USGS Science⌕ Search

SEARCH · USGS Science

Results for “Remote Sensing Information”

Search indexed USGS publications on groundwater, aquifers, geologic maps, mineral resources and earthquakes. Explore source records by subject and place.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 379 records · Page 21Linked to original sources
USGS1985

Water-resources activities of the U.S. Geological Survey in Texas; fiscal years 1982-84

The U.S. Geological Survey (USGS) was established by an act of Congress on March 3, 1879, to provide a permanent Federal agency to conduct the systematic and scientific classification of the public lands, and examination of the geological structure, mineral resources, and products of national domain. An integral part of that original mission includes publishing and disseminating the earth-science information needed to understand, to plan the use of, and to manage the Nation's energy, land, mineral, and water resources. Since 1879, the research and fact-finding role of the USGS has grown and been modified to meet the changing needs of the Nation it serves. As part of that evolution, the USGS has become the Federal Government's largest earth-science research agency, the Nation's largest civilian mapmaking agency, the primary source of data on the Nation's surface- and ground-water resources, and the employer of the largest number of professional earth scientists. Today's programs serve a diversity of needs and users. Programs include: Conducting detailed assessments of the energy and mineral potential of the Nation's land and offshore areas. Investigating and issuing warnings of earthquakes, volcanic eruptions, landslides, and other geologic and hydrologic hazards. Conducting research on the geologic structure of the Nation. Studying the geologic features, structure, processes, and history of the other planets of our solar system. Conducting topographic surveys of the Nation and preparing topographic and thematic maps and related cartographic products. Developing and producing digital cartographic data bases and products. Collecting data on a routine basis to determine the quantity, quality, and use of surface and ground water. Conducting water-resources appraisals in order to describe the consequences of alternative plans for developing land and water resources. Conducting research in hydraulics and hydrology and coordinating all Federal water-data acquisition. Using remotely sensed data to develop new cartographic, geologic, and hydrologic research techniques for natural resources planning and management. Providing earth-science information through an extensive publications program and a network of public access points. Along with its continuing commitment to meet the growing and changing earthscience information needs of the Nation, the USGS remains dedicated to its original mission to collect, analyze, interpret, publish, and disseminate information about the natural resources of the Nation providing "earth science in the public service."

Open-File Report↗
USGS2016

Sedimentologic characteristics of recent washover deposits from Assateague Island, Maryland

The U.S. Geological Survey has a long history of responding to and documenting the impacts of storms along the Nation’s coasts and incorporating these data into storm impact and coastal change vulnerability assessments. Although physical changes caused by tropical and extratropical storms to the sandy beaches and dunes fronting barrier islands are generally well documented, the interaction between sandy shoreline erosion and overwash with the back-barrier wetland and estuarine environments is poorly constrained. The goal of the Barrier Island and Estuarine Wetland Physical Change Assessment project is to integrate a wetland-change assessment with existing coastal-change assessments for the adjacent sandy dunes and beaches, initially focusing on Assateague Island along the Maryland and Virginia coastline. Assateague Island was impacted by waves and storm surge associated with the passage of Hurricane Sandy in October 2012, causing erosion and overwash along the ocean-facing sandy shoreline as well as erosion and overwash deposition in the back-barrier and estuarine bay environments. This report describes sediment data collected using sand augers in active overwash zones on Assateague Island in Maryland. Samples were collected by the U.S. Geological Survey (USGS) during two surveys in March/April and October 2014 (USGS Field Activity Numbers [FAN] 2014-301-FA and 2014-322-FA, respectively). The physical characteristics (for example, sediment texture or bedding structure) of and spatial differences among these deposits will provide information about overwash processes and sediment transport from the sandy barrier-island reaches to the back-barrier environments. Metrics derived from these data, such as mean grain size or deposit thicknesses, can be used to ground-truth remote sensing and geophysical data and can also be incorporated into sediment transport models. Data products, including sample location tables, descriptive core logs, core photographs and x-radiographs, the results of sediment grain-size analyses, and Geographic Information System (GIS) data files with accompanying formal Federal Geographic Data Committee (FGDC) metadata can be downloaded from the Data Downloads page.

