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At least 1,135 records · Page 63Linked to original sources
USGS2021

Comparing geometric differences between Landsat Collection 1 to Collection 2 level-1 products

In late 2020 the U.S. Geological Survey (USGS) began the distribution of Landsat products associated with their collection 2 reprocessing of the archive. Several changes were implemented within the Landsat Product Generation System (LPGS) and the calibration parameters applied to the Landsat imagery for the collection 2 processing. When comparing between collection 1 and collection 2 products, radiometric and geometric differences will be present. One of the most substantial changes between the two collections was an adjustment to the ground control which made the control more accurate from an absolute and relative perspective. Some of the other changes associated with collection 2 processing were to the Digital Elevation Model (DEM) used in terrain correction, the Thermal Infrared Sensor (TIRS) relative gains, TIRS absolute calibration, Operational Land Imagery (OLI) absolute gain model, OLI relative gain, and OLI bias calculation to name a few. Although these changes also have an effect on the differences between the product associated with these two collections, the change in the ground control, although typically less than one 30-meter multispectral pixel in magnitude, will have the largest effect on the differences between the products. This change in ground control is also a spatially dynamic change that although is low in spatial frequency, is nonlinear and is not a change that can be modeled on a global or even on a local Worldwide Reference System-2 (WRS-2) path and row scale. The effects of these ground control changes will be discussed and demonstrated within this paper along with examples showing their effect on specific datasets. This paper demonstrates some of these geometric differences associated with the ground control through both the registration statistics created during product generation and through an example comparison of a set of collection 1 and collection 2 products.

Conference Paper↗
USGS2001

Optical designs for the Mars '03 rover cameras

In 2003, NASA is planning to send two robotic rover vehicles to explore the surface of Mars. The spacecraft will land on airbags in different, carefully chosen locations. The search for evidence indicating conditions favorable for past or present life will be a high priority. Each rover will carry a total of ten cameras of five various types. There will be a stereo pair of color panoramic cameras, a stereo pair of wide- field navigation cameras, one close-up camera on a movable arm, two stereo pairs of fisheye cameras for hazard avoidance, and one Sun sensor camera. This paper discusses the lenses for these cameras. Included are the specifications, design approaches, expected optical performances, prescriptions, and tolerances.

Conference Paper↗
USGS2001

Landsat 7 on-orbit modulation transfer function estimation

The Landsat 7 spacecraft and its Enhanced Thematic Mapper Plus (ETM+) were launched on April 15, 1999. Pre-launch modeling of the ETM+ optical system predicted that modulation transfer function (MTF) performance would change on-orbit. A method was developed to monitor the along-scan MTF performance of the ETM+ sensor system using on-orbit data of the Lake Pontchartrain Causeway in Louisiana. ETM+ image scan lines crossing the bridge were treated as multiple measurements of the target taken at varying sampling phases. These line measurements were interleaved to construct an over-sampled target profile for each ETM+ system transfer function. Model parameters were adjusted to achieve the best fit between the simulated profiles and the image measurements. The ETM+ modulation at the Nyquist frequency and the full width at half maximum of the point spread function were computed from the best-fit system transfer function model. Trending these parameters over time revealed apparent MTF performance degradation, observed mainly in the 15-meter resolution ETM+ panchromatic band. This confirmed the pre-launch model prediction that the panchromatic band was the most sensitive to changes in ETM+ optical performance.

