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13,117 results for “Maps”
Agile Map Version 1
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Tree-ring-based annual aboveground biomass increment maps in North America
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Interactive maps of Iridaceae family in Bulgaria
<p>Pack of interactive distribution maps of Iridaceae in Bulgaria</p> <p>The maps are accessible from here: https://botanica.gallery/wp/archives/27276</p> <p> </p>
Spatial probability maps of the main morphological patterns of the inferior frontal sulcus in fsaverage space
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Data and program of "Impact of schematic representations of road maps on pedestrian route planning"
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Systematic Literature Mapping (2016-2024)
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OpenSemanticLab-MAP-Demo at the BIG-MAP Dataworkshop in Grindelwald
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txt files of the raw triaxial test resutls and MATLAB mapping files
<ul> <li>README Excel file</li> <li>Txt files of the Raw data</li> <li>Matlab files for the void ratio mapping</li> </ul>
Counting region and mapped craters in the Chang'e-6 probe landing area
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Bike Trajectory Mapping Dataset
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Data from: Mapping canopy cover for municipal forestry monitoring: Using free Landsat imagery and machine learning
<p><strong>Paper Abstract:</strong></p> <p>Trees across the urban-rural continuum are recognized for their ecological importance and ecosystem services. Municipalities often utilize spatial canopy cover data for monitoring this resource. Monitoring frameworks typically rely on fine-scale maps derived from very high spatial resolution sensors, which are high quality but expensive and unwieldy for consistent wide-area monitoring. In this paper, we explore how free Landsat imagery, supported by very high-resolution imagery interpretation and/or digital hemispherical photographs, can be used to effectively map canopy cover at a scale appropriate for municipal monitoring. We compare linear models and random forest machine learning for predicting canopy cover across a landscape (general) and within specific land covers (specialized). We create 2018 canopy cover maps and track progress towards forestry objectives in a region of southern Ontario, Canada. Random forest models using all reference data perform best for general use (R<sup>2</sup>: 0.90, RMSE: 10.1%), separating non-canopy vegetation (e.g., agricultural fields) from tree canopy. Specialized models are useful in forest land cover patches, where hemispherical photographs relate with Landsat at a moderate strength (R<sup>2</sup>: 0.67, RMSE: 2.73%), and in residential areas, capturing the totality of canopy cover variation (R<sup>2</sup>: 0.85, RMSE: 5.66%). Accuracy was assessed with standard cross-validation, which is useful given limited resources. However, following best practice, an independent reference sample was also leveraged to assess the best general model (R<sup>2</sup>: 0.86, RMSE: 11.4%), indicating that cross-validation was slightly overoptimistic. Results show that Caledon, a rural-dominant municipality within the study area, is the greenest (34% canopy cover). The two cities (Brampton and Mississauga) have 15.9% and 17.5% canopy cover. Residential canopy criteria indicate “Good” performance in Caledon, “Moderate” in Mississauga, and “Low” in Brampton based on our 2018 assessment. The methods described here can provide municipalities with a low-cost approach for tree canopy monitoring across complex landscapes.</p> <p> </p> <p><strong>Data details:</strong></p> <p>See paper. </p>
MAP 1 in One new species of the genus Acosmetides Chang, Wang & Shi, 2021 (Tettigoniidae: Meconematinae) from Chongqing, China
MAP 1. Distribution map of Acosmetides spp.
