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62 records · Page 4Linked to original sources
USGS2020

A pan-African high-resolution drought index dataset

Droughts in Africa cause severe problems, such as crop failure, food shortages, famine, epidemics and even mass migration. To minimize the effects of drought on water and food security on Africa, a high-resolution drought dataset is essential to establish robust drought hazard probabilities and to assess drought vulnerability considering a multi- and cross-sectional perspective that includes crops, hydrological systems, rangeland and environmental systems. Such assessments are essential for policymakers, their advisors and other stakeholders to respond to the pressing humanitarian issues caused by these environmental hazards. In this study, a high spatial resolution Standardized Precipitation-Evapotranspiration Index (SPEI) drought dataset is presented to support these assessments. We compute historical SPEI data based on Climate Hazards group InfraRed Precipitation with Station data (CHIRPS) precipitation estimates and Global Land Evaporation Amsterdam Model (GLEAM) potential evaporation estimates. The high-resolution SPEI dataset (SPEI-HR) presented here spans from 1981 to 2016 (36 years) with 5 km spatial resolution over the whole of Africa. To facilitate the diagnosis of droughts of different durations, accumulation periods from 1 to 48 months are provided. The quality of the resulting dataset was compared with coarse-resolution SPEI based on Climatic Research Unit (CRU) Time Series (TS) datasets, Normalized Difference Vegetation Index (NDVI) calculated from the Global Inventory Monitoring and Modeling System (GIMMS) project and root zone soil moisture modelled by GLEAM. Agreement found between coarse-resolution SPEI from CRU TS (SPEI-CRU) and the developed SPEI-HR provides confidence in the estimation of temporal and spatial variability of droughts in Africa with SPEI-HR. In addition, agreement of SPEI-HR versus NDVI and root zone soil moisture – with an average correlation coefficient ( R ) of 0.54 and 0.77, respectively – further implies that SPEI-HR can provide valuable information for the study of drought-related processes and societal impacts at sub-basin and district scales in Africa. The dataset is archived in Centre for Environmental Data Analysis (CEDA) via the following link: https://doi.org/10.5285/bbdfd09a04304158b366777eba0d2aeb (Peng et al., 2019a).

