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At least 289 records · Page 16Linked to original sources
USGS2015

EAARL-B coastal topography: Chandeleur Islands, Louisiana, 2012: seamless (bare earth and submerged)

These remotely sensed, geographically referenced elevation measurements of light detection and ranging ( lidar )-derived seamless (bare-earth and submerged) topography datasets were produced by the U.S. Geological Survey ( USGS ), St . Petersburg Coastal and Marine Science Center, St . Petersburg, Florida. This project provides datasets acquired on August 7 and 8, 2012, for a portion of the Chandeleur Islands, Louisiana. An innovative airborne lidar system, known as the second-generation Experimental Advanced Airborne Research Lidar ( EAARL -B), was used during data acquisition. The EAARL -B system is a raster-scanning, waveform-resolving, green-wavelength (532-nanometers) lidar designed to map nearshore bathymetry, topography, and vegetation structure simultaneously. For more information about similar projects, please visit the Lidar for Science and Resource Management Web site.

Louisiana↗
USGS1993

Compositing multitemporal remote sensing data sets

To eliminate cloud and atmosphere-affected pixels, the compositing of multi temporal remote sensing data sets is done by selecting the maximum vale of the normalized different vegetation index (NDVI) within a compositing period. The NDVI classifier, however, is strongly affected by surface type and anisotropic properties, sensor viewing geometries, and atmospheric conditions. Consequently, the composited, multi temporal, remote sensing data contain substantial noise from these external conditions. Consequently, the composited, multi temporal, remote sensing data contain substantial noise from these external effects. To improve the accuracy of compositing products, two key approaches can be taken: one is to refine the compositing classifier (NDVI) and the other is to improve existing compositing algorithms. In this project, an alternative classifier was developed and an alternative pixel selection criterion was proposed for compositing. The new classifier and the alternative compositing algorithm were applied to an advanced very high resolution radiometer data set of different biome types in the United States. The results were compared with the maximum value compositing and the best index slope extraction algorithms. The new approaches greatly reduced the high frequency noises related to the external factors and repainted more reliable data. The results suggest that the geometric-optical canopy properties of specific biomes may be needed in compositing. Limitations of the new approaches include the dependency of pixel selection on the length of the composite period and data discontinuity.

Pecora 12 Symposium↗
USGS2020

Integrating airborne remote sensing and field campaigns for ecology and Earth system science

In recent years, the availability of airborne imaging spectroscopy (hyperspectral) data has expanded dramatically. The high spatial and spectral resolution of these data uniquely enable spatially explicit ecological studies including species mapping, assessment of drought mortality and foliar trait distributions. However, we have barely begun to unlock the potential of these data to use direct mapping of vegetation characteristics to infer subsurface properties of the critical zone. To assess their utility for Earth systems research, imaging spectroscopy data acquisitions require integration with large, coincident ground‐based datasets collected by experts in ecology and environmental and Earth science. Without coordinated, well‐planned field campaigns, potential knowledge leveraged from advanced airborne data collections could be lost. Despite the growing importance of this field, documented methods to couple such a wide variety of disciplines remain sparse. We coordinated the first National Ecological Observatory Network Airborne Observation Platform (AOP) survey performed outside of their core sites, which took place in the Upper East River watershed, Colorado. Extensive planning for sample tracking and organization allowed field and flight teams to update the ground‐based sampling strategy daily. This enabled collection of an extensive set of physical samples to support a wide range of ecological, microbiological, biogeochemical and hydrological studies. We present a framework for integrating airborne and field campaigns to obtain high‐quality data for foliar trait prediction and document an archive of coincident physical samples collected to support a systems approach to ecological research in the critical zone. This detailed methodological account provides an example of how a multi‐disciplinary and multi‐institutional team can coordinate to maximize knowledge gained from an airborne survey, an approach that could be extended to other studies. The coordination of imaging spectroscopy surveys with appropriately timed and extensive field surveys, along with high‐quality processing of these data, presents a unique opportunity to reveal new insights into the structure and dynamics of the critical zone. To our knowledge, this level of co‐aligned sampling has never been undertaken in tandem with AOP surveys and subsequent studies utilizing this archive will shed considerable light on the breadth of applications for which imaging spectroscopy data can be leveraged.

