Search USGSSearch

SEARCH · Search USGS

Results for “Advances in Remote Sensing”

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 73 records · Page 4Linked to original sources

Mapping a glide avalanche with terrestrial lidar in Glacier National Park, USA

Thorough documentation of large avalanche events is important for forecasting efforts, infrastructure planning, and investigating the processes involved in avalanche formation and release. However, due in part to the isolated and dangerous nature of avalanche terrain, collecting in-situ, spatially continuous, and quantitative information surrounding avalanches remains difficult. Advances in remote sensing continue to address this knowledge gap. For example, terrestrial laser scanners (TLSs) can produce snow depth measurements at fine spatial resolutions over large areas. Repeat data acquisitions between precipitation events also allow for depth quantification atop an interface, as well as precise estimations of release volume and runout area after avalanche failure. Here, we explore the benefits of TLS-derived documentation from a large avalanche event by examining the development and release of a glide avalanche that occurred in Glacier National Park, Montana, USA, during the spring of 2022. Three sets of lidar point cloud data were acquired in the Haystack Creek drainage, focused on a well-known glide avalanche site. Lidar scans were collected after glide cracks emerged but prior to glide failure, and shortly (~ 1.5 days) after avalanche occurrence, in addition to a snow-free scan later in the year. With this temporal dataset, we were able to account for and visualize the spatial variability of snow depth across the avalanche start zone, such that we could precisely calculate the release volume (18674 m3) and average start zone depth (3.3 m) of the avalanche. Furthermore, TLS data were used to map the extent of the runout area and entrainment zone.

Montana

Testing a small UAS for mapping artisanal diamond mining sites in Africa

Remote sensing technology is advancing at an unprecedented rate. At the forefront of the new technological developments are unmanned aircraft systems (UAS). The advent of small, lightweight, low-cost, and user-friendly UAS is greatly expanding the potential applications of remote sensing technology and improving the set of tools available to researchers seeking to map and monitor terrain from above. In this article, we explore the applications of a small UAS for mapping informal diamond mining sites in Africa. We found that this technology provides aerial imagery of unparalleled resolution in a data-sparse, difficult to access, and remote terrain.

Photogrammetric Engineering and Remote Sensing

Radiometric, geometric, and image quality assessment of ALOS AVNIR-2 and PRISM sensors

The Advanced Land Observing Satellite (ALOS) was launched on January 24, 2006, by a Japan Aerospace Exploration Agency (JAXA) H-IIA launcher. It carries three remote-sensing sensors: 1) the Advanced Visible and Near-Infrared Radiometer type 2 (AVNIR-2); 2) the Panchromatic Remote-Sensing Instrument for Stereo Mapping (PRISM); and 3) the Phased-Array type L-band Synthetic Aperture Radar (PALSAR). Within the framework of ALOS Data European Node, as part of the European Space Agency (ESA), the European Space Research Institute worked alongside JAXA to provide contributions to the ALOS commissioning phase plan. This paper summarizes the strategy that was adopted by ESA to define and implement a data verification plan for missions operated by external agencies; these missions are classified by the ESA as third-party missions. The ESA was supported in the design and execution of this plan by GAEL Consultant. The verification of ALOS optical data from PRISM and AVNIR-2 sensors was initiated 4 months after satellite launch, and a team of principal investigators assembled to provide technical expertise. This paper includes a description of the verification plan and summarizes the methodologies that were used for radiometric, geometric, and image quality assessment. The successful completion of the commissioning phase has led to the sensors being declared fit for operations. The consolidated measurements indicate that the radiometric calibration of the AVNIR-2 sensor is stable and agrees with the Landsat-7 Enhanced Thematic Mapper Plus and the Envisat MEdium-Resolution Imaging Spectrometer calibration. The geometrical accuracy of PRISM and AVNIR-2 products improved significantly and remains under control. The PRISM modulation transfer function is monitored for improved characterization.

