cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.7923/g4sf2t3p
title: Pocatello, Idaho Historic Orthoimagery for 1963 (~1 meter resolution)

description: Pocatello, Idaho historical orthomosaic for 1963 was created by collecting, scanning, merging and georectifying historic photography of Pocatello. The total spatial error is less than 1 meter. These historical orthomosaic images were derived using SfM (Structure-from-motion photogrammetry). SfM uses a series of overlapping images aligned to form a 3D representation. Classification resulted in raster and vector data with discrete classes grouped into objects located in the urban corridor of Pocatello. High-resolution aerial photography of the Pocatello area was provided by Valley Air Photos and the Idaho State Historical Society for 1963. All images were transferred from a traditional 9x9 photograph and scanned at a 1210 dpi resolution. (Date: 09/04/1963, Scale: 1:12,000, Total GSD [GSD = photo scale x scanning resolution]: 52, Scanned resolution: 11432x11241 1210 dpi). The general workflow for processing was as follows: Image collection, image pre-processing combined with gps positioning and differential correction. Photo alignment, point cloud generation, point cloud meshing, orthomosaic and DSM (Digital Surface Models) output. Photos were aligned using Agisoft Photoscan. Focal lengths for data sets were 152mm. GPS points were collected for ground truthing. Photo alignment, dense cloud, and mesh generation using ground control points, resulted in orthomosaics and DSMs (Digital Surface Models) for time periods. Orthomosaics were produced at a fine scale spatial resolution: .25m resolution in all cases except the final year at .5m due to differences in scale of the original imagery. Each orthomosaic and DEM was outputted at .5 m and 1 m resolution respectively, in order to maintain continuity between data sets. See Brock Lipple Thesis, 2015, for more in-depth discussion of the scanning and merging process.[http://geology.isu.edu/thesis/Lipple.Brock.2015.pdf] See data here: http://miles.isu.edu/Basemap/HistoricPocatello.html
DOI: 10.7923/g4d798bc
title: Pocatello, Idaho Historic Orthoimagery for 1975 (~1 meter resolution)

description: Pocatello, Idaho historical orthomosaic for 1975 was created by collecting, scanning, merging and georectifying historic photography of Pocatello. The total spatial error is less than 1 meter. These historical orthomosaic images were derived using SfM (Structure-from-motion photogrammetry). SfM uses a series of overlapping images aligned to form a 3D representation. Classification resulted in raster and vector data with discrete classes grouped into objects located in the urban corridor of Pocatello. High-resolution aerial photography of the Pocatello area was provided by Valley Air Photos and the Idaho State Historical Society for 1975. All images were transferred from a traditional 9x9 photograph and scanned at a 1210 dpi resolution. (Date: 09/19/1975, Scale: 1:12,000, Total GSD [GSD = photo scale x scanning resolution]: 209, Scanned resolution: 11240x11240 1210 dpi). The general workflow for processing was as follows: Image collection, image pre-processing combined with gps positioning and differential correction. Photo alignment, point cloud generation, point cloud meshing, orthomosaic and DSM (Digital Surface Models) output. Photos were aligned using Agisoft Photoscan. Focal lengths for data sets were 152mm. GPS points were collected for ground truthing. Photo alignment, dense cloud, and mesh generation using ground control points, resulted in orthomosaics and DSMs (Digital Surface Models) for time periods. Orthomosaics were produced at a fine scale spatial resolution: .25m resolution in all cases except the final year at .5m due to differences in scale of the original imagery. Each orthomosaic and DEM was outputted at .5 m and 1 m resolution respectively, in order to maintain continuity between data sets. See Brock Lipple Thesis, 2015, for more in-depth discussion of the scanning and merging process.[http://geology.isu.edu/thesis/Lipple.Brock.2015.pdf] See data here: http://miles.isu.edu/Basemap/HistoricPocatello.html
DOI: 10.7923/0sq1-r267
title: Restoration thinning in a drought-prone Idaho forest creates a persistent carbon deficit
DOI: 10.7923/3d0d-yb04
title: Data from "Deep learning classification of lipid droplets in quantitative phase images"
DOI: 10.7923/g4n877t0
title: Mapping Social-Ecological System Boundaries in Idaho´s Landscapes

