cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.3533328
title: Ichtyological data of Station de biologie des Laurentides (2019)

description: These data combine fish sampling, basic physical variables, and macroinvertebrate data collected in main water bodies of Station de biologie des Laurentides (SBL) during BIO2476 field course in September 2019 (See DOI: 10.5281/zenodo.3246544 for 2018 data). BIO2476 is an undergrad course in the Department of biological sciences of Université de Montréal. During the field course, students sample fish in main SBL waterbodies using different capture techniques (e.g. electrofishing, minnow traps, fyke nets) and visual observation (snorkeling surveys). Fish counts obtained by these different techniques can be expressed as relative abundances using sampling gear dimensions, duration of sampling and/or water volume covered by sampling gear. Data are collected by participating students using standardized and documented methods under the supervision of HQP (teaching assistants and course lecturer). These data are used by students to compute different ichtyological metrics and write their final report. These data consist mainly in datatables accessible openly but fish scale samples and fish photos are also available upon request.
DOI: 10.5281/zenodo.3533327
title: Ichtyological data of Station de biologie des Laurentides (2019)

description: These data combine fish sampling, basic physical variables, and macroinvertebrate data collected in main water bodies of Station de biologie des Laurentides (SBL) during BIO2476 field course in September 2019 (See DOI: 10.5281/zenodo.3246544 for 2018 data). BIO2476 is an undergrad course in the Department of biological sciences of Université de Montréal. During the field course, students sample fish in main SBL waterbodies using different capture techniques (e.g. electrofishing, minnow traps, fyke nets) and visual observation (snorkeling surveys). Fish counts obtained by these different techniques can be expressed as relative abundances using sampling gear dimensions, duration of sampling and/or water volume covered by sampling gear. Data are collected by participating students using standardized and documented methods under the supervision of HQP (teaching assistants and course lecturer). These data are used by students to compute different ichtyological metrics and write their final report. These data consist mainly in datatables accessible openly but fish scale samples and fish photos are also available upon request.
DOI: 10.17909/t9-t116-2c60
title: K2 Data Release Notes Webpage

description: Collection of K2 Data Release Notes.
DOI: 10.5066/p9jnkykh
title: Peak-Flow Frequency Analyses for Selected Streamgages in Missoula and Granite Counties, Montana, Based on Data through Water Year 2018

description: The USGS Wyoming-Montana Water Science Center (WY?MT WSC) completed a report (Sando and McCarthy, 2018) documenting methods for peak-flow frequency analysis following implementation of the Bulletin 17C guidelines. The methods are used to provide estimates of peak-flow quantiles for 50-, 42.9-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities (AEPs) for selected streamgages operated by the WY?MT WSC. This data release presents peak-flow frequency analyses for selected streamgages in Missoula and Granite Counties, Montana, that were based on methods described by Sando and McCarthy (2018). Sando, S.K., and McCarthy, P.M., 2018, Methods for peak-flow frequency analysis and reporting for streamgages in or near Montana based on data through water year 2015: U.S. Geological Survey Scientific Investigations Report 2018?5046, 39 p., https://doi.org/10.3133/sir20185046.
DOI: 10.5281/zenodo.3666041
title: Map of 15 Ecoclimatic Arid and Semi-Arid zones in Africa (6°S-39°N)

description: Ecoclimatic Arid and Semi-Arid zones in Africa (6°S-39°N) based were derived from a multiway analysis of the WorldClim database (1950-2000). See details in the paper:<em> Leibovici DG,<strong> </strong>Quillevere G and Desconnets J-C (2007) A method to Classify Ecoclimatic Arid and Semi-Arid Zones in Circum-Saharan Africa Using Dynamics of Multiple Indicators. <strong>IEEE Transaction in Geoscience And Remote Sensing, 45(12), 4000-4007. </strong></em>doi:10.1109/TGRS.2007.908878 A follow up paper is part of the zip archive for multiscale consideration (Leibovici, D. G., & Jackson, M. (2011). Multi-scale integration for spatio-temporal ecoregioning delineation. <strong><em>International Journal of Image and Data Fusion</em>, <em>2</em>(2), 105-119</strong>. doi:10.1080/19479832.2010.542893)
DOI: 10.5281/zenodo.3666040
title: Map of 15 Ecoclimatic Arid and Semi-Arid zones in Africa (6°S-39°N)