Conference Paper↗
USGS2002

Absolute irradiance of the Moon for on-orbit calibration

The recognized need for on-orbit calibration of remote sensing imaging instruments drives the ROLO project effort to characterize the Moon for use as an absolute radiance source. For over 5 years the ground-based ROLO telescopes have acquired spatially-resolved lunar images in 23 VNIR (Moon diameter ???500 pixels) and 9 SWIR (???250 pixels) passbands at phase angles within ??90 degrees. A numerical model for lunar irradiance has been developed which fits hundreds of ROLO images in each band, corrected for atmospheric extinction and calibrated to absolute radiance, then integrated to irradiance. The band-coupled extinction algorithm uses absorption spectra of several gases and aerosols derived from MODTRAN to fit time-dependent component abundances to nightly observations of standard stars. The absolute radiance scale is based upon independent telescopic measurements of the star Vega. The fitting process yields uncertainties in lunar relative irradiance over small ranges of phase angle and the full range of lunar libration well under 0.5%. A larger source of uncertainty enters in the absolute solar spectral irradiance, especially in the SWIR, where solar models disagree by up to 6%. Results of ROLO model direct comparisons to spacecraft observations demonstrate the ability of the technique to track sensor responsivity drifts to sub-percent precision. Intercomparisons among instruments provide key insights into both calibration issues and the absolute scale for lunar irradiance.

Conference Paper↗
USGS2002

Traceable Radiometry Underpinning Terrestrial- and Helio- Studies (TRUTHS)

The Traceable Radiometry Underpinning Terrestrial- and Helio- Studies (TRUTHS) mission offers a novel approach to the provision of key scientific data with unprecedented radiometric accuracy for Earth Observation (EO) and solar studies, which will also establish well-calibrated reference targets/standards to support other EO missions. This paper will present the TRUTHS mission and its objectives. TRUTHS will be the first satellite mission to calibrate its instrumentation directly to SI in orbit, overcoming the usual uncertainties associated with drifts of sensor gain and spectral shape by using an electrical rather than an optical standard as the basis of its calibration. The range of instruments flown as part of the payload will also provide accurate input data to improve atmospheric radiative transfer codes by anchoring boundary conditions, through simultaneous measurements of aerosols, particulates and radiances at various heights. Therefore, TRUTHS will significantly improve the performance and accuracy of Earth observation missions with broad global or operational aims, as well as more dedicated missions. The provision of reference standards will also improve synergy between missions by reducing errors due to different calibration biases and offer cost reductions for future missions by reducing the demands for on-board calibration systems. Such improvements are important for the future success of strategies such as Global Monitoring for Environment and Security (GMES) and the implementation and monitoring of international treaties such as the Kyoto Protocol. TRUTHS will achieve these aims by measuring the geophysical variables of solar and lunar irradiance, together with both polarised and un-polarised spectral radiance of the Moon, and the Earth and its atmosphere.

Conference Paper↗
USGS2004

Visual enhancement of unmixed multispectral imagery using adaptive smoothing

Adaptive smoothing (AS) has been previously proposed as a method to smooth uniform regions of an image, retain contrast edges, and enhance edge boundaries. The method is an implementation of the anisotropic diffusion process which results in a gray scale image. This paper discusses modifications to the AS method for application to multi-band data which results in a color segmented image. The process was used to visually enhance the three most distinct abundance fraction images produced by the Lagrange constraint neural network learning-based unmixing of Landsat 7 Enhanced Thematic Mapper Plus multispectral sensor data. A mutual information-based method was applied to select the three most distinct fraction images for subsequent visualization as a red, green, and blue composite. A reported image restoration technique (partial restoration) was applied to the multispectral data to reduce unmixing error, although evaluation of the performance of this technique was beyond the scope of this paper. The modified smoothing process resulted in a color segmented image with homogeneous regions separated by sharpened, coregistered multiband edges. There was improved class separation with the segmented image, which has importance to subsequent operations involving data classification.

