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At least 127 records · Page 7Linked to original sources
USGS2024

An open-source workflow for scaling burn severity metrics from drone to satellite to support post-fire watershed management

Wildfires are increasing in size and severity across much of the western United States, exposing vulnerable wildland-urban interfaces to post-fire hazards. The Mediterranean chaparral region of Northern California contains many high sloping watersheds prone to hazardous post-fire flood events and identifying watersheds at high risk of soil loss and debris flows is a priority for post-fire response and management. Uncrewed Aerial Systems (UAS; aka drones) offer post-fire management teams the ability to quickly mobilize and survey burned areas with very high-resolution imagery (∼1 cm), facilitating emergency management and post-fire hazard assessment. However, adoption of this technology by hazard response teams may be hindered by complicated workflows for UAS data acquisition, image processing and analysis. We present an open-source workflow using mature Geographic Information Systems (GIS) software and Python packages in a Jupyter Notebook environment that guides users through classification of true-color UAS imagery to generate high resolution burn severity maps which can then be scaled across larger watersheds using Sentinel-2 normalized burn ratio (NBR) images. Soil burn severity classifications using a weighted brightness (WB) image and Char Index (CI) generated from UAS imagery were validated with in-situ data and random stratified points, resulting in the CI having the highest overall accuracy of 87.5%. CI also displayed a marginally stronger relationship over the WB with the post-fire Sentinel-2 NBR, R 2 = 0.79 and R 2 = 0.78 respectively. Our methods offer the unique opportunity to standardize GIS workflows, promoting replication through transparency, while improving the user's understanding of scientific GIS functionality.

California↗
USGS2001

Transboundary movement of airborne pollutants — A methodology for integrating spaceborne images and ground based data

The availability of relevant and accurate environmental information is essential for environmental policy-makers. Recent improvements in satellite remote sensing technologies, groundbased monitors, and data access have resulted in the ability to observe and assess major atmospheric and ecological events around the world on a timely basis Each of these monitoring technologies reveals different and useful information, yet rarely are the resulting data sets used together in an integrated manner. The U.S. Environmental Protection Agency (EPA) and the United Nations Environment Programme (UNEP) Global Resource Information Database (GRID) office in Sioux Falls identified an environmental issue of global interest as a test case for applying an integrated approach: the transboundary movement of atmospheric pollutants. Transboundary movement of atmospheric pollutants has ramifications for human and environmental health, as well as economic impacts. As a result, it is the focus of many bilateral, regional, and international policy efforts. A central question with atmospheric pollutant transport is how to monitor pollutant movement and how to merge different monitoring datasets into useful information. Highly visible regional plumes of dust, smoke, and urban haze can be seen with satellite sensors, while ground-based monitoring of air pollutants such as fine particulates, SO2 , and toxics occurs at the local level. Integration of these two kinds of measurements allows the user to remotely observe large environmental effects in many areas of the world, while obtaining more detailed information from ground-based monitors. Hence, the combination of satellite-based sensor data and ground-based monitoring data promotes greater understanding of the movement of pollutants than either data set alone. Combined data sets are important for use by both scientists and international policy-makers. A standard methodology did not exist to guide and encourage integrated use of satellite images and ground-based data to monitor and understand major pollution events, such as air pollution. Thus, a small team was assembled to develop a methodology for the integration of satellite images and ground-based data. First, we conducted a literature and project review covering past and current integrated remote and ground-based data projects, a literature search of published work, and a search of data sets and technologies that could be used in a combined form. Second, based on this search and documentation, a general methodology was developed for using integrated spaceborne and ground-based data sets, intended as a guide for general scientists and policy-makers. Third, we found an existing project that was willing to be a pilot for testing the methodology: a U.S. EPANOAA project that was using aerial and ground-based sampling to learn more about the airborne sources of mercury deposition in the Florida Everglades. This document presents the results of the literature and project review, the complete methodology, and the outcome of the Florida Everglades pilot project.

