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At least 145 records · Page 8Linked to original sources

USGS2021

System characterization report on the German Aerospace Center (DLR) Earth Sensing Imaging Spectrometer (DESIS)

Executive Summary This report addresses system characterization of the German Aerospace Center (DLR) Earth Sensing Imaging Spectrometer (DESIS) and is part of a series of system characterization reports produced and delivered by the U.S. Geological Survey Earth Resources Observation and Science Cal/Val Center of Excellence. These reports present the methodology and procedures for characterization and the technical and operational information about the specific sensing system being evaluated. These reports also provide a description of data measurements, data retention practices, and data analysis results and provide system characterization conclusions. In partnership with Teledyne Brown Engineering, DLR built the DESIS hyperspectral instrument, which Teledyne Brown Engineering then integrated onto its International Space Station-based imaging platform, the Multi-User System for Earth Sensing. DLR developed the processing software and, together with Innovative Imaging and Research, completes the validation and calibration of the data products. DESIS was launched in 2018, and the data are used for scientific research in atmospheric physics and Earth sciences. The DESIS sensor contributes to the scientific and commercial utilization of the International Space Station and helps to further hyperspectral remote sensing technologies for future satellites. More information on DLR satellites and sensors is included within the “2020 Joint Agency Commercial Imagery Evaluation—Remote Sensing Satellite Compendium” and at https://www.dlr.de/DE/Home/home_node.html . The Earth Resources Observation and Science Cal/Val Center of Excellence system characterization team completed data analyses to characterize the geometric (interior and exterior), radiometric, and spatial performances. Results of these analyses indicate that DESIS has an interior geometric performance of less than a 3.30-meter (less than 0.11 pixel) root mean square error in band-to-band registration, an exterior geometric performance in the range of a 2.40- (0.08 pixel) to 17.40-meter (0.58 pixel) offset in comparison to the Landsat 8 Operational Land Imager, a radiometric performance in the range of −0.013 to 1.011 (offset and slope), and a spatial performance for band 130 of 1.5 pixels at full width at half maximum, with a modulation transfer function at a Nyquist frequency of 0.167.

Open-File Report↗

USGS2021

DLR Earth Sensing Imaging Spectrometer (DESIS) level 1 product evaluation using RadCalNet measurements

The DLR Earth Sensing Imaging Spectrometer (DESIS) is the first hyperspectral imaging spectrometer installed in the Multi-User System for Earth Sensing (MUSES) on the International Space Station (ISS) for acquiring routine science grade images from orbit. It was launched on 29 June 2018 and integrated into MUSES. DESIS measures energy in the spectral range of 400 to 1000 nm with high spatial and spectral resolution: 30 m and 2.55 nm, respectively. DESIS data should be sufficiently quantitative and accurate to use it for different applications and research. This work performs a radiometric evaluation of DESIS Level 1 product (Top of Atmosphere (TOA) reflectance) by comparing it with coincident Radiometric Calibration Network (RadCalNet) measurements at Railroad Valley Playa (RVUS), Gobabeb (GONA), and La Crau (LCFR). RVUS, GONA, and LCFR offer 4, 15, and 5 coincident datasets between DESIS and RadCalNet measurements, respectively. The results show an agreement between DESIS and RadCalNet TOA reflectance within ~5% for most spectral regions. However, there is an additional ~5% disagreement across the wavelengths affected by water vapor absorption and atmospheric scattering. Among the three RadCalNet sites, RVUS and GONA show a similar measurement disagreement with DESIS of ~5%, while LCFR differs by ~10%. Agreement between DESIS and RadCalNet measurements is variable across all three sites, likely due to surface type differences. DESIS and RadCalNet agreement show a precision of ~2.5%, 4%, and 7% at RVUS, GONA, and LCFR, respectively. RVUS and GONA, which have a similar surface type, sand, have a similar level of radiometric accuracy and precision, whereas LCFR, which consists of sparse vegetation, has lower accuracy and precision. The observed precision of DESIS Level 1 products from all the sites, especially LCFR, can be improved with a better Bidirectional Reflection Distribution Function (BRDF) characterization of the RadCalNet sites.

