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3,105 results for “Vegetation =”
SMEX02 Regional Vegetation Sampling Data, Iowa, Version 1
This data set contains the vegetation parameters plant height, row spacing, stand density, and leaf area index (LAI) as part of the Soil Moisture Experiment 2002 (SMEX02).
VIIRS/JPSS1 Vegetation Indices 16-Day L3 Global 500m SIN Grid V002
The NOAA-20 Visible Infrared Imaging Radiometer Suite (VIIRS) Vegetation Indices (VJ113A1) Version 2 data product provides vegetation indices by a process of selecting the best available pixel over a 16-day acquisition period at 500 meter (m) resolution. The VJ113 data products are designed after the Moderate Resolution Imaging Spectroradiometer (MODIS) Terra and Aqua Vegetation Indices product suite to promote the continuity of the Earth Observation System (EOS) mission.The VJ113 algorithm process produces three vegetation indices: Normalized Difference Vegetation Index (NDVI), the Enhanced Vegetation Index (EVI), and Enhanced Vegetation Index-2 (EVI2). NDVI is one of the longest continual remotely sensed time series observations, using both the red and near-infrared (NIR) bands. EVI is a slightly different vegetation index that is more sensitive to canopy cover, while NDVI is more sensitive to chlorophyll. EVI2 is a reformation of the standard 3-band EVI, using the red band and NIR band. This reformation addresses arising issues when comparing VIIRS EVI to other EVI models that do not include a blue band. EVI2 will eventually become the standard EVI. Along with the three Vegetation Indices layers, this product also includes layers for NIR reflectance; three shortwave infrared (SWIR) reflectance; red, blue, and green reflectance; composite day of year; pixel reliability; relative azimuth, view, and sun angles; and a quality layer. Two low resolution browse images are also available for each VJ113A1 product: EVI and NDVI.Known Issues* Due to missing critical inputs, this product lacks coverage for tiles h33v07 and h18v14, which are located over water.* For complete information about known issues please refer to the [MODIS/VIIRS Land Quality Assessment website](https://landweb.modaps.eosdis.nasa.gov/knownissue?sensor=VIIRS) and the User Guide and ATBD.Improvements/Changes from Previous Version* Improved calibration algorithm and coefficients for entire NOAA-20 mission.* Improved geolocation accuracy and applied updates to fix outliers around maneuver periods.* Corrected the aerosol quantity flag (low, average, high) mainly over brighter surfaces in the mid- to high-latitudes such as desert and tropical vegetation areas. This has an impact on the retrieval of other downstream data products such as VNP13 Vegetation Indices and VNP43 Bidirectional Reflectance Distribution Function (BRDF)/Albedo.* Improved cloud mask input product for corrections along coastlines and artifacts from use of coarse resolution climatology data. * Replaced the land/water mask input product with the eight-class land/water mask from the VNP03 geolocation product that better aligns with MODIS.* Modified QA VI Usefulness bits to ignore BRDF flag.* Implemented VI specific land/water mask.* More details can be found in this [VIIRS Land V2 Changes document](https://landweb.modaps.eosdis.nasa.gov/data/userguide/VIIRS_Land_C2_Changes_09152022.pdf).
SHIFT: Vegetation Plot Photos, Santa Barbara, CA, USA, 2022
This dataset contains photographs of the plots where field vegetation sampling was conducted during the 2022 NASA Surface Biology Geology (SBG) High Frequency Time series (SHIFT) campaign. Sampling occurred at the Jack and Laura Dangermond Preserve, Sedgwick Reserve, and Carpinteria Salt Marsh Reserve, which are located in Santa Barbara County, California, USA. Photographs were taken from 2022-02-23 to 2022-09-18. This project collected field data contemporaneously with weekly flights of Airborne Visible-Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) over the study areas. Related SHIFT data packages contain additional biogeochemical, reflectance, and foliar data.