Report↗
USGS2023

National Civil Applications Center

Introduction The U.S. Geological Survey (USGS) National Civil Applications Center (NCAC) analyzes remote-sensing data from the Intelligence Community (IC) and the U.S. Department of Defense (DOD) to support public safety missions and to study land-surface and environmental changes. The NCAC provides remotely sensed images to USGS scientists and other civilian Federal agencies; the images come from intelligence and military sensors, referred to as U.S. National Imagery Systems (USNIS), and unclassified commercial satellite data purchased by the DOD. Often these data are referred to as Geospatial Intelligence (GEOINT), which is defined in U.S. Code, title 10, section 467 as “the exploitation and analysis of imagery and geospatial information to describe, assess, and visually depict physical features and geographically referenced activities on or about the earth. Geospatial intelligence consists of imagery, imagery intelligence, and geospatial information.” The NCAC also provides the secretariat with staff and manages the U.S. interagency Civil Applications Committee (CAC), which oversees and facilitates the appropriate civilian uses of overhead remote-sensing technology and data collected by military and intelligence systems and commercial sources. Funded by the USGS National Land Imaging Program, the NCAC operates facilities in Reston, Virginia, and Lakewood, Colorado.

Fact Sheet↗
USGS2003

Use of multispectral Ikonos imagery for discriminating between conventional and conservation agricultural tillage practices

There is a global concern about the increase in atmospheric concentrations of greenhouse gases. One method being discussed to encourage greenhouse gas mitigation efforts is based on a trading system whereby carbon emitters can buy effective mitigation efforts from farmers implementing conservation tillage practices. These practices sequester carbon from the atmosphere, and such a trading system would require a low-cost and accurate method of verification. Remote sensing technology can offer such a verification technique. This paper is focused on the use of standard image processing procedures applied to a multispectral Ikonos image, to determine whether it is possible to validate that farmers have complied with agreements to implement conservation tillage practices. A principal component analysis (PCA) was performed in order to isolate image variance in cropped fields. Analyses of variance (ANOVA) statistical procedures were used to evaluate the capability of each Ikonos band and each principal component to discriminate between conventional and conservation tillage practices. A logistic regression model was implemented on the principal component most effective in discriminating between conventional and conservation tillage, in order to produce a map of the probability of conventional tillage. The Ikonos imagery, in combination with ground-reference information, proved to be a useful tool for verification of conservation tillage practices.

Photogrammetric Engineering and Remote Sensing↗
USGS2014

The geobiology of sediment-hosted mineral deposits

The role of biological processes in the formation of sediment-hosted ore deposits has long been recognized. In this review, we focus on the biogeochemical cycling of C, Mn, Fe, and S as they relate to the formation of sediment-hosted Mn and Fe deposits, metalliferous black shales, clastic-dominated (CD) Pb-Zn deposits, and phosphorites. Biological mediation of ore-forming processes occurs over large spans of space and time. The most important step is oxygenic photosynthesis, a biological innovation dating from the Archean Eon that releases free oxygen into the surface oceans and atmosphere and delivers chemical potential, in the form of reduced carbon, to the seafloor. Photosynthetic oxygen is available to precipitate dissolved Fe 2 + and Mn 2 +, and therefore it augments the formation of sedimentary Mn and Fe deposits, and drives oxidative weathering of exposed crust, thereby delivering sulfate and transition metals to the ocean. Where reduced carbon accumulates in the deep oceans and on the seafloor, bacterial sulfate reduction produces hydrogen sulfide thereby facilitating the formation of metalliferous black shales, sediment-hosted Pb and Zn sulfide deposits, and phosphorites. Thus, an understanding of major biogeochemical processes and how they have evolved over time is required in order to refine genetic models for sediment-hosted ore deposits and to guide future mineral exploration. A close secular relationship between deposit formation and trends in major biogeochemical cycles provides a potentially powerful tool for mineral resource assessment. Sedimentary basins that formed during a time that is known to lack deposits of a particular metal can be eliminated during exploration programs, whereas others of permissive ages should be considered priorities. For example, sedimentary basins older than ca. 1.8 Ga are unlikely to contain large CD Pb-Zn deposits, and basins that formed between 1.6 and 0.6 Ga are not prospective for phosphorites. Recent technological advances in the application of nanometer-, micron-, and bulk-scale analytical techniques allow for imaging of complex biological structures and have provided new insights into the role of bacteria, not only in direct formation of mineral deposits, but also in leaching of metals from ore and mineralized rocks. Future exploration for, and exploitation of, mineral deposits may include offshore or land-based, low-grade, high-tonnage targets; understanding the role of bacteria in mineral growth, mineral dissolution, and redox transformations will aid in predicting where such deposits exist, and how metal extraction from ores can be enhanced.

