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At least 145 records · Page 8Linked to original sources
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↗
USGS1984

A bibliography of research conducted by the Earth Resources Observation Systems (EROS) Office, U.S. Geological Survey : 1975-1982

The U.S. Geological Survey's Earth Resources Observation Systems (EROS) Program was established in 1967 by Secretarial order to plan and develop techniques for collecting and analyzing remotely sensed data, and to apply these techniques to the resource inventory and management responsibilities of the Department of the Interior. U.S. Geological Survey scientists, realizing the potential benefits of synoptic views of the Earth, were among the first members of America's scientific community to press for the launch of civilian Earth-surface observation satellites. Under the leadership of Director William T. Pecora, U.S. Geological Survey initiatives greatly influenced the National Aeronautics and Space Administration's (NASA) development of the Landsat program. As part of the Landsat program, an agreement between NASA and the Geological Survey was signed to provide Landsat archiving and data production capabilities at the EROS Data Center in Sioux Falls, South Dakota. This partnership with NASA began in 1972 and continued until Presidential Directive 54 designated the National Oceanic and Atmospheric Administration (NOAA) of the Department of Commerce as the manager of U.S. civil operational land remote-sensing activities. NOAA has managed the Landsat program since Fiscal Year 1983, and EROS continues to process, archive, reproduce, and distribute Landsat data under a Memorandum of Understanding between NOAA and the Geological Survey. Archives at the EROS Data Center include over 2 million worldwide Landsat scenes and over 5 million aerial photographs, primarily of U.S. sites. Since the launch of Landsat 1, global imaging of the Earth's surface has become an operational tool for resource exploration and land management. As technology evolved, so did the EROS Program mission. Research and applications efforts began at the EROS Headquarters Office in the Washington metropolitan area in 1966; at the EROS Data Center in 1971; and at the EROS Field Office in Anchorage, Alaska, in 1980. EROS functions were realined under the National Mapping Division of the Geological Survey in Fiscal Year 1983, when the EROS Headquarters Office v/as closed. EROS research and applications functions are now conducted by the EROS Data Center and the EROS Field Office in Anchorage. Approximately 50 civil servants and 250 contract personnel carry out the EROS mission of research, development, and technology transfer in remote sensing, geographic information systems, and digital data base applications. This bibliography is a compilation of publications between 1975 and 1982 by EROS Program personnel and by persons under contract to the EROS Program. Requests for information regarding EROS research and/or publications should be directed to: Chief, EROS Data Center, Sioux Falls, South Dakota 5719P.

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↗
USGS1999

Overview of the Mars Pathfinder Mission: Launch through landing, surface operations, data sets, and science results

Mars Pathfinder successfully landed at Ares Vallis on July 4, 1997, deployed and navigated a small rover about 100 m clockwise around the lander, and collected data from three science instruments and ten technology experiments. The mission operated for three months and returned 2.3 Gbits of data, including over 16,500 lander and 550 rover images, 16 chemical analyses of rocks and soil, and 8.5 million individual temperature, pressure and wind measurements. Path‐finder is the best known location on Mars, having been clearly identified with respect to other features on the surface by correlating five prominent horizon features and two small craters in lander images with those in high‐resolution orbiter images and in inertial space from two‐way ranging and Doppler tracking. Tracking of the lander has fixed the spin pole of Mars, determined the precession rate since Viking 20 years ago, and indicates a polar moment of inertia, which constrains a central metallic core to be between 1300 and ∼2000 km in radius. Dark rocks appear to be high in silica and geochemically similar to anorogenic andesites; lighter rocks are richer in sulfur and lower in silica, consistent with being coated with various amounts of dust. Rover and lander images show rocks with a variety of morphologies, fabrics and textures, suggesting a variety of rock types are present. Rounded pebbles and cobbles on the surface as well as rounded bumps and pits on some rocks indicate these rocks may be conglomerates (although other explanations are also possible), which almost definitely require liquid water to form and a warmer and wetter past. Air‐borne dust is composed of composite silicate particles with a small fraction of a highly magnetic mineral, interpreted to be most likely maghemite; explanations suggest iron was dissolved from crustal materials during an active hydrologic cycle with maghemite freeze dried onto silicate dust grains. Remote sensing data at a scale of a kilometer or greater and an Earth analog correctly predicted a rocky plain safe for landing and roving with a variety of rocks deposited by catstrophic floods, which are relatively dust free. The surface appears to have changed little since it formed billions of years ago, with the exception that eolian activity may have deflated the surface by ∼3–7 cm, sculpted wind tails, collected sand into dunes, and eroded ventifacts (fluted and grooved rocks). Pathfinder found a dusty lower atmosphere, early morning water ice clouds, and morning near‐surface air temperatures that changed abruptly with time and height. Small scale vortices, interpreted to be dust devils, were observed repeatedly in the afternoon by the meteorology instruments and have been imaged.