IEEE Transactions on Geoscience and Remote Sensing

Using the California Waterfowl Tracker to assess proximity of waterfowl to commercial poultry in the Central Valley of California

Migratory waterfowl are the primary reservoir of avian influenza viruses (AIV) which can be spread to commercial poultry. Surveillance efforts that track the location and abundance of wild waterfowl and link those data to inform assessments of risk and sampling for AIV currently do not exist. To assist surveillance and minimize poultry exposure to AIV, here we explored the utility of remotely sensed MODerate Resolution Imaging Spectroradiometer (MODIS) satellite imagery in combination with land-based climate measurements (e.g., temperature and precipitation) to predict waterfowl location and abundance in near real-time in the California Central Valley (CCV), where both wild waterfowl and domestic poultry are densely located. Specifically, remotely collected MODIS and climate data were integrated into a previously developed Boosted Regression Tree (BRT) model to predict and visualize waterfowl distributions across the CCV. Daily model-based predictions are publicly available during the winter as part of the dynamic California Waterfowl Tracker (CWT) web-app hosted on the University of California’s Cooperative Extension webpage. In this study, we analyzed 52 days of model predictions and produced daily spatio-temporal maps of waterfowl concentrations near the 605 commercial poultry farms in the CCV during January and February of 2019. Exposure of each poultry farm to waterfowl during each day was classified as “high”, “medium”, “low”, or “none” depending on the density of waterfowl within 4 km of a farm. Results indicated that farms were at substantially greater risk of “exposure” in January, when CCV waterfowl populations peak, than in February. For example, during January, 33% (199/605) of the farms were exposed ≥ 1 day to “high” waterfowl density versus 19% (115/605) of the farms in February. In addition to demonstrating the overall variability of waterfowl location and density, these data demonstrate how remote sensing can be used to better triage AIV surveillance and biosecurity efforts via the utilization of a functional web-app based tool. The ability to leverage remote sensing is an integral advancement toward improving AIV surveillance in waterfowl in close proximity to commercial poultry. Expansion of these types of remote sensing methods linked to a user-friendly web-tool could be further developed across the continental U.S. The BRT model incorporated into the CWT reflects a first attempt to give an accurate representation of waterfowl distribution and density relative to commercial poultry.

California

Cross-sensor comparisons between Landsat 5 TM and IRS-P6 AWiFS and disturbance detection using integrated Landsat and AWiFS time-series images

Routine acquisition of Landsat 5 Thematic Mapper (TM) data was discontinued recently and Landsat 7 Enhanced Thematic Mapper Plus (ETM+) has an ongoing problem with the scan line corrector (SLC), thereby creating spatial gaps when covering images obtained during the process. Since temporal and spatial discontinuities of Landsat data are now imminent, it is therefore important to investigate other potential satellite data that can be used to replace Landsat data. We thus cross-compared two near-simultaneous images obtained from Landsat 5 TM and the Indian Remote Sensing (IRS)-P6 Advanced Wide Field Sensor (AWiFS), both captured on 29 May 2007 over Los Angeles, CA. TM and AWiFS reflectances were compared for the green, red, near-infrared (NIR), and shortwave infrared (SWIR) bands, as well as the normalized difference vegetation index (NDVI) based on manually selected polygons in homogeneous areas. All R 2 values of linear regressions were found to be higher than 0.99. The temporally invariant cluster (TIC) method was used to calculate the NDVI correlation between the TM and AWiFS images. The NDVI regression line derived from selected polygons passed through several invariant cluster centres of the TIC density maps and demonstrated that both the scene-dependent polygon regression method and TIC method can generate accurate radiometric normalization. A scene-independent normalization method was also used to normalize the AWiFS data. Image agreement assessment demonstrated that the scene-dependent normalization using homogeneous polygons provided slightly higher accuracy values than those obtained by the scene-independent method. Finally, the non-normalized and relatively normalized ‘Landsat-like’ AWiFS 2007 images were integrated into 1984 to 2010 Landsat time-series stacks (LTSS) for disturbance detection using the Vegetation Change Tracker (VCT) model. Both scene-dependent and scene-independent normalized AWiFS data sets could generate disturbance maps similar to what were generated using the LTSS data set, and their kappa coefficients were higher than 0.97. These results indicate that AWiFS can be used instead of Landsat data to detect multitemporal disturbance in the event of Landsat data discontinuity.

