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Results for “Remote Sensing and the Environment”

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

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At least 541 records · Page 30Linked to original sources
USGS2007

Generation and validation of characteristic spectra from EO1 Hyperion image data for detecting the occurrence of the invasive species, Chinese tallow

Chinese tallow (Triadica sebifera) is an invasive tree that is spreading throughout the south-eastern United States and now into the west, and in many places causing extensive change to native habitat and associated wildlife. Detecting and mapping the relative distribution of this species is important to its control and eradication. To map the relative distribution of Chinese tallow within a southwestern Louisiana coastal wetland to upland environment, Earth Observing 1 (EO1) satellite Hyperion sensor hyperspectral image data were combined with a subpixel extraction method that modelled characteristic spectra from the image data without requiring a priori characteristic spectra. Because of the low percentage occurrences of Chinese tallow and high spectral covariation in the environment, unique validation and verification methods were implemented, relying on simultaneous collection of field canopy reflectance spectra and subsequent classification of canopy compositions. The subpixel extraction method produced five characteristic spectra, which we further refined to four that adequately represented the field spectra, as well as the Hyperion imaged canopy reflectance datasets. Characteristic spectra were designated as senescing foliage, cypress-tupelo trees, and trees without leaves; shadows and green vegetation; senescing Chinese tallow with yellow leaves and yellowing foliage; and senescing Chinese tallow with red leaves ('red tallow'). About 81% (n=34) of the field and 78% (n=33) of the Hyperion imaged characteristic spectra associated with 'red tallow' were explained by the compositions generated in the field slide classifications. ?? 2005 US Government.

International Journal of Remote Sensing↗
USGS2014

Bringing an ecological view of change to Landsat-based remote sensing

When characterizing the processes that shape ecosystems, ecologists increasingly use the unique perspective offered by repeat observations of remotely sensed imagery. However, the concept of change embodied in much of the traditional remote-sensing literature was primarily limited to capturing large or extreme changes occurring in natural systems, omitting many more subtle processes of interest to ecologists. Recent technical advances have led to a fundamental shift toward an ecological view of change. Although this conceptual shift began with coarser-scale global imagery, it has now reached users of Landsat imagery, since these datasets have temporal and spatial characteristics appropriate to many ecological questions. We argue that this ecologically relevant perspective of change allows the novel characterization of important dynamic processes, including disturbances, long-term trends, cyclical functions, and feedbacks, and that these improvements are already facilitating our understanding of critical driving forces, such as climate change, ecological interactions, and economic pressures.

Frontiers in Ecology and the Environment↗
USGS2008

Relationship between remotely-sensed vegetation indices, canopy attributes and plant physiological processes: What vegetation indices can and cannot tell us about the landscape

Vegetation indices (VIs) are among the oldest tools in remote sensing studies. Although many variations exist, most of them ratio the reflection of light in the red and NIR sections of the spectrum to separate the landscape into water, soil, and vegetation. Theoretical analyses and field studies have shown that VIs are near-linearly related to photosynthetically active radiation absorbed by a plant canopy, and therefore to light-dependent physiological processes, such as photosynthesis, occurring in the upper canopy. Practical studies have used time-series VIs to measure primary production and evapotranspiration, but these are limited in accuracy to that of the data used in ground truthing or calibrating the models used. VIs are also used to estimate a wide variety of other canopy attributes that are used in Soil-Vegetation-Atmosphere Transfer (SVAT), Surface Energy Balance (SEB), and Global Climate Models (GCM). These attributes include fractional vegetation cover, leaf area index, roughness lengths for turbulent transfer, emissivity and albedo. However, VIs often exhibit only moderate, non-linear relationships to these canopy attributes, compromising the accuracy of the models. We use case studies to illustrate the use and misuse of VIs, and argue for using VIs most simply as a measurement of canopy light absorption rather than as a surrogate for detailed features of canopy architecture. Used this way, VIs are compatible with “Big Leaf” SVAT and GCMs that assume that canopy carbon and moisture fluxes have the same relative response to the environment as any single leaf, simplifying the task of modeling complex landscapes.

