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At least 1,369 records · Page 76Linked to original sources

It’s time for focused in situ studies of planetary surface-atmosphere interactions

A critical gap in planetary observations has been in situ characterization of extra-terrestrial, present-day atmospheric and surface environments and activity. While some surface activity has been observed and some in situ meteorological measurements have been collected by auxiliary instruments on Mars, existing information is insufficient to conclusively characterize the natural processes via concurrent and high-resolution measurement of environmental drivers and activity. Thus, many atmospheric, aeolian, and other surface processes models – which are used to generate key constraints on science and exploration in many areas of planetary investigation—such as surface exposure/erosion estimates, landscape interpretation, and modeling dust storm development—remain untested under non-Earth conditions. Analogous terrestrial processes are often studied intensively via numerical modeling that integrates empirical results from laboratory and/or field studies of process-response interactions between the atmosphere and relevant surface landforms. Incorporation of such in situ measurements into model development has significantly advanced our understanding of atmosphere-surface interactions and related geomorphic processes on Earth, and is poised to do so on other planets. However, to date, such testing and refinement have not been possible in other planetary environments, partially because investigations of this sort require new technologies, mission architectures, and operations designs (e.g., different from large rovers focused on geochemical investigations) to fully address the key gaps in our understanding while keeping cost and risk low. Fortunately, technological developments in the areas of surface access, instrumentation, and onboard processing/memory now enable small spacecraft to accommodate meteorological and aeolian instrumentation that could collect the needed measurements to fill this critical gap while remaining within typical small spacecraft resource budgets. Furthermore, maturity of our understanding of the broader geologic and atmospheric context on Mars provides a ready framework for ingestion of discrete ground truth measurements into our understanding of the broader and multi-scale martian natural systems and processes. These advancements make addressing key science questions with novel mission concepts feasible, promising results that would significantly advance our understanding of extraterrestrial surface-atmosphere interactions. This summary follows from a community-generated white paper for the ongoing Planetary Science/Astrobiology Decadal Survey, small spacecraft concept development at JPL, and numerous JPL and community discussions.

Conference Paper↗

Mineral mapping and applications of imaging spectroscopy

Spectroscopy is a tool that has been used for decades to identify, understand, and quantify solid, liquid, or gaseous materials, especially in the laboratory. In disciplines ranging from astronomy to chemistry, spectroscopic measurements are used to detect absorption and emission features due to specific chemical bonds, and detailed analyses are used to determine the abundance and physical state of the detected absorbing/emitting species. Spectroscopic measurements have a long history in the study of the Earth and planets. Up to the 1990s remote spectroscopic measurements of Earth and planets were dominated by multispectral imaging experiments that collect high-quality images in a few, usually broad, spectral bands or with point spectrometers that obtained good spectral resolution but at only a few spatial positions. However, a new generation of sensors is now available that combines imaging with spectroscopy to create the new discipline of imaging spectroscopy. Imaging spectrometers acquire data with enough spectral range, resolution, and sampling at every pixel in a raster image so that individual absorption features can be identified and spatially mapped (Goetz et al., 1985).

Conference Paper↗

Use of EO-1 Hyperion data to calculate spectral band adjustment factors (SBAF) between the L7 ETM+ and Terra MODIS sensors

Different applications and technology developments in Earth observations necessarily require different spectral coverage. Thus, even for the spectral bands designed to look at the same region of the electromagnetic spectrum, the relative spectral responses (RSR) of different sensors may be different. In this study, spectral band adjustment factors (SBAF) are derived using hyperspectral Earth Observing-1 (EO-1) Hyperion measurements to adjust for the spectral band differences between the Landsat 7 (L7) Enhanced Thematic Mapper Plus (ETM+) and the Terra Moderate Resolution Imaging Spectroradiometer (MODIS) top-of-atmosphere (TOA) reflectance measurements from 2000 to 2009 over the pseudo-invariant Libya 4 reference standard test site.

