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At least 685 records · Page 38Linked to original sources
USGS2008

Gathering, organizing, and accessing data for use in bird conservation across the Americas

The U.S. North American Bird Conservation Initiative (NABCI) Monitoring Subcommittee (2007) identified the need for a comprehensive plan for integrating and managing bird population monitoring data, and to adapt this as an integral component for improving monitoring activities across North America. While the Subcommittee provided a basic framework to begin development of this data management strategy, input from stakeholders is needed to identify data management needs and the technical capacity necessary to solve those challenges. We organized a session at the Fourth International Partners in Flight Conference to solicit input from session participants from across the Americas and identify their data management needs. Session speakers and participants provided examples of the challenges encountered with data management and how the Internet is increasingly used to provide access to the data needed for bird conservation decisions. Input provided during the session indicated that data management needs extended beyond technology to include scientifi c, conservation, social, institutional, and cultural issues. Because data management is intricately related to all aspects of bird conservation, a coordination process that elevates the importance of data management within the bird conservation community is needed, in addition to improving data management associated with bird population monitoring programs. Development of a comprehensive data management strategy for bird population monitoring data would help address the needs and challenges identified during this session.

Conference Paper↗
USGS2023

2023 Coastal master plan: Landscape input data

Coastal Louisiana is a complex landscape. The composition of the landscape, as well as the processes which influence said landscape, vary in both space and time. The models used in the 2023 Coastal Master Plan must attempt to reflect that spatial and temporal variability. It is therefore of the utmost importance that the spatial data sets upon which the models are initialized are of the highest quality. This task focused on the compilation and creation of spatial data sets pertaining to parameters necessary to initialize models, calibrate their operations, and/or validate their results. Spatial data sets compiled and/or created as part of this effort include 1) an initial Landscape Composition and Configuration spatial data set, 2) an Integrated Topo/Bathymetric Digital Elevation Model 3) a Wetland Vegetation Community Type data set, and 4) Historical Marsh Edge Erosion Rates. Each of these data sets constitutes a fundamental descriptor of the coastal landscape, upon which the models depend. This document describes the data sets compiled and the methodologies used to create the best-available spatial data describing the landscape in coastal Louisiana. While data collection dates vary, the data sets created for this effort are intended to represent 2018. The data described herein form initialization data sets upon which most, if not all, models of the 2023 Coastal Master Plan depend in one way or another.

Louisiana↗
USGS2017

Digitized analog boomer seismic-reflection data collected during U.S. Geological Survey cruises Erda 90-1_HC, Erda 90-1_PBP, and Erda 91-3 in Mississippi Sound, June 1990 and September 1991

The U.S. Geological Survey (USGS) Coastal and Marine Geology Program has actively collected geophysical and sedimentological data in the northern Gulf of Mexico for several decades, including shallow subsurface data in the form of high-resolution seismic-reflection profiles (HRSP). Prior to the mid-1990s most HRSP data were collected in analog format as paper rolls of continuous profiles up to 25 meters long. A large portion of this data resides in a single repository with minimal metadata. As part of the National Geological and Geophysical Data Preservation Program, scientists at the USGS St. Petersburg Coastal and Marine Science Center are converting the analog paper records to digital format using a large-format continuous scanner. This report, along with the accompanying USGS data release (Bosse and others, 2017), serves as an archive of seismic profiles with headers, converted Society of Exploration Geophysicists Y format (SEG-Y) files, navigation data, and geographic information system data files for digitized boomer seismic-reflection data collected from the Research Vessel (R/V) Erda during two cruises in 1990 and 1991. The Erda 90-1 geophysical cruise was conducted in two legs. The first leg included seismic data collected from the Hancock County region of the Mississippi Sound (Erda 90-1_HC) from June 4 to June 6, 1990. The second leg included seismic data collected from the Petit Bois Pass area of Mississippi Sound (Erda 90-1_PBP) from June 8 to June 9, 1990. The Erda 91-3 cruise occurred between September 12 and September 23, 1991, and surveyed the Mississippi Sound region just west of Horn Island, Mississippi.