Book chapter↗
USGS2007

Applying radar technology to migratory bird conservation and management: Strengthening and expanding a collaborative

Executive Summary Understanding the factors affecting migratory bird and bat populations during all three phases of their life cycle—breeding, nonbreeding, and migration—is critical to species conservation planning. This includes the need for information about these species’ responses to natural challenges, as well as information about the effects of human activities and structures. Habitats and other resources critical to migrants during passage and stopover are being destroyed, degraded, and threatened by human activities. Birds and bats are also uniquely susceptible to human use of the airspace. Wind turbines, communication and power transmission towers, and other tall structures, known to cause bird and bat mortality, are being erected or proposed in increasing numbers across the country. In addition, the potential for bird/aircraft collisions poses human safety threats. Management and regulatory agencies, conservation organizations, and industry currently lack the information they need to meet their missions and statutory responsibilities. The biological data available from various radar technologies offer a unique opportunity to learn more about the spatiotemporal distribution patterns, flight characteristics, and habitat use of “aero-fauna.” Recognizing the opportunities presented by radar technologies, the U.S. Geological Survey (USGS), the U.S. Fish and Wildlife Service (USFWS), and university partners collaborated first on individual projects and then in a broader, informal “collaborative” to coordinate their radar-related research and work together to develop the suite of products needed for conservation of birds and bats. Having produced two summary documents (Sojda and others, 2005; Ruth and others, 2005), the next objective was to convene a workshop for researchers, management and regulatory agencies, and other interested parties. The focus of this initial workshop was on strengthening the existing USGS-USFWS-university partnership and expanding the “collaborative” to include new Federal agency partners. The subject matter was centered on discussing available technologies, appropriate applications, management-related needs, and ways to strengthen collaborative research and conservation efforts. The workshop opened with presentations about the history of the “radar collaborative,” a description of the workshop objectives and focuses, and a summary of resource management and regulatory needs. Scientific presentations describing current research projects or subjects followed, given by USGS scientists, as well as scientists from other Federal agencies, academia, conservation and ornithological organizations, and a private contracting firm. Presenters addressed a wide variety of management issues including siting of wind-power facilities, bird/aircraft collisions, effects of hurricanes Katrina and Rita on bird migration, bird use of Conservation Reserve Program land, defining bird migration patterns at a broad regional scale, and associating migrant birds with their stopover habitats. Presentations described a variety of radar technologies including NEXRAD weather surveillance radar, modified mobile marine radar, military tracking radar, pencil beam radar, and dual polarization radar, as well as complementary techniques and analysis methods such as acoustic monitoring, thermal imaging, artificial intelligence, and individual-based modeling. Key issues, themes, and questions identified during the open discussions that followed fell into five main categories: (1) agency needs and challenges; (2) radar technology and applications—technical questions and issues; (3) tools and resources for managers and researchers; (4) standardization of protocols; and (5) collaborative opportunities. Participants identified the following management, regulatory, or business issues facing them which may be addressed with radar technologies: tall structures; wind turbines; identification and protection of key habitats; assessment of management activities; and bird/aircraft strikes. Participants frequently expressed the need for specific information about which radar technologies are best used for answering particular questions. User groups emphasized the importance of clear, defensible scientific information on which they can base their activities. In turn, researchers emphasized their need for clearly defined, specific questions from managers so that they can design and conduct the required research. Discussions about technical issues requiring further research and collaboration included target identity, ground-truthing, linking migrants to habitat, and standardized protocols for applied research. Workshop participants identified and endorsed a series of seven action items that would promote collaboration and begin to address key issues identified at the workshop: Action Item #1 : Establish a working subgroup to address large-scale surveillance radar standardization issues. Action Item #2 : Establish a working subgroup to address small-scale radar standardization issues. Action Item #3 : Bring management and regulatory agencies together to identify the three most important information needs for each key management issue relating to radar technologies. Action Item #4 : Develop Fact Sheet(s) to provide information about radar technology applications to migratory bird and bat conservation issues. Action Item #5 : Create a “radar collaborative” Website to provide information about radar biology applications, contacts, publications, and so forth. Action Item #6 : Formalize and expand the USGS-USFWS “radar collaborative.” Action Item #7 : Advance basic research, such as target identity and validation, which will support and improve our abilities to apply radar technologies to conservation objectives. There was considerable interest in expanding the “radar collaborative” to include those agencies, organizations, and industries represented at the workshop. It was felt that the publication of the workshop proceedings, implementation of action items, and additional future meetings or workshops will be crucial in strengthening the “radar collaborative” effort and promoting the use of these valuable technologies for conserving migratory species.