Colorado↗
USGS2013

Remote sensing survey of Chinese tallow tree in the Toledo Bend Reservoir area, Louisiana and Texas

We applied Hyperion sensor satellite data acquired by the National Aeronautics and Space Administration’s Earth Observing-1 (EO-1) satellite in conjunction with reconnaissance surveys to map the occurrences of the invasive Chinese tallow tree (Triadica sebifera) in the Toledo Bend Reservoir study area of northwestern Louisiana and northeastern Texas. The rationale for application of high spectral resolution EO-1 Hyperion data was based on the successful use of Hyperion data in the mapping of Chinese tallow tree in southwestern Louisiana in 2005. In contrast to the single Hyperion image used in the 2005 project, more than 20 EO-1 Hyperion and Advanced Land Imager (ALI) images of the study area were collected in 2009 and 2010 during the fall senescence when Chinese tallow tree leaves turn red. Atmospherically corrected reflectance spectra of Hyperion imagery collected at ground and aerial observation locations provided the input datasets used in the program for spectral discrimination analysis. Discrimination analysis was used to identify spectral indicator sets to best explain variance contained in the input databases. The expectation was that at least one set of Hyperion-based indicator spectra would uniquely identify occurrences of red-leaf Chinese tallow tree; however, no combination of Hyperion-based reflectance datasets produced a unique identifier. The inability to discover a unique spectral indicator resulted primarily from relatively sparse coverage by red-leaf Chinese tallow tree within the study area (percentage of coverage was less than 5 percent per 30- by 30-meter Hyperion pixel). To enhance the performance of the spectral discrimination analysis, leaf and canopy spectra of Chinese tallow tree were added to the input datasets to guide the indicator selection. In addition, input databases were segregated by land class obtained from an ALI-based landcover classification in order to reduce the input variance and to promote spectral discrimination of red-leaf Chinese tallow tree. Although no unique spectral identifier for red-leaf Chinese tallow tree was uncovered with these enhanced methods, in some cases predicted spatial patterns throughout the Hyperion images revealed alignment with vegetation associations within each land class that was often observed to contain Chinese tallow trees. These instances were associated particularly with the addition of helicopter-based spectra to the input databases. It was attempted to extend such predictions of likely occurrences of Chinese tallow tree by mapping six of the nine Hyperion swaths and four of the nine land classes, but this attempt produced uncertain results that could not be fully evaluated for accuracy. Even though the final mapping showed promise in identifying likely Chinese tallow tree occurrences, the low percentage of occurrences hindered mapping performance and validation. Results of the mapping suggested that successful detection of Chinese tallow tree in the study area would require a spectral sensor similar to the Hyperion but with a higher ground-level spatial resolution. Although the Hyperion-based spectral mapping did not provide the desired results, the associated field (ground and aerial) surveys did provide for a qualitative assessment of the overall Chinese tallow tree distribution within the study area. Ground and aerial surveys suggested that Chinese tallow tree occurrences were uncommon and were without an observed pattern in relation to proximity to the Toledo Bend Reservoir. Although uncommon and scattered, Chinese tallow trees and shrubs most commonly existed along forest edges, water edges, and fence lines, probably most in line with seed dispersal by birds. Chinese tallow trees were observed to be more densely dispersed within some scrublands and grasslands than were observed in pine, hardwood, and mixed forests.