International Journal of Remote Sensing

On-demand global Landsat evapotranspiration product: Development, evaluation, and dissemination

Global actual evapotranspiration (ET) is one of the essential climate variables needed to understand and manage the relationships among food, energy, and water resources. The U.S. Geological Survey Earth Resources Observation and Science (EROS) Center launched a provisional ET product in 2020, offering on-demand, field-scale global coverage derived from Landsat data through the EROS Science Processing Architecture (ESPA) platform. The ESPA interface provides ET data for cloud-free Landsat overpasses starting in 1982 with Landsat 4 through the current Landsat 9. The ET data are delivered as a Provisional Level-3 Science product created using the Operational Simplified Surface Energy Balance (SSEBop) model. Landsat surface temperature and reference ET are the main model drivers along with vegetation index and net radiation for model parameterization. A large volume of Landsat-based ET orders (e.g., over 1,200,000 images from June 2020 through December 2025) around the world indicate increasing awareness and application of the ET data. The ESPA platform enables land and water resource managers and researchers to access a first-order ET product without requiring advanced knowledge of remote sensing technology or evapotranspiration modeling. We present the methodology and workflow of the on-demand Landsat ET product and its performance evaluations over diverse hydro-climatic settings. The product can help estimate field-scale consumptive water use and thus quickly and consistently assess historical water use, allocation, and budget to inform water management under changing environments. Future ET data aggregated to monthly and seasonal time scales are expected to enhance integration with decision-making tools and procedures.

Remote Sensing of Environment

Demography with drones: Detecting growth and survival of shrubs with unoccupied aerial systems

Large-scale disturbances, such as megafires, motivate restoration at equally large extents. Measuring the survival and growth of individual plants plays a key role in current efforts to monitor restoration success. However, the scale of modern restoration (e.g., >10,000 ha) challenges measurements of demographic rates with field data. In this study, we demonstrate how unoccupied aerial system (UAS) flights can provide an efficient solution to the tradeoff of precision and spatial extent in detecting demographic rates from the air. We flew two, sequential UAS flights at two sagebrush ( Artemisia tridentata ) common gardens to measure the survival and growth of individual plants. The accuracy of Bayesian-optimized segmentation of individual shrub canopies was high (73–95%, depending on the year and site), and remotely sensed survival estimates were within 10% of ground-truthed survival censuses. Stand age structure affected remotely sensed estimates of growth; growth was overestimated relative to field-based estimates by 57% in the first garden with older stands, but agreement was high in the second garden with younger stands. Further, younger stands (similar to those just after disturbance) with shorter, smaller plants were sometimes confused with other shrub species and bunchgrasses, demonstrating a need for integrating spectral classification approaches that are increasingly available on affordable UAS platforms. The older stand had several merged canopies, which led to an underestimation of abundance but did not bias remotely sensed survival estimates. Advances in segmentation and UAS structure from motion photogrammetry will enable demographic rate measurements at management-relevant extents.