Open-File Report↗
USGS1973

Value and validity of earth resources observations from space

Observations of the earth from space can provide overall repetitive views in various regions of the electromagnetic spectrum. Data from such surveys can be used as the basis for more detailed observations from aircraft and on the ground to guide resource exploration, development, and conservation activities. The value of earth resource observations from space has been demonstrated by the practical use of photographs from the Gemini and Apollo spaceflights and particularly by a series of multispectral photographs taken during the flight of Apollo 9. The analysis of those photographs has shown that the performance of the planned Earth Resources Technology Satellite will meet the needs of the resource and environmental community for small-scale repetitive images of the earth in the visible and solar infrared portions of the spectrum and has provided a limited base of material for earth scientists to work with in order to ready themselves for the ERTS data. The validity of earth resource observations from space can be derived by analogy from the successively closer observations of the moon, culminating in repeated physical sampling of the moon's surface. The method of inductive reasoning and analysis used for the moon is the opposite of the normal deductive analysis used on the earth. Adoption of the inductive methods and reasoning for earth observations will provide a framework of broad observations and conclusions leading to the identification of target areas for more detailed observation and will, in time, reduce the costs and time required for surveys dealing with resource and environmental problems.

Hydrological Sciences Bulletin↗
USGS2021

SUAS and machine learning integration in waterfowl population surveys

The rapid technological development of small Unmanned Aircraft Systems (sUAS) has led to an increase in capabilities of aerial image collection and analysis for monitoring a variety of wildlife species including waterfowl. Biologists mainly rely on conducting ocular surveys from fixed-wing aircraft or helicopters to estimate waterfowl abundance. sUAS provide an alternative that is safer, less expensive, and more flexible. Researchers have attempted to estimate waterfowl abundance from aerial imagery, but this method has proven to be too time consuming. Machine learning provides the opportunity to more efficiently estimate waterfowl abundance from aerial imagery. In this paper, we present a new integrated system of sUAS and machine learning for waterfowl population surveys. This system provides a user-friendly process for sUAS survey design, deployment, and data post-processing using deep learning methods to automatically detect and count waterfowl. To develop this system, we conducted many sUAS flights to capture a diversity of imagery and assembled six datasets of imagery taken from both fix-winged aircraft and sUAS flights. We used these datasets to develop and evaluate state-of-the-art deep learning models for waterfowl detection. Our system of using a combination of sUAS and machine learning has proved to be an efficient and accurate approach for collecting, analyzing, and estimating waterfowl abundance.

Conference Paper↗
USGS2021

Surface flow velocities from space: Particle image velocimetry of satellite video of a large, sediment-laden river

