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At least 235 records · Page 13Linked to original sources
USGS2023

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↗
USGS2001

Satellite images for land cover monitoring - Navigating through the maze

Policy makers, managers, scientists and the public can view the changing environment using satellite images. More than 60 Earth observing satellites are collecting images of the Earth's surface. Remote sensing satellite systems for land cover assessment are operated by a growing number of countries including India, the United States, Japan, France, Canada and Russia. The focus of this publication is satellite systems for land cover monitoring. On the reverse is a table that compares a selection of these systems, whose data are globally available in a form suitable for land cover analysis. We hope the information presented will help you assess the utility of remotely sensed image to meet your needs.

Report↗
USGS2018

Clarifying regional hydrologic controls of the Marañón River, Peru through rapid assessment to inform system-wide basin planning approaches

We use remote sensing to enhance the interpretation of the first baseline dataset of hydrologic, isotopic and hydrochemical variables spanning 620 km of the upper Marañón River, in Andean Peru, from the steep alpine canyons to the lower lying jungle. Remote, data-scarce river systems are under increased hydropower development pressure to meet rising energy demands. The upstream-downstream river continuum, which serves as a conduit for resource exchange across ecosystems, is at risk, potentially endangering the people, environments, and economies that rely on river resources. The Marañón River, one of the final free-flowing headwater connections between the Andes and the Amazon, is the subject of myriad large-scale hydropower proposals. Due to challenging access, environmental data are scarce in the upper Marañón, limiting our ability to do system-wide river basin planning. We capture key processes and transitions in the context of hydropower development. Two hydrologic regimes control the Marañón dry-season flow: in the higher-elevation upper reaches, a substantial baseflow is fed by groundwater recharged from wet season rains, in contrast to the lower reaches where the mainstem discharge is controlled by rain-fed tributaries that receive rain from lowland Amazon moisture systems. Sustainability of the upper corridor’s dry-season baseflow appears to be more highly connected to the massive natural storage capacity of extensive wetlands in the puna (alpine grasslands) than with cryospheric water inputs. The extent and conservation of puna ecosystems and glacier reservoirs may be interdependent, bringing to bear important conservation questions in the context of changing climate and land use in the region. More generally, this case study demonstrates an efficient combined remote sensing and field observation approach to address data scarcity across regional scales in mountain basins facing imminent rapid change.

Marañón River↗
USGS1992

Assessment of habitat of wildlife communities on the Snake River, Jackson, Wyoming

The composition of the wildlife community in western riparian habitats is influenced by the horizontal and vertical distribution of vegetation, the physical complexity of the channel, and barriers to movement along the corridor. Based on information from the literature and a workshop, a model was developed to evaluate the wildlife community along the Snake River near Jackson, Wyoming. The model compares conditions of the current or future years with conditions in 1956, before constructions of levees along the river. Conditions in 1956 are assumed to approximate the desirable distribution of plant cover types and the associated wildlife community and are used as a standard of comparison in the model. The model may be applied with remotely sensed data and is compatible with a geographic information systems analysis. In addition to comparing existing or future conditions with conditions in 1956, the model evaluated floodplain and channel complexity and assesses anthropogenic disturbance and its potential effect on the quality of wildlife habitat and movements of wildlife in the riparian corridor.