Maryland↗
USGS2022

U.S. Geological Survey Colorado River Basin Actionable and Strategic Integrated Science and Technology (ASIST)—Information Management Technology Plan

Introduction More than 840 publications, 575 data releases, and 330 project web pages from the U.S. Geological Survey (USGS) pertain to the Colorado River Basin. Limited interconnections between Colorado River Basin publications, data, and web pages restrict the ability to synthesize and interpret scientific resources. Currently, these pieces are spread across multiple isolated locations, internal systems, data repositories, and local offices. The increasing size, complexity, and diversity of Colorado River Basin data creates additional need for integration. These different data types—including discrete, continuous, aerial, remote sensing, geophysical, geospatial, and other types in varied formats—are collected over numerous time and space scales and require data-intensive science and technology to integrate. Information management technology (IMT) resources are enterprise capabilities that the USGS workforce can leverage at multiple scales with consistent interoperable solutions to better facilitate integrated science. The USGS 21st Century Science Strategy directs the USGS to establish enterprise IMT capabilities that support integrated work through interoperable software and database solutions at multiple scales. This Information Management Technology Plan identifies nine steps to leverage new and existing technologies, data, models, and scientific knowledge to support integrated science projects conducted across the Colorado River Basin. These steps are transferable to integrated-science studies in other locations.

Arizona, Colorado, Nevada, New Mexico, Utah, Wyomi↗
USGS2017

A land data assimilation system for sub-Saharan Africa food and water security applications

Seasonal agricultural drought monitoring systems, which rely on satellite remote sensing and land surface models (LSMs), are important for disaster risk reduction and famine early warning. These systems require the best available weather inputs, as well as a long-term historical record to contextualize current observations. This article introduces the Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System (FLDAS), a custom instance of the NASA Land Information System (LIS) framework. The FLDAS is routinely used to produce multi-model and multi-forcing estimates of hydro-climate states and fluxes over semi-arid, food insecure regions of Africa. These modeled data and derived products, like soil moisture percentiles and water availability, were designed and are currently used to complement FEWS NET’s operational remotely sensed rainfall, evapotranspiration, and vegetation observations. The 30+ years of monthly outputs from the FLDAS simulations are publicly available from the NASA Goddard Earth Science Data and Information Services Center (GES DISC) and recommended for use in hydroclimate studies, early warning applications, and by agro-meteorological scientists in Eastern, Southern, and Western Africa.

Scientific Data↗
USGS2013

Correlating multispectral imaging and compositional data from the Mars Exploration Rovers and implications for Mars Science Laboratory

