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At least 307 records · Page 17Linked to original sources
USGS2018

National Satellite Land Remote Sensing Data Archive

The National Satellite Land Remote Sensing Data Archive is managed on behalf of the Secretary of the Interior by the U.S. Geological Survey’s Earth Resources Observation and Science Center. The Land Remote Sensing Policy Act of 1992 (51 U.S.C. §601) directed the U.S. Department of the Interior to establish a permanent global archive consisting of imagery over land areas obtained from satellites orbiting the Earth. The law also directed the U.S. Department of the Interior, delegated to the U.S. Geological Survey, to ensure proper storage and preservation of imagery, and timely access for all parties. Since 2008, these images have been available at no cost to the user.

Fact Sheet↗
USGS1980

Introduction to the U.S. Geological Survey's EROS Data Center Sioux Falls, South Dakota

The EROS Data Center is a part of the Earth Resources Observation Systems (EROS) Office of the Department of the Interior and is managed by the U.S. Geological Survey. It is the national clearinghouse for the processing and dissemination of spacecraft- and aircraft-acquired images and photographs and electronic data on the Earth's resources. The Center also trains and assists users in the application of such data.

South Dakota↗
USGS2020

Surface soil temperature seasonal variation estimation in a forested area using combined satellite observations and in-situ measurements

Surface soil temperature is the soil temperature from the surface to 10 cm in depth. Surface soil temperature plays a significant role in agricultural drought monitoring, ecosystem energy transfer modeling, and global carbon cycle evaluation. Studies have been proposed to estimate surface soil temperature, but surface soil temperature monitoring within forested areas still poses a significant challenge. In this study, we proposed a surface soil temperature retrieval method using combined satellite observations and in-situ measurements for the Great Dismal Swamp (GDS). The GDS is a U.S. protected area managed and protected by the U.S. Fish and Wildlife Service. It is located along the boundary of Virginia and North Carolina, with maple gum, Atlantic white cedar, and pine pocosin as the main forest cover types. Ground-based surface soil temperature measurements were collected for these forest types from May 2015 to April 2017. Both the Land Remote Sensing Satellite (Landsat) Thermal Infrared Sensor (TIRS) and the Moderate Resolution Imaging Spectroradiometer (MODIS) carry two thermal infrared (TIR) channels. The TIR channels with similar corresponding wavelengths were first fused using an improved fusing model to generate high resolution TIR measurements. Then the enterprise algorithm was applied to calculate land surface temperature (LST) from the fused TIR bands. An improved soil temperature retrieval method was applied to generate surface soil temperature based on LST and vegetation index (VI) within the study area for the three forest types. In-situ measurements were used to build the surface soil temperature retrieval method, and results were then validated. The normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI) were integrated separately as VIs in the model to monitor surface soil temperature. The R 2 for retrieved surface soil temperature through satellite observations was 0.76, and the RMSE was 1.96 ℃ ">℃ ℃ when NDVI was integrated in the model; the R 2 was 0.78, and the RMSE was 1.85 ℃ ">℃ ℃ when EVI was used.

North Carolina, Virginia↗
USGS1974

First EROS/AID International Course on remote sensing

The First International Training Course on Remote Sensing held at the Earth Resources Observations Systems (EROS) Data Center in Sioux Falls, South Dakota, was sponsored by the Agency for International Development (AID), U.S. Department of State, from June 4 to 27, 1973. This course was conducted by the U.S. Geological Survey (USGS) under Participating Agency Services Agreement (PASA) TA (IC) 2-72, 931-11-995-902-72-3138905, as part of the AID program to provide training in remote sensing technology for earth scientists in the less developed countries.