Journal of Geophysical Research E: Planets↗
USGS2018

Analysis of different sensor performances in impervious surface mapping

The U.S. Geological Survey (USGS) has developed the National Land Cover Database (NLCD) to provide consistent land cover and land cover change products for the nation since 2001. As one of products in the NLCD, the percent impervious surface area (ISA), which was estimated with Landsat imagery, represents the fraction of human-made impervious area in a 30-m grid and has been used to quantify urban land cover types and extents for the United States. However, it is still a challenge to clearly determine urban land cover intensity and extents using remote sensing data with spatial and spectral resolutions similar to Landsat in part because of highly heterogeneous features of urban land cover. Most urban areas, especially in low intensity development areas, exhibit sub-pixel characteristics that mix impervious surface with other land covers (e.g., grass and trees) in the 30-m resolution satellite imagery. Furthermore, the influence of highly heterogeneous features in many urban areas and how they alter the spectral signature of urban landscapes has not yet been fully studied. Recent advances in remote sensing technology have provided multiple spectral and spatial resolution data from several satellites including WorldView (WV), Sentinel-2, and the Landsat Operational Land Imager (OLI). Remote sensing images having different spectral bands and high spatial resolution provide the potential to derive detailed information on the nature and properties of different surface materials on the urban ground. This study focuses on performance of mapping impervious surface using data collected from WorldView-3, Sentinel-2, and Landsat OLI. We compared ISA results estimated from these sensors and evaluated benefits and limitations of radiometric and spatial resolutions for mapping impervious surface in a study area on the Eastern corridor between Washington, D.C., and Baltimore, where developed impervious surface containing both residential housings, office buildings, and roads, in the United States. The impact of different band combinations in Sentinel-2 imagery on mapping urban impervious surface and urban land cover was also evaluated.

Conference Paper↗
USGS2009

SSTL UK-DMC SLIM-6 data quality assessment

Satellite data from the Surrey Satellite Technology Limited (SSTL) United Kingdom (UK) Disaster Monitoring Constellation (DMC) were assessed for geometric and radiometric quality. The UK-DMC Surrey Linear Imager 6 (SLIM-6) sensor has a 32-m spatial resolution and a ground swath width of 640 km. The UK-DMC SLIM-6 design consists of a three-band imager with green, red, and near-infrared bands that are set to similar bandpass as Landsat bands 2, 3, and 4. The UK-DMC data consisted of imagery registered to Landsat orthorectified imagery produced from the GeoCover program. Relief displacements within the UK-DMC SLIM-6 imagery were accounted for by using global 1-km digital elevation models available through the Global Land One-km Base Elevation (GLOBE) Project. Positional accuracy and relative band-to-band accuracy were measured. Positional accuracy of the UK-DMC SLIM-6 imagery was assessed by measuring the imagery against digital orthophoto quadrangles (DOQs), which are designed to meet national map accuracy standards at 1 : 24 000 scales; this corresponds to a horizontal root-mean-square accuracy of about 6 m. The UK-DMC SLIM-6 images were typically registered to within 1.0-1.5 pixels to the DOQ mosaic images. Several radiometric artifacts like striping, coherent noise, and flat detector were discovered and studied. Indications are that the SSTL UK-DMC SLIM-6 data have few artifacts and calibration challenges, and these can be adjusted or corrected via calibration and processing algorithms. The cross-calibration of the UK-DMC SLIM-6 and Landsat 7 Enhanced Thematic Mapper Plus was performed using image statistics derived from large common areas observed by the two sensors.

IEEE Transactions on Geoscience and Remote Sensing↗
USGS2010

Hyperspectral analysis of columbia spotted frog habitat

Wildlife managers increasingly are using remotely sensed imagery to improve habitat delineations and sampling strategies. Advances in remote sensing technology, such as hyperspectral imagery, provide more information than previously was available with multispectral sensors. We evaluated accuracy of high-resolution hyperspectral image classifications to identify wetlands and wetland habitat features important for Columbia spotted frogs (Rana luteiventris) and compared the results to multispectral image classification and United States Geological Survey topographic maps. The study area spanned 3 lake basins in the Salmon River Mountains, Idaho, USA. Hyperspectral data were collected with an airborne sensor on 30 June 2002 and on 8 July 2006. A 12-year comprehensive ground survey of the study area for Columbia spotted frog reproduction served as validation for image classifications. Hyperspectral image classification accuracy of wetlands was high, with a producer's accuracy of 96 (44 wetlands) correctly classified with the 2002 data and 89 (41 wetlands) correctly classified with the 2006 data. We applied habitat-based rules to delineate breeding habitat from other wetlands, and successfully predicted 74 (14 wetlands) of known breeding wetlands for the Columbia spotted frog. Emergent sedge microhabitat classification showed promise for directly predicting Columbia spotted frog egg mass locations within a wetland by correctly identifying 72 (23 of 32) of known locations. Our study indicates hyperspectral imagery can be an effective tool for mapping spotted frog breeding habitat in the selected mountain basins. We conclude that this technique has potential for improving site selection for inventory and monitoring programs conducted across similar wetland habitat and can be a useful tool for delineating wildlife habitats. ?? 2010 The Wildlife Society.

Journal of Wildlife Management↗
USGS2006

Radiometric calibration stability of the EO-1 advanced land imager: 5 years on-orbit

The Advanced Land Imager (ALI) was developed as a prototype sensor for follow on missions to Landsat-7. It was launched in November 2000 on the Earth Observing One (EO-1) satellite as a nominal one-year technology demonstration mission. As of this writing, the sensor has continued to operate in excess of 5 years. Six of the ALl's nine multi-spectral (MS) bands and the panchromatic band have similar spectral coverage as those on the Landsat-7 ETM+. In addition to on-board lamps, which have been significantly more stable than the lamps on ETM+, the ALI has a solar diffuser and has imaged the moon monthly since launch. This combined calibration dataset allows understanding of the radiometric stability of the ALI system, its calibrators and some differentiation of the sources of the changes with time. The solar dataset is limited as the mechanism controlling the aperture to the solar diffuser failed approximately 18 months after launch. Results over 5 years indicate that: the shortest wavelength band (443 nm) has degraded in response about 2%; the 482 nm and 565 nm bands decreased in response about 1%; the 660 nm, 790 nm and 868 nm bands each degraded about 5%; the 1250 nm and 1650 nm bands did not change significantly and the 2215 nm band increased in response about 2%.

Conference Paper↗