Mapped polygons at 1:7.5 million scale contain many vegetation types. The map portrays the zonal vegetation within each mapped polygon. Zonal sites are areas where the vegetation develops under the prevailing climate, uninfluenced by extremes of soil moisture, snow, soil chemistry, or disturbance, and are generally flat or gently sloping, moderately drained sites, with fine-grained soils (Vysotsky 1927). Large areas of azonal vegetation that are dependent on specific soil or hydrological conditions, such as mountain ranges and large wetlands, were also mapped. The legend contains five broad physiognomic categories: B — barrens, G — graminoid-dominated tundras, P — prostrate-shrub-dominated tundras, S — erect-shrub-dominated tundras, and W — wetlands. These are subdivided into 15 vegetation mapping units with numeric codes added to the alphabetic codes. The mapping units are named according to dominant plant functional types except in the mountains where complexes of vegetation are named according to the dominant bedrock (carbonate and noncarbonate mountain complexes). The coloring scheme of the map is suggestive of the physiognomy of the vegetation. The plant functional types are based on a variety of criteria including growth form (e.g., graminoids, shrubs), size (e.g., dwarf and low shrubs), and taxonomical status (e.g., sedges, rushes, grasses). The legend takes into special consideration the stature of woody shrubs, which is a major diagnostic feature of zonal vegetation in the Arctic (Edlund and Alt 1989, Walker et al. 2002, Yurtsev 1994). Very steep bioclimate gradients occur in mountains, so these areas are mapped as complexes of elevation belts. Mountainous areas of the map are shown with hachures; the background color indicates the nature of the bedrock, and the color of the hachures indicate the bioclimate subzone at the base of the mountains. Back to Alaska Arctic Tundra Vegetation Map (Raynolds et al. 2006) Go to Website Link :: Toolik Arctic Geobotanical Atlas below for details on legend units, photos of map units and plant species, glossary, bibliography and links to ground data. Map Themes AVHRR NDVI , Bioclimate Subzone, Elevation, False Color-Infrared CIR, Floristic Province, Lake Cover, Landscape, Substrate Chemistry, Vegetation References Edlund, S. A. and B. T. Alt. 1989. Regional congruence of vegetation and summer climate patterns in the Queen Elizabeth Islands, Northwest Territories, Canada. Arctic 42:3-23. Vysotsky, G.N. 1927. Theses on soil and moisture (conspectus and terminology). Lesovedenie (eds.) Sbornik Lesnogo Obschestva v Leningrade. Leningrad. pp. 67-79 (In Russian). Walker, D. A., W. A. Gould, and M. K. Raynolds. 2002. The Circumpolar Arctic Vegetation Map: Environmental controls, AVHRR-derived base maps, and integrated mapping procedures. International Journal of Remote Sensing 23:2551-2570. Yurtsev, B. A. 1994. Floristic divisions of the Arctic. Journal of Vegetation Science 5:765-776.

The rainbow color map is scientifically incorrect and hinders people with color vision deficiency to view visualizations in a correct way. Due to perceptual non-uniform color gradients within the rainbow color map the data representation is distorted what can lead to misinterpretation of results and flaws in science communication. Here we present the data of a paper survey of 797 scientific publication in the journal Hydrology and Earth System Sciences. With in the survey all papers were classified according to color issues. Find details about the data below.

• year = year of publication (YYYY)
• date = date (YYYY-MM-DD) of publication
• title = full paper title from journal website
• authors = list of authors comma-separated
• n_authors = number of authors (integer between 1 and 27)
• col_code = color-issue classification (see below)
• volume = Journal volume
• start_page = first page of paper (consecutive)
• end_page = last page of paper (consecutive)
• base_url = base url to access the PDF of the paper with /volume/start_page/year/
• filename = specific file name of the paper PDF (e.g. hess-9-111-2005.pdf)

Color classification is stored in the col_code variable with:

• 0 = chromatic and issue-free,
• 1 = red-green issues,
• 2= rainbow issues and
• bw= black and white paper.

See more details (e.g., sample code to analyse the survey data) on https://github.com/modche/rainbow_hydrology

Paper: Stoelzle, M. and Stein, L.: Rainbow color map distorts and misleads research in hydrology – guidance for better visualizations and science communication, Hydrol. Earth Syst. Sci., 25, 4549–4565, https://doi.org/10.5194/hess-25-4549-2021, 2021.