In an effort to infer compositional information about distant targets based on multispectral imaging data, we investigated methods of relating Mars Exploration Rover (MER) Pancam multispectral remote sensing observations to in situ alpha particle X-ray spectrometer (APXS)-derived elemental abundances and Mössbauer (MB)-derived abundances of Fe-bearing phases at the MER field sites in Gusev crater and Meridiani Planum. The majority of the partial correlation coefficients between these data sets were not statistically significant. Restricting the targets to those that were abraded by the rock abrasion tool (RAT) led to improved Pearson’s correlations, most notably between the red–blue ratio (673 nm/434 nm) and Fe 3+ -bearing phases, but partial correlations were not statistically significant. Partial Least Squares (PLS) calculations relating Pancam 11-color visible to near-IR (VNIR; ∼400–1000 nm) “spectra” to APXS and Mössbauer element or mineral abundances showed generally poor performance, although the presence of compositional outliers led to improved PLS results for data from Meridiani. When the Meridiani PLS model for pyroxene was tested by predicting the pyroxene content of Gusev targets, the results were poor, indicating that the PLS models for Meridiani are not applicable to data from other sites. Soft Independent Modeling of Class Analogy (SIMCA) classification of Gusev crater data showed mixed results. Of the 24 Gusev test regions of interest (ROIs) with known classes, 11 had >30% of the pixels in the ROI classified correctly, while others were mis-classified or unclassified. k-Means clustering of APXS and Mössbauer data was used to assign Meridiani targets to compositional classes. The clustering-derived classes corresponded to meaningful geologic and/or color unit differences, and SIMCA classification using these classes was somewhat successful, with >30% of pixels correctly classified in 9 of the 11 ROIs with known classes. This work shows that the relationship between SWIR multispectral imaging data and APXS- and Mössbauer-derived composition/mineralogy is often weak, a perhaps not entirely unexpected result given the different surface sampling depths of SWIR imaging (uppermost few microns) vs. APXS (tens of μm) and MB measurements (hundreds of μm). Results from the upcoming Mars Science Laboratory (MSL) rover’s ChemCam Laser Induced Breakdown Spectroscopy (LIBS) instrument may show a closer relationship to Mastcam SWIR multispectral observations, however, because the initial laser shots onto a target will analyze only the upper few micrometers of the surface. The clustering and classification methods used in this study can be applied to any data set to formalize the definition of classes and identify targets that do not fit in previously defined classes.

Icarus↗
USGS2011

A working environment for digital planetary data processing and mapping using ISIS and GRASS GIS

Since the beginning of planetary exploration, mapping has been fundamental to summarize observations returned by scientific missions. Sensor-based mapping has been used to highlight specific features from the planetary surfaces by means of processing. Interpretative mapping makes use of instrumental observations to produce thematic maps that summarize observations of actual data into a specific theme. Geologic maps, for example, are thematic interpretative maps that focus on the representation of materials and processes and their relative timing. The advancements in technology of the last 30 years have allowed us to develop specialized systems where the mapping process can be made entirely in the digital domain. The spread of networked computers on a global scale allowed the rapid propagation of software and digital data such that every researcher can now access digital mapping facilities on his desktop. The efforts to maintain planetary missions data accessible to the scientific community have led to the creation of standardized digital archives that facilitate the access to different datasets by software capable of processing these data from the raw level to the map projected one. Geographic Information Systems (GIS) have been developed to optimize the storage, the analysis, and the retrieval of spatially referenced Earth based environmental geodata; since the last decade these computer programs have become popular among the planetary science community, and recent mission data start to be distributed in formats compatible with these systems. Among all the systems developed for the analysis of planetary and spatially referenced data, we have created a working environment combining two software suites that have similar characteristics in their modular design, their development history, their policy of distribution and their support system. The first, the Integrated Software for Imagers and Spectrometers (ISIS) developed by the United States Geological Survey, represents the state of the art for processing planetary remote sensing data, from the raw unprocessed state to the map projected product. The second, the Geographic Resources Analysis Support System (GRASS) is a Geographic Information System developed by an international team of developers, and one of the core projects promoted by the Open Source Geospatial Foundation (OSGeo). We have worked on enabling the combined use of these software systems throughout the set-up of a common user interface, the unification of the cartographic reference system nomenclature and the minimization of data conversion. Both software packages are distributed with free open source licenses, as well as the source code, scripts and configuration files hereafter presented. In this paper we describe our work done to merge these working environments into a common one, where the user benefits from functionalities of both systems without the need to switch or transfer data from one software suite to the other one. Thereafter we provide an example of its usage in the handling of planetary data and the crafting of a digital geologic map. ?? 2010 Elsevier Ltd. All rights reserved.