Earth System Science Data↗
USGS2009

Optical satellite data volcano monitoring: a multi-sensor rapid response system

In this chapter, the use of satellite remote sensing to monitor active geological processes is described. Specifically, threats posed by volcanic eruptions are briefly outlined, and essential monitoring requirements are discussed. As an application example, a collaborative, multi-agency operational volcano monitoring system in the north Pacific is highlighted with a focus on the 2007 eruption of Kliuchevskoi volcano, Russia. The data from this system have been used since 2004 to detect the onset of volcanic activity, support the emergency response to large eruptions, and assess the volcanic products produced following the eruption. The overall utility of such integrative assessments is also summarized. The work described in this chapter was originally funded through two National Aeronautics and Space Administration (NASA) Earth System Science research grants that focused on the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) instrument. A skilled team of volcanologists, geologists, satellite tasking experts, satellite ground system experts, system engineers and software developers collaborated to accomplish the objectives. The first project, Automation of the ASTER Emergency Data Acquisition Protocol for Scientific Analysis, Disaster Monitoring, and Preparedness , established the original collaborative research and monitoring program between the University of Pittsburgh (UP), the Alaska Volcano Observatory (AVO), the NASA Land Processes Distributed Active Archive Center (LP DAAC) at the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center, and affiliates on the ASTER Science Team at the Jet Propulsion Laboratory (JPL) as well as associates at the Earth Remote Sensing Data Analysis Center (ERSDAC) in Japan. This grant, completed in 2008, also allowed for detailed volcanic analyses and data validation during three separate summer field campaigns to Kamchatka Russia. The second project, Expansion and synergistic use of the ASTER Urgent Request Protocol (URP) for natural disaster monitoring and scientific analysis , has expanded the project to other volcanoes around the world and is in progress through 2011. The focus on ASTER data is due to the suitability of the sensor for natural disaster monitoring and the availability of data. The instrument has several unique facets that make it especially attractive for volcanic observations (Ramsey and Dehn, 2004). Specifically, ASTER routinely collects data at night, it has the ability to generate digital elevation models using stereo imaging, it can collect data in various gain states to minimize data saturation, it has a cross-track pointing capability for faster targeting, and it collects data up to ±85° latitude for better global coverage. As with any optical imaging-based remote sensing, the viewing conditions can negatively impact the data quality. This impact varies across the optical and thermal infrared wavelengths as well as being a function of the specific atmospheric window within a given wavelength region. Water vapor and cloud formation can obscure surface data in the visible and near infrared (VNIR)/shortwave infrared (SWIR) region due mainly to non-selective scattering of the incident photons. In the longer wavelengths of the thermal infrared (TIR), scattering is less of an issue, but heavy cloud cover can still obscure the ground due to atmospheric absorption. Thin clouds can be optically-transparent in the VNIR and TIR regions, but can cause errors in the extracted surface reflectance or derived surface temperatures. In regions prone to heavy cloud cover, optical remote sensing can be improved through increased temporal resolution. As more images are acquired in a given time period the chances of a clear image improve dramatically. The Advanced Very High Resolution Radiometer (AVHRR) routine monitoring, which commonly collects 4-6 images per day of any north Pacific volcano, takes advantage of this fact. The rapid response program described in this chapter also improves the temporal resolution of the ASTER instrument. ASTER has been acquiring images of volcanic eruptions since soon after its launch in December 1999. An early example included the observations of the large pyroclastic flow deposit emplaced at Bezymianny volcano in Kamchatka, Russia. The first images in March 2000, just weeks after the eruption, revealed the extent, composition, and cooling history of this large deposit and of the active lava dome (Ramsey and Dehn, 2004). The initial results from these early datasets spurred interest in using ASTER data for expanded volcano monitoring in the north Pacific. It also gave rise to the multi-year NASA-funded programs of rapid response scheduling and imaging throughout the Aleutian, Kamchatka and Kurile arcs. Since the formal establishment of the programs, the data have provided detailed descriptions of the eruptions of Augustine, Bezymianny, Kliuchevskoi and Sheveluch volcanoes over the past nine years (Wessels et al., in press; Carter et al., 2007, 2008; Ramsey et al., 2008; Rose and Ramsey, 2009). The initial research focus of this rapid response program was specifically on automating the ASTER sensor’s ability for targeted observational scheduling using the expedited data system. This urgent request protocol is one of the unique characteristics of ASTER. It provides a limited number of emergency observations, typically at a much-improved temporal resolution and quicker turnaround with data processing in the United States rather than in Japan. This can speed the reception of the processed data by several days to a week. The ongoing multi-agency research and operational collaboration has been highly successful. AVO serves as the primary source for status information on volcanic activity, working closely with the National Weather Service (NWS), Federal Aviation Administration (FAA), military and other state and federal emergency services. Collaboration with the Russian Institute of Volcanology and Seismology (IVS)/Kamchatka Volcanic Eruption Response Team (KVERT) is also maintained. Once a volcano is identified as having increased thermal output, ASTER is automatically tasked and the volcano is targeted at the next available opportunity. After the data are acquired, scientists at all the agencies have access to the images, with the primary science analysis carried out at the University of Pittsburgh and AVO. Results are disseminated to the responsible monitoring agencies and the global community through e-mail mailing lists.

Book chapter↗
USGS2005

Advancing migratory bird conservation and management by using radar: An interagency collaboration