Conference Paper↗

The U. S. Geological Survey’s approach to analysis ready data

Analysis Ready Data (ARD) is a recent concept in Earth observing remote sensing which encompasses many different initiatives by individual imagery providers and collaborative international organizations working towards easing/minimizing data preprocessing required by users. This allows users to spend more time on analysis and less time on downloading, formatting, and ingesting. The U. S. Geological Survey (USGS), the primary provider of Landsat image data, has been making internal strides to provide ARD: moving towards Level-2 surface reflectance and surface temperature as standard products. External cooperation, working toward a common ARD definition, has also been a focus of the USGS by working directly with other governmental or commercial providers, both national and international, or through organizations such as the Committee on Earth Observation Satellites (CEOS) and the Joint Agency Commercial Imagery Evaluation (JACIE) workshop. The USGS is determined to provide users with the most accurate and easy to use data.

Conference Paper↗

USGS CEOS analysis ready data for land achievements and future plans

The efforts of the Committee on Earth Observation Satellites (CEOS) to bring CEOS Analysis Ready Data for Land (CARD4L) products to countries and international organizations quickly and easily continues to receive important support from the U.S. Geological Survey (USGS). As part of its engagement with CARD4L, the USGS worked to address specific Threshold and Target Product Family Specification (PFS) requirements for its Landsat Collection 2 Level-2 science products and in July 2020, received formal CEOS endorsement for 100 percent CARD4L-compliance at the Threshold level for Collection 2 surface reflectance and surface temperature. This endorsement ensures these products meet a level of interoperability with data from other Earth-observing platforms, such as Europe's Sentinel-2 satellites, as the European Space Agency also works toward CARD4L-compliant products. In addition to the Collection 2 Level-2 land surface data products, the USGS recognizes Landsat's potential to make a valuable contribution to aquatic science and environmental monitoring capabilities for aquatic ecosystems, especially in coastal and inland waters. Working with subject matter experts, the USGS has been coordinating an international agency effort to establish a new CARD4L PFS for aquatic reflectance to be considered for CEOS endorsement in 2021.

Conference Paper↗

Interactive access to LP DAAC satellite data archives through a combination of open-source and custom middleware web services

Current methods of searching for and retrieving data from satellite land remote sensing archives do not allow for interactive information extraction. Instead, Earth science data users are required to download files over low-bandwidth networks to local workstations and process data before science questions can be addressed. New methods of extracting information from data archives need to become more interactive to meet user demands for deriving increasingly complex information from rapidly expanding archives. Moving the tools required for processing data to computer systems of data providers, and away from systems of the data consumer, can improve turnaround times for data processing workflows. The implementation of middleware services was used to provide interactive access to archive data. The goal of this middleware services development is to enable Earth science data users to access remote sensing archives for immediate answers to science questions instead of links to large volumes of data to download and process. Exposing data and metadata to web-based services enables machine-driven queries and data interaction. Also, product quality information can be integrated to enable additional filtering and sub-setting. Only the reduced content required to complete an analysis is then transferred to the user.

IEEE Geoscience and Remote Sensing Letters↗

Updated radiometric calibration for the Landsat-5 thematic mapper reflective bands

The Landsat-5 Thematic Mapper (TM) has been the workhorse of the Landsat system. Launched in 1984, it continues collecting data through the time frame of this paper. Thus, it provides an invaluable link to the past history of the land features of the Earth's surface, and it becomes imperative to provide an accurate radiometric calibration of the reflective bands to the user community. Previous calibration has been based on information obtained from prelaunch, the onboard calibrator, vicarious calibration attempts, and cross-calibration with Landsat-7. Currently, additional data sources are available to improve this calibration. Specifically, improvements in vicarious calibration methods and development of the use of pseudoinvariant sites for trending provide two additional independent calibration sources. The use of these additional estimates has resulted in a consistent calibration approach that ties together all of the available calibration data sources. Results from this analysis indicate a simple exponential, or a constant model may be used for all bands throughout the lifetime of Landsat-5 TM. Where previously time constants for the exponential models were approximately one year, the updated model has significantly longer time constants in bands 1-3. In contrast, bands 4, 5, and 7 are shown to be best modeled by a constant. The models proposed in this paper indicate calibration knowledge of 5% or better early in life, decreasing to nearly 2% later in life. These models have been implemented at the U.S. Geological Survey Earth Resources Observation and Science (EROS) and are the default calibration used for all Landsat TM data now distributed through EROS. ?? 2008 IEEE.