description: Ecoclimatic Arid and Semi-Arid zones in Africa (6°S-39°N) based were derived from a multiway analysis of the WorldClim database (1950-2000). See details in the paper:<em> Leibovici DG,<strong> </strong>Quillevere G and Desconnets J-C (2007) A method to Classify Ecoclimatic Arid and Semi-Arid Zones in Circum-Saharan Africa Using Dynamics of Multiple Indicators. <strong>IEEE Transaction in Geoscience And Remote Sensing, 45(12), 4000-4007. </strong></em>doi:10.1109/TGRS.2007.908878 A follow up paper is part of the zip archive for multiscale consideration (Leibovici, D. G., & Jackson, M. (2011). Multi-scale integration for spatio-temporal ecoregioning delineation. <strong><em>International Journal of Image and Data Fusion</em>, <em>2</em>(2), 105-119</strong>. doi:10.1080/19479832.2010.542893)
DOI: 10.14272/cmrjbhjxhqcuch-uhfffaoysa-n/chmo0000630
title: infrared absorption spectroscopy (IR) ()
title: InChI=1S/C22H19N/c1-18-11-13-20(14-12-18)17-23-22-10-6-5-9-21(22)16-15-19-7-3-2-4-8-19/h2-14,23H,17H2,1H3

description: dataset for infrared absorption spectroscopy (IR) IR (ATR, ṽ) = 375 (w), 384 (w), 390 (w), 401 (w), 411 (w), 426 (w), 435 (w), 443 (w), 475 (m), 504 (w), 521 (w), 551 (m), 579 (w), 615 (w), 643 (w), 690 (vs), 745 (vs), 805 (s), 840 (w), 853 (w), 912 (w), 932 (w), 966 (w), 990 (w), 997 (w), 1021 (w), 1043 (w), 1068 (w), 1109 (w), 1147 (w), 1160 (m), 1177 (w), 1215 (w), 1262 (m), 1279 (s), 1300 (s), 1323 (vs), 1358 (w), 1378 (w), 1414 (w), 1441 (s), 1456 (vs), 1470 (w), 1487 (s), 1507 (vs), 1572 (s), 1595 (s), 1894 (vw), 2204 (w), 2847 (w), 2895 (w), 2919 (w), 2945 (w), 3020 (w), 3046 (w), 3071 (w), 3404 (w) cm–1.
DOI: 10.14272/cmrjbhjxhqcuch-uhfffaoysa-n/chmo0000593
title: 1H nuclear magnetic resonance spectroscopy (1H NMR) ()
title: InChI=1S/C22H19N/c1-18-11-13-20(14-12-18)17-23-22-10-6-5-9-21(22)16-15-19-7-3-2-4-8-19/h2-14,23H,17H2,1H3

description: dataset for 1H nuclear magnetic resonance spectroscopy (1H NMR) 1H NMR (400 MHz, CDCl3 [7.26 ppm], ppm) δ = 7.52–7.45 (m, 2H), 7.40 (dd, J = 7.6, 1.6 Hz, 1H), 7.33–7.35 (m, 3H), 7.28–7.30 (m, 2H), 7.20–7.14 (m, 3H), 6.67 (td, J = 7.4, 0.9 Hz, 1H), 6.60 (d, J = 8.3 Hz, 1H), 5.15 (br. s, 1H), 4.42 (s, 2H), 2.35 (s, 3H). Impurities: 0.5 % of ethyl acetate (4.12, 2.05 and 1.27 ppm).
DOI: 10.14272/cmrjbhjxhqcuch-uhfffaoysa-n.1
title: N-(4-methylbenzyl)-2-(phenylethynyl)aniline
title: InChI=1S/C22H19N/c1-18-11-13-20(14-12-18)17-23-22-10-6-5-9-21(22)16-15-19-7-3-2-4-8-19/h2-14,23H,17H2,1H3

description: This dataset contains experimental data from a sample (InChI=1S/C22H19N/c1-18-11-13-20(14-12-18)17-23-22-10-6-5-9-21(22)16-15-19-7-3-2-4-8-19/h2-14,23H,17H2,1H3). The datasets from the following experiments are available: 1H nuclear magnetic resonance spectroscopy (1H NMR) 13C nuclear magnetic resonance spectroscopy (13C NMR) infrared absorption spectroscopy (IR) mass spectrometry (MS)
DOI: 10.14272/cmrjbhjxhqcuch-uhfffaoysa-n/chmo0000470
title: mass spectrometry (MS) ()
title: InChI=1S/C22H19N/c1-18-11-13-20(14-12-18)17-23-22-10-6-5-9-21(22)16-15-19-7-3-2-4-8-19/h2-14,23H,17H2,1H3

