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At least 199 records · Page 11Linked to original sources
USGS2019

Monitoring live vegetation in semiarid and arid rangeland environments with satellite remote sensing in northern Kenya

As part of the U.S. Department of the Interior’s (DOI) commitment to provide technical assistance to the Kenyan Northern Rangelands Trust (NRT), the U.S. Geological Survey, in collaboration with the DOI International Technical Assistance Program and the U.S. Agency for International Development’s regional mission in East Africa, created a high spatial and time-sensitive live vegetation monitoring system for NRT. The system built with advanced field and sensor technologies produced directly calibrated and highly accurate satellite mapping that is extendable both forward and backward in time. The maps are produced in a simple 0–100-percent representation of live vegetation status and change over time. The backbone of the mapping is the Sentinel satellite remote sensing systems with 5-day collection frequencies and ground spatial resolutions of 10 meters. The European Space Agency (ESA) offers free Sentinel satellite image data through conveniently accessed websites and free user-friendly image processing software downloadable directly onto a personal workstation. ESA provides free online software support. The mapping capability was extended from the forward mapping of Sentinel back in time with the Landsat satellite remote sensing system that has an available and free data archive back to 1983. Although Landsat has coarser spatial resolution, the Landsat to Sentinel live vegetation mapping comparison supports the use of Landsat to provide NRT the historical recreation of prominent live vegetation changes.

Open-File Report↗
USGS2008

A Versatile Time-Lapse Camera System Developed by the Hawaiian Volcano Observatory for Use at Kilauea Volcano, Hawaii

Volcanoes can be difficult to study up close. Because it may be days, weeks, or even years between important events, direct observation is often impractical. In addition, volcanoes are often inaccessible due to their remote location and (or) harsh environmental conditions. An eruption adds another level of complexity to what already may be a difficult and dangerous situation. For these reasons, scientists at the U.S. Geological Survey (USGS) Hawaiian Volcano Observatory (HVO) have, for years, built camera systems to act as surrogate eyes. With the recent advances in digital-camera technology, these eyes are rapidly improving. One type of photographic monitoring involves the use of near-real-time network-enabled cameras installed at permanent sites (Hoblitt and others, in press). Time-lapse camera-systems, on the other hand, provide an inexpensive, easily transportable monitoring option that offers more versatility in site location. While time-lapse systems lack near-real-time capability, they provide higher image resolution and can be rapidly deployed in areas where the use of sophisticated telemetry required by the networked cameras systems is not practical. This report describes the latest generation (as of 2008) time-lapse camera system used by HVO for photograph acquisition in remote and hazardous sites on Kilauea Volcano.

Scientific Investigations Report↗
USGS2019

A preliminary assessment of hyperspectral remote sensing technology for mapping submerged aquatic vegetation in the Upper Delaware River National Parks

Hyperspectral remote sensing of submerged aquatic vegetation is a complex and difficult process that is affected by unique constraints on the energy flow profile near and below the water surface. In addition, shallow, winding, lotic systems, such as the Upper Delaware River, present additional remote sensing problems in the form of specular reflectance, variable depth and constituents in the water column and sometimes extremely weak signal strength due to absorption and scattering in the water column that can be statistically overwhelmed by the reflectance from upland vegetation in any individual image scene. Here we test hyperspectral imagery from the Civil Air Patrol’s (CAP), Airborne Real-time Cueing Hyperspectral Enhanced Recon (ARCHER) system in the scenic waters of two National Parks on the Upper Delaware River. A number of unique image processing problems were encountered, including specular reflectance from winding lotic systems, variable depth and flow dynamics of the riverine environment, and disproportionate signal strength from surface reflectance in this riverine environment. This were solved by applying a specular reflectance removal algorithm, applying field data collections to classification results and masking upland vegetation so as to not statistically overwhelm the weak reflectance signal from surface and near-surface water. Much was learned about conducting imaging spectroscopy in such difficult conditions. Significant results include successful mapping of SAV presenece/absence, advantages of upland masking of the reflectance signal, and a numkber of processing approaches that are unique to this environment. In this paper we summarize our results and identify unique issues that must be addressed in this environment