Wyoming↗
USGS2007

Southern California Bight 2003 Regional Monitoring Program: V. water quality

More than $30 million is expended annually on environmental monitoring in the Southern California Bight (SCB), yet only 5% of the Bight is monitored on an ongoing basis. Therefore, environmental managers in the SCB decided to expand their monitoring program and, starting in 1994, decided to conduct periodic regional assessments of ecosystem condition and assess the overall health of the SCB. Sixty-five different organizations collaborated in 2003 to create the third SCB Regional Monitoring Program (Bight '03). Bight '03 was designed to be integrated regional monitoring program that encompasses regulatory, academic, and non-governmental agencies. Bight '03 had three components: Coastal Ecology, Shoreline Microbiology, and Water Quality. This report addresses the purpose, approach, findings, and recommendations from the Water Quality component, which focused on contamination-laden stormwater runoff, in particularly its variability in time and space as well as its short-term ecological impacts. Specifically, the Bight '03 Water Quality component had three primary goals, the first of which was to described the temporal evolution of stormwater plumes produced by the major southern California rivers. Specifically, the study was intended to determine how far offshore the plumes extended, how rapidly they advected, how long before the plumes dispersed and how these properties differed among storms and river systems. The second goal was to describe how the physical properties (e.g., turbidity, temperature, salinity) of the plume related to biogeochemical and ecological properties that are of more direct concern to the water quality management community. Accomplished primarily through ship-based sampling of water quality parameters, this second goal was to describe how far offshore, and for how ;long after the storm, elevated bacterial concentrations, toxicity, and nutrients could be detected. Similar to the fist goal, the study also addressed how these answers differed among storms and river systems. The final goal was to determine whether relationships between environmental indicators derived from coincident satellite remote sensing and in situ data sets are sufficiently robust for remote sensing to become a routine water quality monitoring programs. Remote sensing data potentially provide coastal managers with synoptic near-real time regional information about prevailing ocean conditions and hazards that would complement existing field-based sampling protocols, but only if there is a thorough understanding of how to interpret and utilize the proxy measures, such as ocean color. The understanding of these priorities through Bight '03 sampling is intended to provide the basis for developing more efficient, widespread and coast-effective coastal ocean monitoring techniques. Water quality data were collected across eight major river systems within four geographic regions of southern California. Field measurements included the primary contaminants of interest, i.e., bacterial concentrations, water toxicity, and nutrients, as well as related parameters such as temperatures, salinity, total suspended solids, transmissivity, chlorophyll, and colored dissolved organic material (CDOM) concentrations. For each of the four major regions, i.e., Santa Clara/Ventura Rivers, Ballona Creek/Santa Monica Bay, San Pedro Shelf, and the San Diego, Tijuana Rivers, two stormwater events were sampled for up to three days by ship resulting in 574 water column CTD+ profiles and 705 discrete water samples during 36 ship-days. These data were analyzed in combination with MODIS ocean color satellite remote sensing, buoy meteorological observations, drifters, and HF radar current measurements to evaluate the dispersal patterns, dynamics, and impacts of the freshwater runoff plumes. Based on these data and resulting analyses, the principal conclusions were as follow: - Stormwater runoff turbidity plumes were found to be spatially extensive, covering up to 2500 km 2 within the Southern California Bight nearshore zone, and persisting over the entire duration of the post-storm sampling period (at least 3 days). - The spatial and temporal extent of the portion of the plume with contaminants was far less than that of the turbidity plume, typically representing <10% of its area (30-70% off Tijuana); however, with contaminant impacts generally greatly reduced or absent by the third or fourth day of sampling - Pseudo-nitzschia , a harmful algae that produces domoic acid, was found to be more abundant than previously reported. - Accurately describing stormwater runoff plumes requires a combination of in situ and remote sensing assessment tools, with satellite data providing valuable synoptic information. From these conclusions, the following recommendations are provided: - Future studies designed to describe stormwater plumes should include a combination of ship - and remote sensing-based methods. - CDOM is a good proxy of the freshwater runoff plume and should be added as a standard measurement parameter on water quality instrument packages. - Investigations are needed that assess on a local basis the spatial extent of ecological effects of stormwater plumes early in the storm, ideally accompanied by airborne imagery to provide improved temporal & spatial resolution, to fill in knowledge gaps. The next Bight regional monitoring program should focus on quantifying nutrient loadings and dynamics in association with stormwater runoff and other sources, and characterize their attendant ecosystem impacts such as phytoplankton blooms.

California↗
USGS2001

Mapping wildland fuels for fire management across multiple scales: integrating remote sensing, GIS, and biophysical modeling

Fuel maps are essential for computing spatial fire hazard and risk and simulating fire growth and intensity across a landscape. However, fuel mapping is an extremely difficult and complex process requiring expertise in remotely sensed image classification, fire behavior, fuels modeling, ecology, and geographical information systems (GIS). This paper first presents the challenges of mapping fuels: canopy concealment, fuelbed complexity, fuel type diversity, fuel variability, and fuel model generalization. Then, four approaches to mapping fuels are discussed with examples provided from the literature: (1) field reconnaissance; (2) direct mapping methods; (3) indirect mapping methods; and (4) gradient modeling. A fuel mapping method is proposed that uses current remote sensing and image processing technology. Future fuel mapping needs are also discussed which include better field data and fuel models, accurate GIS reference layers, improved satellite imagery, and comprehensive ecosystem models.