Data Series↗
USGS2009

Archive of digital boomer seismic reflection data collected offshore east-central Florida during USGS cruise 00FGS01, July 14-22, 2000

In July of 2000, the U.S. Geological Survey (USGS), in cooperation with the Florida Geological Survey (FGS), conducted a geophysical survey of the Atlantic Ocean offshore Florida's east coast from Brevard County to northern Martin County. This report serves as an archive of unprocessed digital boomer seismic reflection data, trackline maps, navigation files, Geographic Information System (GIS) information, digital and handwritten Field Activity Collection System (FACS) logs, and Federal Geographic Data Committee (FGDC) metadata. A filtered and gained (a relative increase in signal amplitude) digital image of each seismic profile is also provided. Refer to the Acronyms page for expansions of all acronyms and abbreviations used in this report. The archived trace data are in standard Society of Exploration Geophysicists (SEG) SEG-Y format (Barry and others, 1975) and may be downloaded and processed with commercial or public domain software such as Seismic Unix (SU) (Cohen and Stockwell, 2005). Example SU processing scripts and USGS Software for viewing the SEG-Y files (Zihlman, 1992) are also provided. The USGS St. Petersburg Coastal and Marine Science Center assigns a unique identifier to each cruise or field activity. For example, 00FGS01 tells us the data were collected in 2000 for cooperative work with the Florida Geological Survey (FGS) and the data were collected during the first field activity for that study in that calendar year. Refer to http://walrus.wr.usgs.gov/infobank/programs/html/definition/activity.html for a detailed description of the method used to assign the field activity ID. The boomer plate is an acoustic energy source that consists of capacitors charged to a high voltage and discharged through a transducer in the water. The transducer is towed on a sled floating on the water surface and when discharged, emits a short acoustic pulse, or shot, which propagates through the water, sediment column, or rock beneath. The acoustic energy is reflected at density boundaries (such as the seafloor, sediment, or rock layers beneath the seafloor), detected by the receiver, and recorded by a PC-based seismic acquisition system. This process is repeated at timed intervals (for example, 0.5 s) and recorded for specific intervals of time (for example, 100 ms). In this way, a two-dimensional (2D) vertical profile of the shallow geologic structure beneath the ship track is produced. Figure 1 displays the acquisition geometry. Refer to table 1 for a summary of acquisition parameters. The unprocessed seismic data are stored in SEG-Y format (Barry and others, 1975). For a detailed description of the data format, refer to the SEG-Y Format page. See the How To Download SEG-Y Data page for download instructions. The printable profiles provided are GIF images that were filtered and gained using Seismic Unix software. Refer to the Software page for details about the processing and examples of the processing scripts. The printable profiles can be viewed from the Profiles page or from links located on the trackline maps. To view the trackline maps and navigation files, and for more information about these items, see the Navigation page. Detailed information about the navigation system used can be found in table 1. Of a total record length of 200 ms, only the upper 100 ms of each profile are displayed because no useful information was observed deeper in the sections. A 10 ms deep water delay appears on lines b57-b63 and sl2-sl28. No digital data were collected for line sl6. However, line sl6r is a second attempt to collect digital data for this line. Digital data and 500-shot-interval location navigation are not available for the last 1,161 shots of line sl26 due to an equipment malfunction.