Restoration Ecology

The U.S. Geological Survey Land Remote Sensing Program

In 2002, the U. S. Geological Survey (USGS) launched a program to enhance the acquisition, preservation, and use of remotely sensed data for USGS science programs, as well as for those of cooperators and customers. Remotely sensed data are fundamental tools for studying the Earth's land surface, including coastal and near-shore environments. For many decades, the USGS has been a leader in providing remotely sensed data to the national and international communities. Acting on its historical topographic mapping mission, the USGS has archived and distributed aerial photographs of the United States for more than half a century. Since 1972, the USGS has acquired, processed, archived, and distributed Landsat and other satellite and airborne remotely sensed data products to users worldwide. Today, the USGS operates and manages the Landsats 5 and 7 missions and cooperates with the National Aeronautics and Space Administration (NASA) to define and implement future satellite missions that will continue and expand the collection of moderate-resolution remotely sensed data. In addition to being a provider of remotely sensed data, the USGS is a user of these data and related remote sensing technology. These data are used in natural resource evaluations for energy and minerals, coastal environmental surveys, assessments of natural hazards (earthquakes, volcanoes, and landslides), biological surveys and investigations, water resources status and trends analyses and studies, and geographic and cartographic applications, such as wildfire detection and tracking and as a source of information for The National Map. The program furthers these distinct but related roles by leading the USGS activities in providing remotely sensed data while advancing applications of such data for USGS programs and a wider user community.

Fact Sheet

Earth Observing-1 Extended Mission

From its beginning in November 2000, the NASA Earth Observing-1 (EO-1) mission demonstrated the feasibility and performance of a dozen innovative sensor, spacecraft, and operational technologies. The 1-year mission tested a variety of technologies, some of which may be included on the planned 2007 Landsat Data Continuity Mission. Onboard the spacecraft are two land remote sensing instruments: the Advanced Land Imager (ALI), which acquires data in spectral bands and at resolutions similar to Landsat, and Hyperion, which acquires data in 220 10-nanometer-wide bands covering the visible, near-, and shortwave-infrared bands. Recognizing the remarkable performance of the satellite's instruments and the exceptional value of the data, the U.S. Geological Survey (USGS) and NASA agreed in December 2001 to share responsibility for operating EO-1 on a cost-reimbursable basis as long as customer sales are sufficient to recover flight and ground operations costs. The EO-1 extended mission operates within constraints imposed by its technology-pioneering origins, but it also provides unique and valuable capabilities. The spacecraft can acquire a target scene three times in a 16-day period. The ALI instrument has additional spectral coverage and greater radiometric dynamic range compared with the sensors on Landsat 7. Hyperion is the first civilian spaceborne hyperspectral imager. As of January 2003, more than 5,000 scenes had been acquired, indexed, and archived.

Fact Sheet

Earth Observing-1 Extended Mission

Since November 2000, the National Aeronautics and Space Administration (NASA) Earth Observing-1 (EO-1) mission has demonstrated the capabilities of a dozen spacecraft sensor and communication innovations. Onboard the EO-1 spacecraft are two land remote sensing instruments. The Advanced Land Imager (ALI) acquires data in spectral bands and at resolutions similar to Landsat. The Hyperion instrument, which is the first civilian spaceborne hyperspectral imager, acquires data in 220 10-nanometer bands covering the visible, near, and shortwave-infrared bands. The initial one-year technology demonstration phase of the mission included a detailed comparison of ALI with the Landsat Enhanced Thematic Mapper Plus (ETM+) instrument. Specifications for the Operational Land Imager (OLI), the planned successor to ETM+, were formulated in part from performance characteristics of ALI. Recognizing the remarkable performance of the satellite's instruments and the exceptional value of the data, the U.S. Geological Survey (USGS) and NASA agreed in December 2001 to share responsibility for operating EO-1. The extended mission continues, on a cost-reimbursable basis, as long as customer sales fully recover flight and ground operations costs. As of May 2005, more than 17,800 scenes from each instrument have been acquired, indexed, archived, and made available to the public.

Fact Sheet

U.S. Geological Survey Benchmark Glacier Project

The ​U.S. Geological Survey Benchmark Glacier Project combines decades of direct glaciological data with remote sensing data to advance the quantitative understanding of glacier-climate interactions. The global loss of glaciers, and consequent implications for water resources, sea level rise, and ecosystem function underscores the importance of U.S. Geological Survey glaciology research to facilitate adaptive strategies.