International Journal of Wildland Fire↗
USGS2022

Sediment source fingerprinting as an aid to large-scale landscape conservation and restoration: A review for the Mississippi River Basin

Reliable quantitative information on sediment sources to rivers is critical to mitigate contamination and target conservation and restoration actions. However, the determination of the relative importance of sediment sources is complicated at the scale of large river basins by immense variability in erosional processes and sediment sources over space and time, heterogeneity in sediment transport and deposition, and a paucity of sediment monitoring data. Sediment source fingerprinting is an increasingly adopted field-based technique that identifies the nature and relative source contribution of sediment transported in waterways. Notably, sediment source fingerprinting provides information that is independent of other field, modeling, or remotely sensed techniques. However, the diversity in sediment fingerprinting sampling, analytical, and interpretive methods has been recognized as a problem in terms of developing standardized procedures for its application at the scale of large river basins. Accordingly, this review focuses on established sediment source fingerprinting studies conducted within the Mississippi River Basin (MRB), summarizes unique information provided by sediment source fingerprinting that is distinct from traditional monitoring techniques, evaluates consistency and reliability of methodological approaches among MRB studies, and provides prospects for the use of the sediment source fingerprinting technique as an aid to large-scale landscape conservation and restoration under current management frameworks. Most established MRB studies got creditable fingerprinting results and considered near-channel sources as the dominant sediment sources in most cases, while the comparability of their results suffers from a lack of standardization in procedural steps. Findings from MRB studies demonstrate that sediment source fingerprinting is a highly valuable and reliable sediment source assessment approach to assist land and water resource management under current management frameworks, but efforts are still needed to make this technique ready to be used in a more predominant way in large-scale landscape conservation and restoration efforts. We summarized research needs and suggested the best fingerprinting practices for management purposes with the aim of ensuring that this technique is as robust and reliable as it moves forward.

Mississippi River Basin↗
USGS1996

Origins and philosophy of building a temporal database to examine human transformation processes

The U.S. Geological Survey (USGS), in partnership with the University of Maryland Baltimore County, is using historical maps and satellite images to map human-induced land transformations for the Baltimore-Washington metropolitan area. This work builds on an earlier effort that documented the historical urban development for the San Francisco Bay area. That effort used a geographic information system to compile a database that provided a visual and historical perspective of the urban growth experienced in the Bay area between 1850 and 1990. Historical overviews of urban development can be used to provide insights into the future. The Bay area work was inspired by the desire to draw upon the USGS's rich 100-year topographic map, and 20-year Landsat satellite data archives. A methodology was developed to combine the information from a variety of sources into an integrated, multi-scale, and multi-resolution dataset. Temporal urban mapping is used to examine past landscapes by incorporating historic maps, census statistics, and commerce records to generate a progressive geo-referenced representation of the past changes in the region. Contemporary analysis focuses on the use of remotely sensed data, existing digital land use data, digital census information, and a variety of Earth science infrastructure data, such as Digital Line Graphs, Digital Elevation Models, and key ancillary demographic information. The resulting database of temporal urban demographic changes provides an ideal source of test data and information for both urban geographers and global change research scientists.

San Francisco Bay↗
USGS2021

Enhancing the application of Earth observations for improved environmental decision-making using the Early Warning eXplorer (EWX)

The mitigation of losses due to extreme climate events and long-term climate adaptation requires climate informed decision-making. In the past few decades, several remote sensing and modeled-based Earth observations (EOs) have been developed to provide an unprecedented global overview and routine monitoring of climate and its impacts on vegetation and hydrologic conditions, with the goal of supporting informed decision-making. However, their usage in decision-making is particularly limited in climate-risk vulnerable and in situ data-scarce regions such as sub-Saharan Africa, due to lack of access to EOs. Here, we describe the Early Warning eXplorer (EWX), which was developed to address this crucial limitation and facilitate the application of EOs in decision-making, particularly in the food and water-insecure regions of the world. First, the EWX's core framework, which includes (i) the Viewer, (ii) GeoEngine, and (iii) Support Applications, is described. Then, a comprehensive overview of the Viewer, which is a web-based interface used to access EOs, is provided. This includes a description of (i) the maps and associated features to access gridded EO data and anomalies for different temporal averaging periods, (ii) time series graphs and associated features to access EOs aggregated over polygons such as administrative boundaries, and (iii) commonly used EOs served by the EWX that provide assessments of climate and vegetation conditions. Next, examples are provided to demonstrate how EWX can be used to monitor development, progression, spatial extent, and severity of climate-driven extreme events to support timely decisions related to mitigation of food insecurity and flooding impacts. Finally, the value of a regional implementation of EWX at the Regional Centre for Mapping of Resources for Development (RCMRD) in Nairobi, Kenya, is highlighted. Regional implementation of the EWX facilitates access to regionally focused EOs and their availability at polygon boundaries most relevant to the local decision-makers. Similar instances of EWX implemented in other regions, especially those susceptible to food and water security, will likely further enhance the application of EOs for informed decision-making.

