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At least 91 records · Page 5Linked to original sources
USGS2014

National Land Imaging Requirements (NLIR) Pilot Project summary report: Summary of moderate resolution imaging user requirements

Under the National Land Imaging Requirements (NLIR) Project, the U.S. Geological Survey (USGS) is developing a functional capability to obtain, characterize, manage, maintain and prioritize all Earth observing (EO) land remote sensing user requirements. The goal is a better understanding of community needs that can be supported with land remote sensing resources, and a means to match needs with appropriate solutions in an effective and efficient way. The NLIR Project is composed of two components. The first component is focused on the development of the Earth Observation Requirements Evaluation System (EORES) to capture, store and analyze user requirements, whereas, the second component is the mechanism and processes to elicit and document the user requirements that will populate the EORES. To develop the second component, the requirements elicitation methodology was exercised and refined through a pilot project conducted from June to September 2013. The pilot project focused specifically on applications and user requirements for moderate resolution imagery (5–120 meter resolution) as the test case for requirements development. The purpose of this summary report is to provide a high-level overview of the requirements elicitation process that was exercised through the pilot project and an early analysis of the moderate resolution imaging user requirements acquired to date to support ongoing USGS sustainable land imaging study needs. The pilot project engaged a limited set of Federal Government users from the operational and research communities and therefore the information captured represents only a subset of all land imaging user requirements. However, based on a comparison of results, trends, and analysis, the pilot captured a strong baseline of typical applications areas and user needs for moderate resolution imagery. Because these results are preliminary and represent only a sample of users and application areas, the information from this report should only be used to indicate general user needs for the applications covered. Users of the information are cautioned that use of specific numeric results may be inappropriate without additional research. Any information used or cited from this report should specifically be cited as preliminary findings.

Open-File Report↗
USGS2022

The future of coastal monitoring through satellite remote sensing

Satellite remote sensing is transforming coastal science from a “data-poor” field into a “data-rich” field. Sandy beaches are dynamic landscapes that change in response to long-term pressures, short-term pulses, and anthropogenic interventions. Until recently, the rate and breadth of beach change have outpaced our ability to monitor those changes, due to the spatiotemporal limitations of our observational capacity. Over the past several decades, only a handful of beaches worldwide have been regularly monitored with accurate yet expensive in situ surveys. The long-term coastal-change data of these few well-monitored beaches have led to in-depth understanding of many site-specific coastal processes. However, because the best-monitored beaches are not representative of all beaches, much remains unknown about the processes and fate of the other >99% of unmonitored beaches worldwide. The fleet of Earth-observing satellites has enabled multiscale monitoring of beaches, for the very first time, by providing imagery with global coverage and up to daily frequency. The long-standing and ever-expanding archive of satellite imagery will enable coastal scientists to investigate coastal change at sites vulnerable to future sea-level rise, that is, (almost) everywhere. In the past decade, our capability to observe coastal change from space has grown substantially with computing and algorithmic power. Yet, further advances are needed in automating monitoring using machine learning, deep learning, and computer vision to fully leverage this massive treasure trove of data. Extensive monitoring and investigation of the causes and effects of coastal change at the requisite spatiotemporal scales will provide coastal managers with additional, valuable information to evaluate problems and solutions, addressing the potential for widespread beach loss due to accelerated sea-level rise, development, and reduced sediment supply. Monitoring from Earth-observing satellites is currently the only means of providing seamless data with high spatiotemporal resolution at the global scale of the impending impacts of climate change on coastal systems.

Cambridge Prisms: Coastal Futures↗
USGS2016

Global trends in satellite-based emergency mapping

Over the past 15 years, scientists and disaster responders have increasingly used satellite-based Earth observations for global rapid assessment of disaster situations. We review global trends in satellite rapid response and emergency mapping from 2000 to 2014, analyzing more than 1000 incidents in which satellite monitoring was used for assessing major disaster situations. We provide a synthesis of spatial patterns and temporal trends in global satellite emergency mapping efforts and show that satellite-based emergency mapping is most intensively deployed in Asia and Europe and follows well the geographic, physical, and temporal distributions of global natural disasters. We present an outlook on the future use of Earth observation technology for disaster response and mitigation by putting past and current developments into context and perspective.

