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3,105 results for “Vegetation =”
Back scattering data of AnisoVeg: Anisotropy and Nadir-normalized MODIS MAIAC datasets for satellite vegetation studies in South America
<p><strong>Title: Back scattering data of AnisoVeg: Anisotropy and Nadir-normalized MODIS MAIAC datasets for satellite vegetation studies in South America</strong></p> <p>Ricardo Dalagnol (ricds@hotmail.com)</p> <p> </p> <p><strong>This dataset is associated with the dataset found in the Zenodo repository below and a paper under review. Feel free to use this dataset, but please cite the repository below (while the paper is under review).</strong></p> <p>Dalagnol, Ricardo; Galvão, Lênio Soares; Wagner, Fabien Hubert; Moura, Yhasmin Mendes; Gonçalves, Nathan; Wang, Yujie; Lyapustin, Alexei; Yang, Yan; Saatchi, Sassan; Aragão, Luiz Eduardo Oliveira e Cruz. (2022). "AnisoVeg: Anisotropy and Nadir-normalized MODIS MAIAC datasets for satellite vegetation studies in South America". (Version v1) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.3878879</p>
Remaining bands of Forward scattering data of AnisoVeg: Anisotropy and Nadir-normalized MODIS MAIAC datasets for satellite vegetation studies in South America
<p><strong>Title: Remaining bands of Forward scattering data of AnisoVeg: Anisotropy and Nadir-normalized MODIS MAIAC datasets for satellite vegetation studies in South America</strong></p> <p>Ricardo Dalagnol (ricds@hotmail.com)</p> <p> </p> <p><strong>This dataset is associated with the dataset found in the Zenodo repository below and a paper under review. Feel free to use this dataset, but please cite the repository below (while the paper is under review).</strong></p> <p>Dalagnol, Ricardo; Galvão, Lênio Soares; Wagner, Fabien Hubert; Moura, Yhasmin Mendes; Gonçalves, Nathan; Wang, Yujie; Lyapustin, Alexei; Yang, Yan; Saatchi, Sassan; Aragão, Luiz Eduardo Oliveira e Cruz. (2022). "AnisoVeg: Anisotropy and Nadir-normalized MODIS MAIAC datasets for satellite vegetation studies in South America". (Version v1) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.3878879</p>
Forward scattering data of AnisoVeg: Anisotropy and Nadir-normalized MODIS MAIAC datasets for satellite vegetation studies in South America
<p><strong>Title: Forward scattering data of AnisoVeg: Anisotropy and Nadir-normalized MODIS MAIAC datasets for satellite vegetation studies in South America</strong></p> <p>Ricardo Dalagnol (ricds@hotmail.com)</p> <p> </p> <p><strong>This dataset is associated with the dataset found in the Zenodo repository below and a paper under review. Feel free to use this dataset, but please cite the repository below (while the paper is under review).</strong></p> <p>Dalagnol, Ricardo; Galvão, Lênio Soares; Wagner, Fabien Hubert; Moura, Yhasmin Mendes; Gonçalves, Nathan; Wang, Yujie; Lyapustin, Alexei; Yang, Yan; Saatchi, Sassan; Aragão, Luiz Eduardo Oliveira e Cruz. (2022). "AnisoVeg: Anisotropy and Nadir-normalized MODIS MAIAC datasets for satellite vegetation studies in South America". (Version v1) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.3878879</p>
The relative influence of history, climate, topography and vegetation structure on local animal richness varies among taxa and spatial grains
<p>Understanding the spatial scales at which environmental factors drive species richness patterns is a major challenge in ecology. Due to the trade-off between spatial grain and extent, studies tend to focus on a single spatial scale, and the effects of multiple environmental variables operating across spatial scales on the pattern of local species richness have rarely been investigated.</p> <p>Here, we related variation in local species richness of ground beetles, landbirds, and small mammals to variation in vegetation structure and topography, regional climate, biome diversity, and glaciation history for 27 sites across the USA at two different spatial grains.</p> <p>We studied the relative influence of broad-scale (landscape) environmental conditions using variables estimated at the site level (climate, productivity, biome diversity, and glacial era ice cover) and fine-scale (local) environmental conditions using variables estimated at the plot level (topography and vegetation structure) to explain local species richness. We also examined whether plot-level factors scale up to drive continental scale richness patterns. We used Bayesian hierarchical models and quantified the amount of variance in observed richness that was explained by environmental factors at different spatial scales.</p> <p>For all three animal groups, our models explained much of the variation in local species richness (85-89%), but site-level variables explained a greater proportion of richness variance than plot-level variables. Temperature was the most important site-level predictor for explaining variance in landbirds and ground beetles richness. Some aspects of vegetation structure were the main plot-level predictors of landbird richness. Environmental predictors generally had poor explanatory power for small mammal richness, while glacial era ice cover was the most important site-level predictor.