Louisiana;Texas↗
USGS2007

Ground-water recharge in the arid and semiarid southwestern United States

Ground-water recharge in the arid and semiarid southwestern United States results from the complex interplay of climate, geology, and vegetation across widely ranging spatial and temporal scales. Present-day recharge tends to be narrowly focused in time and space. Widespread water-table declines accompanied agricultural development during the twentieth century, demonstrating that sustainable ground-water supplies are not guaranteed when part of the extracted resource represents paleorecharge. Climatic controls on ground-water recharge range from seasonal cycles of summer monsoonal and winter frontal storms to multimillennial cycles of glacial and interglacial periods. Precipitation patterns reflect global-scale interactions among the oceans, atmosphere, and continents. Large-scale climatic influences associated with El Niño and Pacific Decadal Oscillations strongly, but irregularly, control weather in the study area, so that year-to-year variations in precipitation and ground-water recharge are large and difficult to predict. Proxy data indicate geologically recent periods of naturally occurring multidecadal droughts unlike any in the modern instrumental record. Any anthropogenically induced climate change will likely reduce ground-water recharge through diminished snowpack at higher elevations. Future changes in El Niño and monsoonal patterns, both crucial to precipitation in the study area, are highly uncertain in current models. Current land-use modifications influence ground-water recharge through vegetation, irrigation, and impermeable area. High mountain ranges bounding the study area—the San Bernadino Mountains and Sierra Nevada to the west, and the Wasatch and southern Colorado Rocky Mountains to the east—provide external geologic controls on ground-water recharge. Internal geologic controls stem from tectonic processes that led to numerous, variably connected alluvial-filled basins, exposure of extensive Paleozoic aquifers in mountainous recharge areas, and distinct modes of recharge in the Colorado Plateau and Basin and Range subregions. The chapters in this professional paper present (first) an overview of climatic and hydrogeologic framework (chapter A), followed by a regional analysis of ground-water recharge across the entire study area (chapter B). These are followed by an overview of site-specific case studies representing different subareas of the geographically diverse arid and semiarid southwestern United States (chapter C); the case studies themselves follow in chapters D–K. The regional analysis includes detailed hydrologic modeling within the framework of a high-resolution geographic-information system (GIS). Results from the regional analysis are used to explore both the distribution of ground-water recharge for mean climatic conditions as well as the influence of two climatic patterns—the El Niño-Southern Oscillation and Pacific Decadal Oscillation—that impart a high degree of variability to the hydrologic cycle. Individual case studies employ a variety of geophysical and geochemical techniques to investigate recharge processes and relate the processes to local geologic and climatic conditions. All of the case studies made use of naturally occurring tracers to quantify recharge. Thermal and geophysical techniques that were developed in the course of the studies are presented in appendices. The quantification of ground-water recharge in arid settings is inherently difficult due to the generally low amount of recharge, its spatially and temporally spotty nature, and the absence of techniques for directly measuring fluxes entering the saturated zone from the unsaturated zone. Deep water tables in arid alluvial basins correspond to thick unsaturated zones that produce up to millennial time lags between changes in hydrologic conditions at the land surface and subsequent changes in recharge to underlying ground water. Recent advances in physical, chemical, isotopic, and modeling techniques have fostered new types of recharge assessments. Chemical and isotopic techniques include an increasing variety of environmental tracers that are useful and robust. Physically based techniques include the use of heat as a tracer and computationally intensive geophysical imaging tools for characterizing hydrologic conditions in the unsaturated zone. Modeling-based techniques include spatially distributed water-budget computations using high-resolution remotely sensed and ground-based geographic data. Application of these techniques to arid and semiarid settings in the southwestern United States reveals distinct patterns of recharge corresponding to geologic setting, climatic and vegetative history, and land use. Analysis of recharge patterns shows that large expanses of alluvial basin floors are drying out under current climatic conditions, with little to no recharge to underlying ground water. Ground-water recharge occurs mainly beneath upland catchments in which thin soils overlie permeable bedrock, ephemeral channels in which flow may average only several hours per year, and active agricultural areas. The chapters in this professional paper represent a coordinated attempt to develop a better understanding of one of the Nation's most critical yet difficult-to-quantify renewable resources.

Professional Paper↗
USGS1981

Objectives, accomplishments, and future plans of IGCP project 143, remote sensing and mineral exploration

The International Geological Correlation Programme (IGCP) is a worldwide cooperative research programme that began in 1974 under the auspices of the International Union of Geological Sciences. Because of the global availability of Earth resources data collected by satellites and the great interest among geologists in taking advantage of these new sources of information, a project was begun in 1976 to improve the rate of technology transfer in the field of remote-sensing exploration for energy and mineral resources. Conducting joint workshops in cooperation with COSPAR has been an important part of this project. It is to be hoped the project will improve our capability to explore, identify, and develop new resources to meet the burgeoning demands of society. ?? 1981.