Florida↗
USGS2012

Archive of side scan sonar and swath bathymetry data collected during USGS cruise 10CCT03 offshore of the Gulf Islands National Seashore, Mississippi, from East Ship Island, Mississippi, to Dauphin Island, Alabama, April 2010

In April of 2010, the U.S. Geological Survey (USGS) conducted a geophysical survey from the east end of East Ship Island, Miss., extending to the middle of Dauphin Island, Ala. (fig. 1). This survey had a dual purpose: (1) to interlink previously conducted nearshore geophysical surveys (shoreline to ~2 km) with those of offshore surveys (~2 to ~9 km) in the area, and (2) to extend the geophysical survey to include a portion of the Dauphin Island nearshore zone. The efforts were part of the USGS Gulf of Mexico Science Coordination partnership with the U.S. Army Corps of Engineers (USACE) to assist the Mississippi Coastal Improvements Program (MsCIP) and the Northern Gulf of Mexico (NGOM) Ecosystem Change and Hazards Susceptibility Project by mapping the shallow geological stratigraphic framework of the Mississippi Barrier Island Complex. These geophysical surveys will provide the data necessary for scientists to define, interpret, and provide baseline bathymetry and seafloor habitat for this area and to aid scientists in predicting future geomorpholocial changes of the islands with respect to climate change, storm impact, and sea-level rise. Furthermore, these data will provide information for barrier island restoration feasibility, particularly in Camille Cut, and efforts for the preservation of historical Fort Massachusetts. For more information refer to http://ngom.usgs.gov/gomsc/mscip/. This report serves as an archive of the processed multibeam bathymetry and side scan sonar (SSS) data. Data products herein include gridded and interpolated digital depth surfaces, seabed surface backscatter imagery, and x,y,z data products for both multibeam bathymetry and side scan sonar imagery. Additional files include trackline maps, navigation files, geograpahic information system (GIS) files, Field Activity Collection System (FACS) logs, and formal Federal Geographic Data Committee (FGDC) metadata. Scanned images of the handwritten FACS logs and digital FACS logs are also provided as PDF files. Refer to the Acronyms page for description of acronyms and abbreviations used in this report or hold the cursor over an acronym for a pop-up explanation. The USGS St. Petersburg Coastal and Marine Science Center assigns a unique identifier to each cruise or field activity. For example, 10CCT03 tells us the data were collected in 2010 for the Coastal Change and Transport (CCT) study and the data were collected during the third (03) field activity for that project in that calendar year. Refer to http://walrus.wr.usgs.gov/infobank/programs/html/definition/activity.html for a detailed description of the method used to assign the field activity ID. Data were collected aboard the U.S. Army Corps of Engineers (USACE) SV Irvington , a 56-foot (ft) Kvichak Marine Industries, Inc., catamaran (fig. 2). Side scan sonar and multibeam bathymetry data were collected simultaneously along the tracklines. The side scan sonar towfish was towed off the starboard side just slightly behind the vessel, close to the seafloor. The multibeam transducer was attached to a retractable strut-arm lowered between the catamaran hulls. Navigation was acquired with an Applanix POS MV and differentially corrected using the broadcast signal from a local National Geodetic Survey (NGS) Continuously Operating Reference Station (CORS) beacon. See the digital FACS equipment log for details about the acquisition equipment used. Raw datasets were stored digitally and processed using HYPACK Inc., HYSWEEP software at the USACE Mobile, Ala., District office. For more information on processing refer to the Equipment and Processing page. Chirp seismic data were also collected during this survey and are archived separately.