</p> <p>Relationships between plot-level factors and richness varied greatly among geographical regions and spatial grains, and most relationships did not hold when predictors were scaled up to continental scale. Our results suggest that the factors that determine richness may be highly dependent on spatial grain, geography, and animal group. We demonstrate that instead of artificially manipulating the resolution to study multi-scale effects, a hierarchical approach that uses fine grain data at broad extents could help solve the issue of scale selection in environment-richness studies. </p>
Differential seasonal avoidance of anthropogenic features and woody vegetation by Lesser Prairie-chickens
<p>The influence of seasonal variation in animal behavior and the corresponding response in habitat selection is a critical component of habitat selection analyses. To examine this relationship, we conducted multi-scale analyses of Lesser Prairie-chicken (<em>Tympanuchus pallidicinctus</em>) habitat selection in relation to anthropogenic infrastructure associated with oil and gas development, mesquite, and trees during the spring and summer at home range and lek area scales. We tracked 159 Lesser Prairie-chickens using VHF radiotelemetry or PTT-GPS transmitters in the sand shinnery oak prairie region of eastern New Mexico, USA. We used discrete choice models and logistic regression to assess seasonal patterns of habitat selection at home range and lek area scales, respectively. The static habitat features we examined allowed us to observe differential patterns of habitat selection between the two seasons, revealing an overall increase in the degree of avoidance following the spring season. Results of our home range scale analysis indicate that utility pole density, mesquite cover and proximity, distance to active well pads, and proximity to private roads have significant negative effects on habitat selection during both seasons. Avoidance of dense utility pole areas was significantly greater during the summer. Lek area habitat selection results were similar, but differences in sensitivity to features between seasons were stronger. Avoidance of high mesquite cover and utility pole and tree densities, in particular, was significantly greater in the summer. The effects of density and cover of these features, which have previously been understudied or overlooked in Lesser Prairie-chicken research, provide critical information for future conservation practices. Furthermore, our study highlights the importance of accounting for potential seasonal patterns of their study species to best examine habitat selection.</p>
Data for: The formation of "mega‐flocks" depends on vegetation structure in montane coniferous forests of Taiwan
<p>A mixed-species bird flock is a social assemblage where two or more bird species are moving together while foraging and might benefit from increased foraging efficiency and antipredator vigilance. A "mega-flock," which includes flocking species from different vegetation layers, often exhibits high species diversity. Mechanisms for the formation of mega-flocks have not yet been explored. In this study, we evaluated the influence of vegetation structure and bird species diversity/richness in driving the occurrence of mega-flocks. We investigated the composition of mixed-species flocks, local bird communities, and vegetation structure in five vegetation types of two high-elevation sites in central Taiwan. (For more details, please see the paper which has been published in Ecology and Evolution, entitled "The formation of "mega-flocks" depends on vegetation structure in montane coniferous forests of Taiwan." Doi: https://doi.org/10.1002/ece3.8608)</p>
Data from: Defensible-space treatment of <114,000 ha 40 m from high-risk buildings near wildland vegetation could reduce loss in WUI wildfire disasters across Colorado's 27 million ha