Conference Paper↗
USGS2005

Landsat-4 and Landsat-5 thematic mapper band 6 historical performance and calibration

Launched in 1982 and 1984 respectively, the Landsat-4 and -5 Thematic Mappers (TM) are the backbone of an extensive archive of moderate resolution Earth imagery. However, these sensors and their data products were not subjected to the type of intensive monitoring that has been part of the Landsat-7 system since its launch in 1999. With Landsat-4's 11 year and Landsat-5's 20+ year data record, there is a need to understand the historical behavior of the instruments in order to verify the scientific integrity of the archive and processed products. Performance indicators of the Landsat-4 and -5 thermal bands have recently been extracted from a processing system database allowing for a more complete study of thermal band characteristics and calibration than was previously possible. The database records responses to the internal calibration system, instrument temperatures and applied gains and offsets for each band for every scene processed through the National Landsat Archive Production System (NLAPS). Analysis of this database has allowed for greater understanding of the calibration and improvement in the processing system. This paper will cover the trends in the Landsat-4 and -5 thermal bands, the effect of the changes seen in the trends, and how these trends affect the use of the thermal data.

Conference Paper↗
USGS2008

L5 TM radiometric recalibration procedure using the internal calibration trends from the NLAPS trending database

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. The multispectral data from the Landsat 5 (L5) Thematic Mapper (TM) sensor provide the backbone for this extensive archive. Historically, the radiometric calibration procedure for this imagery used the instrument's response to the Internal Calibrator (IC) on a scene-by-scene basis to determine the gain and offset for each detector. The IC system degraded with time causing radiometric calibration errors up to 20 percent. In May 2003 the National Landsat Archive Production System (NLAPS) was updated to use a gain model rather than the scene acquisition specific IC gains to calibrate TM data processed in the United States. Further modification of the gain model was performed in 2007. L5 TM data that were processed using IC prior to the calibration update do not benefit from the recent calibration revisions. A procedure has been developed to give users the ability to recalibrate their existing Level-1 products. The best recalibration results are obtained if the work order report that was originally included in the standard data product delivery is available. However, many users may not have the original work order report. In such cases, the IC gain look-up table that was generated using the radiometric gain trends recorded in the NLAPS database can be used for recalibration. This paper discusses the procedure to recalibrate L5 TM data when the work order report originally used in processing is not available. A companion paper discusses the generation of the NLAPS IC gain and bias look-up tables required to perform the recalibration.

Conference Paper↗
USGS2011

Feature-based and statistical methods for analyzing the Deepwater Horizon oil spill with AVIRIS imagery

The Deepwater Horizon oil spill covered a very large geographical area in the Gulf of Mexico creating potentially serious environmental impacts on both marine life and the coastal shorelines. Knowing the oil's areal extent and thickness as well as denoting different categories of the oil's physical state is important for assessing these impacts. High spectral resolution data in hyperspectral imagery (HSI) sensors such as Airborne Visible and Infrared Imaging Spectrometer (AVIRIS) provide a valuable source of information that can be used for analysis by semi-automatic methods for tracking an oil spill's areal extent, oil thickness, and oil categories. However, the spectral behavior of oil in water is inherently a highly non-linear and variable phenomenon that changes depending on oil thickness and oil/water ratios. For certain oil thicknesses there are well-defined absorption features, whereas for very thin films sometimes there are almost no observable features. Feature-based imaging spectroscopy methods are particularly effective at classifying materials that exhibit specific well-defined spectral absorption features. Statistical methods are effective at classifying materials with spectra that exhibit a considerable amount of variability and that do not necessarily exhibit well-defined spectral absorption features. This study investigates feature-based and statistical methods for analyzing oil spills using hyperspectral imagery. The appropriate use of each approach is investigated and a combined feature-based and statistical method is proposed.