New Jersey, New York, Pennsylvania↗
USGS2019

US Topo Product Standard

This document defines a U.S. Geological Survey (USGS) digital topographic map. This map product series, named “US Topo,” is modeled on the now historical USGS 7.5-minute (1:24,000 scale) topographic map series produced and printed by the USGS from 1947 to 2006. US Topo maps have the same extent, scale, and general layout as the historical topographic maps. US Topo maps incorporate an orthorectified image (hereinafter referred to as “orthoimage”) and shaded relief image along with a selection of data that were included in the historical 7.5-minute topographic maps. Between June and September of 2017, the USGS transitioned the format of US Topo maps to be published, by using a geospatial extension, in an International Organization for Standardization (ISO) 32000-compliant Adobe® portable document format (PDF) that is called a “geospatial PDF.” Previously, US Topo maps were published, by using geospatial extensions patented by TerraGo® Technologies, in PDF in a format called a “GeoPDF®.” The geospatial PDF design allows a user to zoom in and out in a georeferenced environment, turn layers on and off, view or print any combination of layers, and print any portion of the map at the published scale. US Topo maps are intended to serve conventional map users by providing geographic information system (GIS) information in symbolized form in the customary topographic map layout. The maps are not intended for advanced GIS analysis applications. These products are built on standard coordinate systems and include full U.S. National Grid (USNG) lines, making US Topo maps particularly useful for emergency first-response operations. These maps are also used by traditional topographic map users, such as resource managers, planners, and recreational users who continue to have a need for the symbolized feature data contained in the 7.5-minute quadrangle maps. Full-size style sheet templates in PDF defining the placement of map elements, marginalia, and font sizes and styles accompany this standard. US Topo maps published as geospatial PDFs are fashioned to conform to these style sheets so that a user can print out a map at the 1:24,000, 1:25,000, or 1:20,000 scale using the dimensions of the traditional standard 7.5-minute quadrangle. Symbology and type specifications for feature content and detailed requirements for geospatial content will be published separately. This document is an update of the US Topo Product Standard published in 2011 (Cooley and others, 2011). It is applicable to all US Topo maps. Updates in this version include the introduction of an ISO 32000-compliant geospatial PDF as a new file format for published maps; new style sheet templates for 1:24,000-scale maps (conterminous United States and Hawaii), 1:25,000-scale maps (Alaska), and 1:20,000-scale maps (Puerto Rico and U.S. Virgin Islands); an updated US Topo Map Symbol attachment; minor updates to text, including changes to the features and layers included in the US Topo product and the sheet size of the US Topo maps; updated figures demonstrating the US Topo product; an updated metadata file containing map-specific information.

Techniques and Methods↗
USGS2016

A world of minerals in your mobile device

Mobile phones and other high-technology communications devices could not exist without mineral commodities. More than one-half of all components in a mobile device—including its electronics, display, battery, speakers, and more—are made from mined and semiprocessed materials (mineral commodities). Some mineral commodities can be recovered as byproducts during the production and processing of other commodities. As an example, bauxite is mined for its aluminum content, but gallium is recovered during the aluminum production process. The images show the ore minerals (sources) of some mineral commodities that are used to make components of a mobile device. On the reverse side, the map and table depict the major source countries producing these mineral commodities along with how these commodities are used in mobile devices. For more information on minerals, visit http://minerals.usgs.gov .

General Information Product↗
USGS2013

Applying UV cameras for SO 2 detection to distant or optically thick volcanic plumes

Ultraviolet (UV) camera systems represent an exciting new technology for measuring two dimensional sulfur dioxide (SO 2 ) distributions in volcanic plumes. The high frame rate of the cameras allows the retrieval of SO 2 emission rates at time scales of 1 Hz or higher, thus allowing the investigation of high-frequency signals and making integrated and comparative studies with other high-data-rate volcano monitoring techniques possible. One drawback of the technique, however, is the limited spectral information recorded by the imaging systems. Here, a framework for simulating the sensitivity of UV cameras to various SO 2 distributions is introduced. Both the wavelength-dependent transmittance of the optical imaging system and the radiative transfer in the atmosphere are modeled. The framework is then applied to study the behavior of different optical setups and used to simulate the response of these instruments to volcanic plumes containing varying SO 2 and aerosol abundances located at various distances from the sensor. Results show that UV radiative transfer in and around distant and/or optically thick plumes typically leads to a lower sensitivity to SO 2 than expected when assuming a standard Beer–Lambert absorption model. Furthermore, camera response is often non-linear in SO 2 and dependent on distance to the plume and plume aerosol optical thickness and single scatter albedo. The model results are compared with camera measurements made at Kilauea Volcano (Hawaii) and a method for integrating moderate resolution differential optical absorption spectroscopy data with UV imagery to retrieve improved SO 2 column densities is discussed.

