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USGS2021

Integrating airborne and mobile lidar data with UAV photogrammetry for rapid assessment of changing forest snow depth and cover

Forest structure and topography can influence the ecohydrologic function and resiliency to drought and changing climate. It is, therefore, important to understand how forest restoration treatments alter snowpack distribution and design the treatments accordingly. We use a combination of aerial lidar, multi-temporal terrestrial mobile lidar, and UAV photogrammetry to estimate rapidly changing snow depth and cover in northern Arizona, USA. We then examine the impact of forest structure and topography on snow depth and snow cover persistence to inform forest restoration treatments. Our results show that mobile lidar data can be used to estimate snow depth with standard errors of 8 cm when differenced with snow-off airborne lidar data. UAV-based Structure-from-Motion data can be used to estimate snow cover persistence with 92–97% overall accuracies in forested ecosystems. Random forest models indicate spatially varying importance of forest structural and topographic variables in predicting snow depth and cover persistence, when summarized at different spatial scales (from 5 m to 250 m) and with variable directional location offsets. Forest snow depth was best explained (R 2 ≈ 0.46) by canopy height metrics at summary scales of >75 m, while canopy cover was most important at summary scales of <40 m (R 2 ≈ 0.3). Snow cover persistence was best explained at very local scales by canopy cover (R 2 ≈ 0.38) and less so at larger scales (>75 m) by topographic and forest patch characteristics (R 2 ≈ 0.34). Our results demonstrate that 3-dimensional datasets are critical in rapidly characterizing changing snowpack to better understand the impacts of forest structure and topography to inform forest restoration treatment designs. The relationships observed in our study can inform currently ongoing regional-scale forest restoration in the southwest to improve forest health and resiliency.

Science of Remote Sensing↗

USGS2017

Value of information analysis as a decision support tool for biosecurity

This chapter demonstrates the economic concept of ‘value of information’(VOI), and how biosecurity managers can use VOI analysis to decide whether or not to reduce uncertainty by collecting additional information through monitoring, experimentation, or some other form of research. We first explore how some uncertainties may be scientifically interesting to resolve, but ultimately irrelevant to decision-making. We then develop a prototype model where a manager must choose between eradication or containment of an infestation. Eradication is more cost-effective for smaller infestations, but once the extent reaches a certain size it becomes more cost-effective to contain. When choosing between eradication and containment, how much does knowing the extent of the infestation more exactly improve the outcome of the decision? We calculate the expected value of perfect information (EVPI) about the extent, which provides an upper limit for the value of reducing uncertainty. We then illustrate the approach using the example of red imported fire ant management in south-east Queensland. We calculate the EVPI for three different uncertain variables: the extent of the infestation, the sensitivity (true positive rate) of remote sensing, and the efficacy of baiting.

Book chapter↗

USGS2006

National Institute of Invasive Species Science (NIISS)

The National Institute of Invasive Species Science (www.NIISS.org) is a consortium of governmental and nongovernmental partners, led by the U.S. Geological Survey (USGS), whose aim is to provide reliable information and advanced decision support tools for documenting, understanding, predicting, assessing, and addressing the threat of invasive species in the United States. The Institute coordinates the National Aeronautical and Space Administrationa??s (NASAa??s) Invasive Species National Application activities for the Department of the Interior and has al lead role in developing NASA-derived remote sensing and landscape-scale predictive modeling capabilities for the invasive species community.

Fact Sheet↗

USGS2012

Integrated monitoring of ecological conditions in wetland-upland landscapes

Landscapes of interwoven wetlands and uplands offer a rich set of ecosystem goods and services. Managing lands to maximize ecosystem services requires information that distinguishes change caused by local actions from broader-scale shifts in climate, land use, and other forms of global change. Satellite and airborne sensors collect valuable data for this purpose, especially when the data are analyzed along with data collected from ground-based sensors. The U.S. Geological Survey (USGS) is using remote sensing technology in this way as part of the Terrestrial Wetland Global Change Research Network to assess effects of climate change interacting with land-use change and other potential stressors along environmental gradients of wetland-upland landscapes in the United States and Canada.