Remote Sensing↗

USGS2010

eMODIS: A User-Friendly Data Source

The U.S. Geological Survey's (USGS) Earth Resources Observation and Science (EROS) Center is generating a suite of products called 'eMODIS' based on Moderate Resolution Imaging Spectroradiometer (MODIS) data acquired by the National Aeronautics and Space Administration's (NASA) Earth Observing System (EOS). With a more frequent repeat cycle than Landsat and higher spatial resolutions than the Advanced Very High Resolution Spectroradiometer (AVHRR), MODIS is well suited for vegetation studies. For operational monitoring, however, the benefits of MODIS are counteracted by usability issues with the standard map projection, file format, composite interval, high-latitude 'bow-tie' effects, and production latency. eMODIS responds to a community-specific need for alternatively packaged MODIS data, addressing each of these factors for real-time monitoring and historical trend analysis. eMODIS processes calibrated radiance data (level-1B) acquired by the MODIS sensors on the EOS Terra and Aqua satellites by combining MODIS Land Science Collection 5 Atmospherically Corrected Surface Reflectance production code and USGS EROS MODIS Direct Broadcast System (DBS) software to create surface reflectance and Normalized Difference Vegetation Index (NDVI) products. eMODIS is produced over the continental United States and over Alaska extending into Canada to cover the Yukon River Basin. The 250-meter (m), 500-m, and 1,000-m products are delivered in Geostationary Earth Orbit Tagged Image File Format (Geo- TIFF) and composited in 7-day intervals. eMODIS composites are projected to non-Sinusoidal mapping grids that best suit the geography in their areas of application (see eMODIS Product Description below). For eMODIS products generated over the continental United States (eMODIS CONUS), the Terra (from 2000) and Aqua (from 2002) records are available and continue through present time. eMODIS CONUS also is generated in an expedited process that delivers a 7-day rolling composite, created daily with the most recent 7 days of acquisition, to users monitoring real-time vegetation conditions. eMODIS Alaska is not part of expedited processing, but does cover the Terra mission life (2000-present). A simple file transfer protocol (FTP) distribution site currently is enabled on the Internet for direct download of eMODIS products (ftp://emodisftp.cr.usgs.gov/eMODIS), with plans to expand into an interactive portal environment.

Open-File Report↗

USGS2026

Landsat 8–9 geometric and radiometric calibration and characterization

The U.S. Geological Survey Earth Resources Observation and Science Cal/Val (Calibration and Validation) Center of Excellence is a global leader in improving the accuracy, precision, and quality of remote-sensing data. Calibration is the process of quantitatively defining a system’s response to known and controlled signal inputs. Validation is the process of assessing, by independent means, the quality of the calibrated data products derived from system outputs. The Landsat Cal/Val team, comanaged by the Earth Resources Observation and Science Cal/Val Center of Excellence and the National Aeronautics and Space Administration Landsat Science Project, continually monitors the geometric and radiometric performance of active Landsat missions and makes calibration adjustments, as needed, to maintain data quality at the highest level, ensuring its reliability for scientific research. Landsat data quality is often referred to as the “gold standard” and gives other civil and commercial satellite programs a trusted reference point for measuring their own data quality. The Landsat program started more than 50 years ago. Since then, Landsat missions have gone through multiple technological advances, which, together with improved calibration and validation techniques, have led to higher data quality over time. The Cal/Val team also maintains consistency in data calibration across the multiple generations of sensors, which is vital to many scientists for time-series analysis.