South Dakota↗
USGS2014

Forecasting distribution of numbers of large fires

Systems to estimate forest fire potential commonly utilize one or more indexes that relate to expected fire behavior; however they indicate neither the chance that a large fire will occur, nor the expected number of large fires. That is, they do not quantify the probabilistic nature of fire danger. In this work we use large fire occurrence information from the Monitoring Trends in Burn Severity project, and satellite and surface observations of fuel conditions in the form of the Fire Potential Index, to estimate two aspects of fire danger: 1) the probability that a 1 acre ignition will result in a 100+ acre fire, and 2) the probabilities of having at least 1, 2, 3, or 4 large fires within a Predictive Services Area in the forthcoming week. These statistical processes are the main thrust of the paper and are used to produce two daily national forecasts that are available from the U.S. Geological Survey, Earth Resources Observation and Science Center and via the Wildland Fire Assessment System. A validation study of our forecasts for the 2013 fire season demonstrated good agreement between observed and forecasted values.

Book↗
USGS2013

Hierarchical Bayesian spatial models for predicting multiple forest variables using waveform LiDAR, hyperspectral imagery, and large inventory datasets

In this paper we detail a multivariate spatial regression model that couples LiDAR, hyperspectral and forest inventory data to predict forest outcome variables at a high spatial resolution. The proposed model is used to analyze forest inventory data collected on the US Forest Service Penobscot Experimental Forest (PEF), ME, USA. In addition to helping meet the regression model's assumptions, results from the PEF analysis suggest that the addition of multivariate spatial random effects improves model fit and predictive ability, compared with two commonly applied modeling approaches. This improvement results from explicitly modeling the covariation among forest outcome variables and spatial dependence among observations through the random effects. Direct application of such multivariate models to even moderately large datasets is often computationally infeasible because of cubic order matrix algorithms involved in estimation. We apply a spatial dimension reduction technique to help overcome this computational hurdle without sacrificing richness in modeling.

Maine↗
USGS2024

On-orbit calibration and performance of the EMIT imaging spectrometer

The Earth surface Mineral dust source InvesTigation (EMIT) is a remote visible to shortwave infrared (VSWIR) imaging spectrometer that has been operating onboard the International Space Station since July 2022. This article describes EMIT's on-orbit spectroradiometric calibration and validation. Accurate spectroscopy is vital to achieve consistent mapping results with orbital imaging spectrometers. EMIT takes a unique approach to this challenge, with just six optical elements, no shutter, and no onboard calibration systems. Its simple design focuses on uniformity and stability to enable vicarious spectroradiometric calibration. Our experiments demonstrate that this approach is successful, approaching the fidelity of manual field spectroscopy in some cases, and enabling new and more accurate products across diverse Earth science disciplines. EMIT achieves several notable firsts for an instrument of its class. It demonstrates successful on-orbit adjustments of Focal Plane Array (FPA) alignment with sub-micron precision. It offers spectral uniformity better than 98%. Optical artifacts in the measurement channels are at least three orders of magnitude below the primary solar-reflected surface signals. Its noise performance enables percent-level discrimination in the depths of mineral absorption features. In these aspects, EMIT satisfies the stringent performance needs for the next generation of VSWIR imaging spectrometers to observe the Earth's ecosystems, geology , and water resources.

Remote Sensing of Environment↗
USGS2023

ECCOE Landsat quarterly Calibration and Validation report—Quarter 1, 2023

Executive Summary The U.S. Geological Survey Earth Resources Observation and Science Calibration and Validation (Cal/Val) Center of Excellence (ECCOE) focuses on improving the accuracy, precision, calibration, and product quality of remote-sensing data, leveraging years of multiscale optical system geometric and radiometric calibration and characterization experience. The ECCOE Landsat Cal/Val Team 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. This report provides observed geometric and radiometric analysis results for Landsats 7–8 for quarter 1 (January–March) of 2023. All data used to compile the Cal/Val analysis results presented in this report are freely available from the U.S. Geological Survey EarthExplorer website: https://earthexplorer.usgs.gov . One specific activity that the ECCOE Landsat Cal/Val Team closely monitored was a Landsat 8 safehold anomaly. On January 26, 2023, the Global Positioning System (GPS) onboard Landsat 8 became invalid because the GPS fault tripped. Later that same day, the GPS was reinitialized, but a Field of View 1 fault trip occurred early the next morning, causing the observatory to go into Earth Point Safe mode, which put the Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) into safehold. Once it was safe to reactivate the sensors, the OLI was transitioned to operational status late on January 27 and TIRS was reactivated early on January 28. Additional information about the Landsat 8 safehold anomaly is here: https://www.usgs.gov/landsat-missions/news/landsat-8-recovers-safehold .

