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36 results for “moisture content”
Input files, plotting scripts, and figures for "Smoldering combustion in cellulose and hemicellulose mixtures: Examining the roles of density, fuel composition, oxygen concentration, and moisture content"
<p>This bundle of files contains all the <a href="http://reaxfire.com/trac/gpyro">Gpyro</a> input files, data, plotting scripts, and figures for "Smoldering combustion in cellulose and hemicellulose mixtures: Examining the roles of density, fuel composition, oxygen concentration, and moisture content". The README.txt file contains additional details about the contents.</p>
Theory of Maximum Entropy Production (MEP) and Its Application to Microwave Remote Sensing - Simultaneous Retrieval of Soil Moisture and Vegetation Water Content
<p>A theory of maximum entropy production (MEP) for electromagnetic wave propagation in dielectric materials is proposed and applied to simultaneously retrieving soil moisture (SM) and vegetation water content (VWC) from L-band microwave brightness temperature (TB). One representation of the MEP principle states that a non-equilibrium system corresponds to such a configuration of energy fluxes that minimizes a dissipation function under the constraint of energy conservation. The dissipation function for radiative transfer is formulated as an analogy of that for heat transfer. A new physical parameter, radiative inertia as an analogy of thermal inertia, is introduced to characterize radiative attenuation in dielectric media. The radiative inertia is parameterized in terms of the penetration depth of electromagnetic waves as a function of the complex dielectric constant. The MEP based retrieval algorithm predicts SM and VWC by minimizing the dissipation function under the constraint of the conservation of radiative energy. The retrievals of SM and VWC based on the MEP theory were validated against field observations in tropical and temperate forested regions of the Amazon and North America. The proof-of-concept analysis demonstrates the capability of the MEP algorithm for simultaneous retrievals of SM and VWC even for dense canopy (e.g. VWC > 5 kg m-2). The MEP method is a new theoretical framework for developing innovative remote sensing algorithms of the Earth system not limited to just microwave observations.</p><p>Note: We would appreciate if users contact us for the use of the data.</p>
Ensemble of optimised machine learning algorithms for predicting surface soil moisture content at global scale (v1.0)
<p>This study investigates the estimation of daily SSM using eight optimised ML algorithms and ten ensemble models (constructed via model bootstrap aggregating techniques and five-fold cross-validation). The algorithmic implementations were trained and tested using the international soil moisture network (ISMN) data collected from 1722 stations distributed across the World. </p>
Sentinel-1 data over forest canopies ad different moisture content
<p>Data collected from three years of Sentinel-1 data over areas with full canopy cover and with consistent local incidence angle. Moisture was proxied from DC values taken from daily DC information estimated from weather stations.</p> <p>Process.R file will process the data and create the excel output that contains the output.</p>
Seed dormancy and germination traits of 27 species inhabiting the degraded karst mountain from central Yunnan-Guizhou Plateau: Seed mass and moisture content correlates with germination capacity
<p>Seed dormancy and germination play an important roles in regulating germination timing and plant fitness in harsh environment, especially for fragile karst region. Broadening the knowledge regarding seed ecology of native plant species can improve local restoration management due to the increased biodiversity and success of seedling establishment, yet few studies have addressed this. We examined the dormancy types and germination responses to temperature regimes as well as light conditions of totally 27 that were dominant or common species inhabiting a degraded karst mountain from central Yunnan-Guizhou Plateau and assessed the relationships between seed traits and germination index using a partial least squares regression (PLSR). Approximately 48% of the investigated species exhibited physiological dormancy, 37% exhibited nondormancy, 7% exhibited morphophysiological dormancy, 4% exhibited morphological dormancy and 4% exhibited physical dormancy. Germination behaviors occurred in 16 of 27 species. The seed germination of 13 species strongly responded to seasonal temperature regimes, whereas 12 species were substantially affected by light conditions. About 94% species germinated to the maximum percent in warm temperature regimes (20/13 and 25/18 °C), while the remaining was in cool temperature regime (10/4 °C). The PLSR analysis indicated a significant positive correlation between seed mass and T50 m (time to 50% final germination), and a negative correlation between seed moisture content and percent germination, showing that small seeds, particularly those with a low moisture content, were more likely to have a greater germination capacity (including relative less germination time and higher germination percent) than large seeds in harsh karst environments. In general, these results strengthen the understanding of seed dormancy classification of dormant species and germination requirements of nondormant ones that representative of pioneer species of early stage of positive succession in seriously degraded sites and provide suggestion for species selection in local seed-based vegetation restoration.</p>