This dataset is the result of a systematic survey of scientific publication to investigate the extent to which rainbow colour maps are used in geoscience publications. Papers were surveyed from five journals - Earth System Dynamics (ESD), Geophysical Research Letters (GRL), Ocean Science (OS), Solid Earth (SE) and The Cryosphere (TC) - for the years 2005, 2010, 2015 and 2020.

The final data set includes the pre-existing Stoelzle and Stein (2021) survey data for HESS, which is independently available at https://doi.org/10.5281/zenodo.5145746 (Stoelzle, 2021).

All papers (n=2638) were classified according to the type of colour encoding used.

year = year of publication (YYYY) title = full paper title authors = list of authors seperated by semi-colon n_authors = number of authors col_code = color-issue classification (see below) volume = Journal volume start_page = first page of paper (where available) end_page = last page of paper (where available) base_url = url to access the paper on the journal website filename = file name of the PDF version of the paper

Color classification is stored in the col_code variable with:

0 = Colour visualisations with no colour issues 1 = At least one visualisation with red-green issues 2 = At least one visualisation with a rainbow colour map bw = Black and white paper

Accuracy result metrics from the automated georeferencing of real-world country-maps.

The Arctic has a relatively consistent core ofplant species that occur throughout the circumpolar region, but there is also considerable east to west variation in regional floras, particularly in the southern bioclimate subzones. These differences are due to factors such as different histories related to glaciations, land bridges, and north-south trending mountain ranges that have influenced the exchange of species between parts of the Arctic. Floristic provinces are used to explain the east-west variation in species distribution in the Arctic. Alaska is included within the Beringian Floristic Province, and includes three of the 23 circumpolar Sub-Provinces: North Beringian Islands, Beringian Alaska, and Northern Alaska (Yurtsev 1994, Walker 2005). Floristic provinces were mapped from the Panarctic Flora Initiative (Elvebakk et al. 1999), based largely on Yurtsev (1994). The boundaries were then adjusted to follow vegetation polygon boundaries. The vegetation polygons are drawn at a much finer resolution than the floristic province boundaries, so little information was lost in this process. Back to Alaska Arctic Tundra Vegetation Map (Raynolds et al. 2006) Back to Alaska Arctic Tundra Vegetation Map (Raynolds et al. 2006) Go to Website Link :: Toolik Arctic Geobotanical Atlas below for details on legend units, photos of map units and plant species, glossary, bibliography and links to ground data. Map Themes AVHRR NDVI , Bioclimate Subzone, Elevation, False Color-Infrared CIR, Floristic Province, Lake Cover, Landscape, Substrate Chemistry, Vegetation References Elvebakk, A. 1999. Bioclimate delimitation and subdivisions of the Arctic. Pages 81-112 in I. Nordal and V. Y. Razzhivin, editors. The Species Concept in the High North - A Panarctic Flora Initiative. The Norwegian Academy of Science and Letters, Oslo. Walker, D. A., M. K. Raynolds, F. J. A. Daniels, E. Einarsson, A. Elvebakk, W. A. Gould, A. E. Katenin, S. S. Kholod, C. J. Markon, E. S. Melnikov, N. G. Moskalenko, S. S. Talbot, B. A. Yurtsev, and CAVM Team. 2005. The Circumpolar Arctic Vegetation Map. Journal of Vegetation Science 16:267-282. Yurtsev, B. A. 1994. Floristic divisions of the Arctic. Journal of Vegetation Science 5:765-776.

