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135 results for “Water content”
SMEX04 Vegetation Water Content Data, Sonora, Version 1
Notice to Data Users: The documentation for this data set was provided solely by the Principal Investigator(s) and was not further developed, thoroughly reviewed, or edited by NSIDC. Thus, support for this data set may be limited.This data set consists of Vegetation Water Content (VWC) data for two Soil Moisture Experiment 2004 (SMEX04) regional study areas: Arizona, USA and Sonora, Mexico. VWC was derived from the Normalized Difference Infrared Index (NDII) which was obtained from Landsat 5 Thematic Mapper (TM) imagery.
SMEX04 Vegetation Water Content Data, Arizona, Version 1
Notice to Data Users: The documentation for this data set was provided solely by the Principal Investigator(s) and was not further developed, thoroughly reviewed, or edited by NSIDC. Thus, support for this data set may be limited.This data set consists of Vegetation Water Content (VWC) data for two Soil Moisture Experiment 2004 (SMEX04) regional study areas: Arizona, USA and Sonora, Mexico.
CAMEX-4 DC-8 NEVZOROV TOTAL CONDENSED WATER CONTENT SENSOR V1
The CAMEX-4 DC-8 Nevzorov Total Condensed Water Content Sensor dataset was collected by the Nevzorov total condensed water content sensor which was used to measure the total water content of air sampled during the CAMEX-4 campaign. The Nevzorov water vapor probe flew aboard the NASA DC-8 aircraft during CAMEX-4 to study tropical storms and hurricanes. Nevzorov is a so-called hot-wire device, where two resistors are heated to evaporate all hydrometeors that touch their surfaces during the flight. Due to their shape, they are able to catch small droplets or droplets and ice crystals. The amount of energy necessary to evaporate particles is a direct measure of the liquid water content of the hydrometeor (liquid or frozen) and also gives an indication of the water vapor present.
CAMEX-4 CVI CLOUD CONDENSED WATER CONTENT V1
The CAMEX-4 DC-8 Forward and NADIR Video dataset consists of DVDs which capture the forward and nadir views from the NASA DC-8 aircraft during CAMEX-4 flights. These videos contain timestamps and the recorded voice channels of the scientists and mission managers aboard the aircraft during flights studying storm conditions.
SMEX02 Vegetation Water Content, Iowa Regional and Walnut Creek Watershed, Version 1
This data set consists of Vegetation Water Content (VWC) data.
NAMMA CVI CLOUD CONDENSED WATER CONTENT V1
In the NAMMA CVI Cloud Condensed Water Content dataset the counterflow virtual impactor (CVI) was used to measure condensed water content (liquid water or ice in particles about 8 microns in diameter and up) and Cloud Condensation Nuclei (CCN) on the DC-8 during NASA African Monsoon Multidisciplinary Analyses (NAMMA). This mission was based in the Cape Verde Islands, 350 miles off the coast of Senegal in west Africa. Commencing in August 2006, NASA scientists employed surface observation networks and aircraft to characterize the evolution and structure of African Easterly Waves (AEWs) and Mesoscale Convective Systems over continental western Africa, and their associated impacts on regional water and energy budgets. Water vapor was measured with a MayComm Tunable Diode Laser (TDL) hygrometer and non-volatile particles are examined with an optical particle counter, a condensation nuclei counter, and an impactor for subsequent chemical analyses.
Body Water Content in Cyanotic Congenital Heart Disease
ClinicalTrials.gov study NCT00000107. IPD Sharing: Not stated. Countries: 1. Publications: 0.
SMAPVEX12 Vegetation Water Content Map V001
The daily Vegetation Water Content (VWC) maps for the Soil Moisture Active Passive Validation Experiment 2012 (SMAPVEX12) were derived by calculating Normalized Difference Vegetation Index (NDVI) from SPOT and RapidEye satellite overpasses and then interpolating it for each day of the campaign. In addition, samples from a range of vegetation types were used to compare ground-based measurements to the satellite-based estimates.
CLASIC07 Vegetation Water Content Map V001
The Vegetation Water Content (VWC) map for the Cloud and Land Surface Interaction Campaign 2007 (CLASIC07) was derived by calculating Normalized Difference Water Index (NDWI) from ResourceSat-1 satellite imagery.
SMAPVEX08 Vegetation Water Content Map V001
The Vegetation Water Content (VWC) map for the Soil Moisture Active Passive Validation Experiment 2008 (SMAPVEX08) was derived by calculating Normalized Difference Water Index (NDWI) from Satellite Pour l'Observation de la Terre-4 (SPOT-4) overpasses on 11 October 2008. In addition, samples from a range of vegetation types were used to compare VWC and NDWI to the satellite imagery.
CLASIC07 Vegetation Water Content Map V001
The Vegetation Water Content (VWC) map for the Cloud and Land Surface Interaction Campaign 2007 (CLASIC07) was derived by calculating Normalized Difference Water Index (NDWI) from ResourceSat-1 satellite imagery.
SMAPVEX12 Vegetation Water Content Map V001
The daily Vegetation Water Content (VWC) maps for the Soil Moisture Active Passive Validation Experiment 2012 (SMAPVEX12) were derived by calculating Normalized Difference Vegetation Index (NDVI) from SPOT and RapidEye satellite overpasses and then interpolating it for each day of the campaign. In addition, samples from a range of vegetation types were used to compare ground-based measurements to the satellite-based estimates.
SMAPVEX08 Vegetation Water Content Map V001
The Vegetation Water Content (VWC) map for the Soil Moisture Active Passive Validation Experiment 2008 (SMAPVEX08) was derived by calculating Normalized Difference Water Index (NDWI) from Satellite Pour l'Observation de la Terre-4 (SPOT-4) overpasses on 11 October 2008. In addition, samples from a range of vegetation types were used to compare VWC and NDWI to the satellite imagery.
Relationship between Condensed Water Content and Liquid-Ice Mixing Homogeneity in Mixed-Phase Stratiform Clouds: Dataset
Open the record for dataset details and reuse information.
Average seasonal contents and standard deviations of chemical elements in drinking water samples of Almaty
<p>Water is an important component of all life on Earth, and water pollution with heavy metals can lead to detrimental consequences for public health. The purpose of this study was to determine the health risks caused by trace elements present in the drinking water supply systems of Almaty City. As part of this research, the elemental composition of 78 drinking water samples taken in winter, summer, and autumn of 2023 in different areas of the city was studied.Based on the data obtained, drinking water contamination indices were calculated for heavy metal groups, and the degree of water suitability for drinking purposes was assessed for each sampling point.</p>
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Allen Brain Atlas
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DANDI Archive for NWB datasets
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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.