Migratory birds face many changes to the landscapes they traverse and the habitats they use. Wind turbines and communications towers, which pose hazards to birds and bats in flight, are being erected or proposed across the United States and offshore. Human activities can also destroy or threaten habitats critical to birds during migratory passage, and climate change appears to be altering migratory patterns. The U.S. Fish and Wildlife Service (USFWS) and other agencies are under increasing pressure to identify and evaluate movement patterns and habitats used during migration and other times. Few tools for deciphering migratory travels exist, but radar-based studies of movements and habitat use patterns in songbirds, waterfowl, and bats hold promise. The U.S. system of over 150 Doppler weather radars provides continental coverage, similar to the scale of bird migration. Although data stored from weather radar represent perhaps the second largest biological data archive in the world, use of those data is currently limited to technically savvy biologists who can handle the obscure data formats. Complementary mobile radar units and thermal and acoustic monitoring are also used in site-specific studies. Efforts to advance bird conservation and management through the use of radar arose independently in several USFWS/USGS collaborations. Recently, this coalition of scientists and resource managers identified the need to work together more closely to foster radar-related research and software development. U.S. Geological Survey (USGS) scientists at Fort Collins Science Center, National Wetlands Research Center, Northern Rocky Mountain Science Center, and Patuxent Wildlife Research Center, as well as USFWS Migratory Bird biologists across the country, are collaborating with university partners to develop a suite of products for managers. The goals are to identify migratory pathways and stopover sites for conservation, mitigation, and landscape planning; convey the importance of functional landscapes and unobstructed airspaces for migrating wildlife; enable use of radar by the wider biological, wind power, and related communities; and simplify the analysis of radar data. The long term focus is to use radar technologies to better understand movement patterns and habitat associations of migratory birds and other wildlife. Land managers and industry may use the knowledge and tools developed to optimize the siting of energy projects, other facilities, and migratory bird habitat projects. The complementary endeavors, not all of which are funded, concentrate on four fundamentals: (1) develop software, in collaboration with National Oceanic and Atmospheric Administration (NOAA) scientists, that enables biologists to access unfiltered weather data and integrate it into standard geographic information systems; (2) develop artificial intelligence-based filters that separate bird from nonbird radar echoes; (3) determine characteristics of bird migration in terms of altitude, speed and direction, daily movements, seasonality, and associations with habitats and landforms; and (4) examine specific movement patterns in relation to towers, wind generation facilities, and tall obstructions. Many technical issues make this work difficult, including complex data structures, massive data sets, digital recognition of birds, large areas not covered by weather radar, and model validation; however, progress will only be furthered by tackling the challenge. The new coalition will meets its goals by: (1) facilitating a productive collaboration with NOAA, Department of the Interior bureaus, state wildlife agencies, universities, power companies, and other potential partners; (2) building and strengthening scientific capabilities within USGS; (3) addressing key migratory bird management issues; and (4) ensuring full funding for the collaborative effort.

Open-File Report↗
USGS2021

The green mole, Astromycter prasinatus T. M. Harris, 1825 (Mammalia: Eulipotyphla: Talpidae): An origin story

Thaddeus William Harris described the green mole of Maine, Condylura prasinata (Mammalia: Eulipotyphla: Talpidae), in the July 1825 issue of the Boston Journal of Philosophy and the Arts , and this was considered the original description of the species throughout most of the nineteenth century. In the early twentieth century, taxonomists began instead to cite an earlier notice in the June 1825 issue of the American Journal of Science and Arts . This short article also described the species, but also established a separate genus for it, Astromycter , despite Harris’s indications elsewhere that the species was congeneric with the star-nosed mole, Condylura cristata (Linnaeus, 1758). Moreover, the American Journal of Science and Arts article cited as its source the “ Machias Star ”, indicating the possibility of an even earlier description of the animal. With Astromycter prasinata in synonymy with C. cristata for over a century, little effort has been exerted to determine whether earlier source materials exist or why, within two months, the green mole was allocated to two different genera by its describer. The question is taxonomically relevant today because C. prasinata predates C. cristata nigra ( Smith, 1940), as an available name for north-eastern populations of star-nosed moles. If subspecies of C. cristata are to be recognized, the north-eastern subspecies should correctly bear the name C. cristata prasinata . In fact, authority for both genus- and species-group names for the green mole have been misattributed since 1825. The descriptions of C. prasinata by Thaddeus William Harris in the Boston Journal of Philosophy and the Arts and American Journal of Science and Arts were preceded by at least three published descriptions of A. prasinatus by Thaddeus Mason Harris, his father.

Archives of Natural History↗
USGS2016

Developing integrated methods to address complex resource and environmental issues