<p><strong>Context </strong> </p> <p>WUI wildfire disasters are increasing, as fires are pushed by strong winds and drier fuels across landscapes and into communities. Possible disasters make maintaining and restoring landscape-scale fire in fire-adapted ecosystems difficult. Rapid action is needed to reduce building loss in WUI wildfire disasters. </p> <p><strong>Objectives </strong> </p> <p>In a Colorado case study, I used distance-based empirical modeling to refine potential risk of building loss in WUI wildfire disasters to focus risk-reduction efforts.</p> <p><strong>Methods</strong> </p> <p>New empirical modeling showed 95% of USA building loss in WUI wildfire disasters was within 100 m of wildland vegetation. I used modeling to estimate and map potential relative risk of a WUI wildfire disaster for each of 2,185,953 buildings in Colorado.</p> <p><strong>Results </strong> </p> <p>High-risk buildings were 241,375 or 11% of total buildings. However, the 20-40 m essential defensible space around these buildings covered only 46,767- 114,084 ha. Area within 100 m of wildland vegetation, containing these buildings, covered 475,840 ha or 1.8% of Colorado's 27 million ha. About 95% of at-risk land within 100 m of wildland vegetation is not federally owned, and WUI wildfire disasters are mostly from fires started on private land.</p> <p><strong>Conclusions</strong> </p> <p>Treating ≤114,084 ha of defensible space could leave the 27 million ha of Colorado with lower WUI wildfire disaster-risk to buildings. High risk of building loss is rarely a federal land-management problem. If the goal is rapid reduction of building loss in WUI wildfire disasters, focus resources on defensible space 20-40 m from WUI buildings within 100 m of wildland vegetation.</p>
Molecular gut content analysis indicates the inter- and intra-guild predation patterns of spiders in conventionally managed vegetable fields
<p>Inter- and intra-guild interactions are important in the coexistence of predators and their prey, especially in highly disturbed vegetable cropping systems with sporadic food resources. Assessing the dietary range of a predator taxon characterized by diverse foraging behavior using conventional approaches, such as visual observation and conventional molecular approaches for prey detection, has serious logistical problems.<i> </i>In this study, we investigated the trophic interactions of a functionally diverge group of predators -spiders- to accomplish the ultimate goal that is the predation of spiders on major crop pests. We used high-throughput sequencing (HTS) and biotic interaction networks to precisely annotate the predation spectrum and highlight the predator–predator and predator-prey interactions in Brassica fields. The prey taxa in the gut of spiders were mainly enriched with insects (including dipterans, coleopterans, orthopterans, hemipterans and lepidopterans) and arachnids (such as Araneae) along with a wide range of other prey factions. Despite the generalist foraging behavior of spiders, the community structure analysis and interaction networks highlighted the overrepresentation of particular prey taxa in the gut of each spider family, as well as showed the intra-family predation between different spiders. Identifying the diverse trophic niche proportions underpins the importance of spiders as predators of pests in highly disturbed agroecosystems. More specifically, combining HTS with advanced ecological community analysis reveals the preferences and biological control potential of particular spider taxa, so provides a valuable evidence base for targeted conservation biological control efforts in complex trophic networks.</p>
A dataset of sulfur content and density of vegetation on the Tibetan Plateau
<p>As an important part of China's terrestrial ecosystem, the variation and distribution of sulfur in the vegetation of the Tibetan Plateau (TP) will have a profound impact on the national and even global sulfur cycle. We collected and sorted out the field survey and test data of the research group from 2019 to 2020. This dataset encompasses forest, grassland, shrubland, desert and other major ecosystem types, including the average sulfur content, density and storage data of different vegetation types and plant organs. The establishment of this data set provides important basic data for the assessment of regional vegetation biomass and sulfur reserves and the optimization of sulfur cycle model.</p>
FIGURE. Landscapes and vegetation types at Quiçama National Park. A. Wooded savannah with Adansonia digitata. B. Mosaic of wooded savannah and thicket. C. Grassy savannah. D. Slope with thicket. E. Grassy savanna with Setaria welwitschi. F. Wooded savannah. G. Cuanza River shores with herbaceous vegetation. H. Herbaceous vegetation on the banks of the Cuanza River and slope with open forest. I. Coastal sands. J. Mangrove at the Cuanza River estuary, with Rhizophora racemosa. (Photographs by the authors). in An annotated checklist of the vascular flora of Quiçama National Park, Angola
FIGURE. Landscapes and vegetation types at Quiçama National Park. A. Wooded savannah with Adansonia digitata. B. Mosaic of wooded savannah and thicket. C. Grassy savannah. D. Slope with thicket. E. Grassy savanna with Setaria welwitschi. F. Wooded savannah. G. Cuanza River shores with herbaceous vegetation. H. Herbaceous vegetation on the banks of the Cuanza River and slope with open forest. I. Coastal sands. J. Mangrove at the Cuanza River estuary, with Rhizophora racemosa. (Photographs by the authors).