Arizona↗
USGS1987

Summary mineral resource appraisal of the Richfield 1° x 2° quadrangle, west-central Utah

The mineral resource potential of the Richfield 1° x 2° quadrangle, Utah, has been appraised using geological, geophysical, geochemical, and remote-sensing techniques. These studies have led to many publications giving basic data and interpretations; of these, a series of 18 maps at 1:250,000 and 1:500,000 scales summarizing aspects of the geology, geophysics, geochemistry, and remote sensing is designated the CUSMAP (Conterminous United States Mineral Appraisal Program) folio. This circular uses the data shown on these maps to appraise the mineral resource potential of the quadrangle. The oldest rocks exposed in the Richfield quadrangle are small patches of Early Proterozoic (1.7 billion years old) gneiss and schist on the west side of the Mineral Mountains. These rocks presumably formed the basement on which many thousands of meters of Late Proterozoic, Paleozoic, and lower Mesozoic sedimentary strata were deposited. These rocks were deformed during the Late Cretaceous Sevier orogeny when Precambrian and Paleozoic strata in the western part of the quadrangle were thrust relatively eastward across Paleozoic and Mesozoic strata in the eastern part of the quadrangle. Late Cretaceous and early Tertiary highlands above the overthrust belt were eroded and much of the debris was deposited in broad basins east of the belt. Volcanism in Oligocene and earliest Miocene time formed an east-northeast-trending belt of calcalkalic volcanoes across the southern half of the quadrangle. In early Miocene time, the composition of the volcanic rocks changed to a bimodal assemblage of mafic rocks and high-silica alkali rhyolite that has been erupted episodically ever since. Syngenetic mineral resources developed during formation of both sedimentary and volcanic rocks. These include limestone and dolomite, silica-rich sandstone, metalliferous black shale, evaporite deposits, zeolite deposits, pumice, cinders and scoria, and evaporitic or diagenetic deposits in playa environments. Most of these deposits need to have markets established, or extraction and fabrication techniques developed, for them to be utilized. Most epigenetic deposits are of volcanogenic-hydrothermal origin. Deposits associated with calc-alkalic igneous activity largely contain Cu, Pb, Zn, Au, and Ag, and occur in a variety of types zoned around core intrusions. Younger deposits are mostly associated with silicic igneous centers belonging to the bimodal mafic-silicic igneous association. Resources associated with this latter group are likely to contain one or more of the elements Mo, W, U, Sn, Be, and F, as well as Pb, Zn, Au, and Ag. Alunite and kaolinite deposits are found at many mineralized centers. Most epigenetically mineralized areas expose only the upper, near-surface parts of the different hydrothermal systems; most of whatever mineral deposits formed in these systems probably still exist at depth, awaiting discovery. Our conclusion is that many mineralized areas have excellent possibilities for the occurrence of mineral resources. Each of the many identified centers of mineralization is discussed briefly in this report and an estimate made of its resource potential.

Utah↗
USGS2011

Hapke modeling of Rhea surface properties through Cassini-VIMS spectra

T The surface properties of the icy bodies in the saturnian system have been investigated by means of the Cassini-VIMS (Visual Infrared Mapping Spectrometer) hyperspectral imager which operates in the 0.35–5.1 μm wavelength range. In particular, we have analyzed 111 full disk hyperspectral images of Rhea ranging in solar phase between 0.08° and 109.8°. These data have been previously analyzed by Filacchione et al. (Filacchione, G. et al. [2007]. Icarus 186, 259–290; Filacchione, G. et al. [2010]. Icarus 206, 507–523) to study, adopting various “spectral indicators” (such as spectral slopes, band depth, and continuum level), the relations among various saturnian satellites. As a further step we proceed in this paper to a quantitative evaluation of the physical parameters determining the spectrophotometric properties of Rhea’s surface. To do this we have applied Hapke (Hapke, B. [1993]. Theory of Reflectance and Emittance Spectroscopy, Topics in Remote Sensing: 3. Springer, Berlin) IMSA model (Isotropic Multiple Scattering Approximation) which allow us to model the phase function at VIS–IR (visible–infrared) wavelengths as well as the spectra taking into account various types of mixtures of surface materials. Thanks to this method we have been able to constrain the size of water ice particles covering the surface, the amount of organic contaminants, the large scale surface roughness and the opposition effect surge. From our analysis it appears that wavelength dependent parameters, e.g. opposition surge width ( h ) and single-particle phase function parameters ( b , v ), are strongly correlated to the estimated single-scattering albedo of particles. For Rhea the best fit solution is obtained by assuming: (1) an intraparticle mixture of crystalline water ice and a small amount (0.4%) of Triton tholin; (2) a monodisperse grain size distribution having a particle diameter a m = 38 μm; and (3) a surface roughness parameter value of 33°. The study of phase function shows that both shadow hiding and coherent backscattering contribute to the opposition surge. This study represents the first attempt, in the case of Rhea, to join the spectral and the photometric analysis. The surface model we derived gives a good quantitative description of both spectrum and phase curve of the satellite. The same approach and model, with appropriate modifications, shall be applied to VIMS data of the other icy satellites of Saturn, in order to reveal similarities and differences in the surface characteristics to understand how these bodies interact with their environment.