Advances in Space Research↗
USGS2020

Volcanological applications of unoccupied aircraft systems (UAS): Developments, strategies, and future challenges

Unoccupied aircraft systems (UAS) are developing into fundamental tools for tackling the grand challenges in volcanology; here, we review the systems used and their diverse applications. UAS can typically provide image and topographic data at two orders of magnitude better spatial resolution than space-based remote sensing, and close-range observations at temporal resolutions down to those of video frame rates. Responsive deployments facilitate dense time-series measurements, unique opportunities for geophysical surveys, sample collection from hostile environments such as volcanic plumes and crater lakes, and emergency deployment of ground-based sensors (and robots) into hazardous regions. UAS have already been used to support hazard management and decision-makers during eruptive crises. As technologies advance, increased system capabilities, autonomy and availability, supported by more diverse and lighter-weight sensors, will offer unparalleled potential for hazard monitoring. UAS are expected to provide opportunities for pivotal advances in our understanding of complex physical and chemical volcanic processes.

Volcanica↗
USGS2021

Mangroves and people: Impacts and interactions

Mangroves have long been associated with human populations, as coastal communities rely on the various ecosystem services that mangroves provide. However, human degradation and destruction of mangrove forests is common, despite and because of our reliance on them as valuable ecosystems. Mangrove research and management must elucidate and reconcile these conflicts to maintain mangrove forests and the services that humans depend on. To better understand the complex dynamics, interactions and relationships that exist between mangroves and coastal communities, the 5th Mangrove Macrobenthos and Management (MMM5) conference was held in Singapore in July 2019, with the theme “ Mangroves and People: Impacts and Interactions”. This theme was chosen because Southeast Asia is the epicentre of ongoing mangrove loss, and a large number of coastal communities in the region rely on the ecosystem services that mangroves provide. The 32 papers published in this Special Issue represent the breadth of mangrove research presented at MMM5, including topics in faunal biology, ecosystem ecology, genetics, physical geography, biogeochemistry, remote sensing and the social sciences. The articles are characterized under the following topics: 1) mangrove ecosystem functioning; 2) range expansion of mangroves; 3) ecosystem services of mangroves; 4) anthropogenic and natural threats to mangroves; and 5) the management and social-ecology of mangroves. This Special Issue highlights the current state of the art of mangrove research and application, and describes a number of emerging new ideas and research opportunities that will continue to advance mangrove ecosystem science into the future.

Estuarine, Coastal and Shelf Science↗
USGS2010

EAARL coastal topography-western Florida, post-Hurricane Charley, 2004: seamless (bare earth and submerged.

Project Description These remotely sensed, geographically referenced elevation measurements of lidar-derived seamless (bare-earth and submerged) topography were produced as a collaborative effort between the U.S. Geological Survey (USGS), Coastal and Marine Geology Program (CMGP), St. Petersburg, FL, and the National Aeronautics and Space Administration (NASA), Wallops Flight Facility, VA. This project provides highly detailed and accurate datasets of a portion of the western Florida coastline beachface, acquired post-Hurricane Charley on August 17 and 18, 2004. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative airborne lidar instrument originally developed at the NASA Wallops Flight Facility, and known as the Experimental Advanced Airborne Research Lidar (EAARL), was used during data acquisition. The EAARL system is a raster-scanning, waveform-resolving, green-wavelength (532-nanometer) lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive lidar, a down-looking red-green-blue (RGB) digital camera, a high-resolution multispectral color infrared (CIR) camera, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for sub-meter georeferencing of each laser sample. The nominal EAARL platform is a twin-engine Cessna 310 aircraft, but the instrument may be deployed on a range of light aircraft. A single pilot, a lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the EAARL system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of lidar data in an interactive or batch mode. Modules for presurvey flight-line definition, flight-path plotting, lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is used routinely to create maps that represent submerged or sub-aerial topography. Specialized filtering algorithms have been implemented to determine the 'bare earth' under vegetation. For more information about similar projects, please visit the Decision Support for Coastal Science and Management website. Selected References Brock, J.C., Wright, C.W., Sallenger, A.H., Krabill, W.B., and Swift, R.N., 2002, Basis and methods of NASA airborne topographic mapper Lidar surveys for coastal studies: Journal of Coastal Research, v. 18, no. 1, p. 1-13. Crane, Michael, Clayton, Tonya, Raabe, Ellen, Stoker, Jason, Handley, Larry, Bawden, Gerald, Morgan, Karen, and Queija, Vivian, 2004, Report of the U.S. Geological Survey Lidar workshop sponsored by the Land Remote Sensing Program and held in St. Petersburg, FL, November 2002: U.S. Geological Survey Open-File Report 2004-1456, 72 p. Nayegandhi, Amar, Brock, J.C., and Wright, C.W., 2009, Small-footprint, waveform-resolving Lidar estimation of submerged and sub-canopy topography in coastal environments: International Journal of Remote Sensing, v. 30, no. 4, p. 861-878. Sallenger, A.H., Wright, C.W., and Lillycrop, Jeff, 2005, Coastal impacts of the 2004 hurricanes measured with airborne Lidar; initial results: Shore and Beach, v. 73, nos. 2-3, p. 10-14. Resources Included Readme.txt File