Gulf Islands National Seashore↗
USGS2013

Data entry module and manuals for the Land Treatment Digital Library

Across the country, public land managers make decisions each year that influence landscapes and ecosystems within their jurisdictions. Many of these decisions involve vegetation manipulations, which often are referred to as land treatments. These treatments include removal or alteration of plant biomass, seeding of burned areas, application of herbicides, and other activities. Data documenting these land treatments usually are stored at local management offices in various formats. Therefore, anyone interested in the types and effects of land treatments across multiple jurisdictions must first assemble the information, which can be difficult if data discovery and organization involve multiple local offices. A centralized system for storing and accessing the data helps inform land managers when making policy and management considerations and assists scientists in developing sampling designs and studies. The Land Treatment Digital Library (LTDL) was created by the U.S. Geological Survey (USGS) as a comprehensive database incorporating tabular data, documentation, photographs, and spatial data about land treatments in a single system. It was developed over a period of several years and refined based on feedback from partner agencies and stakeholders. Currently, Bureau of Land Management (BLM) land treatment data are being entered by USGS personnel as part of a memorandum of understanding between the USGS and BLM. The LTDL has a website maintained by the USGS Forest and Rangeland Ecosystem Science Center where LTDL data can be viewed https://www.usgs.gov/apps/ltdl . The resources and information provided in this data series allow other agencies, organizations, and individuals to download an empty, stand-alone LTDL database to individual or networked computers. Data entered in these databases may be submitted to the USGS for possible inclusion in the online LTDL. Multiple computer programs are used to accomplish the objective of the LTDL. The support of an information-technology specialist or professionals familiar with Microsoft Access™, ESRI’s ArcGIS™, Python, Adobe Acrobat Professional™, and computer settings is essential when installing and operating the LTDL. After the program is operational, a critical element for successful data entry is an understanding of the difference between database tables and forms, and how to edit data in both formats. Complete instructions accompany the program, and they should be followed carefully to ensure the setup and operation of the database goes smoothly.

Data Series↗
USGS2004

Data files from the Grays Harbor Sediment Transport Experiment Spring 2001

This publication consists of two DVD-ROMs, both of which are presented here. This report describes data collected during the Spring 2001 Grays Harbor Sediment Transport Experiment, and provides additional information needed to interpret the data. Two DVDs accompany this report; both contain documentation in html format that assist the user in navigating through the data. DVD-ROM-1 contains a digital version of this report in .pdf format, raw Aquatec acoustic backscatter (ABS) data in .zip format, Sonar data files in .avi format, and coastal processes and morphology data in ASCII format. ASCII data files are provided in .zip format; bundled coastal processes ASCII files are separated by deployment and instrument; bundled morphology ASCII files are separated into monthly data collection efforts containing the beach profiles collected (or extracted from the surface map) at that time; weekly surface maps are also bundled together. DVD-ROM-2 contains a digital version of this report in .pdf format, the binary data files collected by the SonTek instrumentation, calibration files for the pressure sensors, and Matlab m-files for loading the ABS data into Matlab and cleaning-up the optical backscatter (OBS) burst time-series data.

Washington↗
USGS2003

Water resources data for New Hampshire and Vermont, water year 2002

The Water Resources Division of the U.S. Geological Survey, in cooperation with State agencies, obtains a large amount of data pertaining to the water resources of New Hampshire and Vermont each water year. These data, accumulated during many water years, constitute a valuable data base for developing an improved understanding of the water resources of the States. To make these data readily available to interested parties outside the U.S. Geological Survey, the data are published annually in this report series entitled 'Water Resources Data-New Hampshire and Vermont.' This report series includes records of stage, discharge, and water quality of streams; contents of lakes and reservoirs; and water levels of ground-water wells. This volume contains records for water discharge at 84 gaging stations; stage records for 5 lakes; month end contents for 2 lakes and reservoirs; and water levels at 38 observation wells. Also included are data for 43 crest-stage partial record stations. Locations of these sites are shown in figures 1 and 2. Additional water data were collected at various sites not involved in the systematic data-collection program and are published under miscellaneous discharge measurements for gaging stations in New Hampshire and Vermont. The data in this report represent that part of the National Water Data System collected by the U.S. Geological Survey and cooperating State and Federal agencies in New Hampshire and Vermont.

Water Data Report↗
USGS1987

Water resources data, Texas, water year 1986, Volume 1: Arkansas River basin, Red River basin, Sabine River basin, Neches River basin, Trinity River basin, and intervening and adjacent coastal basins

The Water Resources Division of the U.S. Geological Survey, in cooperation with Federal, State, and City agencies, obtains a large amount of data pertaining to the water resources of Texas each water year. Such data, accumulated during many water years, constitute a valuable data base for developing an improved understanding of the water resources of the State. To make these data readily available to interested parties outside the Geological Survey, the data are published annually in three volumes of this report series entitled "Water Resources Data - Texas." This report series includes records of stage, discharge, and water quality of streams and canals; stage, contents, and water quality of lakes and reservoirs. Volume 1 contains records for water discharge at 139 gaging stations; stage only at 5 gaging station; stage and contents at 40 lakes and reservoirs; and water quality at 72 gaging stations. Also included are data for 13 partial-record stations. Additional water data were collected at 2 miscellaneous sites not involved in the systematic data-collection program. The data in this report represent that part of the National Water Data System collected by the U.S. Geological Survey and cooperating City, State, and Federal agencies in Texas.