Science↗
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↗
USGS2013

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↗
USGS2021

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↗
USGS2019

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↗
USGS2008

Moderate Resolution Imaging Spectroradiometer (MODIS) Overview

The Moderate Resolution Imaging Spectroradiometer (MODIS) is an instrument that collects remotely sensed data used by scientists for monitoring, modeling, and assessing the effects of natural processes and human actions on the Earth's surface. The continual calibration of the MODIS instruments, the refinement of algorithms used to create higher-level products, and the ongoing product validation make MODIS images a valuable time series (2000-present) of geophysical and biophysical land-surface measurements. Carried on two National Aeronautics and Space Administration (NASA) Earth Observing System (EOS) satellites, MODIS acquires morning (EOS-Terra) and afternoon (EOS-Aqua) views almost daily. Terra data acquisitions began in February 2000 and Aqua data acquisitions began in July 2002. Land data are generated only as higher-level products, removing the burden of common types of data processing from the user community. MODIS-based products describing ecological dynamics, radiation budget, and land cover are projected onto a sinusoidal mapping grid and distributed as 10- by 10-degree tiles at 250-, 500-, or 1,000-meter spatial resolution. Some products are also created on a 0.05-degree geographic grid to support climate modeling studies. All MODIS products are distributed in the Hierarchical Data Format-Earth Observing System (HDF-EOS) file format and are available through file transfer protocol (FTP) or on digital video disc (DVD) media. Versions 4 and 5 of MODIS land data products are currently available and represent 'validated' collections defined in stages of accuracy that are based on the number of field sites and time periods for which the products have been validated. Version 5 collections incorporate the longest time series of both Terra and Aqua MODIS data products.

Fact Sheet↗
USGS2010

Preliminary assessment of several parameters to measure and compare usefulness of the CEOS reference pseudo-invariant calibration sites

Test sites are central to any future quality assurance and quality control (QA/QC) strategy. The Committee on Earth Observation Satellites (CEOS) Working Group for Calibration and Validation (WGCV) Infrared Visible Optical Sensors (IVOS) worked with collaborators around the world to establish a core set of CEOS-endorsed, globally distributed, reference standard test sites (both instrumented and pseudo-invariant) for the post-launch calibration of space-based optical imaging sensors. The pseudo-invariant calibration sites (PICS) have high reflectance and are usually made up of sand dunes with low aerosol loading and practically no vegetation. The goal of this paper is to provide preliminary assessment of "several parameters" than can be used on an operational basis to compare and measure usefulness of reference sites all over the world. The data from Landsat 7 (L7) Enhanced Thematic Mapper Plus (ETM+) and the Earth Observing-1 (EO-1) Hyperion sensors over the CEOS PICS were used to perform a preliminary assessment of several parameters, such as usable area, data availability, top-of-atmosphere (TOA) reflectance, at-sensor brightness temperature, spatial uniformity, temporal stability, spectral stability, and typical spectrum observed over the sites.

Conference Paper↗
USGS2008

Landsat continuity: Issues and opportunities for land cover monitoring

Initiated in 1972, the Landsat program has provided a continuous record of earth observation for 35 years. The assemblage of Landsat spatial, spectral, and temporal resolutions, over a reasonably sized image extent, results in imagery that can be processed to represent land cover over large areas with an amount of spatial detail that is absolutely unique and indispensable for monitoring, management, and scientific activities. Recent technical problems with the two existing Landsat satellites, and delays in the development and launch of a successor, increase the likelihood that a gap in Landsat continuity may occur. In this communication, we identify the key features of the Landsat program that have resulted in the extensive use of Landsat data for large area land cover mapping and monitoring. We then augment this list of key features by examining the data needs of existing large area land cover monitoring programs. Subsequently, we use this list as a basis for reviewing the current constellation of earth observation satellites to identify potential alternative data sources for large area land cover applications. Notions of a virtual constellation of satellites to meet large area land cover mapping and monitoring needs are also presented. Finally, research priorities that would facilitate the integration of these alternative data sources into existing large area land cover monitoring programs are identified. Continuity of the Landsat program and the measurements provided are critical for scientific, environmental, economic, and social purposes. It is difficult to overstate the importance of Landsat; there are no other systems in orbit, or planned for launch in the short-term, that can duplicate or approach replication, of the measurements and information conferred by Landsat. While technical and political options are being pursued, there is no satellite image data stream poised to enter the National Satellite Land Remote Sensing Data Archive should system failures occur to Landsat-5 and -7.