Datasets used in "Machine Learning and VIIRS Satellite Retrievals for Skillful Fuel Moisture Content Monitoring in Wildfire Management"
<p>Data sets used to train, validate, and test machine learning models for the prediction of 10-hour dead fuel moisture content. The data sets are for 375 m and 1 km resolutions. MADIS climatography data is also included. The datasets may be processed using the code supplied at https://github.com/NCAR/fmc_viirs. </p>
Seed dormancy and germination traits of 27 species inhabiting the degraded karst mountain from central Yunnan-Guizhou Plateau: Seed mass and moisture content correlates with germination capacity
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Chlorophyll fluorescence, moisture and chloride content for Morella cerifera on Hog Island, VA, 2007
Water content and fluorescence were measured for Morella cerifera shrubs on Hog Island, VA in 2007.
Data from: Fuel moisture content enhances nonadditive effects of plant mixtures on flammability and fire behavior
Fire behavior of plant mixtures includes a complex set of processes for which the interactive contributions of its drivers, such as plant identity and moisture, have not yet been unraveled fully. Plant flammability parameters of species mixtures can show substantial deviations of fire properties from those expected based on the component species when burnt alone; that is, there are nonadditive mixture effects. Here, we investigated how fuel moisture content affects nonadditive effects in fire behavior. We hypothesized that both the magnitude and variance of nonadditivity in flammability parameters are greater in moist than in dry fuel beds. We conducted a series of experimental burns in monocultures and 2‐species mixtures with two ericaceous dwarf shrubs and two bryophyte species from temperate fire‐prone heathlands. For a set of fire behavior parameters, we found that magnitude and variability of nonadditive effects are, on average, respectively 5.8 and 1.8 times larger in moist (30% MC) species mixtures compared to dry (10% MC) mixed fuel beds. In general, the moist mixtures caused negative nonadditive effects, but due to the larger variability these mixtures occasionally caused large positive nonadditive effects, while this did not occur in dry mixtures. Thus, at moister conditions, mixtures occasionally pass the moisture threshold for ignition and fire spread, which the monospecific fuel beds are unable to pass. We also show that the magnitude of nonadditivity is highly species dependent. Thus, contrary to common belief, the strong nonadditive effects in mixtures can cause higher fire occurrence at moister conditions. This new integration of surface fuel moisture and species interactions will help us to better understand fire behavior in the complexity of natural ecosystems.
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>
Experimental moisture content and water saturation and modeled output NAPL-phase saturation
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Graph of dependence of moisture content of sheepskin leather tissue in the canning process
<p>Graph of dependence of moisture content of sheepskin leather tissue in the canning process</p>
Data from: Seed moisture content as a primary trait regulating the lethal temperature thresholds of seeds.
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Data from: Fuel moisture content enhances nonadditive effects of plant mixtures on flammability and fire behavior
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BOREAS TE-06 Predawn Leaf Water Potentials and Foliage Moisture Content Data
The BOREAS TE-06 team collected several data sets to examine the influence of vegetation, climate, and their interactions on the major carbon fluxes for boreal forest species. This data set contains summaries of predawn leaf water potentials and foliage moisture contents collected at the TF and CEV sites that had canopy access towers. The data was collected on a nearly weekly basis from early June to late August 1994 by TE-06, members of the BOREAS staff, and employees of Environment Canada.
Spectra of walnut kernel for moisture content measurement
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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.