Conventional, field-based streamflow monitoring in remote, inaccessible locations such as Alaska poses logistical challenges. Safety concerns, financial considerations, and a desire to expand water-observing networks make remote sensing an appealing alternative means of collecting hydrologic data. In an ongoing effort to develop non-contact methods for measuring river discharge, we evaluated the potential to estimate surface flow velocities from satellite video of a large, sediment-laden river in Alaska via particle image velocimetry (PIV). In this setting, naturally occurring sediment boil vortices produced distinct water surface features that could be tracked from frame to frame as they were advected by the flow, obviating the need to introduce artificial tracer particles. In this study, we refined an end-to-end workflow that involved stabilization and geo-referencing, image preprocessing, PIV analysis with an ensemble correlation algorithm, and post-processing of PIV output to filter outliers and scale and geo-reference velocity vectors. Applying these procedures to image sequences extracted from satellite video allowed us to produce high resolution surface velocity fields; field measurements of depth-averaged flow velocity were used to assess accuracy. Our results confirmed the importance of preprocessing images to enhance contrast and indicated that lower frame rates (e.g., 0.25 Hz) lead to more reliable velocity estimates because longer capture intervals allow more time for water surface features to translate several pixels between frames, given the relatively coarse spatial resolution of the satellite data. Although agreement between PIV-derived velocity estimates and field measurements was weak ( R 2 = 0.39) on a point-by-point basis, correspondence improved when the PIV output was aggregated to the cross-sectional scale. For example, the correspondence between cross-sectional maximum velocities inferred via remote sensing and measured in the field was much stronger ( R 2 = 0.76), suggesting that satellite video could play a role in measuring river discharge. Examining correlation matrices produced as an intermediate output of the PIV algorithm yielded insight on the interactions between image frame rate and sensor spatial resolution, which must be considered in tandem. Although further research and technological development are needed, measuring surface flow velocities from satellite video could become a viable tool for streamflow monitoring in certain fluvial environments.

Alaska↗
USGS2009

NBII-SAIN Data Management Toolkit

The Strategic Plan for the U.S. Geological Survey Biological Informatics Program (2005-2009) recognizes the need for effective data management: Though the Federal government invests more than $600 million per year in biological data collection, it is difficult to address these issues because of limited accessibility and lack of standards for data and information...variable quality, sources, methods, and formats (for example observations in the field, museum specimens, and satellite images) present additional challenges. This is further complicated by the fast-moving target of emerging and changing technologies such as GPS and GIS. Even though these technologies offer new solutions, they also create new informatics challenges (Ruggiero and others, 2005). The USGS National Biological Information Infrastructure program, hereafter referred to as NBII, is charged with the mission to improve the way data and information are gathered, documented, stored, and accessed. The central objective of this project is a direct reflection of the purpose of NBII as described by John Mosesso, Program Manager of the U.S. Geological Survey-Biological Informatics Program-GAP Analysis: At the outset, the reason for bringing about NBII was that there were significant amounts of data and information scattered all over the U.S., not accessible, in incompatible formats, and that NBII was tasked with addressing this problem...NBII's focus is to pull data together that truly matters to someone or communities. Essentially, the core questions are: 1) what are the issues, 2) where is the data, and 3) how can we make it usable and accessible (John Mosesso, U.S. Geological Survey, oral commun., 2006). Redundancy in data collection can be a major issue when multiple stakeholders are involved with a common effort. In 2001 the U.S. General Accounting Office (USGAO) estimated that about 50 percent of the Federal government's geospatial data at the time was redundant. In addition, approximately 80 percent of the cost of a spatial information system is associated with spatial data collection and management (U.S. General Accounting Office, 2003). These figures indicate that the resources (time, personnel, money) of many agencies and organizations could be used more efficiently and effectively. Dedicated and conscientious data management coordination and documentation is critical for reducing such redundancy. Substantial cost savings and increased efficiency are direct results of a pro-active data management approach. In addition, details of projects as well as data and information are frequently lost as a result of real-world occurrences such as the passing of time, job turnover, and equipment changes and failure. A standardized, well documented database allows resource managers to identify issues, analyze options, and ultimately make better decisions in the context of adaptive management (National Land and Water Resources Audit and the Australia New Zealand Land Information Council on behalf of the Australian National Government, 2003). Many environmentally focused, scientific, or natural resource management organizations collect and create both spatial and non-spatial data in some form. Data management appropriate for those data will be contingent upon the project goal(s) and objectives and thus will vary on a case-by-case basis. This project and the resulting Data Management Toolkit, hereafter referred to as the Toolkit, is therefore not intended to be comprehensive in terms of addressing all of the data management needs of all projects that contain biological, geospatial, and other types of data. The Toolkit emphasizes the idea of connecting a project's data and the related management needs to the defined project goals and objectives from the outset. In that context, the Toolkit presents and describes the fundamental components of sound data and information management that are common to projects involving biological, geospatial, and other related data

Open-File Report↗
USGS2007

Remote sensing and GIS technology in the Global Land Ice Measurements from Space (GLIMS) Project