Icarus↗
USGS2013

Vegetation impoverishment despite greening: a case study from central Senegal

Recent remote sensing studies have documented a greening trend in the semi-arid Sahel and Sudan zones of West Africa since the early 1980s, which challenges the mainstream paradigm of irreversible land degradation in this region. What the greening trend means on the ground, however, has not yet been explored. This research focuses on a region in central Senegal to examine changes in woody vegetation abundance and composition in selected sites by means of a botanical inventory of woody vegetation species, repeat photography, and perceptions of local land users. Despite the greening, an impoverishment of the woody vegetation cover was observed in the studied sites, indicated by an overall reduction in woody species richness, a loss of large trees, an increasing dominance of shrubs, and a shift towards more arid-tolerant, Sahelian species since 1983. Thus, interpretation of the satellite-derived greening trend as an improvement or recovery is not always justified. The case of central Senegal represents only one of several possible pathways of greening throughout the region, all of which result in similar satellite-derived greening signals.

Journal of Arid Environments↗
USGS2015

Quantifying and predicting fuels and the effects of reduction treatments along successional and invasion gradients in sagebrush habitats

Sagebrush shrubland ecosystems in the Great Basin are prime examples of how altered successional trajectories can create dynamic fuel conditions and, thus, increase uncertainty about fire risk and behavior. Although fire is a natural disturbance in sagebrush, post-fire environments are highly susceptible to conversion to an invasive grass-fire regime (often referred to as a “grass-fire cycle”). After fire, native shrub-steppe plants are often slow to regenerate, whereas nonnative annuals, especially cheatgrass (Bromus tectorum) and medusahead (Taeniatherum caput-medusae), can establish quickly and outcompete native species. Once fire-prone annuals become established, fire occurrences increase, further promoting dominance of nonnative species. The invasive grass-fire regime also alters nutrient and hydrologic cycles, pushing ecosystems beyond ecological thresholds toward steady-state, fire-prone, nonnative communities. These changes affect millions of hectares in the Great Basin and increase fire risk, decrease habitat quality and biodiversity, accelerate soil erosion, and degrade rangeland resources for livestock production. In many sagebrush landscapes, constantly changing plant communities and fuel conditions hinder attempts by land managers to predict and control fire behavior, restore native communities, and provide ecosystem services (e.g., forage production for livestock). We investigated successional and nonnative plant invasion states and associated fuel loads in degraded sagebrush habitat in a focal study area, the Morley Nelson Snake River Birds of Prey National Conservation Area (hereafter the NCA), in the Snake River Plain Ecoregion of southern Idaho. We expanded our inference by comparing our findings to similar data collected throughout seven major land resource areas (MLRAs) across the Great Basin (JFSP Project “Fire Rehabilitation Effectiveness: A Chronosequence Approach for the Great Basin” [09-S-02-1]). 4 We used a combination of field-sampling, experimental treatments, and remotely sensed data to address the following questions: (1) How do fuel loads change along gradients of succession and invasion in sagebrush ecological sites? (2) How do fuel reduction treatments influence fuels in invaded areas formerly dominated by sagebrush? (3) How do fuel loads vary across landscapes and which remote sensing techniques are effective for characterizing them?

Idaho↗
USGS2021

Improved fire severity mapping in the North American boreal forest using a hybrid composite method

Fire severity is a key driver shaping the ecological structure and function of North American boreal ecosystems, a biome dominated by large, high-intensity wildfires. Satellite-derived burn severity maps have been an important tool in these remote landscapes for both fire and resource management. The conventional methodology to produce satellite-inferred fire severity maps generally involves comparing imagery from 1 year before and 1 year after a fire, yet environmental conditions unique to the boreal have limited the accuracy of resulting products. We introduce an alternative method – the ‘hybrid composite’ – based on deriving mean severity over time on a per-pixel basis within the cloud-computing environment of Google Earth Engine. It constructs the post-fire image from satellite data composited from all valid images (i.e., clear-sky and snow-free) acquired in the time period immediately after fire through the early growing season of the following year. We compare this approach to paired-scene and composite approaches where the post-fire time period is from the growing season 1 year after fire. Validation statistics based on field-derived data for 52 fires across Alaska and Canada indicate that the hybrid composite method outperforms the other approaches. This approach presents an efficient and cost-effective means to monitor and explore trends and patterns across broad spatial domains, and could be applied to fires in other regions, especially those with frequent cloud cover or rapid vegetation recovery.