Introduction This circular provides an overview of selected activities that were conducted within the U.S. Geological Survey (USGS) Integrated Methods Development Project, an interdisciplinary project designed to develop new tools and conduct innovative research requiring integration of geologic, geophysical, geochemical, and remote-sensing expertise. The project was supported by the USGS Mineral Resources Program, and its products and acquired capabilities have broad applications to missions throughout the USGS and beyond. In addressing challenges associated with understanding the location, quantity, and quality of mineral resources, and in investigating the potential environmental consequences of resource development, a number of field and laboratory capabilities and interpretative methodologies evolved from the project that have applications to traditional resource studies as well as to studies related to ecosystem health, human health, disaster and hazard assessment, and planetary science. New or improved tools and research findings developed within the project have been applied to other projects and activities. Specifically, geophysical equipment and techniques have been applied to a variety of traditional and nontraditional mineral- and energy-resource studies, military applications, environmental investigations, and applied research activities that involve climate change, mapping techniques, and monitoring capabilities. Diverse applied geochemistry activities provide a process-level understanding of the mobility, chemical speciation, and bioavailability of elements, particularly metals and metalloids, in a variety of environmental settings. Imaging spectroscopy capabilities maintained and developed within the project have been applied to traditional resource studies as well as to studies related to ecosystem health, human health, disaster assessment, and planetary science. Brief descriptions of capabilities and laboratory facilities and summaries of some applications of project products and research findings are included in this circular. The work helped support the USGS mission to “provide reliable scientific information to describe and understand the Earth; minimize loss of life and property from natural disasters; manage water, biological, energy, and mineral resources; and enhance and protect our quality of life.” Activities within the project include the following: Spanned scales from microscopic to planetary; Demonstrated broad applications across disciplines; Included life-cycle studies of mineral resources; Incorporated specialized areas of expertise in applied geochemistry including mineralogy, hydrogeology, analytical chemistry, aqueous geochemistry, biogeochemistry, microbiology, aquatic toxicology, and public health; and Incorporated specialized areas of expertise in geophysics including magnetics, gravity, radiometrics, electromagnetics, seismic, ground-penetrating radar, borehole radar, and imaging spectroscopy. This circular consists of eight sections that contain summaries of various activities under the project. The eight sections are listed below: Laboratory Facilities and Capabilities, which includes brief descriptions of the various types of laboratories and capabilities used for the project; Method and Software Development, which includes summaries of remote-sensing, geophysical, and mineralogical methods developed or enhanced by the project; Instrument Development, which includes descriptions of geophysical instruments developed under the project; Minerals, Energy, and Climate, which includes summaries of research that applies to mineral or energy resources, environmental processes and monitoring, and carbon sequestration by earth materials; Element Cycling, Toxicity, and Health, which includes summaries of several process-oriented geochemical and biogeochemical studies and health-related research activities; Hydrogeology and Water Quality, which includes descriptions of innovative geophysical, remote-sensing, and geochemical research pertaining to hydrogeology and water-quality applications; Hazards and Disaster Assessment, which includes summaries of research and method development that were applied to natural hazards, human-caused hazards, and disaster assessments; and Databases and Framework Studies, which includes descriptions of fundamental applications of geophysical studies and of the importance of archived data.