Conference Paper↗
USGS2014

Seasonal cultivated and fallow cropland mapping using MODIS-based automated cropland classification algorithm

Increasing drought occurrences and growing populations demand accurate, routine, and consistent cultivated and fallow cropland products to enable water and food security analysis. The overarching goal of this research was to develop and test automated cropland classification algorithm (ACCA) that provide accurate, consistent, and repeatable information on seasonal cultivated as well as seasonal fallow cropland extents and areas based on the Moderate Resolution Imaging Spectroradiometer remote sensing data. Seasonal ACCA development process involves writing series of iterative decision tree codes to separate cultivated and fallow croplands from noncroplands, aiming to accurately mirror reliable reference data sources. A pixel-by-pixel accuracy assessment when compared with the U.S. Department of Agriculture (USDA) cropland data showed, on average, a producer’s accuracy of 93% and a user’s accuracy of 85% across all months. Further, ACCA-derived cropland maps agreed well with the USDA Farm Service Agency crop acreage-reported data for both cultivated and fallow croplands with R-square values over 0.7 and field surveys with an accuracy of ≥95% for cultivated croplands and ≥76% for fallow croplands. Our results demonstrated the ability of ACCA to generate cropland products, such as cultivated and fallow cropland extents and areas, accurately, automatically, and repeatedly throughout the growing season.

California↗
USGS2015

Using satellite images to monitor glacial-lake outburst floods: Lago Cachet Dos drainage, Chile

The U.S. Geological Survey (USGS) is monitoring and analyzing glacial-lake outburst floods (GLOFs) in the Colonia valley in the Patagonia region of southern Chile. A GLOF is a type of flood that occurs when water impounded by a glacier or a glacial moraine is released catastrophically. In the Colonia valley, GLOFs originating from Lago Cachet Dos, which is dammed by the Colonia Glacier, have recurred periodically since 2008. The water discharged during these GLOFs flows under or through the Colonia Glacier, into Lago Colonia and then the Río Colonia, and finally into the Río Baker—Chile's largest river in terms of volume of water. This report presents a GeoEye-1 image collected December 1, 2011 and a WorldView-2 image collected September 27, 2013. The 2011 image shows Lago Cachet Dos when the water level was near its maximum extent. The 2013 image shows the drained lake four days after a GLOF event. The images were used to delineate the differences in water surface area prior to, and immediately following, a GLOF event. The imagery shown here highlights the dramatic changes that typically occur during GLOFs from Lago Cachet Dos. The lake area decreased from 4.84 km 2 in 2011 (pre-GLOF) to only 0.30 km 2 in September 2013 (post-GLOF). The water surface lowered approximately 90 m between the pre- and post-GLOF satellite images, yielding a change in volume of approximately 217,000,000 m 3 ; this value is similar to previous estimates (about 200 million m 3 ) of the volume of flood water that flowed down the Río Colonia during some previous GLOFs. During 2008–2013, 14 GLOFs were released from Lago Cachet Dos and created environmental and safety concerns for downstream residents and to infrastructure. If GLOFs and the consequent headward erosion continue, the moraine that creates Lago Cachet Uno could be destabilized and breached, and the two lakes could merge. If the two lakes become connected, the volume of future GLOFs likely would be greater and thus cause longer and (or) more extensive flooding downstream. Additional GLOFs from Lago Cachet Dos are expected in the future, and continued environmental monitoring could provide an early warning system as well as scientific information that could increase our understanding of GLOFs and their consequences. GLOFs occur in glaciated areas around the world and remote sensing technologies can allow researchers to better understand—and potentially predict—future GLOF events.

Colonia valley, Lago Cachet Dos, Patagonia↗
USGS2008

Mangrove forest distributions and dynamics in Madagascar (1975-2005)