Global Land Ice Measurements from Space (GLIMS) is an international consortium established to acquire satellite images of the world's glaciers, analyze them for glacier extent and changes, and to assess these change data in terms of forcings. The consortium is organized into a system of Regional Centers, each of which is responsible for glaciers in their region of expertise. Specialized needs for mapping glaciers in a distributed analysis environment require considerable work developing software tools: terrain classification emphasizing snow, ice, water, and admixtures of ice with rock debris; change detection and analysis; visualization of images and derived data; interpretation and archival of derived data; and analysis to ensure consistency of results from different Regional Centers. A global glacier database has been designed and implemented at the National Snow and Ice Data Center (Boulder, CO); parameters have been expanded from those of the World Glacier Inventory (WGI), and the database has been structured to be compatible with (and to incorporate) WGI data. The project as a whole was originated, and has been coordinated by, the US Geological Survey (Flagstaff, AZ), which has also led the development of an interactive tool for automated analysis and manual editing of glacier images and derived data (GLIMSView). This article addresses remote sensing and Geographic Information Science techniques developed within the framework of GLIMS in order to fulfill the goals of this distributed project. Sample applications illustrating the developed techniques are also shown. ?? 2006 Elsevier Ltd. All rights reserved.

Computers & Geosciences↗
USGS1975

Applications of remote sensing to structural interpretations in the southern Appalachians

Remote sensing is the technology of studying distant objects by measuring and recording energy from one or more segments of the electromagnetic spectrum. Imaging sensors which operate from medium- and high-altitude aircraft or from spacecraft can provide a synoptic view of large areas and of surface phenomena not evident in the field. Image-acquiring systems and instruments have been designed to partially automate data collection and to reduce the time devoted to analysis, information extraction, and detection of changes of surface phenomena. Among these phenomena are the surface distribution of heat, moisture, snow, water, vegetation, and cultural features. When coupled with ancillary data, including field surveys, sensor data provide useful information for the recognition and mapping of regional structure, jointing patterns, drainage patterns, fault and fracture traces, and rock types. The recognition of several major linear surface features, two of which proved to be traces of previously unrecognized faults (the Canebrake and the Coeburn faults) in the Appalachian Plateaus, demonstrates the pragmatic application of aircraft and spacecraft remote sensing to geological investigations in the Appalachians.

Virginia, West Virginia↗
USGS2012

Archive of digital boomer subbottom data collected during USGS cruise 05FGS01 offshore east-central Florida, July 17-29, 2005

In July of 2005, the U.S. Geological Survey (USGS), in cooperation with the Florida Geological Survey (FGS), conducted a geophysical survey of the Atlantic Ocean offshore of Florida's east coast from Flagler Beach to Daytona Beach. This report serves as an archive of unprocessed digital boomer subbottom data, trackline maps, navigation files, Geographic Information System (GIS) files, Field Activity Collection System (FACS) logs and formal Federal Geographic Data Committee (FGDC) metadata. Filtered and gained (showing a relative increase in signal amplitude) digital images of the seismic profiles are also provided. Refer to the Acronyms page for expansions of acronyms and abbreviations used in this report. The USGS Saint Petersburg Coastal and Marine Science Center (SPCMSC) assigns a unique identifier to each cruise or field activity. For example, 05FGS01 tells us the data were collected in 2005 for cooperative work with the FGS and the data were collected during the first field activity for that project in that calendar year. Refer to http://walrus.wr.usgs.gov/infobank/programs/html/definition/activity.html for a detailed description of the method used to assign the field activity ID. The boomer subbottom processing system consists of an acoustic energy source that is made up of capacitors charged to a high voltage and discharged through a transducer in the water. The transducer is towed on a sled floating on the water surface and when discharged emits a short acoustic pulse, or shot, which propagates through the water column and shallow stratrigraphy below. The acoustic energy is reflected at density boundaries (such as the seafloor or sediment layers beneath the seafloor), detected by the receiver (a hydrophone streamer), and recorded by a PC-based seismic acquisition system. This process is repeated at timed intervals (for example, 0.5 s) and recorded for specific intervals of time (for example, 100 ms). In this way, a two-dimensional (2-D) vertical image of the shallow geologic structure beneath the ship track is produced. Figure 1 displays the acquisition geometry. Refer to table 1 for a summary of acquisition parameters and table 2 for trackline statistics. The archived trace data are in standard Society of Exploration Geophysicists (SEG) SEG Y format (Barry and others, 1975), except an ASCII format is used for the first 3,200 bytes of the card image header instead of the standard EBCDIC format. For a detailed description about the recorded trace headers, refer to the SEG Y Format page. The SEG Y files may be downloaded and processed with commercial or public domain software such as Seismic Unix (Cohen and Stockwell, 2005). See the How To Download SEG Y Data page for download instructions. The printable profiles provided here are GIF images that were processed and gained using SU software; refer to the Software page for links to example SU processing scripts. The processed SEG Y data were also exported to Chesapeake Technology, Inc. (CTI) SonarWeb software to produce a geospatially interactive version of the profile that allows the user to obtain a geographic location and depth from the profile for a given cursor position; this information is displayed in the status bar of the browser. Please note that clicking on the profile image switches it to "Expanded View" (a compressed image of the entire line) and cursor tracking is not available in this mode.