Conference Paper↗

A procedure for radiometric recalibration of Landsat 5 TM reflective-band data

From the Landsat program's inception in 1972 to the present, the Earth science user community has been benefiting 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 the L5 TM imagery used the detectors' 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%. In May 2003, the L5 TM data processed and distributed by the U.S. Geological Survey (USGS) Earth Resources Observation and Science Center through the National Landsat Archive Production System (NLAPS) were updated to use a lifetime lookup-table (LUT) gain model to radiometrically calibrate TM data instead of using scene-specific IC gains. Further modification of the gain model was performed in 2007. The L5 TM data 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 included in the original standard data product delivery is available. However, if users do not have the original work-order report, the IC trends can be used for recalibration. The IC trends were generated using the radiometric gain trends recorded in the NLAPS database. This paper provides the details of the recalibration procedure for the following: 1) data processed using IC where users have the work-order file; 2) data processed using IC where users do not have the work-order file; 3) data processed using prelaunch calibration parameters; and 4) data processed using the previous version of the LUT (e.g., LUT03) that was released before April 2, 2007.

IEEE Transactions on Geoscience and Remote Sensing↗

Landsat 4 Thematic Mapper calibration update

The Landsat 4 Thematic Mapper (TM) collected imagery of the Earth's surface from 1982 to 1993. Although largely overshadowed by Landsat 5 which was launched in 1984, Landsat 4 TM imagery extends the TM-based record of the Earth back to 1982 and also substantially supplements the image archive collected by Landsat 5. To provide a consistent calibration record for the TM instruments, Landsat 4 TM was cross-calibrated to Landsat 5 using nearly simultaneous overpass imagery of pseudo-invariant calibration sites (PICS) in the time period of 1988-1990. To determine if the radiometric gain of Landsat 4 had changed over its lifetime, time series from two PICS locations (a Saharan site known as Libya 4 and a site in southwest North America, commonly referred to as the Sonoran Desert site) were developed. The results indicated that Landsat 4 had been very stable over its lifetime, with no discernible degradation in sensor performance in all reflective bands except band 1. In contrast, band 1 exhibited a 12% decay in responsivity over the lifetime of the instrument. Results from this paper have been implemented at USGS EROS, which enables users of Landsat TM data sets to obtain consistently calibrated data from Landsat 4 and 5 TM as well as Landsat 7 ETM+ instruments.

IEEE Transactions on Geoscience and Remote Sensing↗

Radiometric calibration of the Landsat MSS sensor series

Multispectral remote sensing of the Earth using Landsat sensors was ushered on July 23, 1972, with the launch of Landsat-1. Following that success, four more Landsat satellites were launched, and each of these carried the Multispectral Scanner System (MSS). These five sensors provided the only consistent multispectral space-based imagery of the Earth's surface from 1972 to 1982. This work focuses on developing both a consistent and absolute radiometric calibration of this sensor system. Cross-calibration of the MSS was performed through the use of pseudoinvariant calibration sites (PICSs). Since these sites have been shown to be stable for long periods of time, changes in MSS observations of these sites were attributed to changes in the sensors themselves. In addition, simultaneous data collections were available for some MSS sensor pairs, and these were also used for cross-calibration. Results indicated substantial differences existed between instruments, up to 16%, and these were reduced to 5% or less across all MSS sensors and bands. Lastly, this paper takes the calibration through the final step and places the MSS sensors on an absolute radiometric scale. The methodology used to achieve this was based on simultaneous data collections by the Landsat-5 MSS and Thematic Mapper (TM) instruments. Through analysis of image data from a PICS location and through compensating for the spectral differences between the two instruments, the Landsat-5 MSS sensor was placed on an absolute radiometric scale based on the Landsat-5 TM sensor. Uncertainties associated with this calibration are considered to be less than 5%.