Data Series↗
USGS2024

Novel approach for ranking DEMs: Copernicus DEM improves one arc second open global topography

We present a practical approach to intercompare a range of candidate digital elevation models (DEMs) based on predefined criteria and a statistically sound ranking approach. The presented approach integrates the randomized complete block design (RCBD) into a novel framework for DEM comparison. The method presented provides a flexible, statistically sound, and customizable tool for evaluating the quality of any raster—in this case, a DEM—by means of a ranking approach, which takes into account a confidence level and can use both quantitative and qualitative criteria. The users can design their own criteria for the quality evaluation in relation to their specific needs. The application of the RCBD method to rank six 1′′ global DEMs, considering a wide set of study sites, covering different morphological and land cover settings, highlights the potentialities of the approach. We used a suite of criteria relating to the differences in the elevation, slope, and roughness distributions compared to reference DEMs aggregated from 1- to 5-m light detection and ranging (LiDAR)-derived DEMs. Results confirmed the significant superiority of Copernicus DEM (CopDEM) 1′′ and its derivative forests and buildings removed DEM (FABDEM) as the overall best 1′′ global DEMs. They are slightly better than Advanced Land Observing Satellite (ALOS) and clearly outperform NASADEM and SRTM, which are, in turn, much better than advanced spaceborne thermal emission and reflection radiometer (ASTER).

IEEE Transactions on Geoscience and Remote Sensing↗
USGS2013

The environmental-data automated track annotation (Env-DATA) system: linking animal tracks with environmental data

The movement of animals is strongly influenced by external factors in their surrounding environment such as weather, habitat types, and human land use. With advances in positioning and sensor technologies, it is now possible to capture animal locations at high spatial and temporal granularities. Likewise, scientists have an increasing access to large volumes of environmental data. Environmental data are heterogeneous in source and format, and are usually obtained at different spatiotemporal scales than movement data. Indeed, there remain scientific and technical challenges in developing linkages between the growing collections of animal movement data and the large repositories of heterogeneous remote sensing observations, as well as in the developments of new statistical and computational methods for the analysis of movement in its environmental context. These challenges include retrieval, indexing, efficient storage, data integration, and analytical techniques.

Movement Ecology↗
USGS1985

Remote sensing; a geophysical perspective

In this review of developments in the field of remote sensing from a geophysical perspective, the subject is limited to the electromagnetic spectrum from 0.4 mu m to 25 cm. Three broad energy categories are covered: solar reflected, thermal infrared, and microwave.The reflected solar region has been the most intensely studied. Photointerpretation of images from individual spectral bands or from color composites remains the most widely used method of analysis. New instrumentation and digital processing, based on analysis of laboratory and field spectra, provide significant advances that are beginning to be applied to resource exploration. Color compositing techniques have been effectively used to detect the characteristic spectral reflectance features of iron oxides and hydroxyl-bearing materials in satellite multispectral data for mapping areas of hydrothermal alteration. Airborne spectrometers can now detect individual spectral features of many minerals which are diagnostic of different stages of hydrothermal alteration. Evolution was from discrimination, based on empirical experience, to mineralogic identification and leading to quantification. Current developments also indicate new, promising extensions to vegetated terrains.Advances in thermal infrared studies are due to development of thermal models that permit mapping of physical property variations and to detection of spectral differences that provide important compositional information. Analysis techniques are still in their infancy, and thermal satellite data remain appropriate only for regional investigations.Microwave data have been acquired mainly with radar systems, which can provide very high resolution from space, but use of textural and slope information has had limited application. Long-wavelength radiation has been shown to penetrate dry materials, and this may be applicable in extremely arid regions.