Remote Sensing of Environment↗
USGS2014

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↗
USGS2010

An overview of sensor calibration inter-comparison and applications

Long-term climate data records (CDR) are often constructed using observations made by multiple Earth observing sensors over a broad range of spectra and a large scale in both time and space. These sensors can be of the same or different types operated on the same or different platforms. They can be developed and built with different technologies and are likely operated over different time spans. It has been known that the uncertainty of climate models and data records depends not only on the calibration quality (accuracy and stability) of individual sensors, but also on their calibration consistency across instruments and platforms. Therefore, sensor calibration inter-comparison and validation have become increasingly demanding and will continue to play an important role for a better understanding of the science product quality. This paper provides an overview of different methodologies, which have been successfully applied for sensor calibration inter-comparison. Specific examples using different sensors, including MODIS, AVHRR, and ETM+, are presented to illustrate the implementation of these methodologies.

Frontiers of Earth Science in China↗
USGS2010

An overview of the web-based Google Earth coincident imaging tool

The Committee on Earth Observing Satellites (CEOS) Visualization Environment (COVE) tool is a browser-based application that leverages Google Earth web to display satellite sensor coverage areas. The analysis tool can also be used to identify near simultaneous surface observation locations for two or more satellites. The National Aeronautics and Space Administration (NASA) CEOS System Engineering Office (SEO) worked with the CEOS Working Group on Calibration and Validation (WGCV) to develop the COVE tool. The CEOS member organizations are currently operating and planning hundreds of Earth Observation (EO) satellites. Standard cross-comparison exercises between multiple sensors to compare near-simultaneous surface observations and to identify corresponding image pairs are time-consuming and labor-intensive. COVE is a suite of tools that have been developed to make such tasks easier.

Conference Paper↗
USGS2005

The AmericaView Project - Putting the Earth into Your Hands

The U.S. Geological Survey (USGS) is a leader in collecting, archiving, and distributing geospatial data and information about the Earth. Providing quick, reliable access to remotely sensed images and geospatial data is the driving principle behind the AmericaView Project. A national not-for-profit organization, AmericaView, Inc. was established and is supported by the USGS to coordinate the activities of a national network of university-led consortia with the primary objective of the advancement of the science of remote sensing. Individual consortia members include academic institutions, as well as state, local, and tribal government agencies. AmericaView's focus is to expand the understanding and use of remote sensing through education and outreach efforts and to provide affordable, integrated remote sensing information access and delivery to the American public. USGS's Landsat and NASA's Earth Observing System (EOS) satellite data are downlinked from satellites or transferred from other facilities to the USGS Center for Earth Resources Observation and Science (EROS) ground receiving station in Sioux Falls, South Dakota. The data can then be transferred over high-speed networks to consortium members, where it is archived and made available for public use.

Fact Sheet↗
USGS2023

The founding charter of the Omic Biodiversity Observation Network (Omic BON)

Omic BON is a thematic Biodiversity Observation Network under the Group on Earth Observations Biodiversity Observation Network (GEO BON), focused on coordinating the observation of biomolecules in organisms and the environment. Our founding partners include representatives from national, regional, and global observing systems; standards organizations; and data and sample management infrastructures. By coordinating observing strategies, methods, and data flows, Omic BON will facilitate the co-creation of a global omics meta-observatory to generate actionable knowledge. Here, we present key elements of Omic BON's founding charter and first activities.

GigaScience↗
USGS2013

Next generation of global land cover characterization, mapping, and monitoring

Land cover change is increasingly affecting the biophysics, biogeochemistry, and biogeography of the Earth's surface and the atmosphere, with far-reaching consequences to human well-being. However, our scientific understanding of the distribution and dynamics of land cover and land cover change (LCLCC) is limited. Previous global land cover assessments performed using coarse spatial resolution (300 m–1 km) satellite data did not provide enough thematic detail or change information for global change studies and for resource management. High resolution (∼30 m) land cover characterization and monitoring is needed that permits detection of land change at the scale of most human activity and offers the increased flexibility of environmental model parameterization needed for global change studies. However, there are a number of challenges to overcome before producing such data sets including unavailability of consistent global coverage of satellite data, sheer volume of data, unavailability of timely and accurate training and validation data, difficulties in preparing image mosaics, and high performance computing requirements. Integration of remote sensing and information technology is needed for process automation and high-performance computing needs. Recent developments in these areas have created an opportunity for operational high resolution land cover mapping, and monitoring of the world. Here, we report and discuss these advancements and opportunities in producing the next generations of global land cover characterization, mapping, and monitoring at 30-m spatial resolution primarily in the context of United States, Group on Earth Observations Global 30 m land cover initiative (UGLC).

International Journal of Applied Earth Observation↗