Open-File Report↗
USGS2024

Landsat geometric and radiometric calibration and characterization

The U.S. Geological Survey (USGS) Earth Resources Observation and Science Calibration and Validation (Cal/Val) Center of Excellence (ECCOE) focuses on improving the accuracy, precision, calibration, and product quality of remote-sensing data, leveraging years of multiscale optical system geometric and radiometric calibration and characterization experience. The ECCOE Landsat Cal/Val team 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 ( Haque and others, 2024 ). The accuracy of the ECCOE team calibration adjustments gives other civil and commercial satellite programs around the globe a trusted criterion and reference point. The ECCOE team works with U.S. and international government agencies and commercial vendors to help harmonize data sources as more frequent, consistent views of Earth benefits scientific research. Since the program started, more than 50 years ago, Landsat data have improved. When advances in calibration and validation today are applied to past satellite missions, researchers can consistently see how land changes over decades. To maintain this criterion, the ECCOE team continues to seek new and better ways to calibrate and validate data, which includes using the moon for calibration and drones for ground validation (fig. 1).

Fact Sheet↗
USGS2025

An automated compositing method for producing annual clear images from Landsat Collection 2 for annual NLCD production

Quality image input is fundamental to the quality of derived land cover products. Substantial time and effort are usually required to prepare images. Here, we present a novel and streamlined compositing algorithm that ingests Landsat Collection 2 Analysis Ready Data (ARD) and outputs cloud-free and gap-free composite imagery, which can be directly used for classification. This method leverages and improves the previous National Land Cover Database (NLCD) Virtual Median Value Point (VMVP) compositing method, the first part of the image preparation for NLCD 2019 operational production. The NLCD 2019 image preparation approach includes a second part, a residual cloud and cloud shadow detection and gap-filling method, to produce final cloud-free and gap-free composite imagery. The second part requires one clear reference image for each target year. Additional reference images are needed for producing reasonable observations for perennial ice/snow areas because Pixel QA (Quality Assessment) from ARD has difficulties differentiating ice/snow areas from clouds. Unlike the NLCD 2019 image preparation approach, our new compositing method, which is referred to as Automated VMVP (AVMVP), uses Landsat ARD as the only input and does not require reference images and extra steps. In this method, we developed new spectral filter criteria coupled with counts of clear observations using Pixel QA to identify potential cloud and cloud shadow observations on initially selected observations from the NLCD VMVP compositing algorithm. We also automate “gap-filling” using clear observations retrieved from a maximum of ±2 years around the target year when needed. Finally, a percentile-filtered compositing method was developed for the perennial ice/snow areas. All these steps are streamlined, pixel-based, and directly run on Landsat Collection 2 ARD. We have run successful tests on the conterminous United States (CONUS). Composite images derived from our innovative method were used to produce the CONUS Annual NLCD Collection 1 product suite that covers the period from 1985 to 2023.

conterminous United States↗
USGS1999

The EOS land validation core sites: background information and current status

The EOS Land Validation Core Sites1 will provide the user community with timely ground, aircraft, and satellite data for EOS science and validation investigations. The sites, currently 24 distributed worldwide, represent a consensus among the instrument teams and validation investigators and represent a range of global biome types (see Figure 1 and Table 1; Privette et al., 1999; Justice et al., 1998). The sites typically have a history of in situ and remote observations and can expect continued monitoring and land cover research activities. In many cases, a Core Site will have a tower equipped with above-canopy instrumentation for nearcontinuous sampling of landscape radiometric, energy and CO2 flux, meteorological variables, and atmospheric aerosol and water vapor data. These will be complemented by intensive field measurement campaigns. The data collected at these sites will provide an important resource for the broader science community. These sites can also provide a foundation for a validation network supported and used by all international space agencies.