MAP 1 in On the subgenus Eurysunius Reitter of Turkey IX. Three new species from central northern Anatolia, with an identification key to Turkish species (Coleoptera: Staphylinidae: Paederinae, Astenus)
MAP 1. Distribution of Astenus (Eurysunius) species in Turkey (28 species)
Materials and statistics of map-use experiment
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Baseline and Future Habitat Suitability Maps for Tree Species Prioritized for Food Tree Portfolios for Zambia
<p>This archive includes habitat suitability maps for six native food tree species (<em>Anisophyllea boehmii</em> Engl., <em>Parinari curatellifolia</em> Planch. ex Benth., <em>Strychnos cocculoides</em> Baker, <em>Tamarindus indica </em>L., <em>Thespesia garckeana </em>F.Hoffm. [syn. <em>Azanza garckeana </em>(F.Hoffm.) Exell & Hillc.] and <em>Uapaca kirkiana</em>|Müll.Arg.|) and four exotic food tree species (<em>Carica papaya</em> L., <em>Mangifera indica</em> L., <em>Persea americana</em> Mill. and <em>Psidium guajava</em> L.). These species had been prioritized by the project. Species suitability modelling followed the BIOCLIM algorithm whereby a climate suitability score is calculated that reflects the core distribution (5% - 95%) and the marginal distribution (0% - 5% or 95% or 100%) of a species in environmental space. The BIOCLIM algorithm was expanded to reflect the middle of the environmental range (25% - 75%).</p> <p>Species suitability was inferred through bioclimatic ranges documented in the Tree Globally Observed Environmental Ranges database (TreeGOER; Kindt <a href="https://onlinelibrary.wiley.com/doi/10.1111/gcb.16914">2023</a>). Baseline suitability maps used the historical climate documented by WorldClim 2.1 (Fick & Hijmans <a href="https://doi.org/10.1002/joc.5086">2017</a>). Future suitability maps correspond to a low emissions scenario (Shared Socio-Economic Pathway [SSP] 1-2.6) and a high emissions scenario (SSP 3-7.0), both calculated as medians from Global Climate Models (GCM) projections for the 2050s (2041-2060) available from WorldClim 2.1 (respectively from 23 and 18 GCMs).</p> <p>For larger sets of tree species native to Zambia, it has recently become possible to filter tree species by bioclimatic conditions of the planting site with the GlobalUsefulNativeTrees database (GlobUNT; Kindt et al. <a href="https://www.nature.com/articles/s41598-023-39552-1">2023</a>). The GlobUNT database internally uses TreeGOER environmental ranges and the same BIOCLIM algorithm that was used the generate the habitat suitability maps. Included in this archive is a list of native tree species to Zambia that were filtered for the use category of human food.</p> <p> </p> <p>When using these maps, cite the following:</p> <p>· Fick, S. E., & Hijmans, R. J. (2017). WorldClim 2: New 1‐km spatial resolution climate surfaces for global land areas. <em>International Journal of Climatology</em>, <em>37</em>(12), 4302–4315. <a href="https://doi.org/10.1002/joc.5086">https://doi.org/10.1002/joc.5086</a></p> <p>· Kindt, R. (2023). TreeGOER: A database with globally observed environmental ranges for 48,129 tree species. <em>Global Change Biology</em>, 29, 6303–6318. <a href="https://doi.org/10.1111/gcb.16914">https://doi.org/10.1111/gcb.16914</a></p> <p> </p> <p>Information in this archive were generated for the project of <strong>Piloting incentive-based agricultural portfolios for nutrition and resilience in Zambia</strong>. For more information about this project, check the website: <a href="https://www.worldagroforestry.org/project/piloting-incentive-based-agricultural-portfolios-nutrition-and-resilience-zambia">Piloting incentive-based agricultural portfolios for nutrition and resilience in Zambia | World Agroforestry | Transforming Lives and Landscapes with Trees</a></p>
Live fuel moisture content maps for western USA
<p>The attached .rar file contains live fuel moisture content maps for Western USA at 250 m resolution for every 15 days from 2016 to 2020. The method to create the maps is described in the manuscript Rao, Krishna, A. Park Williams, Jacqueline Fortin Flefil, and Alexandra G. Konings. "SAR-enhanced mapping of live fuel moisture content." Remote Sensing of Environment 245 (2020): 111797.</p>
CSET Map of Science
<p>This dataset contains basic metadata for the <a href="https://sciencemap.eto.tech">CSET Map of Science</a> in JSONL form.</p>
Lithology and Distance to fault maps
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MAPS 21A–D in Synopsis of the Snakes of the Philippines A Synthesis of Data from Biodiversity Repositories, Field Studies, and the Literature
MAPS 21A–D. Geographic range maps for Philippine records of (A) Lycodon alcalai; (B) Lycodon bibonius; (C) Lycodon capucinus; (D) Lycodon chrysoprateros.
MAPS 28A–D in Synopsis of the Snakes of the Philippines A Synthesis of Data from Biodiversity Repositories, Field Studies, and the Literature
MAPS 28A–D. Geographic range maps for Philippine records of (A) Oligodon modestus; (B) Oligodon notospilus; (C) Oligodon perkinsi; (D) Ophiophagus hannah.
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.