Alaska↗
USGS2014

Whiting events in SW Florida coastal waters: a case study using MODIS medium-resolution data

Whitings, floating patches of calcium carbonate mud, have been found in both shallow carbonate banks and freshwater environments around the world. Although these events have been studied for many decades, much of their characteristics remain unknown. Recent sightings of whitings near Ten Thousand Islands, Florida suggest a phenomenon that has not previously been documented in this area. Using medium-resolution (250-m) data collected by the Moderate Resolution Imaging Spectroradiometer (MODIS) from December 2010 to November 2013, we documented whiting events and their spatial and temporal patterns in this region. Classification rules were first established, and then applied to all 474 cloud-free and sun glint-free MODIS images. Whiting occurrences were found between 25°46′N and 25°20′N and less than 40 km from the southwest Florida coastline. Over the 3-year period, whiting occurrence peaked in spring and autumn and reached a minimum during the winter and summer months. Further field and laboratory research are needed to explain driving force(s) behind these events.

Florida↗
USGS2012

A simple method for estimating basin-scale groundwater discharge by vegetation in the basin and range province of Arizona using remote sensing information and geographic information systems

Groundwater is a vital water resource in the arid to semi-arid southwestern United States. Accurate accounting of inflows to and outflows from the groundwater system is necessary to effectively manage this shared resource, including the important outflow component of groundwater discharge by vegetation. A simple method for estimating basin-scale groundwater discharge by vegetation is presented that uses remote sensing data from satellites, geographic information systems (GIS) land cover and stream location information, and a regression equation developed within the Southern Arizona study area relating the Enhanced Vegetation Index from the MODIS sensors on the Terra satellite to measured evapotranspiration. Results computed for 16-day composited satellite passes over the study area during the 2000 through 2007 time period demonstrate a sinusoidal pattern of annual groundwater discharge by vegetation with median values ranging from around 0.3 mm per day in the cooler winter months to around 1.5 mm per day during summer. Maximum estimated annual volume of groundwater discharge by vegetation was between 1.4 and 1.9 billion m 3 per year with an annual average of 1.6 billion m 3 . A simplified accounting of the contribution of precipitation to vegetation greenness was developed whereby monthly precipitation data were subtracted from computed vegetation discharge values, resulting in estimates of minimum groundwater discharge by vegetation. Basin-scale estimates of minimum and maximum groundwater discharge by vegetation produced by this simple method are useful bounding values for groundwater budgets and groundwater flow models, and the method may be applicable to other areas with similar vegetation types.

Arizona↗
USGS2016

Spectrally based mapping of riverbed composition

Remote sensing methods provide an efficient means of characterizing fluvial systems. This study evaluated the potential to map riverbed composition based on in situ and/or remote measurements of reflectance. Field spectra and substrate photos from the Snake River, Wyoming, USA, were used to identify different sediment facies and degrees of algal development and to quantify their optical characteristics. We hypothesized that accounting for the effects of depth and water column attenuation to isolate the reflectance of the streambed would enhance distinctions among bottom types and facilitate substrate classification. A bottom reflectance retrieval algorithm adapted from coastal research yielded realistic spectra for the 450 to 700 nm range; but bottom reflectance-based substrate classifications, generated using a random forest technique, were no more accurate than classifications derived from above-water field spectra. Additional hypothesis testing indicated that a combination of reflectance magnitude (brightness) and indices of spectral shape provided the most accurate riverbed classifications. Convolving field spectra to the response functions of a multispectral satellite and a hyperspectral imaging system did not reduce classification accuracies, implying that high spectral resolution was not essential. Supervised classifications of algal density produced from hyperspectral data and an inferred bottom reflectance image were not highly accurate, but unsupervised classification of the bottom reflectance image revealed distinct spectrally based clusters, suggesting that such an image could provide additional river information. We attribute the failure of bottom reflectance retrieval to yield more reliable substrate maps to a latent correlation between depth and bottom type. Accounting for the effects of depth might have eliminated a key distinction among substrates and thus reduced discriminatory power. Although further, more systematic study across a broader range of fluvial environments is needed to substantiate our initial results, this case study suggests that bed composition in shallow, clear-flowing rivers potentially could be mapped remotely.