FIGURE 2. Dichorisandra rigidifolia. A. Habitat. B. Habit with inflorescence detail. C. Vegetative branch, note the alternate leaves. D in Dichorisandra rigidifolia (Commelinaceae), a new species from Cerrado of Goiás, Brazil
FIGURE 2. Dichorisandra rigidifolia. A. Habitat. B. Habit with inflorescence detail. C. Vegetative branch, note the alternate leaves. D. Detail of the glabrous stem and rest of the leaf sheath. E. Fertile branch. F. Inflorescence showing cincinni and floral buds. G. Flower in ventral view. H. Cincinnus in lateral view. I. Portion of the cincinnus showing the persistent bracts. J. Capsules, note the smooth surface.
MUSES Normalized Difference Vegetation Index (NDVI) 16-Day 30m Geographic Grid over Beijing Since 1984
<p>The MUltiscale Satellite remotE Sensing (MUSES) product suite includes products with different spatial and temporal resolutions for parameters such as Normalized Difference Vegetation Index (NDVI), Near-Infrared Reflectance of Vegetation (NIRv), Leaf Area Index (LAI), Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), Fractional Vegetation Coverage (FVC), Gross Primary Production (GPP), Net Primary Production (NPP). For more information about the MUSES products, please refer to this website (<a href="https://muses.bnu.edu.cn/">https://muses.bnu.edu.cn/</a>).</p> <p>This dataset is the MUSES NDVI product at 30 m spatial resolution and 16-day temporal resolution over Beijing. The MUSES NDVI product is provided on Geographic grid and spans from 1984 to 2021 (continuously updated). It was generated from the Landsat collection 2 surface reflectance data using a temporally continuous vegetation indices-based land-surface reflectance reconstruction (VIRR) method (Xiao <em>et al</em>., 2015; Xiao <em>et al</em>., 2017). The MUSES NDVI product is spatially complete and temporally continuous.</p> <p><strong>Dataset Characteristics:</strong></p> <ul> <li>Spatial Coverage: 115.416599º E – 117.508219º E, 39.441929º N – 41.059283º N</li> <li>Temporal Coverage: 1984 – 2021</li> <li>Spatial Resolution: 0.000269469º (approximately 30 m)</li> <li>Temporal Resolution: 16 days</li> <li>Projection: Geographic</li> <li>Data Format: HDF</li> <li>Scale: 0.0001</li> <li>Valid Range: 0 – 10000</li> </ul> <p><strong>Citation </strong>(Please cite this paper whenever these data are used)<strong>:</strong></p> <ol> <li>Xiao Zhiqiang, <em>et al</em>. (2015). Reconstruction of Satellite-Retrieved Land-Surface Reflectance Based on Temporally-Continuous Vegetation Indices. <em>Remote Sensing</em>, 7, 9844-9864</li> <li>Xiao Zhiqiang, <em>et al</em>. (2017). Reconstruction of Long-Term Temporally Continuous NDVI and Surface Reflectance From AVHRR Data. <em>IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing</em>, 10, 5551-5568</li> </ol> <p>If you have any questions, please contact Prof. Zhiqiang Xiao (zhqxiao@bnu.edu.cn).</p> <p> </p>
Data from: Ornithogenic vegetation: How significant has the seabird influence been on the Aleutian Island vegetation during the Holocene?
<p>In the Aleutian Islands during the Holocene, terrestrial predators were actually absent; as a result, large seabird colonies thrived along the coasts or across entire islands. Bird guano enriches the soil with nitrogen, which can lead to the formation of highly modified ornithogenic (bird-formed) ecosystems. For a more detailed investigation of avian influence, we reconstructed more than 10,000-year-old vegetation dynamics of the coast of Shemya Island (Near Islands) by pollen analysis. At the initial stages of vegetation development (10,000-4,600 cal yr BP), sedge-heather tundra grew in the studied area. A seabird colony existed on Shemya from 4,600 to 2,400 cal yr BP according to stable isotope analysis. During a period of at least 2,200-years nitrogen enrichment led to the development of ornithogenic herb meadows with a high presence of Apiaceae. A long-term increase in δ15N above 9-10‰ led to radical shifts in vegetation. Noticeable reduction of seabird colonies due to human hunting led to grass-meadows spreading. After a prolonged decrease δ15N below 9-10‰ (2,400 cal yr BP to present), there was a shift towards less productive sedge-tundra communities. However, the significant enrichment of guano affected only the coastal vegetation and did not alter the inland Shemya Island.</p>
Data used in paper "The sensitivity of tidal channel systems under the influences of initial bed conditions, vegetation, and tidal asymmetry".