The Earth Observer↗
USGS2001

Geologic Maps of the Dardanus Sulcus (Jg-6), Misharu (Jg-10), Nabu (Jg-11), and Namtar (Jg-14) Quadrangles of Ganymede

Ganymede is the largest (~5,200 km diameter) of the Jovian satellites. Surficial features on Ganymede, as recorded by the Voyager 1 and 2 spacecraft (Smith and others, 1979a; 1979b), indicate a complex history of crustal formation. Several episodes of crustal modification led to the formation of curvilinear systems of furrows in dark terrain, the emplacement of light materials, and the creation of grooves in light terrain. Prior to exploration of the Jovian system by spacecraft, Earth-based observations established that the surface of Ganymede is dominated by water ice with various admixtures of fine silicate (rock) material (Pilcher and others, 1972; Sill and Clark, 1982). No agreement yet exists as to the amount of water in the near surface material; early estimates based on spectral reflectance data suggested that half the surface was covered by nearly pure water ice, whereas later studies by Clark (1981) indicated that up to 95% of the surface could be water ice and still be consistent with spectroscopic data. The Pioneer encounters with the Jovian system in 1973 and 1974 confirmed that Ganymede was made up of patches of light and dark terrain but did not have the spatial resolution needed to determine the percent cover of water ice, or geologic relations of surface materials. Not until the Voyager encounters was the surface seen with sufficient detail to enable geologic mapping. On the basis of albedo contrasts, surface morphology, crater density, and superposition relations, geologic mapping was done using principles and techniques that have been applied to the Earth, Moon, and other terrestrial planets (Wilhelms, 1972). Considerable uncertainty exists in applying such methods to bodies having icy crusts, as the internal processes that produce their surface configurations are poorly understood, and the resolution of the Voyager images is barely sufficient to show the detail required to interpret structural and stratigraphic relations. With the exception of the extreme southeastern portion of the Namtar quadrangle (Jg- 14), all images used for mapping were taken by Voyager 1. At the time of encounter, the eastern portion of the Misharu (Jg–10) and Namtar quadrangles were near the terminator, making it difficult to distinguish albedo variations best seen at high sun angles. The western quadrangles were imaged at resolutions of 2–5 km/pixel (Batson and others, 1980) from an oblique angle, so albedo variations can be seen, but topography and morphology are not well expressed in the images.

IMAP↗
USGS2005

An astrobiological perspective on Meridiani Planum

Sedimentary rocks exposed in the Meridiani Planum region of Mars record aqueous and eolian deposition in ancient dune and interdune playa-like environments that were arid, acidic, and oxidizing. On Earth, microbial populations have repeatedly adapted to low pH and both episodic and chronic water limitation, suggesting that, to a first approximation, the Meridiani plain may have been habitable during at least part of the interval when deposition and early diagenesis took place. On the other hand, the environmental conditions inferred for Meridiani deposition would have posed a challenge for prebiotic chemical reactions thought to have played a role in the origin of life on Earth. Orbital observations suggest that the combination of sulfate minerals and hematite found in Meridiani rocks may be unusual on the martian surface; however, there is reason to believe that acidity, aridity, and oxidizing conditions were broadly distributed on ancient Mars. When these conditions were established and how much environmental heterogeneity existed on early Mars remain to be determined. Because sulfates and iron oxides can preserve detailed geochemical records of environmental history as well as chemical, textural and microfossil signatures of biological activity, Meridiani Planum is an attractive candidate for Mars sample return. ?? 2005 Elsevier B.V. All rights reserved.