Florida↗
USGS2003

Earth Observing-1 Extended Mission

From its beginning in November 2000, the NASA Earth Observing-1 (EO-1) mission demonstrated the feasibility and performance of a dozen innovative sensor, spacecraft, and operational technologies. The 1-year mission tested a variety of technologies, some of which may be included on the planned 2007 Landsat Data Continuity Mission. Onboard the spacecraft are two land remote sensing instruments: the Advanced Land Imager (ALI), which acquires data in spectral bands and at resolutions similar to Landsat, and Hyperion, which acquires data in 220 10-nanometer-wide bands covering the visible, near-, and shortwave-infrared bands. Recognizing the remarkable performance of the satellite's instruments and the exceptional value of the data, the U.S. Geological Survey (USGS) and NASA agreed in December 2001 to share responsibility for operating EO-1 on a cost-reimbursable basis as long as customer sales are sufficient to recover flight and ground operations costs. The EO-1 extended mission operates within constraints imposed by its technology-pioneering origins, but it also provides unique and valuable capabilities. The spacecraft can acquire a target scene three times in a 16-day period. The ALI instrument has additional spectral coverage and greater radiometric dynamic range compared with the sensors on Landsat 7. Hyperion is the first civilian spaceborne hyperspectral imager. As of January 2003, more than 5,000 scenes had been acquired, indexed, and archived.

Fact Sheet↗
USGS2017

Satellite monitoring of cyanobacterial harmful algal bloom frequency in recreational waters and drinking water sources

Cyanobacterial harmful algal blooms (cyanoHAB) cause extensive problems in lakes worldwide, including human and ecological health risks, anoxia and fish kills, and taste and odor problems. CyanoHABs are a particular concern in both recreational waters and drinking water sources because of their dense biomass and the risk of exposure to toxins. Successful cyanoHAB assessment using satellites may provide an indicator for human and ecological health protection. In this study, methods were developed to assess the utility of satellite technology for detecting cyanoHAB frequency of occurrence at locations of potential management interest. The European Space Agency's MEdium Resolution Imaging Spectrometer (MERIS) was evaluated to prepare for the equivalent series of Sentinel-3 Ocean and Land Colour Imagers (OLCI) launched in 2016 as part of the Copernicus program. Based on the 2012 National Lakes Assessment site evaluation guidelines and National Hydrography Dataset, the continental United States contains 275,897 lakes and reservoirs >1 ha in area. Results from this study show that 5.6% of waterbodies were resolvable by satellites with 300 m single-pixel resolution and 0.7% of waterbodies were resolvable when a three by three pixel (3 × 3-pixel) array was applied based on minimum Euclidian distance from shore. Satellite data were spatially joined to U.S. public water surface intake (PWSI) locations, where single-pixel resolution resolved 57% of the PWSI locations and a 3 × 3-pixel array resolved 33% of the PWSI locations. Recreational and drinking water sources in Florida and Ohio were ranked from 2008 through 2011 by cyanoHAB frequency above the World Health Organization’s (WHO) high threshold for risk of 100,000 cells mL −1 . The ranking identified waterbodies with values above the WHO high threshold, where Lake Apopka, FL (99.1%) and Grand Lake St. Marys, OH (83%) had the highest observed bloom frequencies per region. The method presented here may indicate locations with high exposure to cyanoHABs and therefore can be used to assist in prioritizing management resources and actions for recreational and drinking water sources.