Mangrove forests of Madagascar are declining, albeit at a much slower rate than the global average. The forests are declining due to conversion to other land uses and forest degradation. However, accurate and reliable information on their present distribution and their rates, causes, and consequences of change have not been available. Earlier studies used remotely sensed data to map and, in some cases, to monitor mangrove forests at a local scale. Nonetheless, a comprehensive national assessment and synthesis was lacking. We interpreted time-series satellite data of 1975, 1990, 2000, and 2005 using a hybrid supervised and unsupervised classification approach. Landsat data were geometrically corrected to an accuracy of ?? one-half pixel, an accuracy necessary for change analysis. We used a postclassification change detection approach. Our results showed that Madagascar lost 7% of mangrove forests from 1975 to 2005, to a present extent of ???2,797 km2. Deforestation rates and causes varied both spatially and temporally. The forests increased by 5.6% (212 km2) from 1975 to 1990, decreased by 14.3% (455 km 2) from 1990 to 2000, and decreased by 2.6% (73 km2) from 2000 to 2005. Similarly, major changes occurred in Bombekota Bay, Mahajamba Bay, the coast of Ambanja, the Tsiribihina River, and Cap St Vincent. The main factors responsible for mangrove deforestation include conversion to agriculture (35%), logging (16%), conversion to aquaculture (3%), and urban development (1%). ?? 2008 by MDPI.

Sensors↗
USGS1986

Digital merging of Landsat TM and digitized NHAP data for 1:24 000-scale image mapping.

Merging image data collected by different remote sensors is becoming an increasingly important component of digital processing. In this study, two data sets with very different characteristics were digitally merged, and a single data set, which contains information from both sets, was generated. Landsat Thematic Mapper (TM) data were selected for their spectral information, and a digitized panchromatic photograph collected as part of the National High Altitude Program (NHAP), with approximately 4-m resolution after being digitized, was used for the primary spatial information. Five image control points and a second-order polynomial fit were used to combine the information from both data sets.-from Author

Photogrammetric Engineering and Remote Sensing↗
USGS2022

Optimizing satellite resources for the global assessment and mitigation of volcanic hazards—Suggestions from the USGS Powell Center Volcano Remote Sensing Working Group

A significant number of the world’s approximately 1,400 subaerial volcanoes with Holocene eruptions are unmonitored by ground-based sensors yet constitute a potential hazard to nearby residents and infrastructure, as well as air travel and global commerce. Data from an international constellation of more than 60 current satellite instruments provide a cost-effective means of tracking activity and potentially forecasting hazards at volcanoes around the world. These data span the electromagnetic spectrum: ultraviolet, optical, infrared, and microwave (synthetic aperture radar). They can measure volcanic thermal and gas emissions, ground displacement, and surface and topographic change, providing information that addresses one of the grand challenges in volcanology—to overcome our incomplete understanding of the relation between volcanic unrest and eruption, which is currently based on only a few well-studied volcanoes. Although the potential of volcano remote sensing has been recognized for decades, there are many hurdles to clear before remote sensing data can be used fully by all volcano observatories. These include: (1) the limited temporal and spatial coverage of active volcanoes by satellites and the delayed distribution of those data; (2) the lack of background data acquired at all volcanoes; and (3) limited access to, and utilization of, remote sensing data in some areas owing to a lack of expertise, licensing, user-friendly formats, data access portals, or computational infrastructure. While remote sensing data will never replace ground-based monitoring, a joint observation strategy provides a powerful means of assessing volcanic activity before, during, and after hazardous eruptions, especially given the unique spatial, temporal, and spectral perspective provided by remote measurements. A coordinated international remote sensing observation strategy for volcanoes—similar to one used by the cryosphere community—along with a volcano space task group to maximize the utility of satellite data for volcano monitoring would be highly beneficial. Such a vision could facilitate (1) global coordination of satellite observations (as done for polar regions) for background monitoring and eruption response, (2) open data that can be rapidly distributed during crises, (3) communication tools and forums for discussion of satellite data, (4) integrated ground and satellite databases of unrest, and (5) global capacity building.