Journal of Volcanology and Geothermal Research↗
USGS2025

Real-time oil spill concentration assessment through fluorescence imaging and deep learning

Oil spills may pose severe ecological and socioeconomic threats, necessitating rapid and accurate environmental assessment. Traditional assessment methods used to determine the extent of a spill including gas chromatography-mass spectrometry, satellite imaging, and visual surveys, are often time-consuming, expensive, and limited by weather conditions or sampling constraints. Furthermore, these methods frequently struggle to provide real-time data crucial for prompt decision-making during spill emergencies. This study addresses these limitations by combining fluorescence imaging, deep learning, a mobile application, and a data management system for automated and real-time oil spill assessment. Our approach leverages a convolutional neural network architecture for feature extraction coupled with a custom regression model, trained and evaluated on a self-curated comprehensive dataset of 1,530 fluorescence images from two distinct oil types, a napthalenic crude oil and an aromatic-napthalenic crude oil, at concentrations ranging from 0 to 500 mg/L. The proposed approach demonstrates superior performance compared to both traditional machine learning models and more complex deep learning architectures, achieving an R² score of 0.9958 and RMSE of 9.28. The application enables rapid, cost-effective field measurements with robust data tracking and analysis capabilities. This research advances oil spill monitoring technology with a scalable solution that balances accuracy, speed, and accessibility for real-time environmental assessment and emergency response.

Journal of Hazardous Materials↗
USGS2021

Influencing activity of bats by dimly lighting wind turbine surfaces with ultraviolet light

Wind energy producers need deployable devices for wind turbines that prevent bat fatalities. Based on the speculation that bats approach turbines after visually mistaking them for trees, we tested a potential light-based deterrence method. It is likely that the affected bats see ultraviolet (UV) light at low intensities. Here, we present the results of a multi-month experiment to cast dim, flickering UV light across wind turbine surfaces at night. Our objectives were to refine and test a practical system for dimly UV-illuminating turbines while testing whether the experimental UV treatment influenced the activity of bats, birds, and insects. We mounted upward-facing UV light arrays on turbines and used thermal-imaging cameras to quantify the presence and activity of night-flying animals. The results demonstrated that the turbines can be lit to the highest reaches of the blades with “invisible” UV light, and the animal responses to such experimental treatment can be concurrently monitored. The UV treatment did not significantly change nighttime bat, insect, or bird activity at the wind turbine. Our findings show how observing flying animals with thermal cameras at night can help test emerging technologies intended to variably affect their behaviors around wind turbines.

Animals↗
USGS2010

Use of EO-1 Hyperion data to calculate spectral band adjustment factors (SBAF) between the L7 ETM+ and Terra MODIS sensors

Different applications and technology developments in Earth observations necessarily require different spectral coverage. Thus, even for the spectral bands designed to look at the same region of the electromagnetic spectrum, the relative spectral responses (RSR) of different sensors may be different. In this study, spectral band adjustment factors (SBAF) are derived using hyperspectral Earth Observing-1 (EO-1) Hyperion measurements to adjust for the spectral band differences between the Landsat 7 (L7) Enhanced Thematic Mapper Plus (ETM+) and the Terra Moderate Resolution Imaging Spectroradiometer (MODIS) top-of-atmosphere (TOA) reflectance measurements from 2000 to 2009 over the pseudo-invariant Libya 4 reference standard test site.