description: Idaho, USA has a high percentage of federally owned land (over 60%), strong gradients in elevation and latitude, diverse landscape types and uses, the third fastest growing population in the United States, and is one of the most agriculturally productive states in the county.  Knowledge of how different biophysical and socioeconomic functional classes in Idaho are distributed and overlapping is of particular interest in this region, and the intersection of these landscapes describe a foundational aspect of the socio-economic system (SES) in that area.  Contemporary interest in SES has spawned efforts to map SES boundaries, but these studies are few in number, and do not converge on a consensus approach.  We adapted aspects of previous studies to develop an improved methodology for mapping SES boundaries in Idaho.  We performed a spatially explicit, nested Principal Component Analysis (PCA) on suites of biophysical and socio-economic data aggregated by 5 km grids, followed by a comparison of two common, but mathematically distinct clustering techniques, k-means and Agglomerative Hierarchical Clustering (AHC), to classify homogeneous functional classes across the state.  To address the issue of non-independence inherent to spatial datasets, we included XY coordinates in the PCA, but removed them for score calculation, thereby holding spatial locations constant without explicitly including them in score-based clustering analyses.  Both K-means and AHC generated outputs with a high percent agreement between analogous numbers of clusters, although cluster evaluators did not converge on a single most likely number of clusters for either dataset, biophysical or socioeconomic, and the median evaluator score was used to select a most likely number of clusters.  Generally, AHC resulted in a greater number of likely clusters than did k-means, thus providing better resolution - particularly in urban areas.  Composite SES maps were created by overlapping the shared 5km grid geometry of the classified biophysical and socioeconomic landscape maps, and distinct SES domains emerged.  We detected notable differences in management interpretations between the k-means and AHC composite SES maps, given a small difference in the number of landscape classes selected by clustering analysis.
DOI: 10.7923/g4xp72zb
title: Data for Building an Open Science Framework to Model Soil Organic Carbon

description: As funding agencies embrace open science principles that encourage sharing data and computer code developed to produce research outputs, we must respond with new modes of publication. Furthermore, as we address the expanding reproducibility crisis in the sciences, we must work to release research materials in ways that enable reproducibility—publishing data, computer code, and research products in addition to the traditional journal article. Toward addressing these needs, we present an example framework to model and map soil organic carbon (SOC) in the cereal grains production region of the northwestern United States. Primarily associated with soil organic matter, SOC relates to many soil properties that influence resiliency and soil health for agriculture. It is also critical for understanding soil-atmospheric carbon flux, a significant part of the overall carbon budget of the Earth. The scorpan technique for modeling soil properties uses seven categories of environmental input data to make predictions: known soil attributes, climatic values, organisms present, relief, parent material, age, and spatial location. We gather data representing these categories from various public sources. The map is produced using a random forest statistical model with scorpan inputs to predict SOC content on a 30 m spatial grid. All modeling components including input data, metadata, computer code, and output products are made freely available under an explicit open source license. In this way, reproducibility is supported; the methods and code released are available to be re-used by other researchers; and the research products are open to critical review and improvement.
DOI: 10.7923/g4765ccn
title: Social Characterization of Fernan Lake Watershed, Idaho (2014)

description: A social survey was conducted in the Fernan Lake watershed in Idaho to understand how people interact with the landscape around them. Blue-green algae growth occurs naturally, but human activities can significantly increase the frequency of blooms. The Idaho Department of Environmental Quality has identified excess amounts of phosphorus as the driver of the recurrent algae blooms in Fernan Lake. Some types of blue-green algae produce cyanotoxins which can threaten human and animal health, thus diminishing the use and enjoyment of the lake. This survey assessed human values and perceptions surrounding watershed use and water quality. The Fernan Lake watershed is comprised of all the land that eventually drains to the lake and includes all properties from the ridge tops to the valley. All households in the Fernan Lake watershed received the residential survey and all undeveloped property owners received the undeveloped property owner survey. The survey was conducted from March 2014 and all participants were instructed to return the survey by April 1, 2014. This data set contains the survey materials mailed to participants, survey data, and a collection of summarized survey results. During this same time, in-depth interviews were simultaneously conducted with residents of the Fernan Lake watershed. This data set contains the full transcripts of interview participants who waived confidentiality. Interview data was summarized by node (i.e., a term or idea expressed during the interview) and congruent node (i.e., a grouping of thematically similar nodes).
DOI: 10.7923/g4t43r4w
title: REACCH-PNA Study Area 2012