Scientific Investigations Report↗
USGS2006

Spectral mixture analyses of hyperspectral data acquired using a tethered balloon

Tethered balloon remote sensing platforms can be used to study radiometric issues in terrestrial ecosystems by effectively bridging the spatial gap between measurements made on the ground and those acquired via airplane or satellite. In this study, the Short Wave Aerostat-Mounted Imager (SWAMI) tethered balloon-mounted platform was utilized to evaluate linear and nonlinear spectral mixture analysis (SMA) for a grassland-conifer forest ecotone during the summer of 2003. Hyperspectral measurement of a 74-m diameter ground instantaneous field of view (GIFOV) attained by the SWAMI was studied. Hyperspectral spectra of four common endmembers, bare soil, grass, tree, and shadow, were collected in situ, and images captured via video camera were interpreted into accurate areal ground cover fractions for evaluating the mixture models. The comparison between the SWAMI spectrum and the spectrum derived by combining in situ spectral data with video-derived areal fractions indicated that nonlinear effects occurred in the near infrared (NIR) region, while nonlinear influences were minimal in the visible region. The evaluation of hyperspectral and multispectral mixture models indicated that nonlinear mixture model-derived areal fractions were sensitive to the model input data, while the linear mixture model performed more stably. Areal fractions of bare soil were overestimated in all models due to the increased radiance of bare soil resulting from side scattering of NIR radiation by adjacent grass and trees. Unmixing errors occurred mainly due to multiple scattering as well as close endmember spectral correlation. In addition, though an apparent endmember assemblage could be derived using linear approaches to yield low residual error, the tree and shade endmember fractions calculated using this technique were erroneous and therefore separate treatment of endmembers subject to high amounts of multiple scattering (i.e. shadows and trees) must be done with caution. Including the short wave infrared (SWIR) region in the hyperspectral and multispectral endmember data significantly reduced the Pearson correlation coefficient values among endmember spectra. Therefore, combination of visible, NIR, and SWIR information is likely to further improve the utility of SMA in understanding ecosystem structure and function and may help narrow uncertainties when utilizing remotely sensed data to extrapolate trace glas flux measurements from the canopy scale to the landscape scale.

Remote Sensing of Environment↗
USGS2015

Calculating crop water requirement satisfaction in the West Africa Sahel with remotely sensed soil moisture

The Soil Moisture Active Passive (SMAP) mission will provide soil moisture data with unprecedented accuracy, resolution, and coverage, enabling models to better track agricultural drought and estimate yields. In turn, this information can be used to shape policy related to food and water from commodity markets to humanitarian relief efforts. New data alone, however, do not translate to improvements in drought and yield forecasts. New tools will be needed to transform SMAP data into agriculturally meaningful products. The objective of this study is to evaluate the possibility and efficiency of replacing the rainfall-derived soil moisture component of a crop water stress index with SMAP data. The approach is demonstrated with 0.1°-resolution, ~10-day microwave soil moisture from the European Space Agency and simulated soil moisture from the Famine Early Warning Systems Network Land Data Assimilation System. Over a West Africa domain, the approach is evaluated by comparing the different soil moisture estimates and their resulting Water Requirement Satisfaction Index values from 2000 to 2010. This study highlights how the ensemble of indices performs during wet versus dry years, over different land-cover types, and the correlation with national-level millet yields. The new approach is a feasible and useful way to quantitatively assess how satellite-derived rainfall and soil moisture track agricultural water deficits. Given the importance of soil moisture in many applications, ranging from agriculture to public health to fire, this study should inspire other modeling communities to reformulate existing tools to take advantage of SMAP data.

Journal of Hydrometeorology↗
USGS2004

Monitoring Colonias Development along the United States-Mexico Border: A Process Application using GIS and Remote Sensing in Douglas, Arizona, and Agua Prieta, Sonora

