, State, and local agencies, and Tribal governments, collects a large amount of data pertaining to the water resources of Montana each water year. This report is a compilation of Montana site-data sheets for the 2006 water year, which consists of records of stage and discharge of streams; water quality of streams and ground water; stage and contents of lakes and reservoirs; water levels in wells; and precipitation data. Site-data sheets for selected stations in Canada and Wyoming also are included in this report. The data for Montana, along with data from various parts of the Nation, are included in 'Water-Resources Data for the United States, Water Year 2006', which is published as U.S. Geological Survey Water-Data Report WDR-US-2006 and is available at http://pubs.water.usgs.gov/wdr2006. Additional water year 2006 data collected at crest-stage gage and miscellaneous-measurement stations were collected but were not published. These data are stored in files of the U.S. Geological Survey Montana Water Science Center in Helena, Montana, and are available on request.

Montana↗

Helicopter Electromagnetic and Magnetic Geophysical Survey Data for Portions of the North Platte River and Lodgepole Creek, Nebraska, June 2008

This report is a release of digital data from a helicopter electromagnetic and magnetic survey that was conducted during June 2008 in areas of western Nebraska as part of a joint hydrologic study by the North Platte Natural Resource District, South Platte Natural Resource District, and U.S. Geological Survey. The objective of the contracted survey, conducted by Fugro Airborne, Ltd., was to improve the understanding of the relationship between surface water and groundwater systems critical to developing groundwater models used in management programs for water resources. The survey covered 1,375 line km (854 line mi). A unique aspect of this survey is the flight line layout. One set of flight lines were flown paralleling each side of the east-west trending North Platte River and Lodgepole Creek. The survey also included widely separated (10 km) perpendicular north-south lines. The success of this survey design depended on a well understood regional hydrogeologic framework and model developed by the Cooperative Hydrologic Study of the Platte River Basin. Resistivity variations along lines could be related to this framework. In addition to these lines, more traditional surveys consisting of parallel flight lines separated by about 270 m were carried out for one block in each of the drainages. These surveys helped to establish the spatial variations of the resistivity of hydrostratigraphic units. The electromagnetic equipment consisted of six different coil-pair orientations that measured resistivity at separated frequencies from about 400 Hz to about 140,000 Hz. The electromagnetic data along flight lines were converted to electrical resistivity. The resulting line data were converted to geo-referenced grids and maps which are included with this report. In addition to the electromagnetic data, total field magnetic data and digital elevation data were collected. Data released in this report consist of data along flight lines, digital grids, and digital maps of the apparent resistivity and total magnetic field. The depth range of the subsurface investigation for the electromagnetic survey (estimated as deep as 60 m) is comparable to the depth of shallow aquifers. The geophysical data and hydrologic information from U.S. Geological Survey and cooperator studies are being used by resource managers to develop groundwater resource plans for the area. In addition, data will be used to refine hydrologic models in western Nebraska.

Open-File Report↗