Fact Sheet↗

USGS2026

Monitoring changes in Landsat thermal features in urban and non-urban interfaces from 1986 to 2023 in two international urban centers: Implications for climate and global issues

Rapid urbanization is reshaping thermal environments worldwide, with the strongest impacts occurring at the interface between urban and non-urban areas. Impervious surfaces, as key indicators of urban expansion, are critical for monitoring urban growth and assessing surface urban heat island (SUHI) effects. Land use and land cover change (LULCC) provides an essential link between urban dynamics and their environmental and societal consequences. Here, we integrated the U.S. Geological Survey (USGS) Climate Global Issues (CGI) Land Cover Product with Landsat thermal time-series to investigate SUHI evolution in two contrasting metropolitan regions: Wuhan, China, and Brasília, Brazil. Using data spanning 1986–2023, we analyzed the relationships between land cover, Landsat-based land surface temperature (LST), and SUHI intensity, and identified persistent thermal hotspots. Results demonstrate that the land cover data utilized increases the accuracy of impervious surface mapping along urban–rural gradients. Average SUHI intensities were 3.4 °C in Wuhan and 3.3 °C in Brasília, with statistically significant warming trends of 0.04 °C/year and 0.01 °C/year, respectively. Maximum temperature proved to be a robust indicator of SUHI intensification, capturing long-term upward trends. Our findings highlight the important role of urban land cover dynamics in shaping temporal SUHI variability and hotspot emergence. This prototype framework demonstrates the scientific and policy value of combining long-term land cover monitoring information with satellite thermal monitoring to quantify and track SUHI at city scale, supporting sustainable urban planning and climate adaptation strategies.

Remote Sensing↗

USGS2005

Volcano surveillance by ACR silver fox

Recent growth in the business of unmanned air vehicles (UAVs) both in the US and abroad has improved their overall capability, resulting in a reduction in cost, greater reliability and adoption into areas where they had previously not been considered. Uses in coastal and border patrol, forestry and agriculture have recently been evaluated in an effort to expand the observed area and reduce surveillance and reconnaissance costs for information gathering. The scientific community has both contributed and benefited greatly in this development. A larger suite of light-weight miniaturized sensors now exists for a range of applications which in turn has led to an increase in the gathering of information from these autonomous vehicles. In October 2004 the first eruption of Mount St Helens since 1986 caused tremendous interest amoUg people worldwide. Volcanologists at the U.S. Geological Survey rapidly ramped up the level of monitoring using a variety of ground-based sensors deployed in the crater and on the flanks of the volcano using manned helicopters. In order to develop additional unmanned sensing methods that can be used in potentially hazardous and low visibility conditions, a UAV experiment was conducted during the ongoing eruption early in November. The Silver Fox UAV was flown over and inside the crater to perform routine observation and data gathering, thereby demonstrating a technology that could reduce physical risk to scientists and other field operatives. It was demonstrated that UAVs can be flown autonomously at an active volcano and can deliver real time data to a remote location. Although still relatively limited in extent, these initial flights provided information on volcanic activity and thermal conditions within the crater and at the new (2004) lava dome. The flights demonstrated that readily available visual and infrared video sensors mounted in a small and relatively low-cost aerial platform can provide useful data on volcanic phenomena. This was made possible by utilizing GPS and computer-controlled flight direction and stabilization to acquire and track target areas within the Mount St. Helens crater. It was also determined that additional light-weight sensor development will be needed to enable autonomous measurements of volcanic gasses and imaging in poor-weather conditions. Copyright ?? 2005 by the American Institute of Aeronautics and Astronautics, Inc. All rights reserved.

Conference Paper↗

USGS2015

Landsat maps (phase V, deliverable 60), ASTER maps (phase V, deliverable 62), ASTER_DEM maps (phase V, deliverable 63), and spectral remote sensing in support of PRISM-II mineral resource assessment project, Islamic Republic of Mauritania (phase V, deliverables 61 and 64)

Multispectral satellite data acquired by the Landsat 5 Thematic Mapper (TM), Landsat 7 Enhanced Thematic Mapper Plus (ETM+), and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) sensors were processed and interpreted in support of the PRISM-II project (Second Projet de Renforcement Institutionnel du Secteur Minier de la Republique Islamique de Mauritanie). This report and accompanying maps constitute project deliverables 60–64. All digital data for use in Geographic Information System (GIS) and image processing software will be included in the GIS deliverable 92. Image maps in PDF format of the processed Landsat and ASTER scenes are referenced in the appendixes. Samples of rock, alluvium, colluvium, and (or) eolian sediments were collected at 41 locations during the 2007 field campaign. A point shapefile (“IRM07_sample_gps_points.shp”) containing these locations will be included in GIS deliverable 92. Most of the samples were characterized in the laboratory using a full-range ASD™ (Analytical Spectral Devices) FieldSpec II spectrometer. The image products derived from Landsat TM and ASTER data enable the delineation of mineral groups across wide areas based on color response. Guides are provided that allow users to interpret these colors as to mineral group occurrence over lithologic units and known deposits. This information can be extrapolated to other geologically permissive tracts for various deposit types in the search for similar mineralogic responses that may be indicative of concealed deposits.