Frontiers in Climate↗
USGS2004

Review of Results and Recommendations from the GCMRC 2000-2003 Remote-Sensing Initiative for Monitoring Environmental Resources Within the Colorado River Ecosystem

In mid-2000, the Grand Canyon Monitoring and Research Center (GCMRC) began a remote-sensing initiative to evaluate all remote-sensing technologies and methods that had potential for providing improved data (capability) for its various programs that monitor the Colorado River ecosystem (CRE). The primary objective of the initiative was to determine the most cost-effective data collection protocols for GCMRC programs that (1) provide the accuracies required for currently measured parameters, (2) provide additional parameters for ecological monitoring, (3) reduce environmental impact by being less invasive than current methods, and (4) expand geographic extent of current ground approaches. The initial phase of the remote-sensing initiative determined the types of sampling parameters and their required accuracies for monitoring. This information was used to determine the most appropriate sensors for evaluation. The initiative evaluated 25 different data collections over a three-year period; many more remote-sensing instruments were considered, but were not evaluated because they could not meet the basic requirements on spatial resolution, wavelength, positional accuracy, or elevation accuracy. It was hoped that the evaluations would lead to a minimum set of technologies that would satisfy many program requirements. The results from all of our evaluations are reviewed in this report and are briefly summarized in this report.

Open-File Report↗
USGS2020

Comparative performance and trend of remotely sensed phenology and productivity metrics across the Western United States

Vegetation phenology and productivity play a crucial role in surface energy balance, plant and animal distribution, and animal movement and habitat use and can be measured with remote sensing metrics including start of season (SOS), peak instantaneous rate of green-up date (PIRGd), peak of season (POS), end of season (EOS), and integrated vegetation indices. However, for most metrics, we do not yet understand the agreement of remotely sensed data products with near-surface observations. We also need summaries of changes over time, spatial distribution, variability, and consistency in remote sensing dataset metrics for vegetation timing and quality. We compare metrics from 10 leading remote sensing datasets against a network of PhenoCam near-surface cameras throughout the western United States from 2002 to 2014. Most phenology metrics representing a date (SOS, PIRGd, POS, and EOS), rather than a duration (length of spring, length of growing season), better agreed with near-surface metrics but results varied by dataset, metric, and land cover, with absolute value of mean bias ranging from 0.38 (PIRGd) to 37.92 days (EOS). Datasets had higher agreement with PhenoCam metrics in shrublands, grasslands, and deciduous forests than in evergreen forests. Phenology metrics had higher agreement than productivity metrics, aside from a few datasets in deciduous forests. Using two datasets covering the period 1982–2016 that best agreed with PhenoCam metrics, we analyzed changes over time to growing seasons. Both datasets exhibited substantial spatial heterogeneity in the direction of phenology trends. Variability of metrics increased over time in some areas, particularly in the Southwest. Approximately 60% of pixels had consistent trend direction between datasets for SOS, POS, and EOS, with the direction varying by location. In all ecoregions except Mediterranean California, EOS has become later. This study comprehensively compares remote sensing datasets across multiple growing season metrics and discusses considerations for applied users to inform their data choices. des indicators of vegetation timing and quality through metrics such as start of season (SOS), peak instantaneous rate of green-up date (PIRGd), peak of season (POS), end of season (EOS), and integrated vegetation indices. Few comparisons guide users in dataset selection, examine a large spatial extent, and include multiple metrics. This study compares metrics from 10 leading remote sensing datasets against a network of PhenoCam near-surface cameras throughout the Western United States from 2002-2014. Correlation (R2) and mean bias varied substantially by dataset, metric, and land cover. The closest association with PhenoCam measured phenology metrics represented a date (SOS, PIRGd, POS, and EOS) rather than a duration (length of spring, length of growing season), with R2 of individual datasets ranging from 0.03 (SOS) – 0.55 (PIRGd), and absolute value of mean bias ranging from 0.38 (PIRGd) – 37.92 days (EOS). Datasets had higher agreement with PhenoCam metrics in shrublands, grasslands, and deciduous/broadleaf forests than in evergreen forests. Productivity metrics agreed worse than phenology metrics, though some datasets showed high correlations in deciduous/broadleaf forests. Using the two datasets that agreed best with PhenoCam metrics and covered 1982-2016, we conducted a trend analysis to study changes to growing seasons. Trends in phenology exhibited substantial spatial heterogeneity in the direction of trend for both datasets. Variability of metrics increased over time in some areas, particularly in the Southwest. Approximately 60% of pixels had consistent trend direction (both earlier and later) for SOS, POS, and EOS. In all ecoregions except Mediterranean California EOS trended toward a later date. This study provides a comprehensive comparison of remote sensing datasets across many important phenology and productivity metrics and discusses considerations for users to make informed decisions about their data choices.