Earth and Planetary Science Letters↗
USGS2009

New satellite observations and rainfall forecasts help provide earlier warning of African drought

The poor nations of sub-Saharan Africa face a constant struggle against weather and climate. The outcome of that struggle profoundly influences these nations’ economic growth, health, and social stability. Advances in climate monitoring and forecasting can help African nations and international aid organizations reduce the impact of these natural hazards. Satellites play a crucial role in this effort as they enable scientists to track climate conditions over data-sparse land and ocean areas. In this article, I discuss how a multi-organizational group of scientists use satellite data and statistical forecasts to provide earlier and more accurate early warning of potential drought conditions. We frame our discussion in a specific, timely context—that of probable dramatic food insecurity in Zimbabwe, Eastern Kenya, and Somalia. As this article was being prepared in mid-December, very warm conditions in the Indian Ocean appear likely to produce below normal December–January–February rainfall in both Eastern Kenya/Somalia and Zimbabwe.

Earth Observer↗
USGS2014

Performance and effects of land cover type on synthetic surface reflectance data and NDVI estimates for assessment and monitoring of semi-arid rangeland

Federal land management agencies provide stewardship over much of the rangelands in the arid andsemi-arid western United States, but they often lack data of the proper spatiotemporal resolution andextent needed to assess range conditions and monitor trends. Recent advances in the blending of com-plementary, remotely sensed data could provide public lands managers with the needed information.We applied the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) to five Landsat TMand concurrent Terra MODIS scenes, and used pixel-based regression and difference image analyses toevaluate the quality of synthetic reflectance and NDVI products associated with semi-arid rangeland. Pre-dicted red reflectance data consistently demonstrated higher accuracy, less bias, and stronger correlationwith observed data than did analogous near-infrared (NIR) data. The accuracy of both bands tended todecline as the lag between base and prediction dates increased; however, mean absolute errors (MAE)were typically ≤10%. The quality of area-wide NDVI estimates was less consistent than either spectra lband, although the MAE of estimates predicted using early season base pairs were ≤10% throughout the growing season. Correlation between known and predicted NDVI values and agreement with the 1:1regression line tended to decline as the prediction lag increased. Further analyses of NDVI predictions,based on a 22 June base pair and stratified by land cover/land use (LCLU), revealed accurate estimates through the growing season; however, inter-class performance varied. This work demonstrates the successful application of the STARFM algorithm to semi-arid rangeland; however, we encourage evaluation of STARFM’s performance on a per product basis, stratified by LCLU, with attention given to the influence of base pair selection and the impact of the time lag.

Idaho, Utah, Wyoming↗
USGS2004

Ancient wet aeolian environments on Earth: Clues to presence of fossil/live microorganisms on Mars

Ancient wet aeolian (wet-sabkha) environments on Earth, represented in the Entrada and Navajo sandstones of Utah, contain pipe structures considered to be the product of gas/water release under pressure. The sediments originally had considerable porosity allowing the ingress of living plant structures, microorganisms, clay minerals, and fine-grained primary minerals of silt and sand size from the surface downward in the sedimentary column. Host rock material is of a similar size and porosity and presumably the downward migration of fine-grained material would have been possible prior to lithogenesis and final cementation. Recent field emission scanning electron microscopy (FESEM) and EDS (energy-dispersive spectrometry) examination of sands from fluidized pipes in the Early Jurassic Navajo Sandstone reveal the presence of fossil forms resembling fungal filaments, some bearing hyphopodium-like structures similar to those produced by modern tropical leaf parasites. The tropical origin of the fungi is consistent with the paleogeography of the sandstone, which was deposited in a tropical arid environment. These fossil fungi are silicized, with minor amounts of CaCO3 and Fe, and in some cases a Si/Al ratio similar to smectite. They exist as pseudomorphs, totally depleted in nitrogen, adhering to the surfaces of fine-grained sands, principally quartz and orthoclase. Similar wet aeolian paleoenvironments are suspected for Mars, especially following catastrophic sediment-charged floods of enormous magnitudes that are believed to have contributed to rapid formation of large water bodies in the northern plains, ranging from lakes to oceans. These events are suspected to have contributed to a high frequency of constructional landforms (also known as pseudocraters) related to trapped volatiles and water-enriched sediment underneath a thick blanket of materials that were subsequently released to the martian surface, forming piping structures at the near surface and constructional landforms at the surface. This constructional process on Mars may help unravel the complex history of some of the piping structures observed on Earth; on Earth, evidence for the constructional landforms has been all but erased and the near-surface piping structures exposed through millions of years of differential erosion and topographic inversion now occur as high-standing promontories. If the features on both Earth and Mars formed by similar processes, especially involving water and other volatiles, and since the piping structures of Earth provided suitable environments for life to thrive in, the martian features in the northern plains should be considered as prime targets for physico/mineral/chemical/microbiological analyses once the astrobiological exploration of the red planet begins in earnest. ?? 2004 Elsevier Inc. All rights reserved.