Geophysics↗
USGS2007

EAARL submarine topography: Florida Keys National Marine Sanctuary

This Web site contains 46 Lidar-derived submarine topography maps and GIS files for the Florida Keys National Marine Sanctuary. These Lidar-derived submarine topographic maps were produced as a collaborative effort between the U.S. Geological Survey (USGS) Coastal and Marine Geology Program, FISC St. Petersburg, Florida, the National Oceanic and Atmospheric Administration (NOAA), Remote Sensing Division, the National Park Service (NPS) South Florida/Caribbean Network Inventory and Monitoring Program, and the National Aeronautics and Space Administration (NASA) Wallops Flight Facility. One objective of this research is to create techniques to survey coral reefs and barrier islands for the purposes of geomorphic change studies, habitat mapping, ecological monitoring, change detection, and event assessment. As part of this project, data from an innovative instrument under development at the NASA Wallops Flight Facility, the NASA Experimental Airborne Advanced Research Lidar (EAARL) are being used. This sensor has the potential to make significant contributions in this realm for measuring subaerial and submarine topography within cross-environment surveys. High spectral resolution, water-column correction, and low costs were found to be key factors in providing accurate and affordable imagery to coastal resource managers.

Florida↗
USGS2009

Comparison of ASTER- and AVIRIS-derived mineral and vegetation maps of the White Horse replacement alunite deposit and surrounding area, Marysvale volcanic field, Utah

This report presents and compares mineral and vegetation maps of parts of the Marysvale volcanic field in west-central Utah that were published in a recent paper describing the White Horse replacement alunite deposit. Detailed, field-verified maps of the deposit were produced from Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data acquired from a low-altitude Twin Otter turboprop airborne platform. Reconnaissance-level maps of surrounding areas including the central and northern Tushar Mountains, Pahvant Range, and portions of the Sevier Plateau to the east were produced from visible, near-infrared, and shortwave-infrared data acquired by the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) sensor carried aboard the Terra satellite platform. These maps are also compared to a previously published mineral map of the same area generated from AVIRIS data acquired from the high-altitude NASA ER-2 jet platform. All of the maps were generated by similar analysis methods, enabling the direct comparison of the spatial scale and mineral composition of surface geologic features that can be identified using the three types of remote sensing data. The high spatial (2-17 meter) and spectral (224 bands) resolution AVIRIS data can be used to generate detailed mineral and vegetation maps suitable for geologic and geoenvironmental studies of individual deposits, mines, and smelters. The lower spatial (15-30 meter) and spectral (9 bands) resolution ASTER data are better suited to less detailed mineralogical studies of lithology and alteration across entire hydrothermal systems and mining districts, including regional mineral resource and geoenvironmental assessments. The results presented here demonstrate that minerals and mineral mixtures can be directly identified using AVIRIS and ASTER data to elucidate spatial patterns of mineralogic zonation; AVIRIS data can enable the generation of maps with significantly greater detail and accuracy. The vegetation mapping results suggest that ASTER data may provide an efficient alternative to spectroscopic data for studies of burn severity after wildland fires. A new, semiautomated methodology for the analysis of ASTER data is presented that is currently being applied to ASTER data coverage of large areas for regional assessments of mineral-resource potential and mineral-environmental effects. All maps are presented in a variety of digital formats, including jpeg, pdf, and ERDAS Imagine (.img). The Imagine format files are georeferenced and suitable for viewing with other geospatial data in Imagine, ArcGIS, and ENVI. The mineral and vegetation maps are attributed so that the material identified for a pixel can be determined easily in ArcMap by using the Identify tool and in Imagine by using the Inquire Cursor tool.

Utah↗
USGS2012

Mapping river bathymetry with a small footprint green LiDAR: Applications and challenges

Airborne bathymetric Light Detection And Ranging (LiDAR) systems designed for coastal and marine surveys are increasingly sought after for high-resolution mapping of fluvial systems. To evaluate the potential utility of bathymetric LiDAR for applications of this kind, we compared detailed surveys collected using wading and sonar techniques with measurements from the United States Geological Survey’s hybrid topographic⁄ bathymetric Experimental Advanced Airborne Research LiDAR (EAARL). These comparisons, based upon data collected from the Trinity and Klamath Rivers, California, and the Colorado River, Colorado, demonstrated that environmental conditions and postprocessing algorithms can influence the accuracy and utility of these surveys and must be given consideration. These factors can lead to mapping errors that can have a direct bearing on derivative analyses such as hydraulic modeling and habitat assessment. We discuss the water and substrate characteristics of the sites, compare the conventional and remotely sensed river-bed topographies, and investigate the laser waveforms reflected from submerged targets to provide an evaluation as to the suitability and accuracy of the EAARL system and associated processing algorithms for riverine mapping applications.