Geomorphology↗
USGS2004

Sequestration of carbon in soil organic matter in Senegal: an overview

Sequestration of Carbon in Soil Organic Matter ( SOCSOM ) in Senegal is a multi-disciplinary development project planned and refined through two international workshops. The project was implemented by integrating a core of international experts in remote sensing, biogeochemical modeling, community socio-economic assessments, and carbon measurements in a fully collaborative manner with Senegal organizations, national scientists, and local knowledge and expertise. The study addresses the potential role developing countries in semi-arid areas can play in climate mitigation activities. Multiple benefits to smallholders could accrue as a result of management practices to re-establish soil carbon content lost because of land use changes or management practices that are not sustainable. The specific importance for the Sahel is because of the high vulnerability to climate change in already impoverished rural societies. The project focuses on four objectives in specific locations across the agroecological zones of Senegal. These objectives are: use of soil sampling and biogeochemical modeling to quantify the biophysical potential for carbon sequestration and to determine the sensitivity of the carbon stocks to various management and climate scenarios, to evaluate the socio-economic and cultural requirements necessary for successful project implementation directed toward an aggregation of smallholders to sequester around 100,000 t carbon (C), to support capacity building to develop a Carbon Specialist Team, and to initiate extrapolation from site-specific project areas to the Sahel region and the national level.

Journal of Arid Environments↗
USGS2023

2023 Coastal master plan: ICM-wetlands – Submerged aquatic vegetation (SAV) updates

Submerged aquatic vegetation (SAV) provides critical structural habitat for valuable nekton and wildlife species across coastal ecosystems and can buffer the negative effects of land loss. Landscape change and restoration efforts across coastal Louisiana can impact the occurrence, coverage, and species assemblages of SAV, and changes to these foundational species can have cascading impacts across food webs. To support the 2023 Coastal Master Plan efforts, a unique SAV model was developed to assess coverage and occurrence of SAV across aquatic waterbodies in response to environmental variables evaluated. This effort created a spatial model describing the probability of presence of SAV across the study area in response to changing conditions over the modeled time period. To develop the initial coverage data layer, we used remotely sensed Normalized Difference Vegetation Index (NDVI) and modified Normalized Difference Water Index (mNDWI) data from 2015-2018 to identify areas containing variable vegetation and water spectral reflectance. Key environmental variables evaluated included total suspended sediments (TSS), salinity, and physical exposure. Seasonal estimates for TSS and salinity were used, as research indicates that seasonal environmental variability is a significant driver for SAV establishment. Seasonal salinity was derived from Coast-wide Reference Monitoring Station (CRMS) data, and seasonal TSS was estimated from hyperspectral imagery. Estimates of physical exposure have previously been provided by calculating fetch (the distance across water over which waves can propagate), but this proved to be too computationally intensive to be feasible, and we found distance to land to be a reasonable proxy for exposure. To represent geographic conditions and historical factors influences on SAV establishment and occurrence (e.g., variables too numerous and complex to model) we developed a basin variable that served as a proxy for complex historical, or prior, conditions, determined by the forested, fresh, intermediate, brackish, or saline (FFIBS) score. The final model included spring TSS, spring salinity, distance to land, and the basin prior. The model performed well for the area evaluated, correctly classifying SAV (as present or absent) 89% of the time (Kappa = 580). SAV probability of presence responded as expected to change in these environmental variables, with likelihood of occurrence decreasing in response to increasing spring TSS, spring salinity, and distance to land. However, the model was more accurate at predicting absence (true negative = 0.940) than predicting presence (true positive = 0.626), suggesting that the scale of the model may limit the ability to predict presence. Moreover, the simplicity of the model limited the accuracy in highly dynamic environments, for example near the outflow of diversions or areas of significant changes in salinity or TSS. Through incorporating underwater communities like SAV, this master plan provides a holistic view of coastal change and restoration. To create healthy ecological structure and function in wetland habitats, the submergent communities must be considered alongside the emergent habitats. As the benefits of SAV are increasingly recognized, both here in Louisiana and beyond, SAV restoration and the use of SAV communities in assessing and improving ecological condition are becoming more common.