description: This is a polygon shapefile containing the boundary of the REACCH-PNA study area in 2012.
DOI: 10.7923/g4w66hpm
title: Hells Canyon National Recreation Area - Water Quality Monitoring Project

description: Water quality data collected 1 meter below surface over 8-10 hours overnight at five locations in Hells Canyon NRA. Parameters include pH, conductivity, dissolved oxygen, temperature.
DOI: 10.7923/g40z7150
title: Water Quality of Drinking Wells in the Lower Portneuf River Valley of Pocatello, Idaho

description: This 2015 dataset includes water quality information for private drinking wells sampled in the Lower Portneuf River Valley (LPRV) aquifer located in Pocatello, Idaho. This dataset includes the spatial locations and measured concentrations of nitrate-N (mg/L), total dissolved liquid (TDS) (mg/L), chloride (mg/L), sulfate (mg/L), isotopes of dissolved nitrate-N (δ15N‰, δ18O‰), and isotopes of groundwater (δ2H‰, δ18O‰). Also included are measured concentrations of pharmacuticals and personal care products (PPCPs) found in drinking water. To protect homeowner anonymity we will not be providing these spatial locations, if you would like this information please contact Dr. Sarah Godsey godsey@isu.edu.
DOI: 10.7923/g4kw5cxt
title: Student Survey to Assess University of Idaho's IGERT program (2014); Data from: A pedagogical model for team-based interdisciplinary, problem-solving doctoral education

description: A survey of 22 doctoral students enrolled in the University of Idaho Integrative Graduate Education and Research Traineeship (IGERT) program. The survey was administered online, responses were anonymous, and the response rate was 100%. Survey metrics included both Likert-scale and open-ended questions. Likert- scale metrics included a self-assessment of student interdisciplinary communication skills prior to and three to four years after joining the program, and asked participants to rate the importance of elements of the educational model in fostering their development as interdisciplinary scientists. Likert-scales ranged from 1 to 7, where 7 represented the highest score and 1 the lowest. Open-ended questions solicited student views concerning interdisciplinary communication across the project lifespan, the utility of coursework, the benefits and tradeoffs of formal and informal meetings, the advantages and disadvantages of interdisciplinary research, the most challenging and rewarding aspects of team research, and the ability of team-based interdisciplinary research to prepare them for their chosen careers.
DOI: 10.7923/g4qn64nj
title: Digital Orthoimagery of Idaho (2013, 0.5-meter)

description: This data set contains imagery from the National Agriculture Imagery Program (NAIP). The NAIP program is administered by USDA FSA and has been established to support two main FSA strategic goals centered on agricultural production. These are, increase stewardship of America's natural resources while enhancing the environment, and to ensure commodities are procured and distributed effectively and efficiently to increase food security. The NAIP program supports these goals by acquiring and providing ortho imagery that has been collected during the agricultural growing season in the U.S. The NAIP ortho imagery is tailored to meet FSA requirements and is a fundamental tool used to support FSA farm and conservation programs. Ortho imagery provides an effective, intuitive means of communication about farm program administration between FSA and stakeholders. New technology and innovation is identified by fostering and maintaining a relationship with vendors and government partners, and by keeping pace with the broader geospatial community. As a result of these efforts the NAIP program provides three main products: DOQQ tiles, Compressed County Mosaics (CCM), and Seamline shape files. The Contract specifications for NAIP imagery have changed over time reflecting agency requirements and improving technologies. These changes include image resolution, horizontal accuracy, coverage area, and number of bands. In general, flying seasons are established by FSA and are targeted for peak crop growing conditions. The NAIP acquisition cycle is based on a minimum 3 year refresh of base ortho imagery. The tiling format of the NAIP imagery is based on a 3.75' x 3.75' quarter quadrangle with a 300 pixel buffer on all four sides. NAIP quarter quads are formatted to the UTM coordinate system using the North American Datum of 1983. NAIP imagery may contain as much as 10% cloud cover per tile.
DOI: 10.7923/g4vd6wcw
title: Orthophotos of Toolik Field Station, Alaska, 2013