Open-File Report↗

USGS2026

A conceptual framework and methods for studying the connectivity of fishes

Connectivity is a multifaceted concept that has important implications for the management and conservation of marine and freshwater fishes. We developed a conceptual framework that encompasses multiple, interrelated categories of connectedness, including landscape (e.g., structural, functional) connectivity and ecological (e.g., trophic, genetic, demographic) connectivity, that together shape the flow of organisms, energy and information across ecosystems. We also synthesised six key methods that can be used to study connectivity of fishes: (1) telemetry, including satellite, acoustic, radio and passive integrated transponders (PIT), (2) mark-recapture, (3) environmental tracers, including stable isotopes and otolith-microchemistry, (4) genetics, (5) community structure analysis and (6) emerging technologies and tools (e.g., remote sensing and artificial intelligence). For each method, we describe the categories of connectivity it can assess and provide real-world examples where they have been effectively used. We also identify limitations of each method. This article highlights the diverse and evolving toolbox of methods used to assess fish connectivity, underscoring the need for continued collaboration, innovation and integration of new approaches to refine our understanding and address remaining challenges in this critical area of aquatic ecology and fisheries management.

Fish and Fisheries↗

USGS2022

Foraging ecology of Red-billed Tropicbird Phaethon aethereus in the Caribbean during early chick rearing revealed by GPS tracking

Investigating the foraging patterns of tropical seabirds can provide important information about their ocean habitat affinities as well as prey choice. Foraging studies of Red-billed Tropicbird Phaethon aethereus populations in the Caribbean are lacking. We sought to rectify this by opportunistically sampling regurgitates at nest sites on the island of St. Eustatius, Lesser Antilles, and by linking the GPS tracks of foraging adults to remotely sensed environmental variables. Diet samples were dominated by Exocoetidae (59.5%) and Belonidae (14.9%), although we were unable to identify 25.5% of samples due to digestion. Tropicbirds nesting on St. Eustatius exhibited diurnal foraging patterns, foraged in deeper waters with higher chlorophyll concentration, and consumed fewer Exocoetidae species compared to travelling behaviour. The maximum distance travelled from the colony was 953.7 km, with an average trip length of 176.8 (± 249.8) km. The biologged birds crossed multiple exclusive economic zones and marine protected areas, and on that basis, we suggest that efforts to protect and conserve this species may require transboundary collaboration throughout the wider Caribbean.

Marine Ornithology: Journal of Seabird Research an↗

USGS2001

Recognition of fiducial surfaces in lidar surveys of coastal topography

A new method for the recognition and mapping of surfaces in coastal landscapes that provide accurate and low variability topographic measurements with respect to airborne lidar surveys is described and demonstrated in this paper. Such surfaces are herein termed "fiducial" because they can represent reference baseline morphology in Studies of coastal change due to natural or anthropogenic causes. Non-fiducial surfaces may also be identified in each separate lidar survey to be used in a given geomorphic change analysis. Sites that are non-fiducial in either or both lidar surveys that bracket the time period under investigation may be excluded from consideration in subsequent calculations of survey-to-survey elevation differences to eliminate spurious indications of landscape change. This new analysis method, or lidar fiducial surface recognition (LFSR) algorithm, is intended to more fully enable the non-ambiguous Use of topographic lidar in a range of coastal investigations. The LFSR algorithm may be widely applied, because it is based solely on the information inherent in the USGS/NASA/NOAA airborne topographic lidar coverage that exists for most of the contiguous U.S. coastline.