Conference Paper↗
USGS2022

NABat ML: Utilizing deep learning to enable crowdsourced development of automated, scalable solutions for documenting North American bat populations

Bats play crucial ecological roles and provide valuable ecosystem services, yet many populations face serious threats from various ecological disturbances. The North American Bat Monitoring Program (NABat) aims to use its technology infrastructure to assess status and trends of bat populations, while developing innovative and community-driven conservation solutions. Here, we present NABat ML , an automated machine-learning algorithm that improves the scalability and scientific transparency of NABat acoustic monitoring. This model combines signal processing techniques and convolutional neural networks (CNNs) to detect and classify recorded bat echolocation calls. We developed our CNN model with internet-based computing resources (‘cloud environment’), and trained it on >600,000 spectrogram images. We also incorporated species range maps to improve the robustness and accuracy of the model for future ‘unseen’ data. We evaluated model performance using a comprehensive, independent, holdout dataset. NABat ML successfully distinguished 31 classes (30 species and a noise class) with overall weighted-average accuracy and precision rates of 92%, and ≥90% classification accuracy for 19 of the bat species. Using a single cloud-environment computing instance, the entire model training process took <16 h. Synthesis and applications . Our convolutional neural network (CNN)-based model, NABat ML , classifies 30 North American bat species using their recorded echolocation calls with an overall accuracy of 92%. In addition to providing highly accurate species-level classification, NABat ML and its outputs are compatible with Bayesian and other statistical techniques for measuring uncertainty in classification. Our model is open-source and reproducible, enabling future implementations as software on end-user devices and cloud-based web applications. These qualities make NABat ML highly suitable for applications ranging from grassroots community science initiatives to big-data methods developed and implemented by researchers and professional practitioners. We believe the transparency and accessibility of NABat ML will encourage broad-scale participation in bat monitoring, and enable development of innovative solutions needed to conserve North American bat species.

Journal of Applied Ecology↗
USGS1981

Mid-range sidescan-sonar images covering parts of proposed tracts for OCS lease sale 56 and contiguous areas, Manteo, Cape Fear, and adjacent quadrangles off North Carolina

The U.S. Geological Survey (USGS), in cooperation with the U.S. Bureau of Land Management (BLM) and the Lamont-Doherty Geological Observatory (LDGO), collected 335 km of mid-range sidescan-sonar data in some of the tracts proposed for inclusion in Federal OCS (Outer Continental Shelf) Oil and Gas Lease Sale 56 and in some contiguous areas (R.V. GYRE, September 18-25, 1980 [GYRE 80-9, leg 1]). The data were collected by use of the Sea Mark I mid-range sidescan-sonar system designed by International Submarine Technology, Ltd. (IST). This system surveys a swath having a width of approximately 2-1/2 km on each side of the deep-towed fish. Transducers were towed about 300 m above the bottom on a neutrally bouyant vehicle at a speed of 1-1/2 to 2 knots. Transducers were pulsed at 4-second intervals at a frequency of 27 kHz on one side and 30 kHz on the other. Data recorded on seven EPC recorders aboard ship included slant-range corrected port channel, starboard channel, and port and starboard channels; uncorrected port channel, starboard channel, and port and starboard channels, and a 3.5-kHz tuned-transducer record of the bottom. Fish height or the altitude above the bottom was recorded on a strip-chart recorder. Distance of the fish from the ship (slant range) was recorded by use of a sled-mounted 4.5-kHz transducer. Data recorded on sonograms lagged the 3.5-kHz tuned-transducer record and ship navigational fix by as much as 1 hour (2 km) owing to tow-cable length (up to 5 km). Navigation of the ship was by Loran-C at a 5-minute fix interval, supplemented by satellite fixes. Data are of excellent quality and bottom features several meters high and about 6-12 m wide can be identified. Figures 1 and 2 show the location of track lines in the Manteo (NI 18-2) quadrangle just east of Cape Hatteras where the upper slope within proposed lease tract areas was surveyed. Figures 3 and 4 show track lines in the Cape Fear (NI 18-7) and contiguous quadrangles where data were recorded over the outer Blake Plateau, the Continental Slope, and the upper Continental Rise. The original records may be examined at the U.S. Survey, Woods Hole, MA 02543. Microfilm copies of the data are available for purchase only from the National Geophysical and Solar-Terrestrial Data c,nt er, NOAA/EDIS/NGSDC, Code D621, 325 Broadway, Boulder, CO 80303 (303-497-6338).