Fact Sheet↗

USGS2025

System characterization report on Resourcesat-2A Advanced Wide Field Sensor

Executive Summary This report documents the system characterization of the Indian Space Research Organisation Resourcesat-2A Advanced Wide Field Sensor (AWiFS) and is part of a series of system characterization reports produced by the U.S. Geological Survey Earth Resources Observation and Science Cal/Val Center of Excellence. These reports describe the methodology and procedures used for characterization, present technical and operational information about the specific sensing system being evaluated, and provide a summary of test measurements, data retention practices, data analysis results, and conclusions. Resourcesat-2A was launched in 2016 on the Polar Satellite Launch Vehicle-C36; it is identical to Resourcesat-2, and together, they decrease imaging revisit time from 5 days to 2–3 days, providing data continuity and improved temporal resolution. Resourcesat-2 and -2A carry the AWiFS, Linear Imaging Self Scanning-3, and Linear Imaging Self Scanning-4 medium-resolution imaging sensors, continuing the legacy of the Indian Space Research Organisation’s Indian Remote Sensing-1C/1D/P3 satellite programs. More information about Indian Space Research Organisation satellites and sensors is available through the Joint Agency Commercial Imagery Evaluation Earth Observing Satellites Online Compendium and from the Indian Space Research Organisation at https://www.isro.gov.in/ . The Earth Resources Observation and Science Cal/Val Center of Excellence system characterization team assessed the geometric, radiometric, and spatial performance of the Resourcesat-2A AWiFS sensor. Geometric performance is divided into the interior geometric performance of band-to-band registration and the exterior geometric performance of geolocation accuracy. The interior geometric performance had offsets in the range of −1.10 meters (m; −0.020 pixel) to 3.67 m (0.066 pixel) in easting and −5.68 m (−0.101 pixel) to 10.38 m (0.185 pixel) in northing with root mean square error values from 5.60 m (0.100 pixel) to 11.31 m (0.202 pixel) in easting and from 3.00 m (0.054 pixel) to 13.52 m (0.241 pixel) in northing. The exterior geometric performance had mean offsets of −25.29 m in easting and 16.22 m northing with root mean square error values of 26.07 m in easting and 17.60 m in northing compared to the Landsat 8 Operational Land Imager sensor. The radiometric performance had offsets from −0.002 to 0.029 and slopes from 0.733 to 1.012. Spatial performance was in the range of 1.354 to 1.639 pixels for full width at half maximum with a modulation transfer function at a Nyquist frequency in the range of 0.108 to 0.174.

Open-File Report↗

USGS2025

System characterization report on Resourcesat-2A Linear Imaging Self Scanning-4 sensor

Executive Summary This report documents the system characterization of the Indian Space Research Organisation Resourcesat-2A Linear Imaging Self Scanning-4 (LISS–4) sensor. It is part of a series of system characterization reports produced by the U.S. Geological Survey Earth Resources Observation and Science Cal/Val Center of Excellence. These reports describe the methodology and procedures used for characterization, present technical and operational information about the specific sensing system being evaluated, and provide a summary of test measurements, data retention practices, data analysis results, and conclusions. Resourcesat-2A was launched in 2016 on the Polar Satellite Launch Vehicle-C36; it is identical to Resourcesat-2, and together, they decrease imaging revisit time from 5 days to 2–3 days, providing data continuity and improved temporal resolution. Resouresat-2 and 2A carry the Advanced Wide Field Sensor, Linear Imaging Self Scanning-3, and LISS–4 medium-resolution imaging sensors, continuing the legacy of the Indian Space Research Organisation’s Indian Remote Sensing-1C/1D/P3 satellite programs. More information about the Indian Space Research Organisation’s satellites and sensors is available through the Joint Agency Commercial Imagery Evaluation Earth Observing Satellites Online Compendium at https://calval.cr.usgs.gov/apps/compendium/ and from the manufacturer at https://www.isro.gov.in/ . The Earth Resources Observation and Science Cal/Val Center of Excellence system characterization team assessed the geometric, radiometric, and spatial performances of the Resourcesat-2A LISS–4 sensor. Geometric performance is divided into the interior geometric performance of band-to-band registration and the exterior geometric performance of geolocation accuracy. The interior geometric performance had mean offsets in the range of −0.118 to 0.024 pixel in easting and −0.053 to 0.022 pixel in northing with root mean square error values from 0.067 to 0.230 pixel in easting and from 0.087 to 0.2 pixel in northing. The exterior geometric performance had offsets in the range of 2.55 to 7.85 meters (m) in easting and −6.15 to 11.15 m in northing with root mean square error values in the range of 2.6 to 8.2 m in easting and 6.35 to 11.8 m in northing compared to the U.S. Department of Agriculture National Agriculture Imagery Program and WorldView-3 orthoimages. The measured radiometric performance had offsets from 0.003 to 0.024 and slopes from 0.736 to 0.952, and spatial performance was in the range of 1.633 to 1.903 pixels for the full width at half maximum with a modulation transfer function at a Nyquist frequency in the range of 0.0529 to 0.0952.