The U.S. Department of Housing and Urban Development (HUD) and the U.S. Geological Survey (USGS) have developed a joint project to create Internet-enabled geographic information systems (GIS) that will help cities along the United States-Mexico border deal with issues related to colonias. HUD defines colonias as rural neighborhoods in the United States-Mexico border region that lack adequate infrastructure or housing and other basic services. They typically have high poverty rates that make it difficult for residents to pay for roads, sanitary water and sewer systems, decent housing, street lighting, and other services through assessment. Many Federal agencies recognize colonias designations and provide funding assistance. It is the intention of this project to empower Arizona-Sonora borderland neighborhoods and community members by recognizing them as colonias. This recognition will result in eligibility for available economic subsidies and accessibility to geospatial tools and information for urban planning. The steps to achieve this goal include delineation of colonia-like neighborhoods, identification of their urbanization over time, development of geospatial databases describing their infrastructure, and establishment of a framework for distributing Web-based GIS decision support systems. A combination of imagery and infrastructure information was used to help delineate colonia boundaries. A land-use change analysis, focused on urbanization in the cities over a 30-year timeframe, was implemented. The results of this project are being served over the Internet, providing data to the public as well as to participating agencies. One of the initial study areas for this project was the City of Douglas, Ariz., and its Mexican sister-city Agua Prieta, Sonora, which are described herein. Because of its location on the border, this twin-cities area is especially well suited to international manufacturing and commerce, which has, in turn, led to an uncontrolled spread of colonias. The USGS worked with local organizations in developing the Web-based GIS database. Community involvement ensured that the database and map server would meet the current and long-term needs of the communities and end users. Partners include Federal agencies, State agencies, county officials, town representatives, universities, and youth organizations, as well as interested local advocacy groups and individuals. A significant component of this project was development of relationships and partnerships in the border towns for facilitating binational approaches to land management.

Open-File Report↗
USGS2001

Abstracts from "Coastal Marsh Dieback in the Northern Gulf of Mexico: Extent, Causes, Consequences, and Remedies

In the spring of 2000, scientists discovered a new and unprecedented loss of salt marsh vegetation in coastal Louisiana and other areas along the northern coast of the Gulf of Mexico. This dieback of salt marsh vegetation, sometimes called the brown marsh phenomenon', primarily involved the rapid browning and dieback of smooth cordgrass (Spanina alterniflora). Coastal Louisiana has already undergone huge, historical losses of coastal marsh due to both human-induced and natural factors, and the current overall rate of wetland loss (25-35 sq mi 65-91 SQ KM each year) stands to threaten Louisiana's coastal ecosystem, infrastructure, and economy. On January 11-12, 2001, individuals from Federal and State agencies, universities, and the private sector met at the conference 'Coastal Marsh Dieback in the Northern Gulf of Mexico: Extent, Causes, Consequences, and Remedies' to discuss and share information shout the marsh dieback. Presentations discussed trends in the progress of dieback during the summer of 2000 and in environmental conditions occurring at field study sites, possible causes including drought and Mississippi low flow' conditions, changes in soil conditions (salinity, the bioavailability of metals, pathogens, etc.), the potential for wetland loss that could occur if above and below normality occurs and is sustained over an extended period, advanced techniques for tracking the dieback via aerial photography and remote sensing, linkages of marsh hydrology to the dieback, and mechanisms of modeling dieback and recovery. In addition, presentations were made regarding development of a web site to facilitate information sharing and progress in preparation for requests for proposals based on an emergency appropriation by the U.S. Congress. All findings tended to support the idea that the dieback constituted a continuing environmental emergency and research and natural resource management efforts should be expended accordingly.

Information and Technology Report↗
USGS2007

Climate Change Research at USGS Center for Earth Resources Observation and Science (EROS)

Research and development projects at EROS apply unique resources to support the USGS mission of developing understanding, monitoring, and modeling of climate variability and change and their human, physical, and biological impacts. Remote sensing resources, both new and archived, form the core of our ability to determine changes in the state or condition of the Earth’s surface and its dynamic landscape and ecosystem processes. This rich resource provides powerful biophysical information for local to global areas. Archival data form the basis for assessing human and climate impacts on the land surface, trends of land use, and an understanding of climate and management impacts. Biophysical information from satellite data is assimilated into quantitative models that allow all disciplines of the USGS to understand impacts on ecosystem processes. Major processes and problems we address include: carbon fluxes, hydrological processes, albedo changes and regional climates, mangroves and wetland protection of coastal environments, natural and manmade hazards (e.g., fire and drought), ecosystem change and succession, land use and land cover change, and more. The integration of remote sensing, modeling, and multidisciplinary approaches fosters international scientific leadership across all disciplines for the USGS.