Texas↗
USGS2013

A new data set for estimating organic carbon storage to 3 m depth in soils of the northern circumpolar permafrost region

High-latitude terrestrial ecosystems are key components in the global carbon cycle. The Northern Circumpolar Soil Carbon Database (NCSCD) was developed to quantify stocks of soil organic carbon (SOC) in the northern circumpolar permafrost region (a total area of 18.7 × 10 6 km 2 ). The NCSCD is a geographical information system (GIS) data set that has been constructed using harmonized regional soil classification maps together with pedon data from the northern permafrost region. Previously, the NCSCD has been used to calculate SOC storage to the reference depths 0–30 cm and 0–100 cm (based on 1778 pedons). It has been shown that soils of the northern circumpolar permafrost region also contain significant quantities of SOC in the 100–300 cm depth range, but there has been no circumpolar compilation of pedon data to quantify this deeper SOC pool and there are no spatially distributed estimates of SOC storage below 100 cm depth in this region. Here we describe the synthesis of an updated pedon data set for SOC storage (kg C m -2 ) in deep soils of the northern circumpolar permafrost regions, with separate data sets for the 100–200 cm (524 pedons) and 200–300 cm (356 pedons) depth ranges. These pedons have been grouped into the North American and Eurasian sectors and the mean SOC storage for different soil taxa (subdivided into Gelisols including the sub-orders Histels, Turbels, Orthels, permafrost-free Histosols, and permafrost-free mineral soil orders) has been added to the updated NCSCDv2. The updated version of the data set is freely available online in different file formats and spatial resolutions that enable spatially explicit applications in GIS mapping and terrestrial ecosystem models. While this newly compiled data set adds to our knowledge of SOC in the 100–300 cm depth range, it also reveals that large uncertainties remain. Identified data gaps include spatial coverage of deep (> 100 cm) pedons in many regions as well as the spatial extent of areas with thin soils overlying bedrock and the quantity and distribution of massive ground ice. An open access data-portal for the pedon data set and the GIS-data sets is available online at http://bolin.su.se/data/ncscd/ .

Earth System Science Data↗
USGS2022

Both real-time and long-term environmental data perform well in predicting shorebird distributions in managed habitat

Highly mobile species, such as migratory birds, respond to seasonal and inter-annual variability in resource availability by moving to better habitats. Despite the recognized importance of resource thresholds, species distribution models typically rely on long-term average habitat conditions, mostly because large-extent, temporally-resolved, environmental data are difficult to obtain. Recent advances in remote sensing make it possible to incorporate more frequent measurements of changing landscapes; however, there is often a cost in terms of model building and processing and the added value of such efforts is unknown. Our study tests whether incorporating real-time environmental data increases the predictive ability of distribution models, relative to using long-term average data. We developed and compared distribution models for shorebirds in California's Central Valley based on high temporal resolution (every 16-days), and 17-year long-term average, surface water data. Using abundance-weighted boosted regression trees, we modeled monthly shorebird occurrence as a function of surface water availability, crop type, wetland type, road density, temperature, and bird data source. While modeling with both real-time and long-term average data provided good fit to withheld validation data (0.79 < AUC < 0.89 across taxa), there were small differences in model performance. The best models incorporated long-term average conditions and spatial pattern information for real-time flooding (e.g. perimeter-area ratio of real-time water bodies). There was not a substantial difference in the performance of real-time and long-term average data models within time periods when real-time surface water differed substantially from the long-term average (specifically during drought years 2013-2016) and in intermittently flooded months or locations. Spatial predictions resulting from the models differed most in the southern region of the study area where there is lower water availability, fewer birds, and lower sampling density. Prediction uncertainty in the southern region of the study area highlights the need for increased sampling in this area. Because both sets of data performed similarly, the choice of which data to use may depend on the management context. Real-time data may ultimately be best for guiding dynamic, adaptive conservation actions whereas models based on long-term averages may be more helpful for guiding permanent wetland protection and restoration.