VEMAP 1: U.S. Potential Natural Vegetation
The Vegetation/Ecosystem Modeling and Analysis Project (VEMAP) is an ongoing multiinstitutional, international effort addressing the response of biogeography and biogeochemistry to environmental variability in climate and other drivers in both space and time domains. The objectives of VEMAP are the intercomparison of biogeochemistry models and vegetationtype distribution models (biogeography models) and determination of their sensitivity to changing climate, elevated atmospheric carbon dioxide concentrations, and other sources of altered forcing. The vegetation data set includes one variable: vegetation type. Vegetation types are defined physiognomically in terms of dominant lifeform and leaf characteristics (including leaf seasonal duration, shape, and size) and, in the case of grasslands, physiologically with respect to dominance of species with the C3 versus C4 photosynthetic pathway. The physiognomic classification criteria are based on our understanding of vegetation characteristics that influence biogeochemical dynamics (Running et al. 1994). The U.S. distribution of these types is based on a 0.5 degree latitude/longitude gridded map of Kuchler's (1964, 1975) potential natural vegetation provided by the TEM group (D. Kicklighter and A.D. McGuire, personal communication). Kuchler's map is based on current vegetation and historical information and, for purposes of VEMAP Phase I model experiments, is presumed to represent potential vegetation under current climate and atmospheric CO2 concentrations (355 ppm). A complete users guide to the VEMAP Phase I database which includes more information about this data set can be found at ftp://daac.ornl.gov/data/vemap-1/comp/Phase_1_User_Guide.pdf. ORNL DAAC maintains additional information associated with the VEMAP Project. Data Citation: This data set should be cited as follows: Kittel, T. G. F., N. A. Rosenbloom, T. H. Painter, D. S. Schimel, H. H. Fisher, A. Grimsdell, VEMAP Participants, C. Daly, and E. R. Hunt, Jr. 1998. VEMAP Phase I Database, revised. Available on-line from Oak Ridge National Laboratory Distributed Active Archive Center, Oak Ridge, Tennessee, U.S.A.
ISLSCP II C4 Vegetation Percentage
The photosynthetic composition (C3 or C4) of vegetation on the land surface is essential for accurate simulations of biosphere-atmosphere exchanges of carbon, water, and energy. C3 and C4 plants have different responses to light, temperature, CO2, and nitrogen; they also differ in physiological functions like stomatal conductance and isotope fractionation. A fine-scale distribution of these plant types is essential for earth science modeling.The C4 percentage is determined from datasets that describe the continuous distribution of plant growth forms (i.e., the percent of a grid cell covered by herbaceous or woody vegetation), climate classifications, the fraction of a grid cell covered in croplands, and national crop type harvest area statistics. The staff from the International Satellite Land Surface Climatology Project (ISLSCP) Initiative II have made the original data set consistent with the ISLSCP-2 land/water mask. This data set contains a single file in ArcInfo ASCIIGRID format.This data set is one of the products of the International Satellite Land-Surface Climatology Project, Initiative II (ISLSCP II) data collection which contains 50 global time series data sets for the ten-year period 1986 to 1995. Selected data sets span even longer periods. ISLSCP II is a consistent collection of data sets that were compiled from existing data sources and algorithms, and were designed to satisfy the needs of modelers and investigators of the global carbon, water and energy cycle. The data were acquired from a number of U.S. and international agencies, universities, and institutions. The global data sets were mapped at consistent spatial (1, 0.5 and 0.25 degrees) and temporal (monthly, with meteorological data at finer (e.g., 3-hour)) resolutions and reformatted into a common ASCII format. The data and documentation have undergone two peer reviews.ISLSCP is one of several projects of Global Energy and Water Cycle Experiment (GEWEX) [http://www.gewex.org/] and has the lead role in addressing land-atmosphere interactions -- process modeling, data retrieval algorithms, field experiment design and execution, and the development of global data sets.
HLS Operational Land Imager Vegetation Indices Daily Global 30 m V2.0
The Harmonized Landsat and Sentinel-2 (HLS) project provides consistent data products from the Operational Land Imager (OLI) aboard the joint NASA/USGS Landsat 8 and Landsat 9 satellites and the Multi-Spectral Instrument (MSI) aboard Europe’s Copernicus Sentinel-2A, Sentinel-2B, and Sentinel-2C satellites. The combined measurement enables global observations of the land every 2–3 days at 30 meter (m) spatial resolution. The HLSL30 Vegetation Indices (HLSL30_VI) product is derived from Landsat 8 and Landsat 9 OLI data products. Vegetation indices combine specific bands of satellite data to quantify various aspects of vegetation. Analysis of vegetation indices allows for tracking changes in vegetation over time, identifying areas of stress or deforestation, and assessing crop health. Vegetation indices provide a reliable and efficient means of understanding the complex dynamics of vegetation health. The HLSS30_VI and HLSL30_VI products are gridded to the same resolution and Military Grid Reference System ([MGRS](https://hls.gsfc.nasa.gov/products-description/tiling-system/)) tiling system and thus are “stackable” for time series analysis.The HLSL30_VI product is provided in Cloud Optimized GeoTIFF (COG) format, and each variable is distributed as a separate file. Nine indicators of vegetation health are included in the HLSL30_VI product: Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Soil Adjusted Vegetation Index (SAVI), Modified Soil Adjusted Vegetation Index (MSAVI), Normalized Difference Moisture Index (NDMI), Normalized Difference Water Index (NDWI), Normalized Burn Ratio (NBR), Normalized Burn Ratio 2 (NBR2), and Triangular Vegetation Index (TVI). See the User Guide for a more detailed description of the individual vegetation health variables provided in the HLSL30_VI product.