Fact Sheet↗
USGS2007

Estimation of forest fuel load from radar remote sensing

Understanding fire behavior characteristics and planning for fire management require maps showing the distribution of wildfire fuel loads at medium to fine spatial resolution across large landscapes. Radar sensors from airborne or spaceborne platforms have the potential of providing quantitative information about the forest structure and biomass components that can be readily translated to meaningful fuel load estimates for fire management. In this paper, we used multifrequency polarimetric synthetic aperture radar (SAR) imagery acquired over a large area of the Yellowstone National Park by the Airborne SAR sensor to estimate the distribution of forest biomass and canopy fuel loads. Semiempirical algorithms were developed to estimate crown and stem biomass and three major fuel load parameters, namely: 1) canopy fuel weight; 2) canopy bulk density; and 3) foliage moisture content. These estimates, when compared directly to measurements made at plot and stand levels, provided more than 70% accuracy and, when partitioned into fuel load classes, provided more than 85% accuracy. Specifically, the radar-generated fuel parameters were in good agreement with the field-based fuel measurements, resulting in coefficients of determination of R2 = 85 for the canopy fuel weight, R 2 = 0.84 for canopy bulk density, and R2 =0.78 for the foliage biomass. ?? 2007 IEEE.

IEEE Transactions on Geoscience and Remote Sensing↗
USGS2021

Sentinel-2 and WorldView-3 atmospheric correction and signal normalization based on ground-truth spectroradiometric measurements

Remote sensing satellite Earth Observing Systems (EOS) provide a variety of products for monitoring Earth surface processes at varying spatial and spectral resolutions. Combining information from high and medium spatial resolution images is valuable for monitoring ground cover and vegetation status in cropland, grassland, forests, and other natural settings. However, coupling information from different EOS requires compensating for atmospheric and view angle effects before integrating comparable surface reflectance (SR) values. The objectives of this study were i) to assess how different atmospheric constituents affect the atmospheric correction results in Sentinel-2 and WorldView-3 imagery, ii) to establish a relationship with field spectra measurements, and iii) to develop an empirical approach to ensure that SR values extracted from different EOS can be normalized for use in monitoring vegetation and land cover status. We compared surface reflectance values derived from Sentinel-2 images corrected with Sen2Cor, MODTRAN or FLAASH atmospheric correction approaches for the visible-to-near infrared regions. Additionally, this information was compared to SR values extracted from WorldView-3 imagery acquired from the same dates and location (Central Spain) and corrected with MODTRAN and FLAASH approaches. Assessment of the atmospheric correction was conducted by comparing satellite image SR with ground-truth spectra acquired with a FieldSpec hand-held spectroradiometer. The results emphasized the importance of using common atmospheric parameters collected from ancillary data sources (i.e. MODIS Atmosphere & Land products) to ensure a reliable SR comparison. When compared to field-collected spectral data, SR from corrected Sentinel-2 push-broom imagery showed a reliable match (<4% difference in the visible bands and <0.52% difference in the near infrared bands). However, SR imagery from the pointable WorldView-3 instrument showed significant deviation, likely resulting from the effects of steep off-nadir acquisition angles (24.6° to 39.1°) combined with surface anisotropy. The magnitude and sign of the deviation in SR differed depending on the vegetation type, wavelength and sun-surface-sensor geometry. Therefore, it was necessary to account for angular effects to ensure reliable comparisons of imagery from the different EOS. In this study, an empirical angular correction approach was developed based on calibrating each WorldView-3 band against the ground-truth spectra. This correction allowed for the accurate signal normalization of WorldView-3 and Sentinel-2 imagery SR in the visible-to-near infrared regions.

ISPRS Journal of Photogrammetry and Remote Sensing↗