Arizona, California, Colorado, Idaho, Montana, New↗
USGS2014

Introduction: Hazard mapping

Twenty papers were accepted into the session on landslide hazard mapping for oral presentation. The papers presented susceptibility and hazard analysis based on approaches ranging from field-based assessments to statistically based models to assessments that combined hydromechanical and probabilistic components. Many of the studies have taken advantage of increasing availability of remotely sensed data and nearly all relied on Geographic Information Systems to organize and analyze spatial data. The studies used a range of methods for assessing performance and validating hazard and susceptibility models. A few of the studies presented in this session also included some element of landslide risk assessment. This collection of papers clearly demonstrates that a wide range of approaches can lead to useful assessments of landslide susceptibility and hazard.

Book chapter↗
USGS2014

Placing prairie pothole wetlands along spatial and temporal continua to improve integration of wetland function in ecological investigations

We evaluated the efficacy of using chemical characteristics to rank wetland relation to surface and groundwater along a hydrologic continuum ranging from groundwater recharge to groundwater discharge. We used 27 years (1974–2002) of water chemistry data from 15 prairie pothole wetlands and known hydrologic connections of these wetlands to groundwater to evaluate spatial and temporal patterns in chemical characteristics that correspond to the unique ecosystem functions each wetland performed. Due to the mineral content and the low permeability rate of glacial till and soils, salinity of wetland waters increased along a continuum of wetland relation to groundwater recharge, flow-through or discharge. Mean inter-annual specific conductance (a proxy for salinity) increased along this continuum from wetlands that recharge groundwater being fresh to wetlands that receive groundwater discharge being the most saline, and wetlands that both recharge and discharge to groundwater (i.e., groundwater flow-through wetlands) being of intermediate salinity. The primary axis from a principal component analysis revealed that specific conductance (and major ions affecting conductance) explained 71% of the variation in wetland chemistry over the 27 years of this investigation. We found that long-term averages from this axis were useful to identify a wetland’s long-term relation to surface and groundwater. Yearly or seasonal measurements of specific conductance can be less definitive because of highly dynamic inter- and intra-annual climate cycles that affect water volumes and the interaction of groundwater and geologic materials, and thereby influence the chemical composition of wetland waters. The influence of wetland relation to surface and groundwater on water chemistry has application in many scientific disciplines and is especially needed to improve ecological understanding in wetland investigations. We suggest ways that monitoring in situ wetland conditions could be linked with evolving remote sensing technology to improve our ability to better inform decisions affecting wetland sustainability and provide periodic inventories of wetland ecosystem services to document temporal trends in wetland function and how they respond to contemporary land-use change.

North Dakota↗
USGS2004

Comparison of AVIRIS and Landsat ETM+ detection capabilities for burn severity

Our study compares data on burn severity collected from multi-temporal Airborne Visible and Infrared Imaging Spectrometer (AVIRIS) with similar data from the Enhanced Thematic Mapper Plus (ETM+) using the differenced Normalized Burn Ratio (dNBR). Two AVIRIS and ETM+ data acquisitions recorded surface conditions immediately before the Hoover Fire began to spread rapidly and again the following year. Data were validated with 63 field plots using the Composite Burn Index (CBI). The relationship between spectral channels and burn severity was examined by comparing pre- and post-fire datasets. Based on the high burn severity comparison, AVIRIS channels 47 and 60 at wavelengths of 788 and 913 nm showed the greatest negative response to fire. Post-fire reflectance values decreased the most on average at those wavelengths, while channel 210 at 2370 nm showed the greatest positive response on average. Fire increased reflectance the most at that wavelength over the entire measured spectral range. Furthermore, channel 210 at 2370 nm exhibited the greatest variation in spectral response, suggesting potentially high information content for fire severity. Based on general remote sensing principles and the logic of variable spectral responses to fire, dNBR from both sensors should produce useful results in quantifying burn severity. The results verify the band–response relationships to burn severity as seen with ETM+ data and confirm the relationships by way of a distinctly different sensor system.