Vegetation Species Data (FIFE)
The Vegetation Species and Cover Abundance Data Set documents the species present at the FIFE staff data measurement sites. Percent cover is estimated for each species at approximately the time of the IFC's. Disturbances occur over a variety of spatial and temporal scales in North American grasslands, and interactions of these different disturbances affect community structure. Two types of disturbance commonly occur over large spatial scales in grasslands, namely, fire and grazing. Analysis of percent cover of dominant species indicated that composition and heterogeneity was significantly affected by grazing intensity and burning. The effects of disturbances on community structure are not additive, and may not be extrapolated from studies of single factors. The interpretation of patterns in natural communities is clearly scale dependent, and processes may act differently when viewed from different spatial or temporal scales. The effects of scale may not always be predictable; therefore, an understanding of pattern and process at one hierarchical level may not provide useful information about pattern and process at a different hierarchical level.
Pre-LBA CABARE Mapped Land Surface and Vegetation Characteristics, Rondonia, Brazil
Surface parameter digital maps of vegetation, soil, and topography were obtained for Rondonia, Brazil, covering the 5x5 degree region bounded by 13-8 degrees S and 65-60 degrees W. Numerical maps of the natural landscape structure were prepared by digitizing existing 1:1,000,000 maps. Satellite data give information about the most recent modifications of the surface due to human activities. This mapping work was the first step of a mesoscale meteorological modeling program (Calvet et al., 1997) in forested and deforested Southwestern Amazonia (Rondonia, Brazil). This work was performed in the framework of a research program (CABARE) supported by the European Union, CEC Environment Program.Data are provided in ArcGIS ArcInfo grid ascii format for the following surface parameters:Elevation of terrain of the Rondonia region (altitude.txt)LANDSAT-derived vegetation classification of the Rondonia region in 1993-1994 (classify.txt)Soil classification of the Rondonia region (soil.txt)Sand and Clay of the Rondonia region (sand.txt and clay.txt)Vegetation classification of the Rondonia region from RADAMBRASIL (Macedo et al., 1979) (vegetation.txt)
Maps of Vegetation Types and Physiographic Features, Toolik Lake Area, Alaska
This data set provides the spatial distributions of vegetation types, soil carbon, and physiographic features in the Toolik Lake area, Alaska. Specific attributes include vegetation, percent water, glacial geology, soil carbon, a digital elevation model (DEM), surficial geology and surficial geomorphology.
Untimely expression of gametogenic genes in vegetative cells causes uniparental disomy
GEO Series GSE77050. Schizosaccharomyces pombe. 23 samples. Type: Genome binding/occupancy profiling by genome tiling array; Expression profiling by high throughput sequencing.
Vegetable omega-3 and omega-6 fatty acids differentially modulate the antiviral and antibacterial immune responses of Atlantic salmon
GEO Series GSE249779. Salmo salar. 116 samples. Type: Expression profiling by RT-PCR.
Genome-wide maps of H3K9me3, H3K27me3 and H3K4me2 in two species of Leptosphaeria maculans during vegetative growth
GEO Series GSE150125. Plenodomus lingam/Leptosphaeria maculans 'brassicae' group; Plenodomus lingam/Leptosphaeria maculans 'lepidii' group. 18 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Effects Of An Encapsulated Fruit And Vegetable Juice Concentrate On Obesity-Induced Systemic Inflammation
GEO Series GSE87454. Homo sapiens. 32 samples. Type: Expression profiling by array.
Deep RNAseq indicates protective mechanisms of cold-tolerant indica rice plants during early vegetative stage
GEO Series GSE103480. Oryza sativa Indica Group. 2 samples. Type: Expression profiling by high throughput sequencing.
Temporal comparison of leaf transcriptomes between early-flowering Arabidopsis thaliana atx1/atx3/atx4 triple mutants and vegetative WT Col-0 plants of the same age.
GEO Series GSE134177. Arabidopsis thaliana. 36 samples. Type: Expression profiling by high throughput sequencing.
Transcriptome study of age-related resistance associated with vegetative phase change in Arabidopsis
GEO Series GSE208657. Arabidopsis thaliana. 18 samples. Type: Expression profiling by high throughput sequencing.
Temporal and spatial frameworks supporting plant responses to vegetation proximity
GEO Series GSE268032. Arabidopsis thaliana. 36 samples. Type: Expression profiling by high throughput sequencing.
Comparative transcriptomic analyses of vegetable and grain pea (Pisum sativum L.) seed development
GEO Series GSE72573. Lathyrus oleraceus. 4 samples. Type: Expression profiling by high throughput sequencing.
Differential gene expression of Appresorium vs Vegetative mycelium of Magnaporthe using oligoarray
GEO Series GSE5518. Pyricularia grisea. 2 samples. Type: Expression profiling by array; Expression profiling by SAGE.
DNA demethylation by ROS1a in rice vegetative cells promotes methylation in sperm
GEO Series GSE126791. Oryza sativa. 4 samples. Type: Methylation profiling by high throughput sequencing.
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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.