Mapped polygons at 1:7.5 million scale contain many vegetation types. The map portrays the zonal vegetation within each mapped polygon. Zonal sites are areas where the vegetation develops under the prevailing climate, uninfluenced by extremes of soil moisture, snow, soil chemistry, or disturbance, and are generally flat or gently sloping, moderately drained sites, with fine-grained soils (Vysotsky 1927). Large areas of azonal vegetation that are dependent on specific soil or hydrological conditions, such as mountain ranges and large wetlands, were also mapped. The legend contains five broad physiognomic categories: • B — barrens • G — graminoid-dominated tundras • P — prostrate-shrub-dominated tundras • S — erect-shrub-dominated tundras • W — wetlands These are subdivided into 15 vegetation mapping units with numeric codes added to the alphabetic codes. The mapping units are named according to dominant plant functional types except in the mountains where complexes of vegetation are named according to the dominant bedrock (carbonate and noncarbonate mountain complexes). The coloring scheme of the map is suggestive of the physiognomy of the vegetation. The plant functional types are based on a variety of criteria including growth form (e.g., graminoids, shrubs), size (e.g., dwarf and low shrubs), and taxonomical status (e.g., sedges, rushes, grasses). The legend takes into special consideration the stature of woody shrubs, which is a major diagnostic feature of zonal vegetation in the Arctic (Edlund and Alt 1989, Walker et al. 2002, Yurtsev 1994). Very steep bioclimate gradients occur in mountains, so these areas are mapped as complexes of elevation belts. Mountainous areas of the map are shown with hachures; the background color indicates the nature of the bedrock, and the color of the hachures indicate the bioclimate subzone at the base of the mountains. Back to Circumpolar Arctic Vegetation Map Go to Website Link :: Toolik Arctic Geobotanical Atlas below for details on legend units, photos of map units and plant species, glossary, bibliography and links to ground data. Map Themes: AVHRR Biomass 2010, AVHRR Biomass Trend 1982-2010, AVHRR False Color Infrared 1993-1995, AVHRR NDVI 1993-1995, AVHRR NDVI Trend 1982-2010, AVHRR Summer Warmth Index 1982-2003, Bioclimate Subzone, Coastline and Treeline Map, Elevation, Floristic Provinces, Lake Cover, Landscape Physiography, Landscape Age, Substrate Chemistry, Vegetation References Edlund, S. A. and B. T. Alt. 1989. Regional congruence of vegetation and summer climate patterns in the Queen Elizabeth Islands, Northwest Territories, Canada. Arctic 42:3-23. Vysotsky, G.N. 1927. Theses on soil and moisture (conspectus and terminology). Lesovedenie (eds.) Sbornik Lesnogo Obschestva v Leningrade. Leningrad. pp. 67-79 (In Russian). Walker, D. A., W. A. Gould, and M. K. Raynolds. 2002. The Circumpolar Arctic Vegetation Map: Environmental controls, AVHRR-derived base maps, and integrated mapping procedures. International Journal of Remote Sensing 23:2551-2570. Yurtsev, B. A. 1994. Floristic divisions of the Arctic. Journal of Vegetation Science 5:765-776.

This description is part of the blog post "Systematic Literature Review of teaching Open Science" https://sozmethode.hypotheses.org/839

According to my opinion, we do not pay enough attention to teaching Open Science in higher education. Therefore, I designed a seminar to teach students the practices of Open Science by doing qualitative research.About this seminar, I wrote the article ”Teaching Open Science and qualitative methods“. For the article ”Teaching Open Science and qualitative methods“, I started to review the literature on ”Teaching Open Science“. The result of my literature review is that certain aspects of Open Science are used for teaching. However, Open Science with all its aspects (Open Access, Open Data, Open Methodology, Open Science Evaluation and Open Science Tools) is not an issue in publications about teaching.

Based on this insight, I have started a systematic literature review. I realized quickly that I need help to analyse and interpret the articles and to evaluate my preliminary findings. Especially different disciplinary cultures of teaching different aspects of Open Science are challenging, as I myself, as a social scientist, do not have enough insight to be able to interpret the results correctly. Therefore, I would like to invite you to participate in this research project!

I am now looking for people who would like to join a collaborative process to further explore and write the systematic literature review on “Teaching Open Science“. Because I want to turn this project into a Massive Open Online Paper (MOOP). According to the 10 rules of Tennant et al (2019) on MOOPs, it is crucial to find a core group that is enthusiastic about the topic. Therefore, I am looking for people who are interested in creating the structure of the paper and writing the paper together with me. I am also looking for people who want to search for and review literature or evaluate the literature I have already found. Together with the interested persons I would then define, the rules for the project (cf. Tennant et al. 2019). So if you are interested to contribute to the further search for articles and / or to enhance the interpretation and writing of results, please get in touch. For everyone interested to contribute, the list of articles collected so far is freely accessible at Zotero: https://www.zotero.org/groups/2359061/teaching_open_science. The figure shown below provides a first overview of my ongoing work. I created the figure with the free software yEd and uploaded the file to zenodo, so everyone can download and work with it:

To make transparent what I have done so far, I will first introduce what a systematic literature review is. Secondly, I describe the decisions I made to start with the systematic literature review. Third, I present the preliminary results.