Open-File Report↗

USGS2016

Landsat Science Team: 2016 winter meeting summary

The winter meeting of the joint U.S. Geological Survey (USGS)–NASA Landsat Science Team (LST) was held January 12-14, 2016, at Virginia Tech University in Blacksburg, VA. LST co-chairs Tom Loveland [USGS’s Earth Resources Observation and Science Data Center (EROS)—Senior Scientist] and Jim Irons [NASA’s Goddard Space Flight Center (GSFC)—Landsat 8 Project Scientist] welcomed more than 50 participants to the three-day meeting. The main objectives of this meeting focused on identifying priorities and approaches to improve the global moderate-resolution satellite record. Overall, the meeting was geared more towards soliciting team member recommendations on several rapidly evolving issues, than on providing updates on individual research activities. All the presentations given at the meeting are available at landsat.usgs. gov//science_LST_january2016.php.

The Earth Observer↗

USGS2006

Absolute calibration accuracy of L4 TM and L5 TM sensor image pairs

The Landsat suite of satellites has collected the longest continuous archive of multispectral data of any land-observing space program. From the Landsat program's inception in 1972 to the present, the Earth science user community has benefited from a historical record of remotely sensed data. However, little attention has been paid to ensuring that the data are calibrated and comparable from mission to mission, Launched in 1982 and 1984 respectively, the Landsat 4 (L4) and Landsat 5 (L5) Thematic Mappers (TM) are the backbone of an extensive archive of moderate resolution Earth imagery. To evaluate the "current" absolute accuracy of these two sensors, image pairs from the L5 TM and L4 TM sensors were compared. The approach involves comparing image statistics derived from large common areas observed eight days apart by the two sensors. The average percent differences in reflectance estimates obtained from the L4 TM agree with those from the L5 TM to within 15 percent. Additional work to characterize the absolute differences between the two sensors over the entire mission is in progress.

Conference Paper↗

USGS2016

How well are you teaching one of the most important biological concepts for humankind? A call to action

We represent several generations of biology educators – with teaching experiences beginning in the 1940s and continuing to the present, from elementary school to graduate-level programs. We find the vast array of subjects that biology teachers can now cover both thrilling and mind-boggling. Depending on the grade level, units exist that focus on neurobiology, forensics, DNA analysis, biotechnology, marine biology, and a host of other topics. Although science teachers cover a potpourri of advanced topics, we must ask ourselves – no matter our biology-teaching responsibilities – how well we are teaching carrying capacity , one of the most fundamental biological concepts for our society, knowledge of which becomes more important every day. As biology teachers, most of you know that carrying capacity is defined as the maximum population an environment can sustain, given the amounts of food, habitat, and other resources available. Every environment – from your goldfish bowl to the local forest to planet Earth – can only sustain a set number (weight) of a particular species, based on available resources and space. Currently, most science classes teach …

The American Biology Teacher↗

USGS2016

Dendritic network models: Improving isoscapes and quantifying influence of landscape and in-stream processes on strontium isotopes in rivers

A critical challenge for the Earth sciences is to trace the transport and flux of matter within and among aquatic, terrestrial, and atmospheric systems. Robust descriptions of isotopic patterns across space and time, called “isoscapes,” form the basis of a rapidly growing and wide-ranging body of research aimed at quantifying connectivity within and among Earth's systems. However, isoscapes of rivers have been limited by conventional Euclidean approaches in geostatistics and the lack of a quantitative framework to apportion the influence of processes driven by landscape features versus in-stream phenomena. Here we demonstrate how dendritic network models substantially improve the accuracy of isoscapes of strontium isotopes and partition the influence of hydrologic transport versus local geologic features on strontium isotope ratios in a large Alaska river. This work illustrates the analytical power of dendritic network models for the field of isotope biogeochemistry, particularly for provenance studies of modern and ancient animals.