description: 4 band RGB color and near-IR orthophotos (pixel resolution: 0.05 meters) were acquired with a Leica RCD 30 aerial camera near the Toolik Field Station (AK) as part of the NASA funded Terrestrial Ecology Project NNX12AK83G, PIs: Lee A. Vierling (University of Idaho, Moscow, Idaho, USA), Jan U.H. Eitel (University of Idaho, Moscow, Idaho, USA), Natalie T. Boelman (Columbia University, New York City, New York, USA), and Kevin L. Griffin (Columbia University, New York City, New York, USA). The spatial extend of the dataset is: -149.675381 (West bounding long); -148.853695 (East bounding long); 68.372569 (South bounding lat); and 68.756794 (North bounding lat). The dataset is discontinuous within this spatial extend covering the following five areas of Interest (AOIs)with approximate mile point locations on the Dalton Highway in parentheses: Roche Moutonnee Creek (263.9 miles), an unnamed site (288.8 miles), Toolik Field Station (284.3 miles), Imnavait (290.6 miles), and Sagavanirktok Department of Transportation (DOT) (305.6 miles). Data were collected August 1, 2013.
DOI: 10.7923/g43x84kk
title: Salmon River RCC Transported Organic Matter

description: The data presented here represent the transported organic matter data collected from 1976 to 1979 along the Salmon River mainstem. These data were part of the original river continuum concept (RCC) project. Seven sites were sampled seasonally over multiple years. Four sites on the upper Salmon River mainstem (i.e., Camp, Smiley, Obsidian, and Casino) were sampled in Feb/Mar, May/Jun, Jul/Aug, and Sept/Oct of 1976. Four sites on the mid to lower Salmon River were sampled in March/April, July, and September/October of 1977 (i.e., Casino, Deadman's hole, Shoup, and Slate). Additional samples were collected in 1978 and 1979 at various sites and seasons. Some of these additional sites were not included in the RCC data papers and are unpublished. Eight different size classes of transport were analyzed separately for ash free dry mass and chlorophyll-a. These data formed the basis of the following manuscripts: Minshall GW, Petersen RC, Bott TL, Cushing CE, Cummins KW, Vannote RL, Sedell JR (1992) Stream ecosystem dynamics of the Salmon River, Idaho: An 8th order system. J. N. Am. Benthol. Soc. 11:111-137 Minshall GW, Petersen RC, Cummins KW, Bott TL, Sedell JR, Cushing CE, Vannote RL (1983) Interbiome comparison of stream ecosystem dynamics. Ecol. Monogr. 53:1-25
DOI: 10.7923/g4cc0xmg
title: Salmon River RCC Benthic Invertebrate Data

description: The data presented here represent the benthic macroinvertebrate data collected in 1976 and 1977 along the Salmon River mainstem. These data were part of the original river continuum concept (RCC) project. Seven sites were sampled seasonally over the two year period. Four sites on the upper Salmon River mainstem (i.e., Camp, Smiley, Obsidian, and Casino) were sampled in March and July of 1976. Four sites on the mid to lower Salmon River were sampled in March/April, July, and September/October of 1977 (i.e., Casino, Deadman's hole, Shoup, and Slate). However, only Shoup and Slate were processed during the July 1977 sampling trip. Additional samples (i.e., transport and benthic organic matter) were sampled during other trips, but the data presented here are the only seasonal samples that were processed for invertebrates. Samples were collected either via a 'dustpan-kicknet' (1976) or a dome sampler (1977). Invertebrates were identified and counted. As the methods differ between years, interannual differences can only be compared based on relative abundance. These data are the basis for the following manuscripts. Minshall, G. W., J. T. Brock, and T. W. Lapoint. 1982. Characterization and dynamics of benthic organic-matter and invertebrate functional feeding group relationships in the upper Salmon River, Idaho (USA). Internationale Revue der Gesamten Hydrobiologie 67:793-820. Minshall, G. W., R. C. Petersen, T. L. Bott, C. E. Cushing, K. W. Cummins, R. L. Vannote, and J. R. Sedell. 1992. Stream ecosystem dynamics of the Salmon River, Idaho: An 8th order system. Journal of the North American Benthological Society 11:111-137. Minshall, G. W., R. C. Petersen, K. W. Cummins, T. L. Bott, J. R. Sedell, C. E. Cushing, and R. L. Vannote. 1983. Interbiome comparison of stream ecosystem dynamics. Ecological Monographs 53:1-25.
DOI: 10.7923/g4rn35sx
title: Downscaled Climate Model Output for the Snake River Basin, Idaho from WCRP CMIP3 Scenarios used in IPCC AR4 [Delta Method]