Proceedings of SPIE↗
USGS2011

Bias estimation for the Landsat 8 operational land imager

The Operational Land Imager (OLI) is a pushbroom sensor that will be a part of the Landsat Data Continuity Mission (LDCM). This instrument is the latest in the line of Landsat imagers, and will continue to expand the archive of calibrated earth imagery. An important step in producing a calibrated image from instrument data is accurately accounting for the bias of the imaging detectors. Bias variability is one factor that contributes to error in bias estimation for OLI. Typically, the bias is simply estimated by averaging dark data on a per-detector basis. However, data acquired during OLI pre-launch testing exhibited bias variation that correlated well with the variation in concurrently collected data from a special set of detectors on the focal plane. These detectors are sensitive to certain electronic effects but not directly to incoming electromagnetic radiation. A method of using data from these special detectors to estimate the bias of the imaging detectors was developed, but found not to be beneficial at typical radiance levels as the detectors respond slightly when the focal plane is illuminated. In addition to bias variability, a systematic bias error is introduced by the truncation performed by the spacecraft of the 14-bit instrument data to 12-bit integers. This systematic error can be estimated and removed on average, but the per pixel quantization error remains. This paper describes the variability of the bias, the effectiveness of a new approach to estimate and compensate for it, as well as the errors due to truncation and how they are reduced.

Conference Paper↗
USGS2001

Geophysics: Silent slip on the Cascadia subduction interface

G eodetic satellites of the Global Positioning System (GPS) now permit continuous recording of surface motions around earthquake faults and volcanoes with millimeter precision. Data from distinct points on Earth's surface can be combined to infer the locations of the sources of deformation at depth in the crust. These data are radically altering our understanding of earthquake processes, justifying ambitious new sensor arrays to image active deformation sources in Earth's crust. In recent years, large continuous GPS arrays have been deployed in Japan and southern California, and smaller networks have been installed in other seismically active regions. On page 1525 of this issue ( 1 ), Dragert et al. provide a glimpse of the kinds of insights we can expect from these arrays.

Cascadia subduction zone↗
USGS1964

Infrared surveys of Hawaiian volcanoes

Aerial infrared-sensor surveys of Kilauea volcano have depicted the areal extent and the relative intensity of abnormal thermal features in the caldera area of the volcano and along its associated rift zones. Many of these anomalies show correlation with visible steaming and reflect convective transfer of heat to the surface from subterranean sources. Structural details of the volcano, some not evident from surface observation, are also delineated by their thermal abnormalities. Several changes were observed in the patterns of infrared emission during the period of study; two such changes show correlation in location with subsequent eruptions, but the cause-and-effect relationship is uncertain. Thermal anomalies were also observed on the southwest flank of Mauna Loa; images of other volcanoes on the island of Hawaii, and of Haleakala on the island of Maui, revealed no thermal abnormalities. Approximately 25 large springs issuing into the ocean around the periphery of Hawaii have been detected. Infrared emission varies widely with surface texture and composition, suggesting that similar observations may have value for estimating surface conditions on the moon or planets.

Hawai'i↗
USGS2020

Ecological insights from three decades of animal movement tracking across a changing Arctic

The Arctic is entering a new ecological state, with alarming consequences for humanity. Animal-borne sensors offer a window into these changes. Although substantial animal tracking data from the Arctic and subarctic exist, most are difficult to discover and access. Here, we present the new Arctic Animal Movement Archive (AAMA), a growing collection of more than 200 standardized terrestrial and marine animal tracking studies from 1991 to the present. The AAMA supports public data discovery, preserves fundamental baseline data for the future, and facilitates efficient, collaborative data analysis. With AAMA-based case studies, we document climatic influences on the migration phenology of eagles, geographic differences in the adaptive response of caribou reproductive phenology to climate change, and species-specific changes in terrestrial mammal movement rates in response to increasing temperature.

Science↗
USGS1997

Mapping hydrothermally altered rocks on Mount Rainier, Washington, with Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data

Mount Rainier has produced numerous Holocene debris flows, the largest of which contain clays and other minerals derived from hydrothermally altered rocks on the volcano's edifice. Imagery from an advanced airborne sensor was used to map altered rocks at Mount Rainier and demonstrates their distinctly nonuniform distribution. The mapping of altered rocks helps to identify edifice failure surfaces and to recognize the source areas for the largest debris flow events. Remote sensing methods like those used at Mount Rainier can enhance ground-based mapping efforts and should prove useful for rapidly identifying hazardous sectors at other volcanoes.