Journal of the American Water Resources Associatio↗
USGS2022

GeoImageNet: A multi-source natural feature benchmark dataset for GeoAI and supervised machine learning

The field of GeoAI or Geospatial Artificial Intelligence has undergone rapid development since 2017. It has been widely applied to address environmental and social science problems, from understanding climate change to tracking the spread of infectious disease. A foundational task in advancing GeoAI research is the creation of open, benchmark datasets to train and evaluate the performance of GeoAI models. While a number of datasets have been published, very few have centered on the natural terrain and its landforms. To bridge this gulf, this paper introduces a first-of-its-kind benchmark dataset, GeoImageNet, which supports natural feature detection in a supervised machine-learning paradigm. A distinctive feature of this dataset is the fusion of multi-source data, including both remote sensing imagery and DEM in depicting spatial objects of interest. This multi-source dataset allows a GeoAI model to extract rich spatio-contextual information to gain stronger confidence in high-precision object detection and recognition. The image dataset is tested with a multi-source GeoAI extension against two well-known object detection models, Faster-RCNN and RetinaNet. The results demonstrate the robustness of the dataset in aiding GeoAI models to achieve convergence and the superiority of multi-source data in yielding much higher prediction accuracy than the commonly used single data source.

GeoInformatica↗
USGS2011

Identification of mineral resources in Afghanistan—Detecting and mapping resource anomalies in prioritized areas using geophysical and remote sensing (ASTER and HyMap) data

As part of the U.S. Geological Survey (USGS) and Department of Defense Task Force for Business and Stability Operations (TFBSO) natural resources revitalization activities in Afghanistan (Peters and others, 2011), three new datasets have been collected, compiled, and analyzed. These data have been used to more fully evaluate the areas of interest (AOIs; fig. 1 ) where, on the basis of previous U.S.S.R. and Afghanistan studies, the opportunity for early economic development of a number of different mineral, commodity, and deposit types had been identified (Peters and others, 2007; Peters and others, 2011). The new data compilations include (1) regional magnetic and gravity data for use in the characterization of subsurface composition and structure (Sweeney and others, 2006a,b; Ashan and others, 2007; Sweeney and others, 2007; Ashan and others, 2008; Shenwary and others, 2011), (2) Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data to identify and evaluate surficial alteration patterns related to industrial minerals and other selected targets, and (3) HyMap imaging spectrometer data for characterization and mapping of surficial mineralogy (Cocks and others, 1998; Kokaly and others, 2008; Peters and others, 2011). These datasets have served as fundamental building blocks for the resource evaluation by Peters and others (2011). During the independent analysis of the geophysical, ASTER, and imaging spectrometer (HyMap) data by USGS scientists, previously unrecognized targets of potential mineralization were identified using evaluation criteria most suitable to the individual dataset. These anomalous zones offer targets of opportunity that warrant additional field verification. This report describes the standards used to define the anomalies, summarizes the results of the evaluations for each type of data, and discusses the importance and implications of regions of anomaly overlap between two or three of the datasets.

Open-File Report↗
USGS2012

Advances in spectroscopic methods for quantifying soil carbon

The current gold standard for soil carbon (C) determination is elemental C analysis using dry combustion. However, this method requires expensive consumables, is limited by the number of samples that can be processed (~100/d), and is restricted to the determination of total carbon. With increased interest in soil C sequestration, faster methods of analysis are needed, and there is growing interest in methods based on diffuse reflectance spectroscopy in the visible, near-infrared or mid-infrared spectral ranges. These spectral methods can decrease analytical requirements and speed sample processing, be applied to large landscape areas using remote sensing imagery, and be used to predict multiple analytes simultaneously. However, the methods require localized calibrations to establish the relationship between spectral data and reference analytical data, and also have additional, specific problems. For example, remote sensing is capable of scanning entire watersheds for soil carbon content but is limited to the surface layer of tilled soils and may require difficult and extensive field sampling to obtain proper localized calibration reference values. The objective of this chapter is to discuss the present state of spectroscopic methods for determination of soil carbon.

Book chapter↗