Florida, Ohio↗
USGS2018

Landsat benefiting society for fifty years

Since 1972, data acquired by the Landsat series of satellites have become integral to land management for both government and the private sector, providing scientists and decision makers with key information about agricultural productivity, ice sheet dynamics, urban growth, forest monitoring, natural resource management, water quality, and supporting disaster response. Landsat 9 continues the mission of unrivaled space-based Earth observation and will lead the Landsat program into its second half century of Earth imagery provided to users, worldwide, at no charge. More than 8 million Landsat scenes held in the USGS archive to date are used in conjunction with advanced geographic information systems, image processing software, and cloud computing capabilities to enable Landsat users to study changes on the Earth’s surface across continental regions and extended time periods. The Operational Land Imager 2 (OLI-2) and the Thermal Infrared Sensor 2 (TIRS-2) instruments onboard Landsat 9 —which replicate the technologically-advanced instruments introduced onboard Landsat 8—allow for the collection of continuous high-quality data required for advancing Earth applications, including our ability to map surface temperature and surface water quality. Landsat 9 will build on the Landsat legacy, achieving a half-century record of global Earth observations.

Report↗
USGS2020

Advancements towards selective barrier passage by automatic species identification: Applications of deep convolutional neural networks on images of dewatered fish

Invasive species negatively affect enterprises such as fisheries, agriculture, and international trade. In the Laurentian Great Lakes Basin, threats include invasive sea lamprey ( Petromyzon marinus ) and the four major Chinese carps. Barriers have proven to be an effective mechanism for managing invasive species but are detrimental in that they also limit the migration of desirable, native species. Fish passage technologies that selectively pass desirable species while blocking undesirable species are needed. Key to an automated selective barrier passage system is a high precision fish classifier to assign fish to be passed or blocked. Presented is an evaluation of two classifiers developed using images of partially dewatered fish captured from a commercial, high-speed camera array. For a lamprey vs. non-lamprey classification task, an ensemble prediction approach achieved near perfect accuracy on both a validation and test dataset. For a species classification task for 13 species found in the Great Lakes region, an ensemble prediction approach achieved accuracies of 96% and 97% on a validation and test dataset, respectively. Both prediction approaches were based on deep convolutional neural networks constructed using transfer learning and image augmentation. The study provides an important proof-of-concept for the viability in fully automated, selective fish passage systems.

Illinois, Michigan,Ohio↗
USGS2017

A method for examining temporal changes in cyanobacterial harmful algal bloom spatial extent using satellite remote sensing

Cyanobacterial harmful algal blooms (CyanoHAB) are thought to be increasing globally over the past few decades, but relatively little quantitative information is available about the spatial extent of blooms. Satellite remote sensing provides a potential technology for identifying cyanoHABs in multiple water bodies and across geo-political boundaries. An assessment method was developed using MEdium Resolution Imaging Spectrometer (MERIS) imagery to quantify cyanoHAB surface area extent, transferable to different spatial areas, in Florida, Ohio, and California for the test period of 2008 to 2012. Temporal assessment was used to evaluate changes in satellite resolvable inland waterbodies for each state of interest. To further assess cyanoHAB risk within the states, the World Health Organization’s (WHO) recreational guidance level thresholds were used to categorize surface area of cyanoHABs into three risk categories: low, moderate, and high-risk bloom area. Results showed that in Florida, the area of cyanoHABs increased largely due to observed increases in high-risk bloom area. California exhibited a slight decrease in cyanoHAB extent, primarily attributed to decreases in Northern California. In Ohio (excluding Lake Erie), little change in cyanoHAB surface area was observed. This study uses satellite remote sensing to quantify changes in inland cyanoHAB surface area across numerous water bodies within an entire state. The temporal assessment method developed here will be relevant into the future as it is transferable to the Ocean Land Colour Instrument (OLCI) on Sentinel-3A/3B missions.

California, Florida, Ohio↗