description: dataset for mass spectrometry (MS) EI (m/z, 70 eV, 80 °C): 298 (11) [M+1]+, 297 (57) [M]+, 220 (30), 207 (15), 206 (100), 204 (14), 202 (20), 193 (58), 192 (15), 191 (17), 190 (11), 165 (54), 139 (11), 105 (79), 89 (12), 79 (12), 77 (21), 57 (12). HRMS (C22H19N1): Calcd 297.1517; Found 297.1519.
DOI: 10.14272/cmrjbhjxhqcuch-uhfffaoysa-n/chmo0000595
title: 13C nuclear magnetic resonance spectroscopy (13C NMR) ()
title: InChI=1S/C22H19N/c1-18-11-13-20(14-12-18)17-23-22-10-6-5-9-21(22)16-15-19-7-3-2-4-8-19/h2-14,23H,17H2,1H3

description: dataset for 13C nuclear magnetic resonance spectroscopy (13C NMR) 13C NMR (100 MHz, CDCl3 [77.16 ppm], ppm) δ = 148.9, 137.0, 136.1, 132.3, 131.6 (2C), 130.1, 129.5 (2C), 128.5 (2C), 128.3, 127.2 (2C), 123.5, 116.7, 110.2, 107.7, 95.4, 86.2, 47.7, 21.3.
DOI: 10.17632/wyn7959sxf.3
title: Data for: Experimental study on the performance of heat pump water heating system coupled with air type PV/T collector

description: Natural weather datas, thermal and electrical performance of the air type PV/T solar collector, heat pump performance combined with PV/T solar collector
DOI: 10.25612/837.5xobj48wox15
title: Licensed Child Care Operations in the Houston-Galveston Area Council Region
title: HHSC CCL Daycare and Residential Operations Data - H-GAC Region

description: List of licensed child care operations (facilities) in the 13 counties of the Houston-Galveston Area Council region as of December 2019.
DOI: 10.5281/zenodo.3873354
title: Rangeland Analysis Platform - vegetation cover 2019

description: Rangeland Analysis Platform vegetation cover 2019 These data represent rangeland cover estimates determined by Jones et al. (2018)<br> and as accessible on the Rangeland Analysis Platform (https://rangelands.app).<br> Values are percent aerial cover of the following rangeland functional groups: Band 1 - annual forbs and grasses<br> Band 2 - bare ground<br> Band 3 - litter<br> Band 4 - perennial forbs and grasses<br> Band 5 - shrubs<br> Band 6 - trees<br> No Data value = 255 Although these data were produced across a broad region, they are primarily<br> intended for rangeland ecosystems. Cover estimates may not be suitable in other<br> ecosystems, e.g., forests, agricultural lands. Data are in WGS84 Geographic Coordinate System (EPSG:4326); spatial resolution<br> is approximately 30m. Please attribute these data to:<br> Jones, M. O., B. W. Allred, D. E. Naugle, J. D. Maestas, P. Donnelly, L. J.<br> Metz, J. Karl, R. Smith, B. Bestelmeyer, C. Boyd, J. D. Kerby, and J. D. McIver.<br> 2018. Innovation in rangeland monitoring: annual, 30 m, plant functional type<br> percent cover maps for U.S. rangelands, 1984-2017. Ecosphere 9:e02430.<br> http://dx.doi.org/10.1002/ecs2.2430
DOI: 10.5281/zenodo.3873353
title: Rangeland Analysis Platform - vegetation cover 2019

description: Rangeland Analysis Platform vegetation cover 2019 These data represent rangeland cover estimates determined by Jones et al. (2018)<br> and as accessible on the Rangeland Analysis Platform (https://rangelands.app).<br> Values are percent aerial cover of the following rangeland functional groups: Band 1 - annual forbs and grasses<br> Band 2 - bare ground<br> Band 3 - litter<br> Band 4 - perennial forbs and grasses<br> Band 5 - shrubs<br> Band 6 - trees<br> No Data value = 255 Although these data were produced across a broad region, they are primarily<br> intended for rangeland ecosystems. Cover estimates may not be suitable in other<br> ecosystems, e.g., forests, agricultural lands. Data are in WGS84 Geographic Coordinate System (EPSG:4326); spatial resolution<br> is approximately 30m. Please attribute these data to:<br> Jones, M. O., B. W. Allred, D. E. Naugle, J. D. Maestas, P. Donnelly, L. J.<br> Metz, J. Karl, R. Smith, B. Bestelmeyer, C. Boyd, J. D. Kerby, and J. D. McIver.<br> 2018. Innovation in rangeland monitoring: annual, 30 m, plant functional type<br> percent cover maps for U.S. rangelands, 1984-2017. Ecosphere 9:e02430.<br> http://dx.doi.org/10.1002/ecs2.2430
DOI: 10.5281/zenodo.3860579
title: Rangeland Analysis Platform - vegetation cover 2018