Photogrammetric Engineering and Remote Sensing↗

USGS2002

Preliminary United States-Mexico border watershed analysis, twin cities area of Nogales, Arizona and Nogales, Sonora

The United States - Mexico border area faces the challenge of integrating aspects of its binational physical boundaries to form a unified or, at least, compatible natural resource management plan. Specified geospatial components such as stream drainages, mineral occurrences, vegetation, wildlife, and land-use can be analyzed in terms of their overlapping impacts upon one another. Watersheds have been utilized as a basic unit in resource analysis because they contain components that are interrelated and can be viewed as a single interactive ecological system. In developing and analyzing critical regional natural resource databases, the Environmental Protection Agency (EPA) and other federal and non-governmental agencies have adopted a ?watershed by watershed? approach to dealing with such complicated issues as ecosystem health, natural resource use, urban growth, and pollutant transport within hydrologic systems. These watersheds can facilitate the delineation of both large scale and locally important hydrologic systems and urban management parameters necessary for sustainable, diversified land-use. The twin border cities area of Nogales, Sonora and Nogales, Arizona, provide the ideal setting to demonstrate the utility and application of a complete, cross-border, geographic information systems (GIS) based, watershed analysis in the characterization of a wide range of natural resource as well as urban features and their interactions. In addition to the delineation of a unified, cross-border watershed, the database contains sewer/water line locations and status, well locations, geology, hydrology, topography, soils, geomorphology, and vegetation data, as well as remotely sensed imagery. This report is preliminary and part of an ongoing project to develop a GIS database that will be widely accessible to the general public, researchers, and the local land management community with a broad range of application and utility.

Arizona, Sonora↗

USGS1975

The EROS Data Center

The EROS Data Center, 16 miles (25 km) northeast of Sioux Falls, South Dakota, is operated by the EROS Program to provide access to NASA's LANDSAT [formerly Earth Resources Technology Satellite (ERTS)] imagery, aerial photography acquired by the U.S. Department of the Interior, and photography and imagery acquired by the National Aeronautics and Space Administration (NASA) from research aircraft and from Skylab, Apollo, and Gemini spacecraft. The primary functions of the Center are data storage and reproduction, and user assistance and training. This publication describes the Data Center operations, data products, services, and procedures for ordering remotely sensed data. The EROS Data Center and its principal facility, the 120,000-square-foot (11,200 m 2 ) Karl E. Mundt Federal Building, were dedicated August 7, 1973.

General Information Product↗

USGS2021

Vegetation monitoring optimization with normalized difference vegetation index and evapotranspiration using remote sensing measurements and land surface models over East Africa

The majority of people in East Africa rely on the agro-pastoral system for their livelihood, which is highly vulnerable to droughts and flooding. Agro-pastoral droughts are endemic to the region and are considered the main natural hazard that contributes to food insecurity. Drought begins with rainfall deficit, gradually leading to soil moisture deficit, higher land surface temperature, and finally impacts to vegetation growth. Therefore, monitoring vegetation conditions is essential in understanding the progression of drought, potential effects on food security, and providing early warning information needed for drought mitigation decisions. Because vegetation processes couple the land and atmosphere, monitoring of vegetation conditions requires consideration of both water provision and demand. While there is consensus in using either the Normalized Difference Vegetation Index (NDVI) or evapotranspiration (ET) for vegetation monitoring, a comprehensive assessment optimizing the use of both has not yet been done. Moreover, the evaluation methods for understanding the relationships between NDVI and ET for vegetation monitoring are also limited. Taking these gaps into account we have developed a framework to optimize vegetation monitoring using both NDVI and ET by identifying where they perform the best by using triple collocation and cross-correlation methods. We estimated the random error structure in Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI; ET from the Operational Simplified Surface Energy Balance (SSEBop) model; and ET from land surface models (LSMs). LSM ET and SSEBop ET have been found to be better indicators for vegetation monitoring during extreme drought events, while NDVI could provide better information on vegetation condition during wetter than normal conditions. The random error structures of these variables suggest that LSM ET is most likely to provide important information for vegetation monitoring over low and high ends of the vegetation fraction areas. Over moderate vegetative areas, any of these variables could provide important vegetation information for drought characterization and food security assessments. While this study provides a framework for optimizing vegetation monitoring for drought and food security assessments over East Africa, the framework can be adopted to optimize vegetation monitoring over any other drought and food insecure region of the world.