Systematic literature review – an Introduction

Systematic literature reviews “are a method of mapping out areas of uncertainty, and identifying where little or no relevant research has been done.” (Petticrew/Roberts 2008: 2). Fink defines the systematic literature review as a “systemic, explicit, and reproducible method for identifying, evaluating, and synthesizing the existing body of completed and recorded work produced by researchers, scholars, and practitioners.” (Fink 2019: 6). The aim of a systematic literature reviews is to surpass the subjectivity of a researchers’ search for literature. However, there can never be an objective selection of articles. This is because the researcher has for example already made a preselection by deciding about search strings, for example “Teaching Open Science”. In this respect, transparency is the core criteria for a high-quality review.

In order to achieve high quality and transparency, Fink (2019: 6-7) proposes the following seven steps:

1. Selecting a research question.
2. Selecting the bibliographic database.
3. Choosing the search terms.
4. Applying practical screening criteria.
5. Applying methodological screening criteria.
6. Doing the review.
7. Synthesizing the results.

I have adapted these steps for the “Teaching Open Science” systematic literature review. In the following, I will present the decisions I have made.

Systematic literature review – decisions I made

1. Research question: I am interested in the following research questions: How is Open Science taught in higher education? Is Open Science taught in its full range with all aspects like Open Access, Open Data, Open Methodology, Open Science Evaluation and Open Science Tools? Which aspects are taught? Are there disciplinary differences as to which aspects are taught and, if so, why are there such differences?
2. Databases: I started my search at the Directory of Open Science (DOAJ). “DOAJ is a community-curated online directory that indexes and provides access to high quality, open access, peer-reviewed journals.” (https://doaj.org/) Secondly, I used the Bielefeld Academic Search Engine (base). Base is operated by Bielefeld University Library and “one of the world’s most voluminous search engines especially for academic web resources” (base-search.net). Both platforms are non-commercial and focus on Open Access publications and thus differ from the commercial publication databases, such as Web of Science and Scopus. For this project, I deliberately decided against commercial providers and the restriction of search in indexed journals. Thus, because my explicit aim was to find articles that are open in the context of Open Science.
3. Search terms: To identify articles about teaching Open Science I used the following search strings: “teaching open science” OR teaching “open science” OR teach „open science“. The topic search looked for the search strings in title, abstract and keywords of articles. Since these are very narrow search terms, I decided to broaden the method. I searched in the reference lists of all articles that appear from this search for further relevant literature. Using Google Scholar I checked which other authors cited the articles in the sample. If the so checked articles met my methodological criteria, I included them in the sample and looked through the reference lists and citations at Google Scholar. This process has not yet been completed.
4. Practical screening criteria: I have included English and German articles in the sample, as I speak these languages (articles in other languages are very welcome, if there are people who can interpret them!). In the sample only journal articles, articles in edited volumes, working papers and conference papers from proceedings were included. I checked whether the journals were predatory journals – such articles were not included. I did not include blogposts, books or articles from newspapers. I only included articles that fulltexts are accessible via my institution (University of Kassel). As a result, recently published articles at Elsevier could not be included because of the special situation in Germany regarding the Project DEAL (https://www.projekt-deal.de/about-deal/). For articles that are not freely accessible, I have checked whether there is an accessible version in a repository or whether preprint is available. If this was not the case, the article was not included. I started the analysis in May 2019.
5. Methodological criteria: The method described above to check the reference lists has the problem of subjectivity. Therefore, I hope that other people will be interested in this project and evaluate my decisions. I have used the following criteria as the basis for my decisions: First, the articles must focus on teaching. For example, this means that articles must describe how a course was designed and carried out. Second, at least one aspect of Open Science has to be addressed. The aspects can be very diverse (FOSS, repositories, wiki, data management, etc.) but have to comply with the principles of openness. This means, for example, I included an article when it deals with the use of FOSS in class and addresses the aspects of openness of FOSS. I did not include articles when the authors describe the use of a particular free and open source software for teaching but did not address the principles of openness or re-use.
6. Doing the review: Due to the methodical approach of going through the reference lists, it is possible to create a map of how the articles relate to each other. This results in thematic clusters and connections between clusters. The starting point for the map were four articles (Cook et al. 2018; Marsden, Thompson, and Plonsky 2017; Petras et al. 2015; Toelch and Ostwald 2018) that I found using the databases and criteria described above. I used yEd to generate the network. „yEd is a powerful desktop application that can be used to quickly and effectively generate high-quality diagrams.” (https://www.yworks.com/products/yed) In the network, arrows show, which articles are cited in an article and which articles are cited by others as well. In addition, I made an initial rough classification of the content using colours. This classification is based on the contents mentioned in the articles’ title and abstract. This rough content classification requires a more exact, i.e., content-based subdivision and