description: Rangeland Analysis Platform vegetation cover 2018 These data represent rangeland cover estimates determined by Jones et al. (2018)<br> and as accessible on the Rangeland Analysis Platform (https://rangelands.app).<br> Values are percent aerial cover of the following rangeland functional groups: Band 1 - annual forbs and grasses<br> Band 2 - bare ground<br> Band 3 - litter<br> Band 4 - perennial forbs and grasses<br> Band 5 - shrubs<br> Band 6 - trees<br> No Data value = 255 Although these data were produced across a broad region, they are primarily<br> intended for rangeland ecosystems. Cover estimates may not be suitable in other<br> ecosystems, e.g., forests, agricultural lands. Data are in WGS84 Geographic Coordinate System (EPSG:4326); spatial resolution<br> is approximately 30m. Please attribute these data to:<br> Jones, M. O., B. W. Allred, D. E. Naugle, J. D. Maestas, P. Donnelly, L. J.<br> Metz, J. Karl, R. Smith, B. Bestelmeyer, C. Boyd, J. D. Kerby, and J. D. McIver.<br> 2018. Innovation in rangeland monitoring: annual, 30 m, plant functional type<br> percent cover maps for U.S. rangelands, 1984-2017. Ecosphere 9:e02430.<br> http://dx.doi.org/10.1002/ecs2.2430
DOI: 10.5281/zenodo.3860578
title: Rangeland Analysis Platform - vegetation cover 2018

description: Rangeland Analysis Platform vegetation cover 2018 These data represent rangeland cover estimates determined by Jones et al. (2018)<br> and as accessible on the Rangeland Analysis Platform (https://rangelands.app).<br> Values are percent aerial cover of the following rangeland functional groups: Band 1 - annual forbs and grasses<br> Band 2 - bare ground<br> Band 3 - litter<br> Band 4 - perennial forbs and grasses<br> Band 5 - shrubs<br> Band 6 - trees<br> No Data value = 255 Although these data were produced across a broad region, they are primarily<br> intended for rangeland ecosystems. Cover estimates may not be suitable in other<br> ecosystems, e.g., forests, agricultural lands. Data are in WGS84 Geographic Coordinate System (EPSG:4326); spatial resolution<br> is approximately 30m. Please attribute these data to:<br> Jones, M. O., B. W. Allred, D. E. Naugle, J. D. Maestas, P. Donnelly, L. J.<br> Metz, J. Karl, R. Smith, B. Bestelmeyer, C. Boyd, J. D. Kerby, and J. D. McIver.<br> 2018. Innovation in rangeland monitoring: annual, 30 m, plant functional type<br> percent cover maps for U.S. rangelands, 1984-2017. Ecosphere 9:e02430.<br> http://dx.doi.org/10.1002/ecs2.2430
DOI: 10.5281/zenodo.3860366
title: Rangeland Analysis Platform - vegetation cover 2017

description: Rangeland Analysis Platform vegetation cover 2017 These data represent rangeland cover estimates determined by Jones et al. (2018)<br> and as accessible on the Rangeland Analysis Platform (https://rangelands.app).<br> Values are percent aerial cover of the following rangeland functional groups: Band 1 - annual forbs and grasses<br> Band 2 - bare ground<br> Band 3 - litter<br> Band 4 - perennial forbs and grasses<br> Band 5 - shrubs<br> Band 6 - trees<br> No Data value = 255 Although these data were produced across a broad region, they are primarily<br> intended for rangeland ecosystems. Cover estimates may not be suitable in other<br> ecosystems, e.g., forests, agricultural lands. Data are in WGS84 Geographic Coordinate System (EPSG:4326); spatial resolution<br> is approximately 30m. Please attribute these data to:<br> Jones, M. O., B. W. Allred, D. E. Naugle, J. D. Maestas, P. Donnelly, L. J.<br> Metz, J. Karl, R. Smith, B. Bestelmeyer, C. Boyd, J. D. Kerby, and J. D. McIver.<br> 2018. Innovation in rangeland monitoring: annual, 30 m, plant functional type<br> percent cover maps for U.S. rangelands, 1984-2017. Ecosphere 9:e02430.<br> http://dx.doi.org/10.1002/ecs2.2430
DOI: 10.5281/zenodo.3860365
title: Rangeland Analysis Platform - vegetation cover 2017