Remote Sensing of Environment↗
USGS2019

Measurement of cyanobacteria bloom magnitude using satellite remote sensing

Cyanobacterial harmful algal blooms (cyanoHABs) are a serious environmental, water quality and public health issue worldwide because of their ability to form dense biomass and produce toxins. Models and algorithms have been developed to detect and quantify cyanoHABs biomass using remotely sensed data but not for quantifying bloom magnitude, information that would guide water quality management decisions. We propose a method to quantify seasonal and annual cyanoHAB magnitude in lakes and reservoirs. The magnitude is the spatio-temporal mean of weekly or biweekly maximum cyanobacteria biomass for the season or year. CyanoHAB biomass is quantified using a standard reflectance spectral shape-based algorithm that uses data from Medium Resolution Imaging Spectrometer (MERIS). We demonstrate the method to quantify annual and seasonal cyanoHAB magnitude in Florida and Ohio respectively during 2003-2011 and rank the lakes based on median magnitude over the study period. The new method can be applied to Ocean Land Color Imager (OLCI) on Sentinel-3 data for assessment of cyanoHABs and the change over time, even with issues such as variable data acquisition frequency or sensor calibration uncertainties between satellites. CyanoHAB magnitude can support monitoring and management decision-making for recreational and drinking water sources.

Florida, Ohio↗
USGS2018

Evaluating potential distribution of high-risk aquatic invasive species in the water garden and aquarium trade at a global scale based on current established populations

Aquatic non‐native invasive species are commonly traded in the worldwide water garden and aquarium markets, and some of these species pose major threats to the economy, the environment, and human health. Understanding the potential suitable habitat for these species at a global scale and at regional scales can inform risk assessments and predict future potential establishment. Typically, global habitat suitability models are fit for freshwater species with only climate variables, which provides little information about suitable terrestrial conditions for aquatic species. Remotely sensed data including topography and land cover data have the potential to improve our understanding of suitable habitat for aquatic species. In this study, we fit species distribution models using five different model algorithms for three non‐native aquatic invasive species with bioclimatic, topographic, and remotely sensed covariates to evaluate potential suitable habitat beyond simple climate matches. The species examined included a frog (Xenopus laevis), toad (Bombina orientalis), and snail (Pomacea spp.). Using a unique modeling approach for each species including background point selection based on known established populations resulted in robust ensemble habitat suitability models. All models for all species had test area under the receiver operating characteristic curve values greater than 0.70 and percent correctly classified values greater than 0.65. Importantly, we employed multivariate environmental similarity surface maps to evaluate potential extrapolation beyond observed conditions when applying models globally. These global models provide necessary forecasts of where these aquatic invasive species have the potential for establishment outside their native range, a key component in risk analyses.

Risk Analysis↗
USGS2024

Identification of kaolins and associated minerals in altered volcanic rocks by infrared spectroscopy

Mid-infrared spectroscopy (2.5-50 /µm) has been extensively used to identify and characterize clays and associated minerals in rocks and soils, with particular emphasis on the 3-, 10-, and 20-/µm regions (Farmer and Russell, 1967; Farmer, 1968; White, 1971; Van der Marel and Beutelspacher, 1976). However, application of mid-infrared spectroscopy in remote-sensing activities has been restricted because the spectral information occurs only as a small perturbation to the emitted radiation from the earth's surface, and much of that which is especially relevant to clays (e.g., the 3.0-µm region) is obscured by atmospheric absorption.

Clays and Clay Minerals↗
USGS2003

Status and interconnections of selected environmental issues in the global coastal zones

This study focuses on assessing the state of population distribution, land cover distribution, biodiversity hotspots, and protected areas in global coastal zones. The coastal zone is defined as land within 100 km of the coastline. This study attempts to answer such questions as: how crowded are the coastal zones, what is the pattern of land cover distribution in these areas, how much of these areas are designated as protected areas, what is the state of the biodiversity hotspots, and what are the interconnections between people and coastal environment. This study uses globally consistent and comprehensive geospatial datasets based on remote sensing and other sources. The application of Geographic Information System (GIS) layering methods and consistent datasets has made it possible to identify and quantify selected coastal zones environmental issues and their interconnections. It is expected that such information provide a scientific basis for global coastal zones management and assist in policy formulations at the national and international levels.

Ambio↗