Golden eagle (Aquila chrysaetos) nest site model spatial data and maps as described in Dunk JR, Woodbridge B, Lickfett TM, Bedrosian G, Noon BR, LaPlante DW, et al. (2019) Modeling spatial variation in density of golden eagle nest sites in the western United States. PLoS ONE 14(9): e0223143. https://doi.org/10.1371/journal.pone.0223143

Percentage of generalization instances identified by the participants and the online tool.

This data is intended as a reference material of street and alley vacations, but not designed for survey, accurate positioning, or legal documents. It is created as polygon feature class, vacation information based on field measurements, types of Right of Way, and citations of Journal of the Common Council (J.C.C.) and the plat Liber and Page is listed under the column titled 'Sub_Plat'. The paper maps of the Street and Alley Vacation, the raster layer version of those maps (Linen Map Markup Mosaic), and the Detroit parcel layer are used as base maps to create this data.

The street and alley vacations were recorded from 1831 to 2022 throughout the whole city, and it will be updated weekly. The existed and/or active street and alley vacations are ready to view, the authors are working on pending and historical records.

Spatial Reference: WGS 1984 Web Mercator Auxiliary Sphere

This Map Journal Story Book is now being retired. A new story can now be accessed through the new Accessing Minnesota's Geological Data using ArcGIS Online. This was created to display the available Minnesota geologic resources that can be accessed Online. The story utilized the Map Journal to help K-12 educators and students find the GIS resources available to them. To find out more about Minnesota's geology please visit the Minnesota Geological Survey's web page at https://cse.umn.edu/mgs. For any questions please email Jacqueline Hamilton at stub0035@umn.edu.

This layer contains a summary of the results of data collected by the Status Monitoring Network of the Florida Department of Environmental Protection's Watershed Monitoring Section (WMS). For more information on the Status Monitoring Network visit this webpage https://floridadep.gov/dear/watershed-monitoring-section/content/status-monitoring-network. The layer consists of sampling results for Cycles 4 through Cycle 11 (2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017 and 2018) years as reported as the percentage of waterbodies attaining water quality standards (threshold or criterion) within either the entire state of Florida or one of the six WMS reporting units (zones). For more information, please review the following document at http://publicfiles.dep.state.fl.us/dear/watershed%20monitoring/documents/WMS-MonitoringDesignDocument.pdf. For more information on the water quality indicators, please review this document at http://publicfiles.dep.state.fl.us/dear/watershed%20monitoring/documents/indicators_status.pdf. Spatial boundaries were inherited from the WMS Cycle 3 Reporting Units.The data, table, and chart URL attributes support the ArcGIS Online Journal Map for the Status Network Report Card. More on the WMS Report Cards for the Status Network can be found at this website and linked webpages here - https://floridadep.gov/dear/watershed-monitoring-section/content/interactive-water-quality-report-cards

DATASET: Alpha version 2000 and 2010 estimates of numbers of people per grid square, with national totals adjusted to match UN population division estimates (http://esa.un.org/wpp/) and MODIS-derived urban extent change built in. REGION: Asia SPATIAL RESOLUTION: 0.000833333 decimal degrees (approx 100m at the equator) PROJECTION: Geographic, WGS84 UNITS: Estimated persons per grid square MAPPING APPROACH: Land cover based, as described on the website and in: Gaughan AE, Stevens FR, Linard C, Jia P and Tatem AJ, 2013, High resolution population distribution maps for Southeast Asia in 2010 and 2015, PLoS ONE, 8(2): e55882 FORMAT: Geotiff (zipped using 7-zip (open access tool): www.7-zip.org) FILENAMES: Example - VNM00urbchg.tif = Vietnam (VNM) population count map for 2000 (00) adjusted to match UN national estimates and incorporating urban extent and urban population estimates for 2000. DATE OF PRODUCTION: July 2013 Dataset construction details and input data are provided here: www.asiapop.org and here: http://www.plosone.org/article/info:doi/10.1371/journal.pone.0055882