Ecological Applications↗
USGS2017

Integrating count and detection–nondetection data to model population dynamics

There is increasing need for methods that integrate multiple data types into a single analytical framework as the spatial and temporal scale of ecological research expands. Current work on this topic primarily focuses on combining capture–recapture data from marked individuals with other data types into integrated population models. Yet, studies of species distributions and trends often rely on data from unmarked individuals across broad scales where local abundance and environmental variables may vary. We present a modeling framework for integrating detection–nondetection and count data into a single analysis to estimate population dynamics, abundance, and individual detection probabilities during sampling. Our dynamic population model assumes that site-specific abundance can change over time according to survival of individuals and gains through reproduction and immigration. The observation process for each data type is modeled by assuming that every individual present at a site has an equal probability of being detected during sampling processes. We examine our modeling approach through a series of simulations illustrating the relative value of count vs. detection–nondetection data under a variety of parameter values and survey configurations. We also provide an empirical example of the model by combining long-term detection–nondetection data (1995–2014) with newly collected count data (2015–2016) from a growing population of Barred Owl ( Strix varia ) in the Pacific Northwest to examine the factors influencing population abundance over time. Our model provides a foundation for incorporating unmarked data within a single framework, even in cases where sampling processes yield different detection probabilities. This approach will be useful for survey design and to researchers interested in incorporating historical or citizen science data into analyses focused on understanding how demographic rates drive population abundance.

Ecology↗
USGS2005

Retrospective ecotoxicological data and current information needs for terrestrial vertebrates residing in coastal habitat of the United States

The Contaminant Exposure and Effects—Terrestrial Vertebrates (CEE-TV) database was developed to conduct simple searches for ecotoxicological information, examine exposure trends, and identify significant data gaps. The CEE-TV database contains 16,696 data records on free-ranging amphibians, reptiles, birds, and mammals residing in estuarine and coastal habitats of the Atlantic, Gulf, and Pacific coasts, Alaska, Hawaii, and the Great Lakes. Information in the database was derived from over 1800 source documents, representing 483 unique species (about 252,000 individuals), with sample collection dates spanning from 1884 to 2003. The majority of the records contain exposure data (generally contaminant concentrations) on a limited number ( n = 209) of chlorinated and brominated compounds, cholinesterase-inhibiting pesticides, economic poisons, metals, and petroleum hydrocarbons, whereas only 9.3% of the records contain biomarker or bioindicator effects data. Temporal examination of exposure data provides evidence of declining concentrations of certain organochlorine pesticides in some avian species ( e.g. , ospreys, Pandion haliaetus ), and an apparent increase in the detection and possibly the incidence of avian die-offs related to cholinesterase-inhibiting pesticides. To identify spatial data gaps, 11,360 database records with specific sampling locations were combined with the boundaries of coastal watersheds, and National Wildlife Refuge and National Park units. Terrestrial vertebrate ecotoxicological data were lacking in 41.9% of 464 coastal watersheds in the continental United States. Recent (1990–2003) terrestrial vertebrate contaminant exposure or effects data were available for only about half of the National Wildlife Refuge and National Park units in the geographic area encompassed by the database. When these data gaps were overlaid on watersheds exhibiting serious water quality problems and/or high vulnerability to pollution, 72 coastal watersheds, and 76 National Wildlife Refuge and 59 National Park units in the continental United States were found to lack recent terrestrial vertebrate ecotoxicology data. Delineation of data gaps in watersheds of concern can help prioritize monitoring in areas with impaired water quality and emphasize the need for comprehensive monitoring to gain a more complete understanding of coastal ecosystem health.