Circular↗
USGS2016

Users and uses of Landsat 8 satellite imagery—2014 survey results

Executive Summary In 2013, Landsat 8 began adding high quality, global, moderate-resolution imagery to the more than 40-year archive of Landsat imagery. To assess the potential effects of the availability of Landsat 8 imagery on users and their work, the U.S. Geological Survey (USGS) Land Remote Sensing Program (LRS) initiated a survey of Landsat users. The objectives of the survey were to 1. Characterize various Landsat user groups, such as United States (U.S.) and international users and Landsat 8 and non-Landsat 8 users; 2. Identify any differences among user groups in uses and preferences; 3. Measure the importance of and satisfaction with Landsat 8 attributes; 4. Assess the importance to users of the frequency of usable imagery; and 5. Determine any challenges in using Landsat 8. The online survey was sent to 51,617 Landsat users registered with USGS in May 2014. Almost 13,000 people responded to the survey for a response rate of 25 percent (n = 12,966). Current Landsat users (users who had used Landsat in their work in the year prior to the survey) composed 89 percent of the sample (n = 11,549) and past Landsat users composed 11 percent (n = 1,417). The results reported here apply to current Landsat users registered with the USGS Earth Resources Observation and Science (EROS) Center. Users from 161 countries responded to the survey. Of those, 19 percent were citizens or permanent residents of the United States and 81 percent resided in other countries. More than 70 percent of current users had used Landsat 8 in the year prior to the survey. The majority of Landsat 8 users (65 percent) were established users who used Landsat imagery regularly both before and after Landsat 8 imagery became available. The average current Landsat user was male, 36 years old, and highly educated, with 9 years of experience using satellite imagery or geographic information system (GIS) software. Landsat 8 users had, on average, two more years of experience than non-Landsat 8 users. Users were employed predominantly by academic institutions (65 percent), followed by private businesses (13 percent), Federal governments (10 percent), State and local governments (6 percent), and nonprofit organizations (6 percent). Of the Landsat imagery obtained in the past year by current users, on average 31 percent came from a Landsat 8 sensor. An equivalent amount came from the Landsat 7 ETM+ sensor (33 percent); slightly less came from Landsats 4 and 5 TM sensors (27 percent). Much less came from Landsats 1 through 5 MSS sensors (5 percent). Overall, more than a third of users’ work used Landsat imagery (38 percent). Of this work, on average, 37 percent of the work was operational. Landsat 8 users considered a greater proportion of their work operational than non-Landsat 8 users (39 percent compared with 29 percent). Environmental sciences and management were the most commonly selected primary applications (selected by 42 percent of users). Land use/land cover (23 percent) was the second most commonly selected primary application, followed by education (12 percent), agriculture (9 percent), and planning and development (6 percent). Landsat 8 users were asked to rank the importance of certain attributes in determining whether to use Landsat 8 imagery in their work. The archive was ranked most important, followed by cost, spatial resolution, extent of coverage, data quality, and frequency of revisit. Users were asked how satisfied they were with these same attributes as they currently apply to Landsat 8 imagery. On average, users were most satisfied with lack of cost, extent of coverage, data quality, and the archive, but they were satisfied with all attributes. Users were asked how often they needed Landsat imagery to meet various requirements for their primary application. The survey question specifically asked how often users needed usable imagery, which differs from how often they would like the Landsat satellites to acquire an image. Users were asked to identify their needed frequency of usable imagery for the following levels: 1. Threshold level—the minimum frequency of usable imagery needed to be of any value to their primary application. 2. Breakthrough level—the frequency of usable imagery that would result in a significant improvement for their primary application of the imagery. 3. Target level—the frequency of usable imagery that would only provide a limited additional increase in the expected performance for their primary application. To meet the threshold level, three-quarters of users needed usable imagery every 17 days or less frequently. At the breakthrough level, two-thirds of users (64 percent) needed a usable image every 5–16 days. The current constellation of two satellites (Landsat 7 and 8) is capable of meeting the threshold and breakthrough needs of most users at least some of the time, but a single satellite would be highly unlikely to do so. Two-fifths of users (40 percent) felt that usable imagery provided every 4 days or more frequently would meet their target level which the current Landsat constellation cannot provide. Landsat 8 users were significantly more likely than non-Landsat 8 users to need usable imagery more frequently to meet their target levels. Additionally, U.S. Landsat 8 users were significantly more likely than other Landsat users to need usable imagery more frequently in order meet both their breakthrough and target levels. To explore the effect of the availability of Landsat 8 imagery on Landsat imagery use in general, established users (those who had consistently used Landsat imagery both before and after Landsat 8 imagery became available) using Landsat 8 imagery were asked about changes in the amount of Landsat imagery they used. The majority of established users using Landsat 8 imagery (60 percent) reported an average increase of 51 percent in the number of scenes obtained after Landsat 8 imagery became available. Landsat 8 users were asked if they had encountered challenges in using Landsat 8 whereas non-Landsat 8 users were asked if such challenges had played a role in why they were not using Landsat 8 imagery. Although many users did not encounter challenges when using or trying to use Landsat 8 data, slightly less than 30 percent did encounter issues with processing the data to a usable point. The most common issue reported was not being able to create or have access to a surface reflectance corrected product. Other challenges were related to the file sizes of images being too large to download, store, or analyze. There were no statistically significant differences between Landsat 8 and non-Landsat 8 users in terms of challenges encountered when using or trying to use the imagery, which indicates that users were not unduly discouraged by the challenges they may have encountered. When asked about potential consequences of not using Landsat 8, more than half of the non-Landsat 8 users did not report detrimental effects on their work from not using the imagery. Of those who did report detrimental effects, decreased quality of work, decreased scope of work, and increased time spent on work were the most common.

Open-File Report↗
USGS2001

Data files from “CWB Free-Field Strong-Motion Data from the 21 September Chi-Chi, Taiwan, Earthquake”