North Carolina↗
USGS1991

Monitoring grasshopper and locust habitats in Sahelian Africa using GIS and remote sensing technology

Development programmes in Sahelian Africa are beginning to use geographic information system (GIS) technology. One of the GIS and remote sensing programmes introduced to the region in the late 1980s was the use of seasonal vegetation maps made from satellite data to support grasshopper and locust control. Following serious outbreaks of these pests in 1987, the programme addressed a critical need, by national and international crop protection organizations, to monitor site-specific dynamic vegetation conditions associated with grasshopper and locust breeding. The primary products used in assessing vegetation conditions were vegetation index (greenness) image maps derived from National Oceanic and Atmospheric Administration satellite imagery. Vegetation index data were integrated in a GIS with digital cartographic data of individual Sahelian countries. These near-real-time image maps were used regularly in 10 countries for locating potential grasshopper and locust habitats. The programme to monitor vegetation conditions is currently being institutionalized in the Sahel.

International Journal of Geographical Information ↗
USGS2019

Imaging spectroscopy for the detection, assessment and monitoring of natural and anthropogenic hazards

Natural and anthropogenic hazards have the potential to impact all aspects of society including its economy and the environment. Diagnostic data to inform decision-making are critical for hazard management whether for emergency response, routine monitoring or assessments of potential risks. Imaging spectroscopy (IS) has unique contributions to make via the ability to provide some key quantitative diagnostic information. In this paper, we examine a selection of key case histories representing the state of the art to gain an insight into the achievements and perspectives in the use of visible to shortwave infrared IS for the detection, assessment and monitoring of a selection of significant natural and anthropogenic hazards. The selected key case studies examined provide compelling evidence for the use of the IS technology and its ability to contribute diagnostic information currently unattainable from operational spaceborne Earth observation systems. User requirements for the applications were also evaluated. The evaluation showed that the projected launch of spaceborne IS sensors in the near-, mid and long term future, together with the increasing availability, quality and moderate cost of off the shelf sensors, the possibilities to couple unmanned autonomous systems with miniaturized sensors, should be able to meet these requirements. The challenges and opportunities for the scientific community in the future when such data become available will then be ensuring consistency between data from different sensors, developing techniques to efficiently handle, process, integrate and deliver the large volumes of data, and most importantly translating the data to information that meets specific needs of the user community in a form that can be digested/understood by them. The latter is especially important to transforming the technology from a scientific to an operational tool. Additionally, the information must be independently validated using current trusted practices and uncertainties quantified before IS derived measurement can be integrated into operational monitoring services.

Colorado↗
USGS2014

Autonomous bed-sediment imaging-systems for revealing temporal variability of grain size

We describe a remotely operated video microscope system, designed to provide high-resolution images of seabed sediments. Two versions were developed, which differ in how they raise the camera from the seabed. The first used hydraulics and the second used the energy associated with wave orbital motion. Images were analyzed using automated frequency-domain methods, which following a rigorous partially supervised quality control procedure, yielded estimates to within 20% of the true size as determined by on-screen manual measurements of grains. Long-term grain-size variability at a sandy inner shelf site offshore of Santa Cruz, California, USA, was investigated using the hydraulic system. Eighteen months of high frequency (min to h), high-resolution (μm) images were collected, and grain size distributions compiled. The data constitutes the longest known high-frequency record of seabed-grain size at this sample frequency, at any location. Short-term grain-size variability of sand in an energetic surf zone at Praa Sands, Cornwall, UK was investigated using the ‘wave-powered’ system. The data are the first high-frequency record of grain size at a single location of a highly mobile and evolving bed in a natural surf zone. Using this technology, it is now possible to measure bed-sediment-grain size at a time-scale comparable with flow conditions. Results suggest models of sediment transport at sandy, wave-dominated, nearshore locations should allow for substantial changes in grain-size distribution over time-scales as short as a few hours.