Geophysical Research Letters↗

USGS2008

Magnetic monitoring of earth and space

For centuries, navigators of the world’s oceans have been familiar with an effect of Earth’s magnetic field: It imparts a directional preference to the needle of a compass. Although in some settings magnetic orientation remains important, the modern science of geomagnetismhas emerged from its romantic nautical origins and developed into a subject of great depth and diversity. The geomagnetic field is used to explore the dynamics of Earth’s interior and its surrounding space environment, and geomagnetic data are used for geophysical mapping, mineral exploration, risk mitigation, and other practical applications. A global distribution of ground-based magnetic observatories supports those pursuits by providing accurate records of the magnetic-field direction and intensity at fixed locations and over long periods of time. Magnetic observatories were first established in the early 19th century in response to the influence of Alexander von Humboldt and Carl Friedrich Gauss. Since then, magnetic measurement has advanced significantly, progressing from simple visual readings of magnetic survey instruments to include automatic photographic measurement and modern electronic acquisition. To satisfy the needs of the scientific community, observatories are being upgraded to collect data that meet ever more stringent standards, to achieve higher acquisition frequencies, and to disseminate data in real time. To appreciate why data from magnetic observatories can be used for so many purposes, one needs only to recall that the geomagnetic field is a continuum, connecting the different parts of Earth to each other and to nearby space. Beneath our feet and above our heads, electric currents generate magnetic fields that contribute to the totality of the geomagnetic field measured at an observatory on Earth’s surface. The many physical processes that operate in each geophysical domain give rise to a complicated field that exhibits a wide variety of time-dependent behavior. In this article I review the status of the global community of magnetic observatories, show how Earth and space can be monitored for purposes of scientific understanding and practical application, and highlight the role played by magnetic observatories in the history of geomagnetism research.

Physics Today↗

USGS1997

The Landsat program: Its origins, evolution, and impacts

Landsat 1 began an era of space-based resource data collection that changed the way science, industry, governments, and the general public view the Earth. For the last 25 years, the Landsat program - despite being hampered by institutional problems and budget uncertainties - has successfully provided a continuous supply of synoptic, repetitive, multi-spectral data of the Earth's land areas. These data have profoundly affected programs for mapping resources, monitoring environmental changes, and assessing global habitability. The societal applications this program generated are so compelling that international systems have proliferated to carry on the tasks initiated with Landsat data.

Photogrammetric Engineering and Remote Sensing↗

USGS2025

System characterization report on Resourcesat-2A Linear Imaging Self Scanning-3 sensor

Executive Summary This report addresses system characterization of the Indian Space Research Organisation Resourcesat-2A Linear Imaging Self Scanning-3 sensor and is part of a series of system characterization reports produced and delivered by the U.S. Geological Survey Earth Resources Observation and Science Cal/Val Center of Excellence since 2021. These reports present and detail the methodology and procedures for characterization, present technical and operational information about the specific sensing system being evaluated, and provide a summary of test measurements, data retention practices, data analysis results, and conclusions. Resourcesat-2A is identical to Resourcesat-2 and was launched in 2016 on the Polar Satellite Launch Vehicle-C36 for continuity of data and improved temporal resolution. The Resourcesat-2 platform (which includes Resourcesat-2A) is of Indian Remote Sensing Satellites-1C/1D–P3 heritage and was built by the Indian Space Research Organisation. Resourcesat-2 and Resourcesat-2A carry the Linear Imaging Self Scanning-3 and Linear Imaging Self Scanning-4 sensors for medium-resolution imaging. More information on Indian Space Research Organisation satellites and sensors is available in the “2022 Joint Agency Commercial Imagery Evaluation—Remote Sensing Satellite Compendium” and from the manufacturer at https://www.isro.gov.in/ . The Earth Resources Observation and Science Cal/Val Center of Excellence system characterization team completed data analyses to characterize the geometric (interior and exterior), radiometric, and spatial performances. To summarize the results, we have determined that this sensor provides an interior geometric performance with mean offsets in the range of 1.75 meters (m; 0.06 pixel) to 6.83 m (0.23 pixel) in easting and −1.83 m (−0.06 pixel) to 1.81 m (0.06 pixel) in northing in band-to-band registration and a root mean square error in the range of 3.81 m (0.13 pixel) to 8.19 m (0.27 pixel) in easting and 2.21 m (0.09 pixel) to 4.72 m (0.16 pixel) in northing. We have measured an exterior geometric error offset in the range of −21.29 to 6.88 m in easting and −7.35 to −2.63 m in northing, and the root mean square error is in the range of 7.19 to 21.43 m in easting and 3.64 to 8.19 m in northing in comparison to the Landsat 8 Operational Land Imager. The measured radiometric performance was in the range of −0.002 to 0.031 in offset and 0.701 to 0.940 in slope, and the spatial performance was in the range of 1.204 to 1.265 pixels for full width at half maximum with a modulation transfer function at a Nyquist frequency in the range of 0.251 to 0.277.