description: Rangeland Analysis Platform vegetation cover 2017 These data represent rangeland cover estimates determined by Jones et al. (2018)<br> and as accessible on the Rangeland Analysis Platform (https://rangelands.app).<br> Values are percent aerial cover of the following rangeland functional groups: Band 1 - annual forbs and grasses<br> Band 2 - bare ground<br> Band 3 - litter<br> Band 4 - perennial forbs and grasses<br> Band 5 - shrubs<br> Band 6 - trees<br> No Data value = 255 Although these data were produced across a broad region, they are primarily<br> intended for rangeland ecosystems. Cover estimates may not be suitable in other<br> ecosystems, e.g., forests, agricultural lands. Data are in WGS84 Geographic Coordinate System (EPSG:4326); spatial resolution<br> is approximately 30m. Please attribute these data to:<br> Jones, M. O., B. W. Allred, D. E. Naugle, J. D. Maestas, P. Donnelly, L. J.<br> Metz, J. Karl, R. Smith, B. Bestelmeyer, C. Boyd, J. D. Kerby, and J. D. McIver.<br> 2018. Innovation in rangeland monitoring: annual, 30 m, plant functional type<br> percent cover maps for U.S. rangelands, 1984-2017. Ecosphere 9:e02430.<br> http://dx.doi.org/10.1002/ecs2.2430
DOI: 10.5281/zenodo.3860714
title: Rangeland Analysis Platform - vegetation cover 2016

description: Rangeland Analysis Platform vegetation cover 2016 These data represent rangeland cover estimates determined by Jones et al. (2018)<br> and as accessible on the Rangeland Analysis Platform (https://rangelands.app).<br> Values are percent aerial cover of the following rangeland functional groups: Band 1 - annual forbs and grasses<br> Band 2 - bare ground<br> Band 3 - litter<br> Band 4 - perennial forbs and grasses<br> Band 5 - shrubs<br> Band 6 - trees<br> No Data value = 255 Although these data were produced across a broad region, they are primarily<br> intended for rangeland ecosystems. Cover estimates may not be suitable in other<br> ecosystems, e.g., forests, agricultural lands. Data are in WGS84 Geographic Coordinate System (EPSG:4326); spatial resolution<br> is approximately 30m. Please attribute these data to:<br> Jones, M. O., B. W. Allred, D. E. Naugle, J. D. Maestas, P. Donnelly, L. J.<br> Metz, J. Karl, R. Smith, B. Bestelmeyer, C. Boyd, J. D. Kerby, and J. D. McIver.<br> 2018. Innovation in rangeland monitoring: annual, 30 m, plant functional type<br> percent cover maps for U.S. rangelands, 1984-2017. Ecosphere 9:e02430.<br> http://dx.doi.org/10.1002/ecs2.2430
DOI: 10.5281/zenodo.3860713
title: Rangeland Analysis Platform - vegetation cover 2016

description: Rangeland Analysis Platform vegetation cover 2016 These data represent rangeland cover estimates determined by Jones et al. (2018)<br> and as accessible on the Rangeland Analysis Platform (https://rangelands.app).<br> Values are percent aerial cover of the following rangeland functional groups: Band 1 - annual forbs and grasses<br> Band 2 - bare ground<br> Band 3 - litter<br> Band 4 - perennial forbs and grasses<br> Band 5 - shrubs<br> Band 6 - trees<br> No Data value = 255 Although these data were produced across a broad region, they are primarily<br> intended for rangeland ecosystems. Cover estimates may not be suitable in other<br> ecosystems, e.g., forests, agricultural lands. Data are in WGS84 Geographic Coordinate System (EPSG:4326); spatial resolution<br> is approximately 30m. Please attribute these data to:<br> Jones, M. O., B. W. Allred, D. E. Naugle, J. D. Maestas, P. Donnelly, L. J.<br> Metz, J. Karl, R. Smith, B. Bestelmeyer, C. Boyd, J. D. Kerby, and J. D. McIver.<br> 2018. Innovation in rangeland monitoring: annual, 30 m, plant functional type<br> percent cover maps for U.S. rangelands, 1984-2017. Ecosphere 9:e02430.<br> http://dx.doi.org/10.1002/ecs2.2430
DOI: 10.5281/zenodo.3860844
title: Rangeland Analysis Platform - vegetation cover 2015