Archives of Environmental Contamination and Toxico↗
USGS2022

Asking nicely: Best practices for requesting data

Compiling disparate datasets into publicly available composite databases helps natural resource communities explore ecological trends and effectively manage across spatiotemporal scales. Though some studies have reported on the database construction phase, fewer have evaluated the data acquisition and distribution process. To facilitate future data sharing collaborations, Louisiana State University surveyed data providers and requestors to understand the characteristics of effective data requests and sharing. Data providers were largely U.S. natural resource agency personnel, and they reported that unclear data requests, privacy issues, and rigid timelines and formats were the greatest barriers toward providing data, but that they were motivated by improving science and collaboration. Data requestors identified challenges such as evolving needs, standardization issues, and insufficient resources (time and funding) as barriers to compiling data for these types of efforts. In a time of big data, open access, and collaboration, significant scientific advances can be made with effective requests and inclusion of data sets into larger and more powerful databases.

Ecological Indicators↗
USGS2005

A comparative analysis of the Global Land Cover 2000 and MODIS land cover data sets

Accurate and up-to-date global land cover data sets are necessary for various global change research studies including climate change, biodiversity conservation, ecosystem assessment, and environmental modeling. In recent years, substantial advancement has been achieved in generating such data products. Yet, we are far from producing geospatially consistent high-quality data at an operational level. We compared the recently available Global Land Cover 2000 (GLC-2000) and MODerate resolution Imaging Spectrometer (MODIS) global land cover data to evaluate the similarities and differences in methodologies and results, and to identify areas of spatial agreement and disagreement. These two global land cover data sets were prepared using different data sources, classification systems, and methodologies, but using the same spatial resolution (i.e., 1 km) satellite data. Our analysis shows a general agreement at the class aggregate level except for savannas/shrublands, and wetlands. The disagreement, however, increases when comparing detailed land cover classes. Similarly, percent agreement between the two data sets was found to be highly variable among biomes. The identified areas of spatial agreement and disagreement will be useful for both data producers and users. Data producers may use the areas of spatial agreement for training area selection and pay special attention to areas of disagreement for further improvement in future land cover characterization and mapping. Users can conveniently use the findings in the areas of agreement, whereas users might need to verify the informaiton in the areas of disagreement with the help of secondary information. Learning from past experience and building on the existing infrastructure (e.g., regional networks), further research is necessary to (1) reduce ambiguity in land cover definitions, (2) increase availability of improved spatial, spectral, radiometric, and geometric resolution satellite data, and (3) develop advanced classification algorithms.

Remote Sensing of Environment↗
USGS2020

Quality control and assessment of interpreter consistency of annual land cover reference data in an operational national monitoring program

The U.S. Geological Survey Land Change Monitoring, Assessment and Projection (USGS LCMAP) initiative is working toward a comprehensive capability to characterize land cover and land cover change using dense Landsat time series data. A suite of products including annual land cover maps and annual land cover change maps will be produced using the Landsat 4-8 data record. LCMAP products will initially be created for the conterminous United States (CONUS) and then extended to include Alaska and Hawaii. A critical component of LCMAP is the collection of reference data using the TimeSync tool, a web-based interface for manually interpreting and recording land cover from Landsat data supplemented with fine resolution imagery and other ancillary data. These reference data will be used for area estimation and validation of the LCMAP annual land cover products. Nearly 12,000 LCMAP reference sample pixels have been interpreted and a simple random subsample of these pixels has been interpreted independently by a second analyst (hereafter referred to as "duplicate interpretations"). The annual land cover reference class labels for the 1984-2016 monitoring period obtained from these duplicate interpretations are used to address the following questions: 1) How consistent are the reference class labels among interpreters overall and per class? 2) Does consistency vary by geographic region? 3) Does consistency vary as interpreters gain experience over time; and 4) Does interpreter consistency change with improving availability and quality of imagery from 1984 to 2016? Overall agreement between interpreters was 88%. Class-specific agreement ranged from 46% for Disturbed to 94% for Water, with more prevalent classes (Tree Cover, Grass/Shrub and Cropland) generally having greater agreement than rare classes (Developed, Barren and Wetland). Agreement between interpreters remained approximately the same over the 12-month period during which these interpretations were completed. Increasing availability of Landsat and Google Earth fine resolution data over the 1984 to 2016 monitoring period coincided with increased interpreter consistency for the post-2000 data record. The reference data interpretation and quality assurance protocols implemented for LCMAP demonstrate the technical and practical feasibility of using the Landsat archive and intensive human interpretation to produce national, annual reference land cover data over a 30 year period. Protocols to quantify and enhance interpreter consistency are critical elements to document and ensure quality of these reference data.