Louisiana↗
USGS2018

Identifying optimal remotely-sensed variables for ecosystem monitoring in Colorado Plateau drylands

Water-limited ecosystems often recover slowly following anthropogenic or natural disturbance. Multitemporal remote sensing can be used to monitor ecosystem recovery after disturbance; however, dryland vegetation cover can be challenging to accurately measure due to sparse cover and spectral confusion between soils and non-photosynthetic vegetation. With the goal of optimizing a monitoring approach for identifying both abrupt and gradual vegetation changes, we evaluated the ability of Landsat-derived spectral variables to characterize surface variability of vegetation cover and bare ground across a range of vegetation community types. Using three year composites of Landsat data, we modeled relationships between spectral information and field data collected at monitoring sites near Canyonlands National Park, UT. We also developed multiple regression models to assess improvement over single variables. We found that for all vegetation types, percent cover bare ground could be accurately modeled with single indices that included a combination of red and shortwave infrared bands, while near infrared-based vegetation indices like NDVI worked best for quantifying tree cover and total live vegetation cover in woodlands. We applied four models to characterize the spatial distribution of putative grassland ecological states across our study area, illustrating how this approach can be implemented to guide dryland ecosystem management.

Colorado Plateau↗
USGS2023

Benchmarking satellite-derived shoreline mapping algorithms

Satellite remote sensing is becoming a widely used monitoring technique in coastal sciences. Yet, no benchmarking studies exist that compare the performance of popular satellite-derived shoreline mapping algorithms against standardized sets of inputs and validation data. Here we present a new benchmarking framework to evaluate the accuracy of shoreline change observations extracted from publicly available satellite imagery (Landsat and Sentinel-2). Accuracy and precision of five established shoreline mapping algorithms are evaluated at four sandy beaches with varying geologic and oceanographic conditions. Comparisons against long-term in situ beach surveys reveal that all algorithms provide horizontal accuracy on the order of 10 m at microtidal sites. However, accuracy deteriorates as the tidal range increases, to more than 20 m for a high-energy macrotidal beach (Truc Vert, France) with complex foreshore morphology. The goal of this open-source, collaborative benchmarking framework is to identify areas of improvement for present algorithms, while providing a stepping stone for testing future developments, and ensuring reproducibility of methods across various research groups and applications.

Communications Earth & Environment↗
USGS2022

Use of high-resolution topobathymetry to assess shoreline topography and potential future development of a slack water harbor near Dardanelle, Arkansas, October 2021

The U.S. Army Corps of Engineers (USACE), Southwestern Division, Little Rock District Civil Works program has a mission to maintain cohesion between physical and naturally developed environments. The USACE authorized the development of an off-channel harbor (hereinafter referred to as the “proposed slack water harbor”) along the McClellan-Kerr Arkansas River Navigation System at river mile 202.6, and an initial evaluation of shoreline stability and adjacent land near the proposed harbor was considered essential in establishing a baseline for potential effects and future monitoring. In October 2021, the U.S. Geological Survey, in cooperation with the USACE, completed high-resolution bathymetric (underwater elevation) and topographic surveys of the Arkansas River and a quarry at the location of the proposed slack water harbor near Dardanelle, Arkansas, using a combination of multibeam sound navigation and ranging (sonar) and high-resolution, low-altitude aerial light detection and ranging (lidar) data to provide data and analysis needed for as-built information and future monitoring of river shoreline and floodplain management and maintenance. Bathymetric data were collected using a high-resolution multibeam mapping system, which consists of a multibeam echosounder and an inertial navigation system mounted on a marine survey vessel. Data were collected as the vessel traversed the river and quarry along overlapping survey lines distributed throughout the areas. Topographic data were collected as a lidar point cloud using an unmanned aircraft system (UAS) with a YellowScan Vx20–100 lidar payload, which consists of the lidar scanner and an inertial navigation system. The lidar point cloud data were collected as the UAS followed two sets of parallel transect lines, oriented perpendicular to each other (nominally north to south and east to west) on separate flights. The bathymetric and UAS topographic datasets were combined with topographic data extracted from publicly available aerial lidar data collected in 2014 to create a multisource point cloud classified as “ground” (code 2) according to the American Society for Photogrammetry and Remote Sensing standard lidar point classes in the proposed harbor area and surroundings, from which topographic contours were derived.