Open-File Report↗

USGS1967

Geomagnetic polarity epochs: new data from Olduvai Gorge, Tanganyika

The lower lava flow of Bed I in Olduvai Gorge, Tanganyika, carries natural remanent magnetization (NRM) having normal polarity. Thermal demagnetization experiments demonstrate the stability of this NRM. Thus the Olduvai geomagnetic polarity event, which was originally named from the upper lava flow in Bed I, is represented in its type locality by two normally magnetized lavas. These lavas have been shown to be 1.9 m.y. old, and although they are distinct from each other in composition and surface structure, their eruptions appear to have been closely spaced in time.

Tanganyika↗

USGS2020

Landslide disparities, flume discoveries, and Oso despair

Landslide dynamics is the branch of science that seeks to understand the motion of landslides by applying Newton's laws. This memoir focusses on a 40‐year effort to understand motion of highly mobile—and highly lethal—landslides such as debris avalanches and debris flows. A major component of this work entailed development and operation of the U.S. Geological Survey debris flow flume, a unique, large‐scale experimental facility in Oregon. Experiments there yielded new insights that informed development of mathematical models that were aimed not only at explaining landslide dynamics but also at evaluating landslide and debris flow hazards. The most sophisticated of these models, called D‐Claw, found its first practical application during investigations of the 2014 Oso, Washington, landslide disaster. That event provided indelible lessons about the utility and sociology of science in the real world.

Washington↗

USGS2016

The Land Processes Distributed Active Archive Center (LP DAAC)

The Land Processes Distributed Active Archive Center (LP DAAC) operates as a partnership with the U.S. Geological Survey and is 1 of 12 DAACs within the National Aeronautics and Space Administration (NASA) Earth Observing System Data and Information System (EOSDIS). The LP DAAC ingests, archives, processes, and distributes NASA Earth science remote sensing data. These data are provided to the public at no charge. Data distributed by the LP DAAC provide information about Earth’s surface from daily to yearly intervals and at 15 to 5,600 meter spatial resolution. Data provided by the LP DAAC can be used to study changes in agriculture, vegetation, ecosystems, elevation, and much more. The LP DAAC provides several ways to access, process, and interact with these data. In addition, the LP DAAC is actively archiving new datasets to provide users with a variety of data to study the Earth.

Fact Sheet↗

USGS2018

Science at the frontier: Multimethod research to evaluate ecosystem change across multiple scales

Changes in the Earth system occur across the full spectrum of spatial and temporal scales, yet our research approaches to understanding and predicting those changes are typically restricted to a pre-defined window of space and time. For this reason, there is substantial power in integrating different approaches, particularly for research associated with the multifaceted nature of ecosystem responses to global change. Within a given research approach – for example, remote sensing, field experimentation, modeling – science promotes the continued advancement of tools and techniques. As technical advancements continue at an unprecedented rate, new opportunities for integrated, multi-approach research emerge, which could more effectively capture the mechanisms and patterns that drive ecosystem structure and function. A capacity to move beyond comparison and into the realm of integration shows promise for promoting significant advances in Earth system science, as evidenced by the Organized Session Science at the Frontier: Using Multimethod Research to Create New Knowledge and Assess Tools Across Spatial and Temporal Scales on December 12, 2017 at the Fall meeting of the American Geophysical Union in New Orleans, Louisiana.

New Phytologist↗

USGS1982

Assessment of models proposed for the 1981 revision of the IGRF

For the second revision of the International Geomagnetic Reference Field (IGRF), the U. S. National Aeronautics and Space Administration (NASA), the U. K. Institute of Geological Sciences (IGS), and the U. S. Geological Survey (USGS) submitted proposed models of the Earth's main magnetic field at 1965.0, 1970.0, 1975.0, and 1980.0, and its secular variation during 1980-1985. We assessed the proposed models by comparing them with annual mean values from worldwide magnetic observatories, data for 1978-1980 from 63 U. S. magnetic repeat stations, and rates-of-change values for worldwide magnetic observatories for 1965-1985 that were derived from straight lines fitted to annual means for five-year intervals. We also mutually compared the 1980 models.

Journal of Geomagnetism & Geoelectricity↗