California↗
USGS2007

Optical data processing and projected applications of the ERTS-1 imagery covering the 1973 Mississippi River Valley floods

Flooding along the Mississippi River and some of its tributaries was detected by the multispectral scanner (MSS) on the Earth Resources Technology Satellite (ERTS-1) on at least three orbits during the spring of 1973. The ERTS data provided the first opportunity for mapping the regional extent of flooding at the time of the imagery. Special optical data processing techniques were used to produce a variety of multispectral color composites enhancing flood-plain details. One of these, a 2-color composite of near infrared bands 6 and 7, was enlarged and registered to 1:250,000-scale topographic maps and used as the basis for preparation of flood image maps. Two specially filtered 3-color composites of MSS bands 5, 6, and 7 and 4, 5, and 7 were prepared to aid in the interpretation of the data. The extent of the flooding was vividly depicted on a single image by 2-color temporal composites produced on the additive-color viewer using band 7 flood data superimposed on pre-flood band 7 images. On May 24, when the floodwaters at St. Louis receded to bankfull stage, imagery was again obtained by ERTS. Analysis of temporal data composites of the pre-flood and post-flood band 7 images indicate that changes in surface reflectance characteristics caused by the flooding can be delineated, thus making it possible to map the overall area flooded without the necessity of a real-time system to track and image the peak flood waves. Regional planning and disaster relief agencies such as the Corps of Engineers, Office of Emergency Preparedness, Soil Conservation Service, interstate river basin commissions and state agencies, as well as private lending and insurance institutions, have indicated strong potential applications for ERTS image-maps of flood-prone areas.

Mississippi River↗
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↗
USGS1995

Deep tunnel detection using crosshole radar tomography

As part of continuing research aimed at the detection of subsurface tunnels and voids, the U.S. Bureau of Mines recently completed a cooperative study with the U.S. Geological Survey at a surface gold mine in the Black Hills mining district of South Dakota. The occurrence of older, poorly mapped mine workings in the section create a consistent health and safety concern for mine employees as well as economic concerns about potential damage to equipment during daily operations at the mine. Accurate knowledge regarding the location of these abandoned tunnels prior to interception by the current mining operation would be beneficial. Previous research efforts on site have demonstrated the suitability of several surface geophysical technologies in detecting shallow workings which present an immediate problem in the safe conduct of the mine operation. Another concern is the existence of deeper abandoned mine tunnels, which occur further in advance of the surface mining operation. In the design and development of a new mine pit, the placement of access roads over a tunnel would be hazardous, due to the volume of traffic and the weight these haulage trucks can carry. In this study we evaluate cross borehole radar tomography methods which might be used to image mine openings in the deep subsurface, and lead to more prudent placement of pit haulage roadways. A pulsed radar system was used to collect both velocity and amplitude information about local rock conditions, and multiple borehole data allowed for the use of 3-D imaging techniques.

South Dakota↗
USGS2016

MODIS imagery improves pest risk assessment: A case study of wheat stem sawfly (Cephus cinctus, Hymenoptera: Cephidae) in Colorado, USA

Wheat stem sawfly ( Cephus cinctus Norton, Hymenoptera: Cephidae) has long been a significant insect pest of spring, and more recently, winter wheat in the northern Great Plains. Wheat stem sawfly was first observed infesting winter wheat in Colorado in 2010 and, subsequently, has spread rapidly throughout wheat production regions of the state. Here, we used maximum entropy modeling (MaxEnt) to generate habitat suitability maps in order to predict the risk of crop damage as this species spreads throughout the winter wheat-growing regions of Colorado. We identified environmental variables that influence the current distribution of wheat stem sawfly in the state and evaluated whether remotely sensed variables improved model performance. We used presence localities of C. cinctus and climatic, topographic, soils, and normalized difference vegetation index and enhanced vegetation index data derived from Moderate Resolution Imaging Spectroradiometer (MODIS) imagery as environmental variables. All models had high performance in that they were successful in predicting suitable habitat for C. cinctus in its current distribution in eastern Colorado. The enhanced vegetation index for the month of April improved model performance and was identified as a top contributor to MaxEnt model. Soil clay percent at 0–5 cm, temperature seasonality, and precipitation seasonality were also associated with C. cinctus distribution in Colorado. The improved model performance resulting from integrating vegetation indices in our study demonstrates the ability of remote sensing technologies to enhance species distribution modeling. These risk maps generated can assist managers in planning control measures for current infestations and assess the future risk of C. cinctus establishment in currently uninfested regions.

Colorado↗