Remote Sensing of Environment↗
USGS2016

Do we need demographic data to forecast plant population dynamics?

Rapid environmental change has generated growing interest in forecasts of future population trajectories. Traditional population models built with detailed demographic observations from one study site can address the impacts of environmental change at particular locations, but are difficult to scale up to the landscape and regional scales relevant to management decisions. An alternative is to build models using population-level data that are much easier to collect over broad spatial scales than individual-level data. However, it is unknown whether models built using population-level data adequately capture the effects of density-dependence and environmental forcing that are necessary to generate skillful forecasts. Here, we test the consequences of aggregating individual responses when forecasting the population states (percent cover) and trajectories of four perennial grass species in a semi-arid grassland in Montana, USA. We parameterized two population models for each species, one based on individual-level data (survival, growth and recruitment) and one on population-level data (percent cover), and compared their forecasting accuracy and forecast horizons with and without the inclusion of climate covariates. For both models, we used Bayesian ridge regression to weight the influence of climate covariates for optimal prediction. In the absence of climate effects, we found no significant difference between the forecast accuracy of models based on individual-level data and models based on population-level data. Climate effects were weak, but increased forecast accuracy for two species. Increases in accuracy with climate covariates were similar between model types. In our case study, percent cover models generated forecasts as accurate as those from a demographic model. For the goal of forecasting, models based on aggregated individual-level data may offer a practical alternative to data-intensive demographic models. Long time series of percent cover data already exist for many plant species. Modelers should exploit these data to predict the impacts of environmental change.

Methods in Ecology and Evolution↗
USGS2013

NCWin — A Component Object Model (COM) for processing and visualizing NetCDF data

NetCDF (Network Common Data Form) is a data sharing protocol and library that is commonly used in large-scale atmospheric and environmental data archiving and modeling. The NetCDF tool described here, named NCWin and coded with Borland C + + Builder, was built as a standard executable as well as a COM (component object model) for the Microsoft Windows environment. COM is a powerful technology that enhances the reuse of applications (as components). Environmental model developers from different modeling environments, such as Python, JAVA, VISUAL FORTRAN, VISUAL BASIC, VISUAL C + +, and DELPHI, can reuse NCWin in their models to read, write and visualize NetCDF data. Some Windows applications, such as ArcGIS and Microsoft PowerPoint, can also call NCWin within the application. NCWin has three major components: 1) The data conversion part is designed to convert binary raw data to and from NetCDF data. It can process six data types (unsigned char, signed char, short, int, float, double) and three spatial data formats (BIP, BIL, BSQ); 2) The visualization part is designed for displaying grid map series (playing forward or backward) with simple map legend, and displaying temporal trend curves for data on individual map pixels; and 3) The modeling interface is designed for environmental model development by which a set of integrated NetCDF functions is provided for processing NetCDF data. To demonstrate that the NCWin can easily extend the functions of some current GIS software and the Office applications, examples of calling NCWin within ArcGIS and MS PowerPoint for showing NetCDF map animations are given.

Cartographic Journal↗