<p>Data used in paper "The sensitivity of tidal channel systems under the influences of initial bed conditions, vegetation, and tidal asymmetry".</p>
MUSES Fractional Vegetation Coverage (FVC) 16-Day 30m Geographic Grid over Beijing Since 1984
<p>The MUltiscale Satellite remotE Sensing (MUSES) product suite includes products with different spatial and temporal resolutions for parameters such as Normalized Difference Vegetation Index (NDVI), Near-Infrared Reflectance of Vegetation (NIRv), Leaf Area Index (LAI), Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), Fractional Vegetation Coverage (FVC), Gross Primary Production (GPP), Net Primary Production (NPP). For more information about the MUSES products, please refer to this website (<a href="https://muses.bnu.edu.cn/">https://muses.bnu.edu.cn/</a>).</p> <p>This dataset is the MUSES FVC product at 30 m spatial resolution and 16-day temporal resolution over Beijing. The MUSES FVC product is provided on Geographic grid and spans from 1984 to 2021 (continuously updated). It was generated from the MUSES LAI product at 30 m resolution and other ancillary information using the complement to unity of the transmittance of light through the entire canopy in the nadir viewing direction (Xiao <em>et al</em>., 2016). The MUSES FVC values are physically consistent with the corresponding MUSES LAI values. The MUSES FVC product is spatially complete and temporally continuous.</p> <p><strong>Dataset Characteristics:</strong></p> <ul> <li>Spatial Coverage: 115.416599º E – 117.508219º E, 39.441929º N – 41.059283º N</li> <li>Temporal Coverage: 1984 – 2021</li> <li>Spatial Resolution: 0.000269469º (approximately 30 m)</li> <li>Temporal Resolution: 16 days</li> <li>Projection: Geographic</li> <li>Data Format: HDF</li> <li>Scale: 0.004</li> <li>Valid Range: 0 – 250</li> </ul> <p><strong>Citation </strong>(Please cite this paper whenever these data are used)<strong>:</strong></p> <ol> <li>Xiao Zhiqiang, <em>et a</em>l. (2016). Estimating the Fractional Vegetation Cover from GLASS Leaf Area Index Product. <em>Remote Sensing</em>, 8, 337.</li> </ol> <p>If you have any questions, please contact Prof. Zhiqiang Xiao (zhqxiao@bnu.edu.cn).</p> <p> </p>
Supplementary material 2 from: Niemi M, Pöyry J, Heiskanen I, Uotinen V, Nieminen M, Erkomaa K, Wallenius K (2014) Variability of soil enzyme activities and vegetation succession following boreal forest surface soil transfer to an artificial hill. Nature Conservation 8: 1-25. https://doi.org/10.3897/natureconservation.8.6369
Figure S1: Explanation note: The studied sites at the onset of the study in June 2003: a) Top b) Grove c) Middle d) North e) Alder f) Spruce.
Supplementary material 5 from: Niemi M, Pöyry J, Heiskanen I, Uotinen V, Nieminen M, Erkomaa K, Wallenius K (2014) Variability of soil enzyme activities and vegetation succession following boreal forest surface soil transfer to an artificial hill. Nature Conservation 8: 1-25. https://doi.org/10.3897/natureconservation.8.6369
Figure S4: Explanation note: The studied s ites after a decade in June 2013: a) Top, b) Grove c) Middle d) North.