Fact Sheet

A comparison of consumptive-use estimates derived from the simplified surface energy balance approach and indirect reporting methods

Recent advances in remote-sensing technology and Simplified Surface Energy Balance (SSEB) methods can provide accurate and repeatable estimates of evapotranspiration (ET) when used with satellite observations of irrigated lands. Estimates of ET are generally considered equivalent to consumptive use (CU) because they represent the part of applied irrigation water that is evaporated, transpired, or otherwise not available for immediate reuse. The U.S. Geological Survey compared ET estimates from SSEB methods to CU data collected for 1995 using indirect methods as part of the National Water Use Information Program (NWUIP). Ten-year (2000-2009) average ET estimates from SSEB methods were derived using Moderate Resolution Imaging Spectroradiometer (MODIS) 1-kilometer satellite land surface temperature and gridded weather datasets from the Global Data Assimilation System (GDAS). County-level CU estimates for 1995 were assembled and referenced to 1-kilometer grid cells to synchronize with the SSEB ET estimates. Both datasets were seasonally and spatially weighted to represent the irrigation season (June-September) and those lands that were identified in the county as irrigated. A strong relation (R2 greater than 0.7) was determined between NWUIP CU and SSEB ET data. Regionally, the relation is stronger in arid western states than in humid eastern states, and positive and negative biases are both present at state-level comparisons. SSEB ET estimates can play a major role in monitoring and updating county-based CU estimates by providing a quick and cost-effective method to detect major year-to-year changes at county levels, as well as providing a means to disaggregate county-based ET estimates to sub-county levels. More research is needed to identify the causes for differences in state-based relations.

Scientific Investigations Report

Implementation of the CCDC algorithm to produce the LCMAP Collection 1.0 annual land surface change product

The increasing availability of high-quality remote sensing data and advanced technologies have spurred land cover mapping to characterize land change from local to global scales. However, most land change datasets either span multiple decades at a local scale or cover limited time over a larger geographic extent. Here, we present a new land cover and land surface change dataset created by the Land Change Monitoring, Assessment, and Projection (LCMAP) program over the conterminous United States (CONUS). The LCMAP land cover change dataset consists of annual land cover and land cover change products over the period 1985-2017 at 30-meter resolution using Landsat and other ancillary data via the Continuous Change Detection and Classification (CCDC) algorithm. In this paper, we describe our novel approach to implement the CCDC algorithm to produce the LCMAP product suite composed of five land cover and five land surface change related products. The LCMAP land cover products were validated using a collection of ~ 25,000 reference samples collected independently across CONUS. The overall agreement for all years of the LCMAP primary land cover product reached 82.5%. The LCMAP products are produced through the LCMAP Information Warehouse and Data Store (IW+DS) and Shared Mesos Cluster systems that can process, store, and deliver all datasets for public access. To our knowledge, this is the first set of published 30m annual land cover and land cover change datasets that span from the 1980s to the present for the United States. The LCMAP product suite provides useful information for land resource management and facilitates studies to improve the understanding of terrestrial ecosystems and the complex dynamics of the Earth system. The LCMAP system could be implemented to produce global land change products in the future.

Earth System Science Data

Scientific developments ISFD3

Highlights, trends, and consensus from the 63 papers submitted to the Scientific Developments theme of the Third International Symposium on Flood Defence (ISFD) are presented. Realizing that absolute protection against flooding can never be guaranteed, trends in flood management have shifted: (1) from flood protection to flood-risk management, (2) from reinforcing structural protection to lowering flood levels, and (3) to sustainable management through integrated problem solving. Improved understanding of watershed responses, climate changes, applications of GIS and remote-sensing technologies, and advanced analytical tools appeared to be the driving forces for renewing flood-risk management strategies. Technical competence in integrating analytical tools to form the basin wide management systems are demonstrated by several large, transnation models. However, analyses from social-economic-environmental points of view are found lag in general. ?? 2006 Taylor & Francis Group.