Frontiers in Climate↗

USGS2021

Remote sensing inventory and geospatial analysis of brick kilns and clay quarrying in Kabul, Afghanistan

Reconstruction and urban development in Kabul, Afghanistan, has prompted vast expansion of the clay quarrying and brick making industry. This study identified the extent and distribution of clay quarrying and brick kilns in the greater Kabul area between 1965 and 2018. Very high-resolution satellite imagery was interpreted to quantify and characterize the type, number, and location of brick kilns for 1965, 2004, 2011, and 2018. Geospatial analysis of kilns together with geologic data and the results of hyperspectral image analysis yielded information regarding the extent of relevant mineral resources. Finally, kernel density analysis of kiln locations for each date called attention to their shifting spatial distribution. The study found that the clay quarrying and brick making industry has expanded exponentially. The type of kilns has transitioned from artisanal style clamp kilns to small-scale Bull’s Trench Kilns (BTK), and ultimately to Fixed Chimney Bull’s Trench Kilns (FCBTK). While quarrying has occurred entirely within quaternary windblown loess and clay deposits, artisanal clamp kilns were located in fine sediments containing montmorillonite and FCBTKs have developed in sediments containing calcite and muscovite. The study’s inventory of kilns was then used to estimate kiln workforce at 27,500 workers and production at 1.579 billion bricks per year.

Kabul↗

USGS2019

Investigating lake-area dynamics across a permafrost-thaw spectrum using airborne electromagnetic surveys and remote sensing time-series data in Yukon Flats, Alaska

Lakes in boreal lowlands cycle carbon and supply an important source of freshwater for wildlife and migratory waterfowl. The abundance and distribution of these lakes are supported, in part, by permafrost distribution, which is subject to change. Relationships between permafrost thaw and lake dynamics remain poorly known in most boreal regions. Here, new airborne electromagnetic (AEM) data collected during June 2010 and February 2016 were used to constrain deep permafrost distribution. AEM data were coupled with Landsat-derived lake surface-area data from 1979 through 2011 to inform temporal lake behavior changes in the 35 500- km 2 Yukon Flats ecoregion of Alaska. Together, over 1500 km of AEM data, and roughly 30 years of Landsat data were used to explore processes that drive lake dynamics across a variety of permafrost thaw states not possible in studies conducted with satellite imagery or field measurements alone. Clustered time-series data identified lakes with similar temporal dynamics. Clusters possessed similarities in lake permanence (i.e. ephemeral versus perennial), subsurface permafrost distribution, and proximity to rivers and streams. Of the clustered lakes, ~66% are inferred to have at least intermittent connectivity with other surface-water features, ~19% are inferred to have shallow subsurface connectivity to other surface water features that served as a low-pass filter for hydroclimatic fluctuations, and ~15% appear to be isolated by surrounding permafrost (i.e. no connectivity). Integrated analysis of AEM and Landsat data reveals a progression from relatively synchronous lake dynamics among disconnected lakes in the most spatially continuous, thick permafrost to quite high spatiotemporal heterogeneity in lake behavior among variably-connected lakes in regions with notably less continuous permafrost. Variability can be explained by the preferential development of thawed permeable gravel pathways for lateral water redistribution in this area. The general spatial progression in permafrost thaw state and lake area behavior may be extended to the temporal dimension. However, extensive permafrost thaw, beyond what is currently observed, is expected to promote ubiquitous subsurface connectivity, eventually evolving to a state of increased lake synchronicity.

Alaska↗

USGS2005

Digital method for regional mapping of surficial basin deposits in arid regions, example from central Death Valley, Inyo County, California

Derivative maps generated from DEM's and panchromatic remote sensing data (TM Landsat 7 or SPOT) can be used to characterize surficial basin deposits in arid regions dominated by basin and range topography. Results indicate the technique is useful for rapid digital mapping of surficial deposits where a first order, systematic subdivision of bedrock, alluvial fan units, and playas is unavailable at regional scales. Digital mapping can provide information about relative age and material properties of units that in part can be derived from the position of units within the basin. This automated mapping, implemented in a GIS system, involves an iterative process applied to a combination of digital elevation models (DEM) and satellite image data, such as SPOT or the high-resolution panchromatic Band 8 of Landsat 7 scenes. The method first discriminates the region into first-order terrains consisting of bedrock mountain highlands, basin piedmonts, and playa-basin interiors based on user-defined slope cutoffs applied to DEM data. The basin areas are subsequently classified into surficial map units such as active channels, ground-water discharge zones, and multiple age alluvial-fan piedmont units based on reflective properties of the associated surfaces in the satellite imagery. The surficial units are differentiated through systematic classification based on specific user-defined ranges of spectral values for each unit. The spectral ranges used in the classification are largely dependent on the composite effects of surface characteristics and material properties, including depositional morphology and texture, pavement development, degree of surface clast varnishing, and (or) properties of exposed soils of the alluvial fan units. We have used the slope-curvature properties derived from the DEM data to discriminate the bajada areas that exhibit non-unique spectral characteristics. Slope curvature is particularly effective at differentiating young undissected surfaces from older dissected piedmont units. Available geologic maps and field observations may be used both to iteratively calibrate the spectral classification scheme and to provide additional verification of the digital map output. Digital mapping combined with detailed field studies in selected areas provides useful regional maps of surficial units until time and funding is available for more field intensive studies. In addition, anomalous areas on the thematic maps indicate where more detailed field or air photo work is warranted. The technique successfully distinguishes between bedrock, alluvial fans (generally multiple fan units), active washes, playas, playa rimming marshes and seeps and other active and inactive discharge zones in arid basin and mountain regions. Limitations occur in the subdivision of some fan units where the dominant detrital clast lithologies are not susceptible to varnish development.