IEEE Transactions on Geoscience and Remote Sensing↗

Applications of spectral band adjustment factors (SBAF) for cross-calibration

To monitor land surface processes over a wide range of temporal and spatial scales, it is critical to have coordinated observations of the Earth's surface acquired from multiple spaceborne imaging sensors. However, an integrated global observation framework requires an understanding of how land surface processes are seen differently by various sensors. This is particularly true for sensors acquiring data in spectral bands whose relative spectral responses (RSRs) are not similar and thus may produce different results while observing the same target. The intrinsic offsets between two sensors caused by RSR mismatches can be compensated by using a spectral band adjustment factor (SBAF), which takes into account the spectral profile of the target and the RSR of the two sensors. The motivation of this work comes from the need to compensate the spectral response differences of multispectral sensors in order to provide a more accurate cross-calibration between the sensors. In this paper, radiometric cross-calibration of the Landsat 7 Enhanced Thematic Mapper Plus (ETM+) and the Terra Moderate Resolution Imaging Spectroradiometer (MODIS) sensors was performed using near-simultaneous observations over the Libya 4 pseudoinvariant calibration site in the visible and near-infrared spectral range. The RSR differences of the analogous ETM+ and MODIS spectral bands provide the opportunity to explore, understand, quantify, and compensate for the measurement differences between these two sensors. The cross-calibration was initially performed by comparing the top-of-atmosphere (TOA) reflectances between the two sensors over their lifetimes. The average percent differences in the long-term trends ranged from $-$5% to $+$6%. The RSR compensated ETM+ TOA reflectance (ETM+$^{ast}$) measurements were then found to agree with MODIS TOA reflectance to within 5% for all bands when Earth Observing-1 Hy- erion hyperspectral data were used to produce the SBAFs. These differences were later reduced to within 1% for all bands (except band 2) by using Environmental Satellite Scanning Imaging Absorption Spectrometer for Atmospheric Cartography hyperspectral data to produce the SBAFs.

IEEE Transactions on Geoscience and Remote Sensing↗

Assessment of spectral band impact on intercalibration over desert sites using simulation based on EO-1 Hyperion data

Since the beginning of the 1990s, stable desert sites have been used for the calibration monitoring of many different sensors. Many attempts at sensor intercalibration have been also conducted using these stable desert sites. As a result, site characterization techniques and the quality of intercalibration techniques have gradually improved over the years. More recently, the Committee on Earth Observation Satellites has recommended a list of reference pseudo-invariant calibration sites for frequent image acquisition by multiple agencies. In general, intercalibration should use well-known or spectrally flat reference. The reflectance profile of desert sites, however, might not be flat or well characterized (from a fine spectral point of view). The aim of this paper is to assess the expected accuracy that can be reached when using desert sites for intercalibration. In order to have a well-mastered estimation of different errors or error sources, this study is performed with simulated data from a hyperspectral sensor. Earth Observing-1 Hyperion images are chosen to provide the simulation input data. Two different cases of intercalibration are considered, namely, Landsat 7 Enhanced Thematic Mapper Plus with Terra Moderate Resolution Imaging Spectroradiometer (MODIS) and Environmental Satellite MEdium Resolution Imaging Spectrometer (MERIS) with Aqua MODIS. The simulation results have confirmed that intercalibration accuracy of 1% to 2% can be achieved between sensors, provided there are a sufficient number of available measurements. The simulated intercalibrations allow explaining results obtained during real intercalibration exercises and to establish some recommendations for the use of desert sites for intercalibration.