Geology↗
USGS1998

Annual cycle of magmatic CO2 in a tree-kill soil at Mammoth Mountain, California: Implications for soil acidification

Time-series sensor data reveal significant short-term and seasonal variations of magmatic CO 2 in soil over a 12 month period in 1995–1996 at the largest tree-kill site on Mammoth Mountain, central-eastern California. Short-term variations leading to ground-level soil CO 2 concentrations hazardous and lethal to humans were triggered by shallow faulting in the absence of increased seismicity or intrusion, consistent with tapping a reservoir of accumulated CO 2 , rather than direct magma degassing. Hydrologic processes closely modulated seasonal variations in CO 2 concentrations, which rose to 65%–100% in soil gas under winter snowpack and plunged more than 25% in just days as the CO 2 dissolved in spring snowmelt. The high efflux of CO 2 through the tree-kill soils acts as an open-system CO 2 buffer causing infiltration of waters with pH values commonly of <4.2, acid loading of up to 7 keq H+ ṁha −1 ṁyr −1 , mobilization of toxic Al 3+ , and long-term decline of soil fertility.

Geology↗
USGS2021

Graph-based reinforcement learning for active learning in real time: An application in modeling river networks

Effective training of advanced ML models requires large amounts of labeled data, which is often scarce in scientific problems given the substantial human labor and material cost to collect labeled data. This poses a challenge on determining when and where we should deploy measuring instruments (e.g., in-situ sensors) to collect labeled data efficiently. This problem differs from traditional pool-based active learning settings in that the labeling decisions have to be made immediately after we observe the input data that come in a time series. In this paper, we develop a real-time active learning method that uses the spatial and temporal contextual information to select representative query samples in a reinforcement learning framework. To reduce the need for large training data, we further propose to transfer the policy learned from simulation data which is generated by existing physics-based models. We demonstrate the effectiveness of the proposed method by predicting streamflow and water temperature in the Delaware River Basin given a limited budget for collecting labeled data. We further study the spatial and temporal distribution of selected samples to verify the ability of this method in selecting informative samples over space and time.

Conference Paper↗
USGS2024

Dams facilitate predation during Atlantic salmon (Salmo salar) smolt migration

Diadromous fish populations have incurred precipitous declines across the globe. Among many stressors, these species are threatened by anthropogenic barriers that impede movement, alter riverine habitat, and augment predator communities. In this study, we used acoustic transmitters ( n = 220) with predation and temperature sensors to characterize Atlantic salmon ( Salmo salar ) smolt predation risk in the Penobscot River, Maine, USA. Across two seasons, we documented 79 predation events through a 170 km migratory pathway, which included three hydropower projects and a large estuary. We detected tagged smolts that were predated by fish ( n = 42), marine mammals ( n = 28), and birds ( n = 9). Using a multistate mark-recapture framework, we estimated that 46% of smolts were predated during downstream migration, which accounted for at least 55% of all mortality. Relative predation risk was greatest through impoundments and the lower estuary, where on average, predation rates were 4.8-fold and 9.0-fold greater than free-flowing reaches, respectively. These results suggest that predation pressure on Atlantic salmon smolts is exacerbated by hydropower projects and that predation in the lower estuary may be greater than expected.

Maine↗
USGS2012

Storm surge modeling and applications in coastal areas

This chapter introduces the reader to a wide spectrum of storm surge modeling systems used to assess the impact of tropical cyclones, covering a range of numerical methods, model domains, forcing and boundary conditions, and purposes. New technologies to obtain data such as deployment of temporary sensors and remote sensing practices to support modeling are also presented. Extensive storm surge modeling applications have been made with existing modeling systems and some of them are described in this chapter. The authors recognize the importance of evaluating river-ocean interactions in coastal environments during tropical cyclones. Therefore, the coupling of hydraulic (riverine) and storm surge models is discussed. In addition, results from studies performed in the coast of India are shown which generated maps to help emergency managers and reduce risk due to coastal inundation.

Book chapter↗