California↗

USGS2012

Alluvial diamond resource potential and production capacity assessment of Guinea

In May of 2000, a meeting was convened in Kimberley, South Africa, by representatives of the diamond industry and leaders of African governments to develop a certification process intended to assure that export shipments of rough diamonds were free of conflict concerns. Outcomes of the meeting were formally supported later in December of 2000 by the United Nations in a resolution adopted by the General Assembly. By 2002, the Kimberley Process Certification Scheme (KPCS) was ratified and signed by diamond-producing and diamond-importing countries. The goal of this study was to estimate the alluvial diamond resource endowment and the current production capacity of the alluvial diamond mining sector of Guinea. A modified volume and grade methodology was used to estimate the remaining diamond reserves within Guinea's diamondiferous regions, while the diamond-production capacity of these zones was estimated by inputting the number of artisanal miners, the number of days artisans work per year, and the average grade of the deposits into a formulaic expression. Guinea's resource potential was estimated to be approximately 40 million carats, while the production capacity was estimated to lie within a range of 480,000 to 720,000 carats per year. While preliminary results have been produced by integrating historical documents, five fieldwork campaigns, and remote sensing and GIS analysis, significant data gaps remain. The artisanal mining sector is dynamic and is affected by a variety of internal and external factors. Estimates of the number of artisans and deposit variables, such as grade, vary from site to site and from zone to zone. This report has been developed on the basis of the most detailed information available at this time. However, continued fieldwork and evaluation of artisanally mined deposits would increase the accuracy of the results.

Scientific Investigations Report↗

USGS2019

Mapping a keystone shrub species, huckleberry (Vaccinium membranaceum), using seasonal colour change in the Rocky Mountains

Black huckleberries ( Vaccinium membranaceum ) provide a critical food resource to many wildlife species, including apex omnivores such as the grizzly bear ( Ursus arctos ), and play an important socioeconomic role for many communities in western North America, especially indigenous peoples. Remote sensing imagery offers the potential for accurate landscape-level mapping of huckleberries because the shrub changes colour seasonally. We developed two methods, for local and regional scales, to map a shrub species using leaf seasonal colour change from remote sensing imagery. We assessed accuracy with ground-based vegetation surveys. The high-resolution supervised random forest classification from one-meter resolution National Agricultural Imagery Program (NAIP) imagery achieved an overall accuracy of 75.31% (kappa = 0.26). The approach using multi-temporal 30-meter Landsat imagery similarly had an overall accuracy of 79.19% (kappa = .31). We found underprediction error was related to higher forest cover and a lack of visible colour change on the ground in some plots. Where forest cover was low, both models performed better. In areas with <10% forest cover, the high-resolution classification achieved an accuracy of 80.73% (kappa = 0.48), while the Landsat model had an accuracy of 82.55% (kappa = 0.47). Based on the fine-scale predictions, we found that 94% of huckleberry shrubs identified in our study area of Glacier National Park, Montana, USA are over 100 meters from human recreation trails. This information could be combined with productivity and phenology information to estimate the timing and availability of food resources for wildlife and to provide managers with a tool to identify and manage huckleberries. The development of the multi-temporal Landsat models sets the stage for assessment of impacts of disturbance at regional scales on this ecologically, culturally, and economically important shrub species. Our approach to map huckleberries is straightforward, efficient and accessible to wildlife and environmental managers and researchers in diverse fields.

Montana↗