IEEE Transactions on Geoscience and Remote Sensing↗

Overview of intercalibration of satellite instruments

Inter-calibration of satellite instruments is critical for detection and quantification of changes in the Earth’s environment, weather forecasting, understanding climate processes, and monitoring climate and land cover change. These applications use data from many satellites; for the data to be inter-operable, the instruments must be cross-calibrated. To meet the stringent needs of such applications requires that instruments provide reliable, accurate, and consistent measurements over time. Robust techniques are required to ensure that observations from different instruments can be normalized to a common scale that the community agrees on. The long-term reliability of this process needs to be sustained in accordance with established reference standards and best practices. Furthermore, establishing physical meaning to the information through robust Système International d'unités (SI) traceable Calibration and Validation (Cal/Val) is essential to fully understand the parameters under observation. The processes of calibration, correction, stability monitoring, and quality assurance need to be underpinned and evidenced by comparison with “peer instruments” and, ideally, highly calibrated in-orbit reference instruments. Inter-calibration between instruments is a central pillar of the Cal/Val strategies of many national and international satellite remote sensing organizations. Inter-calibration techniques as outlined in this paper not only provide a practical means of identifying and correcting relative biases in radiometric calibration between instruments but also enable potential data gaps between measurement records in a critical time series to be bridged. Use of a robust set of internationally agreed upon and coordinated inter-calibration techniques will lead to significant improvement in the consistency between satellite instruments and facilitate accurate monitoring of the Earth’s climate at uncertainty levels needed to detect and attribute the mechanisms of change. This paper summarizes the state-of-the-art of post-launch radiometric calibration of remote sensing satellite instruments, through inter-calibration.

IEEE Transactions on Geoscience and Remote Sensing↗

CEOS visualization environment (COVE) tool for intercalibration of satellite instruments

Increasingly, data from multiple instruments are used to gain a more complete understanding of land surface processes at a variety of scales. Intercalibration, comparison, and coordination of satellite instrument coverage areas is a critical effort of international and domestic space agencies and organizations. The Committee on Earth Observation Satellites Visualization Environment (COVE) is a suite of browser-based applications that leverage Google Earth to display past, present, and future satellite instrument coverage areas and coincident calibration opportunities. This forecasting and ground coverage analysis and visualization capability greatly benefits the remote sensing calibration community in preparation for multisatellite ground calibration campaigns or individual satellite calibration studies. COVE has been developed for use by a broad international community to improve the efficiency and efficacy of such calibration planning efforts, whether those efforts require past, present, or future predictions. This paper provides a brief overview of the COVE tool, its validation, accuracies, and limitations with emphasis on the applicability of this visualization tool for supporting ground field campaigns and intercalibration of satellite instruments.

IEEE Transactions on Geoscience and Remote Sensing↗

Landsat 1-5 Multispectral Scanner System (MSS) sensors radiometric calibration update

First launched in 1972, the Landsat satellite sensors have provided the longest continuous record of high quality images of the Earth’s surface that are used in both civilian and military applications. The Landsat Multispectral Scanner (MSS) sensor was on-board Landsat-1 through Landsat-5. In fact, the MSS sensors provide the only systematic global multispectral space-based imagery of the Earth’s surface from 1972 to 1982. This paper focuses on the radiometric calibration update of the Landsat 1-5 MSS sensors. The radiometric calibration was performed in both radiance and reflectance-based scales through cross-calibration approach. Simultaneous or a near simultaneous image collections were available for MSS sensor pairs and used for the cross-calibration. The estimated uncertainties for this calibration update exhibit progressively decreasing calibration accuracy, ranging from 5.1% for MSS 5 to 8.8% for MSS-1 in the Green spectral band, for example. Lastly, the new radiometric calibration coefficients were validated through the use of pseudo invariant calibration sites (PICS). The temporal TOA Radiance and TOA Reflectance over the Sonoran Desert were plotted with the purpose of verifying the lifetime radiometric stability of MSS sensors. With the previous calibration, the agreement between the measurements of TOA Reflectance over the Sonoran Desert was around 7.5% for all spectral bands. With the calibration update implemented in this study, the agreement between MSS sensors is 3.6%, 2.9%, 3.5% and 5.9% for the Green, Red, NIR-1 and NIR 2 spectral bands, respectively. This study ties all the Landsat legacy instruments from Landsat-1 MSS through Landsat-8 OLI to a consistent radiometric scale.