description: This data series contains 336 temporal datasets. These data are are climate model outputs, primarily precipitation and temperature. They have been bias-corrected and spatially downscaled (BCSD) to 12-km by Maurer et al. (2007) using the CMIP3 climate model data. These monthly products are available from this link (http://gdo-dcp.ucllnl.org/downscaled_cmip3_projections/) which we temporally disaggregated to a daily time step using the Delta method. This temporal disaggregation involved the following steps. This included a random picking of a historical year to compute the mean of the daily precipitation and temperature of the gridded observed record for the same month as the future year. Then, by calculating the difference between the future monthly mean temperature and historical mean of monthly mean temperature, "delta t" and by calculating the ratio between the future monthly mean precipitation and historical mean of monthly mean precipitation, "r", we obtained these two ratios, namely addition (for temperature) and multiplication (for precipitation) factors. Finally, we compute the temperature and precipitation by adding "delta t" to daily temperature of the month of a randomly selected year and multiplying daily precipitation by "r" for the month of a randomly selected year for the given month.
DOI: 10.7923/g4wd3xh8
title: Downscaled Climate Model Output for the Western United States from IPCC AR4 Scenarios [Multivariate Adaptive Constructed Analog (MACA) Method]

description: This data series contains 540 temporal datasets. Wildfire adheres to meteorological enablers and drivers across a spectrum of timescales. However, a majority of downscaling methods are ill suited for wildfire application due the lack of daily timescales and variables such as humidity and winds that are important for fuel flammability and fire spread. Two statistical downscaling methods, the daily Bias-Corrected Spatial Downscaling (BCSD) and the Multivariate Adapted Constructed Analogs (MACA), that directly incorporate daily data were validated over the Western United States with reanalysis data. While both methods outperformed the null interpolation only method, MACA exhibited additional skill in temperature, humidity, wind and precipitation due to its ability to jointly downscale temperature and dew point temperature and its use of analog patterns rather than interpolation. Both downscaling methods exhibited value added information in tracking fire danger indices and periods of extreme fire danger; however, due to its ability to more accurately capture relative humidity and winds, MACA outperformed the daily BCSD.
DOI: 10.7923/g4mw2f2m
title: Downscaled Climate Model Output for the Salmon River Basin, Idaho from WCRP CMIP3 Scenarios used in IPCC AR4 [Delta Method]

description: This data series contains 336 temporal datasets. These data are are climate model outputs, primarily precipitation and temperature. They have been bias-corrected and spatially downscaled (BCSD) to 12-km by Maurer et al. (2007) using the CMIP3 climate model data. These monthly products are available from this link (http://gdo-dcp.ucllnl.org/downscaled_cmip3_projections/) which we temporally disaggregated to a daily time step using the Delta method. This temporal disaggregation involved the following steps. This included a random picking of a historical year to compute the mean of the daily precipitation and temperature of the gridded observed record for the same month as the future year. Then, by calculating the difference between the future monthly mean temperature and historical mean of monthly mean temperature, "delta t" and by calculating the ratio between the future monthly mean precipitation and historical mean of monthly mean precipitation, "r", we obtained these two ratios, namely addition (for temperature) and multiplication (for precipitation) factors. Finally, we compute the temperature and precipitation by adding "delta t" to daily temperature of the month of a randomly selected year and multiplying daily precipitation by "r" for the month of a randomly selected year for the given month.