Conference Paper

Understanding abundances and behaviors of shorebirds in coastal Louisiana

Barrier islands provide resources and ecological services that are integral to economic and environmental interests, such as protection of coastal infrastructure and provision of wildlife habitat. Over time, barrier islands may become eroded and experience land loss, which can require management actions to restore island integrity. Barrier island restoration can create or modify habitats, which can impact the organisms depending on them. Our objective was to understand how the abundance and behaviors of a suite of shorebird species responded to restoration and habitat factors at two restored sites in coastal Louisiana (USA). For five focal species, we used abundance from the breeding and non-breeding seasons as well as breeding, foraging, and maintenance behaviors as response variables in boosted regression tree models to determine the importance of various geospatial and remotely sensed predictor variables related to restoration. Across sites and species, remotely sensed variables, particularly a brightness index, tended to be more important than restoration phases as predictors of bird abundance and behavior. Our results suggest that sediment composition, moisture, and vegetative cover are related to shorebird coastal habitat selection, although the direction and strength of relationships differ among these variables and our focal species. Tying these remote sensing metrics to restoration design and management actions can help land managers better understand factors that attract and benefit birds. Additional research can advance understanding in how remote sensing can be used to monitor the availability of functional habitats for shorebirds.

BioRxiv

Ultraviolet and visible remote sensing of volcanic gases

As magma rises in volcanic systems, volatile species exsolve from the silicate melt and are emitted as gases into the atmosphere. Measuring the magnitude and composition of gas emissions from volcanoes provides insights into processes occurring deep within the Earth and helps constrain the impact of volcanic degassing on atmospheric chemistry. Optical remote sensing techniques allow volcanic gas emissions to be characterized without the need to access hazardous areas near active volcanic vents. This paper reviews the state of the art in ultraviolet and visible volcanic gas remote sensing from the ground, air, and space. Special attention is given to discussing the physics of atmospheric radiative transfer on which these techniques are based. The functionality and limitations of different remote sensing instruments are examined, making clear that the ideal choice of instrumentation will depend on the volcanic system to which it is applied and the sought measurement parameters. Common algorithms for determining trace gas column densities, gas burdens, and volcanic emission rates from measurements of spectral radiance are outlined and compared, showing how some algorithms attempt to model the physics of the measurement while others maximize sensitivity. Several examples demonstrate how remote sensing measurements continue to advance our understanding of volcanic systems and their impact on the atmosphere. Finally, a few promising directions of inquiry are suggested that could lead to improvements in remote sensing instrumentation and analysis techniques. By combining spectroscopic and imaging techniques, improving our understanding of atmospheric radiative transfer, expanding the suite of target gases, and increasing the coverage and frequency of observations, we stand to significantly improve our ability to detect and quantify volcanic gas emissions and gain new insights into important Earth-system processes.

Journal of Volcanology and Geothermal Research

Geographic techniques and recent applications of remote sensing to landscape-water quality studies

This article overviews recent advances in studies of landscape-water quality relationships using remote sensing techniques. With the increasing feasibility of using remotely-sensed data, landscape-water quality studies can now be more easily performed on regional, multi-state scales. The traditional method of relating land use and land cover to water quality has been extended to include landscape pattern and other landscape information derived from satellite data. Three items are focused on in this article: 1) the increasing recognition of the importance of larger-scale studies of regional water quality that require a landscape perspective; 2) the increasing importance of remotely sensed data, such as the imagery-derived normalized difference vegetation index (NDVI) and vegetation phenological metrics derived from time-series NDVI data; and 3) landscape pattern. In some studies, using landscape pattern metrics explained some of the variation in water quality not explained by land use/cover. However, in some other studies, the NDVI metrics were even more highly correlated to certain water quality parameters than either landscape pattern metrics or land use/cover proportions. Although studies relating landscape pattern metrics to water quality have had mixed results, this recent body of work applying these landscape measures and satellite-derived metrics to water quality analysis has demonstrated their potential usefulness in monitoring watershed conditions across large regions.

Water, Air, & Soil Pollution