IEEE Transactions on Geoscience and Remote Sensing↗

Ten ways remote sensing can contribute to conservation

In an effort to increase conservation effectiveness through the use of Earth observation technologies, a group of remote sensing scientists affiliated with government and academic institutions and conservation organizations identified 10 questions in conservation for which the potential to be answered would be greatly increased by use of remotely sensed data and analyses of those data. Our goals were to increase conservation practitioners’ use of remote sensing to support their work, increase collaboration between the conservation science and remote sensing communities, identify and develop new and innovative uses of remote sensing for advancing conservation science, provide guidance to space agencies on how future satellite missions can support conservation science, and generate support from the public and private sector in the use of remote sensing data to address the 10 conservation questions. We identified a broad initial list of questions on the basis of an email chain-referral survey. We then used a workshop-based iterative and collaborative approach to whittle the list down to these final questions (which represent 10 major themes in conservation): How can global Earth observation data be used to model species distributions and abundances? How can remote sensing improve the understanding of animal movements? How can remotely sensed ecosystem variables be used to understand, monitor, and predict ecosystem response and resilience to multiple stressors? How can remote sensing be used to monitor the effects of climate on ecosystems? How can near real-time ecosystem monitoring catalyze threat reduction, governance and regulation compliance, and resource management decisions? How can remote sensing inform configuration of protected area networks at spatial extents relevant to populations of target species and ecosystem services? How can remote sensing-derived products be used to value and monitor changes in ecosystem services? How can remote sensing be used to monitor and evaluate the effectiveness of conservation efforts? How does the expansion and intensification of agriculture and aquaculture alter ecosystems and the services they provide? How can remote sensing be used to determine the degree to which ecosystems are being disturbed or degraded and the effects of these changes on species and ecosystem functions?

Conservation Biology↗

Climate change refugia hotspots for priority species: A case study in East Africa

Natural resource managers and policymakers need actionable climate data to guide conservation decisions. Conserving climate change refugia, areas relatively buffered from contemporary climate change, is increasingly considered an effective strategy for adaptation. Despite tropical species facing heightened vulnerability to climate change, the tropics remain underserved in climate adaptation research. We coproduced with Tanzanian partners the first comprehensive assessment of climate change refugia across Tanzania through extensive consultation, in-person conversations, and field visits to priority ecosystems, ensuring our analysis addressed local conservation needs and decision-making contexts. We developed species distribution models for 33 terrestrial animal species using maximum entropy and boosted regression tree algorithms. We projected future suitable habitats for SSP126 and SSP585, for 2011–2040 and 2071–2100, using GFDL Earth System and the UK Earth System models. More than half under SSP126 and 79% of focal species under SSP585 lost their suitable habitat by 2100. Serengeti National Park, Northern Highlands Forest Reserve, and the Eastern Arc Mountains emerged as key climate change refugia, while other protected areas, including Kigosi and Ugalla River National Parks, had no climate change refugia. This assessment provides actionable insights for Tanzania's conservation prioritization while identifying critical research gaps in western and montane ecosystems.

Conservation Science and Practice↗

Urgent need for warming experiments in tropical forests

Although tropical forests account for only a fraction of the planet's terrestrial surface, they exchange more carbon dioxide with the atmosphere than any other biome on Earth, and thus play a disproportionate role in the global climate. In the next 20 years, the tropics will experience unprecedented warming, yet there is exceedingly high uncertainty about their potential responses to this imminent climatic change. Here, we prioritize research approaches given both funding and logistical constraints in order to resolve major uncertainties about how tropical forests function and also to improve predictive capacity of earth system models. We investigate overall model uncertainty of tropical latitudes and explore the scientific benefits and inevitable trade-offs inherent in large-scale manipulative field experiments. With a Coupled Model Intercomparison Project Phase 5 analysis, we found that model variability in projected net ecosystem production was nearly 3 times greater in the tropics than for any other latitude. Through a review of the most current literature, we concluded that manipulative warming experiments are vital to accurately predict future tropical forest carbon balance, and we further recommend the establishment of a network of comparable studies spanning gradients of precipitation, edaphic qualities, plant types, and/or land use change. We provide arguments for long-term, single-factor warming experiments that incorporate warming of the most biogeochemically active ecosystem components (i.e. leaves, roots, soil microbes). Hypothesis testing of underlying mechanisms should be a priority, along with improving model parameterization and constraints. No single tropical forest is representative of all tropical forests; therefore logistical feasibility should be the most important consideration for locating large-scale manipulative experiments. Above all, we advocate for multi-faceted research programs, and we offer arguments for what we consider the most powerful and urgent way forward in order to improve our understanding of tropical forest responses to climate change.

Global Change Biology↗