The data in this feature service uses the same polygons as the MassGIS USGS 1:24,000 Surficial Geology data layer and includes minimum, maximum, and average hydraulic conductivity in feet per day for each surficial unit. Hydraulic conductivity values were extracted from U.S. Geological Survey groundwater reports, Massachusetts Department of Environmental Protection Zone II reports, and other Massachusetts-specific journal articles (a total of 165 aquifer tests or aggregates of aquifer tests depending on the available data in each report).The Hydrogeologic Atlas of Massachusetts provides data on the hydraulic properties of the statewide surficial aquifers. The datasets were developed using surficial geology, bedrock altitude, a statewide groundwater flow model, and a compilation of hydraulic property data from U.S. Geological Survey groundwater reports, Massachusetts Department of Environmental Protection Zone II reports, and other Massachusetts-specific journal articles (a total of 23 sources).\One of the goals of this project was to understand current and projected future groundwater flooding risks across the state. To understand groundwater flooding risks, we developed a statewide three-dimensional groundwater flow model to simulate the water table elevation. The Hydrogeologic Atlas of Massachusetts compiles new datasets developed as input into the groundwater model, groundwater model simulation results, and other statewide map products created through this project. For further information regarding the methods of this study see Corkran et al. (2024), a report submitted to the Massachusetts Executive Office of Energy and Environmental Affairs.Suggested Citation:Corkran, D., Kirshen, A., Moran, B.J., Blin, N., King, R., Bresee, M., & Boutt, D. (2024). Massachusetts State-wide Groundwater Model and Flooding Risk Assessment 1.0. Report funded by the Massachusetts Executive Office of Energy and Environmental Affairs and published on the ResilientMass website.See full metadata and the map service.

DATASET: Alpha version 2000 and 2010 estimates of numbers of people per grid square, with national totals adjusted to match UN population division estimates (http://esa.un.org/wpp/) and MODIS-derived urban extent change built in. REGION: Asia SPATIAL RESOLUTION: 0.000833333 decimal degrees (approx 100m at the equator) PROJECTION: Geographic, WGS84 UNITS: Estimated persons per grid square MAPPING APPROACH: Land cover based, as described on the website and in: Gaughan AE, Stevens FR, Linard C, Jia P and Tatem AJ, 2013, High resolution population distribution maps for Southeast Asia in 2010 and 2015, PLoS ONE, 8(2): e55882 FORMAT: Geotiff (zipped using 7-zip (open access tool): www.7-zip.org) FILENAMES: Example - VNM00urbchg.tif = Vietnam (VNM) population count map for 2000 (00) adjusted to match UN national estimates and incorporating urban extent and urban population estimates for 2000. DATE OF PRODUCTION: July 2013 Dataset construction details and input data are provided here: www.asiapop.org and here: http://www.plosone.org/article/info:doi/10.1371/journal.pone.0055882

The map and digital data layers present historic sites described in these sources: Maryland’s Upper Choptank River and Tuckahoe River Cultural Resource Inventory (1999)Lower Choptank River Cultural Resource Inventory (2002)1875 Isler Map of Caroline County1897 Salisbury Map of Caroline CountyDenton Journal, 1865-1965National Register of Historic Places (NRHP) sites in the upper Choptank watershedMaryland Historical Trust (MHT) sites in the upper Choptank watershedPurposeChoptank River Heritage (CRH) is a not-for-profit effort based in Caroline County, Maryland. CRH carries out research into historic maps and other sources and publishes digital maps and narratives about people, places, and events in the county's past. We seek to nurture a sense of place, encourage historic preservation, and promote conservation of the Choptank and Tuckahoe Rivers and the county's natural environment.Online ResourceChoptank River Heritage WebsiteData Creation Date2012-08-28Map Publication Date2016-12-20Contact InformationContact NameDon BarkerOrganization NameChoptank River Heritage (CRH)Position NameGeographer-HistorianRoleAuthorContact InstructionsBy email only:info@choptankriverheritage.org