The Central Weather Bureau (CWB) of Taiwan completed a deployment of 1200 modern digital strong-motion instruments in 1996 at free-field sites and in buildings and bridges. Consequently, a very extensive set of strong-motion records were obtained for the M W = 7.6 Chi-Chi earthquake in 1999, including over 60 near-field records within 20 km of the fault ruptures. For documentation purposes, we included all relevant data files on the attached CD-ROM from our article, “CWB Free-Field Strong-Motion Data from the 21 September Chi-Chi, Taiwan, Earthquake” in this issue. We presented the data in four different ways to make the data more user friendly: (1) the original recorded data by accelerograph type; (2) the processed data in ASCII text format; (3) the processed data in SUDS format; and (4) the processed data in SAC format. (1)-(3) are exactly the same as in Lee et al. ( 2001 ), except the files are zipped (or compressed). (4) is provided for users using the SAC software on a Unix computer, and it also contains waveform plots of the data in PDF files for ease of viewing. The attached CD contains the full report of Lee et al. ( 2001 ) in 25 PDF files for viewing or printing. This full report described the data set and the data processing performed in details. It also contains plots of all processed data with an index map showing the fault, mainshock location, and the station location. We also provided a readme.txt on the CDROM to augment this Short Note with further explanations. We classify the recorded data files into four quality groups. Since the recorded strong-motion data are based on a triggering algorithm, a main concern is the amount of pre-event data and whether or not the record is long enough to cover the entire duration of the ground shaking at that station. In addition, we are concerned whether or not the record has defects (e.g., spikes, or a component was not recorded), and whether or not the record has absolute timing. In general, QA-class records are the best and can be used for any studies. QB-class records are the next best, except most of them do not have absolute timing. QC-class records cover the principal strong motions but may not have adequate pre-event data and/or post strong-motion data. QD-class records have some defects; they are included here for completeness and should not be used for most studies. Since most A800 accelerographs have a colocated A900 or A900A accelerograph, the user should use the A900 or A900A data files whenever possible. There are a readme file and six subdirectories containing the data files described in our article on the attached CDROM, under the directory of \LeeWHK: (1) readme.txt: an ASCII text file of this Short Note and additional explanations. (2) DOCfiles (subdirectory): documentary files in PDF format for viewing, and some files in ASCII text format for use in data processing. User should view or print the Reportxx.pdf files which describe the Chi-Chi strong-motion data set in details (xx is a number from 01 through 25). (3) Software (subdirectory): containing computer programs from the accelerograph manufacturers for viewing and converting the original recorded data; they are grouped by manufacturer. (4) ORGfiles (subdirectory): the original recorded data files grouped by accelerograph types; these files are for archival purposes only. (5) SUDfiles (subdirectory): the processed strong-motion data files in PC-SUDS format, and are grouped by quality class. (6) ASCfiles (subdirectory): the processed strong-motion data files are in ASCII text format and are grouped by quality class. (7) SACfiles (subdirectory): the processed strong-motion data files are in SAC format and are grouped by quality class. Within each quality class, the data are given by station. Each station has two files—xxx.pdf for viewing the three-component strong-motion data, and xxx_SAC.zip, a WINZIP file containing three SAC data files corresponding to the three components of the recorded acceleration. We use “xxx” here to denote the station name.

Bulletin of the Seismological Society of America↗
USGS2014

Integrating recent land cover mapping efforts to update the National Gap Analysis Program's species habitat map

Over the past decade, great progress has been made to develop national extent land cover mapping products to address natural resource issues. One of the core products of the GAP Program is range-wide species distribution models for nearly 2000 terrestrial vertebrate species in the U.S. We rely on deductive modeling of habitat affinities using these products to create models of habitat availability. That approach requires that we have a thematically rich and ecologically meaningful map legend to support the modeling effort. In this work, we tested the integration of the Multi-Resolution Landscape Characterization Consortium's National Land Cover Database 2011 and LANDFIRE's Disturbance Products to update the 2001 National GAP Vegetation Dataset to reflect 2011 conditions. The revised product can then be used to update the species models. We tested the update approach in three geographic areas (Northeast, Southeast, and Interior Northwest). We used the NLCD product to identify areas where the cover type mapped in 2011 was different from what was in the 2001 land cover map. We used Google Earth and ArcGIS base maps as reference imagery in order to label areas identified as "changed" to the appropriate class from our map legend. Areas mapped as urban or water in the 2011 NLCD map that were mapped differently in the 2001 GAP map were accepted without further validation and recoded to the corresponding GAP class. We used LANDFIRE's Disturbance products to identify changes that are the result of recent disturbance and to inform the reassignment of areas to their updated thematic label. We ran species habitat models for three species including Lewis's Woodpecker ( Melanerpes lewis ) and the White-tailed Jack Rabbit ( Lepus townsendii ) and Brown Headed nuthatch ( Sitta pusilla ). For each of three vertebrate species we found important differences in the amount and location of suitable habitat between the 2001 and 2011 habitat maps. Specifically, Brown headed nuthatch habitat in 2011 was −14% of the 2001 modeled habitat, whereas Lewis's Woodpecker increased by 4%. The white-tailed jack rabbit ( Lepus townsendii ) had a net change of −1% (11% decline, 10% gain). For that species we found the updates related to opening of forest due to burning and regenerating shrubs following harvest to be the locally important main transitions. In the Southeast updates related to timber management and urbanization are locally important.

The International Archives of the Photogrammetry, ↗