description: Rangeland Analysis Platform vegetation cover 2015 These data represent rangeland cover estimates determined by Jones et al. (2018)<br> and as accessible on the Rangeland Analysis Platform (https://rangelands.app).<br> Values are percent aerial cover of the following rangeland functional groups: Band 1 - annual forbs and grasses<br> Band 2 - bare ground<br> Band 3 - litter<br> Band 4 - perennial forbs and grasses<br> Band 5 - shrubs<br> Band 6 - trees<br> No Data value = 255 Although these data were produced across a broad region, they are primarily<br> intended for rangeland ecosystems. Cover estimates may not be suitable in other<br> ecosystems, e.g., forests, agricultural lands. Data are in WGS84 Geographic Coordinate System (EPSG:4326); spatial resolution<br> is approximately 30m. Please attribute these data to:<br> Jones, M. O., B. W. Allred, D. E. Naugle, J. D. Maestas, P. Donnelly, L. J.<br> Metz, J. Karl, R. Smith, B. Bestelmeyer, C. Boyd, J. D. Kerby, and J. D. McIver.<br> 2018. Innovation in rangeland monitoring: annual, 30 m, plant functional type<br> percent cover maps for U.S. rangelands, 1984-2017. Ecosphere 9:e02430.<br> http://dx.doi.org/10.1002/ecs2.2430
DOI: 10.5281/zenodo.3860843
title: Rangeland Analysis Platform - vegetation cover 2015

description: Rangeland Analysis Platform vegetation cover 2015 These data represent rangeland cover estimates determined by Jones et al. (2018)<br> and as accessible on the Rangeland Analysis Platform (https://rangelands.app).<br> Values are percent aerial cover of the following rangeland functional groups: Band 1 - annual forbs and grasses<br> Band 2 - bare ground<br> Band 3 - litter<br> Band 4 - perennial forbs and grasses<br> Band 5 - shrubs<br> Band 6 - trees<br> No Data value = 255 Although these data were produced across a broad region, they are primarily<br> intended for rangeland ecosystems. Cover estimates may not be suitable in other<br> ecosystems, e.g., forests, agricultural lands. Data are in WGS84 Geographic Coordinate System (EPSG:4326); spatial resolution<br> is approximately 30m. Please attribute these data to:<br> Jones, M. O., B. W. Allred, D. E. Naugle, J. D. Maestas, P. Donnelly, L. J.<br> Metz, J. Karl, R. Smith, B. Bestelmeyer, C. Boyd, J. D. Kerby, and J. D. McIver.<br> 2018. Innovation in rangeland monitoring: annual, 30 m, plant functional type<br> percent cover maps for U.S. rangelands, 1984-2017. Ecosphere 9:e02430.<br> http://dx.doi.org/10.1002/ecs2.2430
DOI: 10.5281/zenodo.3861000
title: Rangeland Analysis Platform - vegetation cover 2014

description: Rangeland Analysis Platform vegetation cover 2014 These data represent rangeland cover estimates determined by Jones et al. (2018)<br> and as accessible on the Rangeland Analysis Platform (https://rangelands.app).<br> Values are percent aerial cover of the following rangeland functional groups: Band 1 - annual forbs and grasses<br> Band 2 - bare ground<br> Band 3 - litter<br> Band 4 - perennial forbs and grasses<br> Band 5 - shrubs<br> Band 6 - trees<br> No Data value = 255 Although these data were produced across a broad region, they are primarily<br> intended for rangeland ecosystems. Cover estimates may not be suitable in other<br> ecosystems, e.g., forests, agricultural lands. Data are in WGS84 Geographic Coordinate System (EPSG:4326); spatial resolution<br> is approximately 30m. Please attribute these data to:<br> Jones, M. O., B. W. Allred, D. E. Naugle, J. D. Maestas, P. Donnelly, L. J.<br> Metz, J. Karl, R. Smith, B. Bestelmeyer, C. Boyd, J. D. Kerby, and J. D. McIver.<br> 2018. Innovation in rangeland monitoring: annual, 30 m, plant functional type<br> percent cover maps for U.S. rangelands, 1984-2017. Ecosphere 9:e02430.<br> http://dx.doi.org/10.1002/ecs2.2430