This data publication contains two collections of raster maps of forest attributes across Canada, the first collection for year 2001, and the second for year 2011. The 2001 collection is actually an improved version of an earlier set of maps produced also for year 2001 (Beaudoin et al 2014, DOI: https://doi.org/10.1139/cjfr-2013-0401) that is itself available through the web site “http://nfi-nfis.org”. Each collection contains 93 maps of forest attributes: four land cover classes, 11 continuous stand-level structure variables such as age, volume, biomass and height, and 78 continuous values of percent composition for tree species or genus. The mapping was done at a spatial resolution of 250m along the MODIS grid. Briefly the method uses forest polygon information from the first version of photoplots database from Canada’s National Forest Inventory as reference data, and the non-parametric k-nearest neighbors procedure (kNN) to create the raster maps of forest attributes. The approach uses a set of 20 predictive variables that include MODIS spectral reflectance data, as well as topographic and climate data. Estimates are carried out on target pixels across all Canada treed landmass that are stratified as either forest or non-forest with 25% forest cover used as a threshold. Forest cover information was extracted from the global forest cover product of Hansen et al (2013) (DOI: https://doi.org/10.1126/science.1244693). The mapping methodology and resultant datasets were intended to address the discontinuities across provincial borders created by their large differences in forest inventory standards. Analysis of residuals has failed to reveal residual discontinuities across provincial boundaries in the current raster dataset, meaning that our goal of providing discontinuity-free maps has been reached. The dataset was developed specifically to address strategic issues related to phenomena that span multiple provinces such as fire risk, insect spread and drought. In addition, the use of the kNN approach results in the maintenance of a realistic covariance structure among the different variable maps, an important property when the data are extracted to be used in models of ecosystem processes. For example, within each pixel, the composition values of all tree species add to 100%. * Details on the product development and validation can be found in the following publication: Beaudoin, A., Bernier, P.Y., Villemaire, P., Guindon, L., Guo, X.-J. 2017. Tracking forest attributes across Canada between 2001 and 2011 using a kNN mapping approach applied to MODIS imagery, Canadian Journal of Forest Research 48: 85–93. DOI: https://doi.org/10.1139/cjfr-2017-0184 * Please cite this dataset as: Beaudoin A, Bernier PY, Villemaire P, Guindon L, Guo XJ. 2017. Species composition, forest properties and land cover types across Canada’s forests at 250m resolution for 2001 and 2011. Natural Resources Canada, Canadian Forest Service, Laurentian Forestry Centre, Quebec, Canada. https://doi.org/10.23687/ec9e2659-1c29-4ddb-87a2-6aced147a990 * This dataset contains these NFI forest attributes: ## LAND COVER : landbase vegetated, landbase non-vegetated, landcover treed, landcover non-treed ## TREE STRUCTURE : total above ground biomass, tree branches biomass, tree foliage biomass, stem bark biomass, stem wood biomass, total dead trees biomass, stand age, crown closure, tree stand heigth, merchantable volume, total volume ## TREE SPECIES : abies amabilis (amabilis fir), abies balsamea (balsam fir), abies lasiocarpa (subalpine fir), abies spp. (unidentified fir), acer macrophyllum (bigleaf maple), acer negundo (manitoba maple, box-elder), acer pensylvanicum (striped maple), acer rubrum (red maple), acer saccharinum (silver maple), acer saccharum (sugar maple), acer spicatum (mountain maple), acer spp. (unidentified maple), alnus rubra (red alder), alnus spp. (unidentified alder), arbutus menziesii (arbutus), betula alleghaniensis (yellow birch), betula papyrifera (white birch), betula populifolia (gray birch), betula spp. (unidentified birch), carpinus caroliniana (blue-beech), carya cordiformis (bitternut hickory), chamaecyparis nootkatensis (yellow-cedar), fagus grandifolia (american beech), fraxinus americana (white ash), fraxinus nigra (black ash), fraxinus pennsylvanica (red ash), juglans cinerea (butternut), juglans nigra (black walnut), juniperus virginiana (eastern redcedar), larix laricina (tamarack), larix lyallii (subalpine larch), larix occidentalis (western larch), larix spp. (unidentified larch), malus spp. (unidentified apple), ostrya virginiana (ironwood, hop-hornbeam), picea abies (norway spruce), picea engelmannii (engelmann spruce), picea glauca (white spruce), picea mariana (black spruce), picea rubens (red spruce), picea sitchensis (sitka spruce), picea spp. (unidentified spruce), pinus albicaulis (whitebark pine), pinus banksiana (jack pine), pinus contorta (lodgepole pine), pinus monticola (western white pine), pinus ponderosa (ponderosa pine), pinus resinosa (red pine), pinus spp. (unidentified pine), pinus strobus (eastern white pine), pinus sylvestris (scots pine), populus balsamifera (balsam poplar), populus grandidentata (largetooth aspen), populus spp. (unidentified poplar), populus tremuloides (trembling aspen), populus trichocarpa (black cottonwood), prunus pensylvanica (pin cherry), prunus serotina (black cherry), pseudotsuga menziesii (douglas-fir), quercus alba (white oak), quercus macrocarpa (bur oak), quercus rubra (red oak), quercus spp. (unidentified oak), salix spp. (unidentified willow), sorbus americana (american mountain-ash), thuja occidentalis (eastern white-cedar), thuja plicata (western redcedar), tilia americana (basswood), tsuga canadensis (eastern hemlock), tsuga heterophylla (western hemlock), tsuga mertensiana (mountain hemlock), tsuga spp. (unidentified hemlock), ulmus americana (white elm), unidentified needleaf, unidentified broadleaf, broadleaf species, needleaf species, unknown species