Arkansas↗
USGS2026

VegET evapotranspiration for Africa: Continental-scale simulation, multi-product evaluation, and drought assessment

Study region Continental Africa, encompassing diverse climatic zones—tropical, arid, and temperate—and spanning major transboundary river basins such as the Nile, Niger, Congo, Volta, and Zambezi River Basins. The region exhibits pronounced hydroclimatic gradients and heterogeneous land use systems ranging from rainfed croplands and rangelands to dense tropical forests and irrigated schemes. Study focus Actual evapotranspiration (ETa) is a central component of the terrestrial water balance, governing the redistribution of water and energy between the land surface and the atmosphere. Accurate estimation of ETa at continental scale is critical for hydrological monitoring, water resource management, and climate adaptation, as well as for quantifying water, energy, and carbon fluxes that underpin sustainable development. In this study, we applied the agro-hydrologic VegET v2 model to simulate a new, high-resolution, continental-scale ETa dataset for Africa (2000–2021). The model results were benchmarked against four widely used remote sensing-based products—MODIS16 v6.1, SSEBop v6.1, WaPOR v3, and GLEAM v4.1a—across major climate zones, land use types, and River Basins, providing a comprehensive multi-product evaluation of evapotranspiration dynamics across the continent. New hydrological insights for the region Validation against eddy covariance flux tower observations at eight representative sites confirmed that VegET v2 accurately reproduces the seasonal dynamics of observed ETa, achieving a correlation (r) of 0.8 and an RMSE of 25 mm month⁻¹ —accuracy that is comparable to or higher than accuracies of satellite-based products MODIS16, SSEBop, and GLEAM. This study represents one of the first Africa-wide hydrological simulations of ETa, extending the VegET model beyond basin-scale applications. Intercomparisons reveal that VegET aligns closely with MODIS16, SSEBop, and GLEAM in humid and tropical regions (r = 0.80–0.90; RMSE < 20 mm month⁻¹), while greater discrepancies appear in arid and semi-arid zones, where WaPOR tends to overestimate ETa (RMSE ≥ 28 mm month⁻¹). Despite these differences, VegET effectively captures spatial and temporal ETa variability across rainfed croplands, forests, and savannas, supporting its utility in regional water balance assessments, water accounting, and drought monitoring. A key application of VegET v2 is the Evapotranspiration Deficit Index (ETDI), derived by integrating VegET-based ETa with potential evapotranspiration (PET) to quantify water stress. ETDI successfully captured major drought episodes across Africa, including persistent Sahelian and southern African dry spells, the 2020–2021 winter drought in the Maghreb, and the 2018–2019 austral summer drought in southern Africa, while identifying positive anomalies over central Africa indicative of recurrent wetness. These results underscore VegET’s capability as a hydrologically consistent, operational tool for continental ETa monitoring and drought assessment, offering support for basin-scale water balance studies, food security planning, and climate resilience across Africa’s diverse hydrological environments.

Journal of Hydrology: Regional Studies↗
USGS2022

One shell of a problem: Cumulative threat analysis of male sea turtles indicates high anthropogenic threat for migratory individuals and Gulf of Mexico residents

Human use of oceans has dramatically increased in the 21st century. Sea turtles are vulnerable to anthropogenic stressors in the marine environment because of lengthy migrations between foraging and breeding sites, often along coastal migration corridors. Little is known about how movement and threat interact specifically for male sea turtles. To better understand male sea turtle movement and the threats they encounter, we satellite-tagged 40 adult male sea turtles of four different species. We calculated movement patterns using state-space modeling (SSM), and quantified threats in seven unique categories; shipping, fishing, light pollution, oil rigs, proximity to coast, marine protected area (MPA) status, and location within or outside of the U.S. Exclusive Economic Zone (EEZ). We found significantly higher threat severity in northern and southern latitudes for green turtles ( Chelonia mydas ) and Kemp’s ridleys ( Lepidochelys kempii ) in our study area. Those threats were pervasive, with only 35.9% of SSM points encountering no high threat exposure, of which 47% belong to just two individuals. Kemp’s ridleys were most exposed to high threats among tested species. Lastly, turtles within MPA boundaries face significantly lower threat exposure, indicating MPAs could be a useful conservation tool.

Remote Sensing↗