Icarus↗
USGS2012

Combining satellite-based fire observations and ground-based lightning detections to identify lightning fires across the conterminous USA

Lightning fires are a common natural disturbance in North America, and account for the largest proportion of the area burned by wildfires each year. Yet, the spatiotemporal patterns of lightning fires in the conterminous US are not well understood due to limitations of existing fire databases. Our goal here was to develop and test an algorithm that combined MODIS fire detections with lightning detections from the National Lightning Detection Network to identify lightning fires across the conterminous US from 2000 to 2008. The algorithm searches for spatiotemporal conjunctions of MODIS fire clusters and NLDN detected lightning strikes, given a spatiotemporal lag between lightning strike and fire ignition. The algorithm revealed distinctive spatial patterns of lightning fires in the conterminous US While a sensitivity analysis revealed that the algorithm is highly sensitive to the two thresholds that are used to determine conjunction, the density of fires it detected was moderately correlated with ground based fire records. When only fires larger than 0.4 km 2 were considered, correlations were higher and the root-mean-square error between datasets was less than five fires per 625 km 2 for the entire study period. Our algorithm is thus suitable for detecting broad scale spatial patterns of lightning fire occurrence, and especially lightning fire hotspots, but has limited detection capability of smaller fires because these cannot be consistently detected by MODIS. These results may enhance our understanding of large scale patterns of lightning fire activity, and can be used to identify the broad scale factors controlling fire occurrence.

IEEE Journal of Selected Topics in Applied Earth O↗
USGS2015

Plant phenolics and absorption features in vegetation reflectance spectra near 1.66 μm

Past laboratory and field studies have quantified phenolic substances in vegetative matter from reflectance measurements for understanding plant response to herbivores and insect predation. Past remote sensing studies on phenolics have evaluated crop quality and vegetation patterns caused by bedrock geology and associated variations in soil geochemistry. We examined spectra of pure phenolic compounds, common plant biochemical constituents, dry leaves, fresh leaves, and plant canopies for direct evidence of absorption features attributable to plant phenolics. Using spectral feature analysis with continuum removal, we observed that a narrow feature at 1.66 μm is persistent in spectra of manzanita, sumac, red maple, sugar maple, tea, and other species. This feature was consistent with absorption caused by aromatic C- H bonds in the chemical structure of phenolic compounds and non-hydroxylated aromatics. Because of overlapping absorption by water, the feature was weaker in fresh leaf and canopy spectra compared to dry leaf measurements. Simple linear regressions of feature depth and feature area with polyphenol concentration in tea resulted in high correlations and low errors (% phenol by dry weight) at the dry leaf ( r 2 = 0.95, RMSE = 1.0%, n = 56), fresh leaf ( r 2 = 0.79, RMSE = 2.1%, n = 56), and canopy ( r 2 = 0.78, RMSE = 1.0%, n = 13) levels of measurement. Spectra of leaves, needles, and canopies of big sagebrush and evergreens exhibited a weak absorption feature centered near 1.63 μm, short ward of the phenolic compounds, possibly consistent with terpenes. This study demonstrates that subtle variation in vegetation spectra in the shortwave infrared can directly indicate biochemical constituents and be used to quantify them. Phenolics are of lesser abundance compared to the major plant constituents but, nonetheless, have important plant functions and ecological significance. Additional research is needed to advance our understanding of the spectral influences of plant phenolics and terpenes relative to dominant leaf biochemistry (water, chlorophyll, protein/nitrogen, cellulose, and lignin).

International Journal of Applied Earth Observation↗