Earth's 7 billion human inhabitants have a nearly insatiable appetite for natural resources, including minerals mined from the planet's crust. But the consumption of mineral resources comes with costs, among them the creation of scars and pock-marks on the face of the Earth. Take a guided tour of some of the world's largest and most prominent surface mines. This story was produced for Smithsonian by Esri's Story Maps team using the new Story Map Journal app. It appears on this Smithsonian website page: http://www.smithsonian.com/science-nature/peering-some-worlds-largest-mines-1-180952010/For more information visit storymaps.arcgis.com.

DATASET: Alpha version 2000 and 2010 estimates of numbers of people per grid square, with national totals adjusted to match UN population division estimates (http://esa.un.org/wpp/) and MODIS-derived urban extent change built in. REGION: Asia SPATIAL RESOLUTION: 0.000833333 decimal degrees (approx 100m at the equator) PROJECTION: Geographic, WGS84 UNITS: Estimated persons per grid square MAPPING APPROACH: Land cover based, as described on the website and in: Gaughan AE, Stevens FR, Linard C, Jia P and Tatem AJ, 2013, High resolution population distribution maps for Southeast Asia in 2010 and 2015, PLoS ONE, 8(2): e55882 FORMAT: Geotiff (zipped using 7-zip (open access tool): www.7-zip.org) FILENAMES: Example - VNM00urbchg.tif = Vietnam (VNM) population count map for 2000 (00) adjusted to match UN national estimates and incorporating urban extent and urban population estimates for 2000. DATE OF PRODUCTION: July 2013 Dataset construction details and input data are provided here: www.asiapop.org and here: http://www.plosone.org/article/info:doi/10.1371/journal.pone.0055882

The map and digital data layers present historic sites described in these sources: Maryland’s Upper Choptank River and Tuckahoe River Cultural Resource Inventory (1999)Lower Choptank River Cultural Resource Inventory (2002)1875 Isler Map of Caroline County1897 Salisbury Map of Caroline CountyDenton Journal, 1865-1965National Register of Historic Places (NRHP) sites in the upper Choptank watershedMaryland Historical Trust (MHT) sites in the upper Choptank watershedPurposeChoptank River Heritage (CRH) is a not-for-profit effort based in Caroline County, Maryland. CRH carries out research into historic maps and other sources and publishes digital maps and narratives about people, places, and events in the county's past. We seek to nurture a sense of place, encourage historic preservation, and promote conservation of the Choptank and Tuckahoe Rivers and the county's natural environment.Online ResourceChoptank River Heritage WebsiteData Creation Date2012-08-28Map Publication Date2016-12-20Contact InformationContact NameDon BarkerOrganization NameChoptank River Heritage (CRH)Position NameGeographer-HistorianRoleAuthorContact InstructionsBy email only:info@choptankriverheritage.org