Data from: Unveiling the landscape predictors of resilient vegetation in coastal wetlands to inform conservation in the face of climate extremes
<div> <p>Unveiling spatial variation in vegetation resilience to climate extremes can inform effective conservation planning under climate change. Although many conservation efforts are implemented on landscape scales, they often remain blind to landscape variation in vegetation resilience. We explored the distribution of drought-resilient vegetation (i.e., vegetation that could withstand and quickly recover from drought) and its predictors across a heterogeneous coastal landscape under long-term wetland conversion, through a series of high-resolution satellite image interpretations, spatial analyses, and nonlinear modelling. We found that vegetation varied greatly in drought resilience across the coastal wetland landscape and that drought-resilient vegetation could be predicted with distances to coastline and tidal channel. Specifically, drought-resilient vegetation exhibited a nearly bimodal distribution and had a seaward optimum at ~2 km from coastline (corresponding to an inundation frequency of ~30%), a pattern particularly pronounced in areas further away from tidal channels. Furthermore, we found that areas with drought-resilient vegetation were more likely to be eliminated by wetland conversion. Even in protected areas where wetland conversion was slowed, drought-resilient vegetation was increasingly lost to wetland conversion at its landward optimum in combination with rapid plant invasions at its seaward optimum. Our study highlights that the distribution of drought-resilient vegetation can be predicted using landscape features but without incorporating this predictive understanding, conservation efforts may risk failing in the face of climate extremes.</p> <p> </p> <p>This ZIP file contains the following datasets and code for the above paper:</p> <p>1. data_cheng_et_al_GCB_2024.zip This file contain a total of three files.</p> <p>(1) analys_grid_50_m.shp This file is a shapefile for the 50-by-50 m grid cells analyzed in the focal study area and their IDs.</p> <p>(2) veg_change.shp This file contains the spatial distribution of vegetation before and after the 2011 drought. </p> <p> Variable list:</p> <p> change: Changes of vegetation after the 2011 drought.</p> <p> vegBefore: Distribution of vegetation before the drought.</p> <p> vegAfter: Distribution of vegetation after the drought.</p> <p>(3) tidalchannel.shp This file contains manually digitized tidal channels (and water surfaces).</p> <p>2. gridfeatures.xlsx This file contains data on the landscape features of each analysis grid.</p> <p>3. analyses.R This file contains the R code used for data analysis.</p> </div>
Vegetation samples at the permanent plots of LTER site "Appennino Centrale: Velino-Duchessa" (1993-2023)
<p>The present dataset comprises observations spanning from 1993 to 2023, focusing on biotic parameters collected from six permanent plots included into the LTER site “Appennino Centrale: Velino-Duchessa” (<a href="https://deims.org/12c79ecb-7890-4b75-9655-0883dacd8a29">https://deims.org/12c79ecb-7890-4b75-9655-0883dacd8a29</a>), located in Central Italy above the timberline (2125-2225 m a.s.l.). Specifically, it includes a synthesis of phytosociological relevés collected, according the Braun-Blanquet approach (coverage scale as modified by Pignatti) in 6 permanent plots of 10x10 m (https://deims.org/dataset/0c540fe8-1984-11e5-a766-005056ab003f), representative of two high-elevation plant communities (alpine tundra, <em>Saxifrago speciosae-Silenetum ceniasiae,</em> and snow-bed grassland, <em>Trifolio thalii-Festucetum microphyllae).</em> Species are named according to Flora d'Italia (Pignatti, 1982). The site, managed by Carabinieri, Forest and Environmental Protection Department, is part of the site “IT01- Apennines - High elevation Ecosystems – Italy” (<a href="https://deims.org/70b5c2bd-b0c3-4132-8988-f527893bfa42">https://deims.org/70b5c2bd-b0c3-4132-8988-f527893bfa42</a>) which belongs to the Long Term Ecological Research national and international networks (LTER-Italy, LTER-Europe and ILTER). The data collection started in 1993 and it is continuously updated every year.</p>
Remotely sensed vegetation phenology drives large fires spreading in northwestern Europe
<p><span>In recent years, an increase in the frequency of large fires has been reported in NW Europe, a region where a deeper understanding of the conditions conducive to dangerous fire behavior is needed. This study builds on recent efforts to characterize rate of spread (ROS) variation in the region and delves into vegetation and climatic drivers. For 58 large fires in this region, we analyzed phenology (using the temporal variation of satellite-measured vegetation indices) and weather, (using as the Canadian Fire Weather Index System). Results suggest that short-term vegetation greenness play an important role in predicting ROS: High greenness correlated non-linearly with low ROS, and fires spreading in the growing season described a drastic reduction in spread. Fire weather did not prove to be a good indicator of fast spread. Contrary to expectations, high danger related to fire weather ratings were associated with low ROS. This indicates the importance of temporal variability of vegetation greenness, the capability of remote sensing in capturing times when an ignition could generate fast-spreading fires, and the need for a fire weather danger rating system tailored to regional conditions.</span></p> <p> </p> <p><span>This is the repository for the clusterd fire events and its isochrones, and ROS vectors.</span></p>
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.