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95 results for “vegetation type”
LBA-ECO LC-22 Vegetation Cover Types from MODIS, 500-m, South America: 2000-2001
This data set contains proportional estimates for the vegetative cover types of tree cover, herbaceous vegetation, and bare ground over South America for the period 2000-2001. These products were derived from all seven bands of the Moderate-resolution Imaging Spectroradiometer (MODIS) sensor onboard NASA's Terra satellite. A set of 500-m MOD09A1 Surface Reflectance 8-day minimum blue reflectance composites were used as input data. To reduce the presence of cloud shadows, The data were converted to 40-day composites using a second darkest albedo (sum of blue, green, and red bands), and the Vegetation Continuous Fields (VCF) algorithmn was utilized (Hansen et al., 2002). The VCF shows how much of a land cover such as forest or grassland exists anywhere on the land surface. The VCF product may depict areas of heterogeneous land cover better than traditional discrete classification schemes which shows where land cover types are concentrated. There are three images provided in GeoTIFF format.
LBA-ECO LC-15 Vegetation Cover Types from MODIS, 1-km, Amazon Basin: 2000-2001
This data set contains proportional estimates for the vegetative cover types of woody vegetation, herbaceous vegetation, and bare ground over the Amazon Basin for the period 2000-2001. These products were derived from all seven bands of the Moderate-resolution Imaging Spectroradiometer (MODIS) sensor onboard NASA's Terra satellite. A set of MODIS 32-day composites were used to create the vegetation cover types using the Vegetation Continuous Fields (VCF) (Hansen et al., 2002) approach which shows how much of a land cover such as "forest" or "grassland" exists anywhere on the land surface. The VCF product may depict areas of heterogeneous land cover better than traditional discrete classification schemes which shows where land cover types are concentrated.The original MODIS products are 500-m spatial resolution and are derived from 2000-2001 data products. The data were resampled to 1-km resolution for the regional study under this project, and provided as 3 separate cover type files in ENVI and GeoTIFF file formats that are provided in six zipped files. These products are registered to the rest of the regional data sets over the Amazon basin. These data are also available for download from the Global Land Cover Facility Website (http://modis.umiacs.umd.edu/).
Maps of Vegetation Types and Physiographic Features, Kuparuk River Basin, Alaska
This data set provides a collection of vegetation, landscape, geobotanical, elevation, hydrology, and geologic maps for the Kuparuk River Basin, North Slope, Alaska. The maps cover either (1) the entire Kuparuk River Basin, from the headwaters on the north side of the Brooks Range to the Beaufort Sea coast, or (2) the selected Upper Kuparuk River Region including the Toolik Lake and Imnavait Creek research areas. The maps were produced from imagery and existing geobotanical maps covering the period 1976-08-04 to 2008-12-31.
Maps of Vegetation Types and Physiographic Features, Imnavait Creek, Alaska
This dataset provides the spatial distribution of vegetation types, soil carbon, and physiographic features in the Imnavait Creek area, Alaska. Specific attributes include vegetation, percent water, glacial geology, soil carbon, a digital elevation model (DEM), surficial geology and surficial geomorphology. Data are also provided on the research grids for georeferencing. The map data are from a variety of sources and encompass the period 1970-06-01 to 2015-08-31.
Delta-X AVIRIS-NG L3 Derived Vegetation Types, MRD, Louisiana, USA
This dataset provides maps of vegetation types for the Atchafalaya and Terrebonne basins in coastal Louisiana, U.S., derived from NASA's Next Generation Airborne Visible Infrared Imaging Spectrometer (AVIRIS-NG) imagery acquired during spring and fall of 2021 for the Delta-X campaign. Vegetation types were classified from Level-2B BRDF-adjusted surface reflectance. Local pixel reflectance spectra coincident with herbaceous vegetation field samples and vegetation plot data from Louisiana's Coastwide Reference Monitoring System were used to generate a machine learning-based model to classify vegetation types. This model was then applied to the AVIRIS-NG mosaic imagery to map vegetation types across the Atchafalaya and Terrebonne Basins. The data are provided in cloud optimized GeoTIFF (COG) format.
Global Vegetation Types, 1971-1982 (Matthews)
The global vegetation type data of 1 x 1 degree latitude and longitude resolution were designed for use in studies of climate and climate change. Vegetation data were compiled in digital form from approximately 100 published sources. The raw data base distinguished about 180 vegetation types that have been collapsed to 32. The vegetation data were encoded using the UNESCO classification system. Additional information about this data set can be found at http://www.giss.nasa.gov/data/landuse/vegeem.html. ORNL DAAC maintains information on related data sets in the Vegetation Collection. Data Citation The data set should be cited as follows: Matthews, E. 1999. Global Vegetation Types, 1971-1982. Available on-line from Oak Ridge National Laboratory Distributed Active Archive Center, Oak Ridge, Tennessee, U.S.A.
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.
Data from: Vegetation type controls root turnover in global grasslands
Abstract: Aim: Root turnover is an important process determining carbon and nutrient cycling in terrestrial ecosystems. It is an established fact that root turnover is jointly regulated by climatic, edaphic, and biotic factors. However, the relative importance of these forces in determining the global patterns of root turnover time is far from clear. Location: Global. Time period: 1946–2017. Major taxa studied: Grasslands. Methods: We compiled a database of 141 sites with 433 observations on root turnover time and applied structural equation modelling (SEM) to investigate the relative contribution of climate, soil properties, and vegetation type to the observed variations in root turnover time. Results: Root turnover time was 3.1 years on average across the global grasslands and differed significantly among grassland types (tropical grassland & savanna, temperate grassland & meadow, alpine grassland & meadow, tundra, and desert). It decreased with mean annual temperature, mean annual precipitation, and Palmer Drought Severity Index but increased with soil organic carbon content, total nitrogen content, and carbon: nitrogen ratio. Soil bulk density and soil texture also significantly affected root turnover time, with clay content negatively correlating to root turnover time and explaining more variations than bulk density and sand content. The SEM showed that climatic factors had dominant effects on root turnover time when vegetation type was not considered. Vegetation type became the primary driver when it was included in the SEM. Main conclusions: Our results highlight that the influences of climatic and edaphic factors on root turnover time are predominantly manifested through vegetation type. The critical role of precipitation as revealed for the first time in this study challenges our current understanding of climate impacts on root turnover time. The findings necessitate accurate representation of vegetation type in Earth system models to predict root function dynamics under global change.
More Fresh Fruit and Vegetable Prescription Program for Families With Type 2 Diabetes Mellitus
ClinicalTrials.gov study NCT05138432. IPD Sharing: NO. Countries: 1. Publications: 0.
The Effects of Types of Fruits and Vegetables on Vascular Function
ClinicalTrials.gov study NCT03410342. IPD Sharing: YES. Countries: 1. Publications: 0.
Data from: Responses of biomass allocation across two vegetation types to climate fluctuations in the northern Qinghai-Tibet Plateau
Open the record for dataset details and reuse information.
Data from: Vegetation type controls root turnover in global grasslands
Open the record for dataset details and reuse information.
Transcriptome and QTL mapping analyses identifying major QTL genes controlling glucosinolates contents between vegetable-type and oilseed-type Brassica rapa plants
GEO Series GSE213605. Brassica rapa. 12 samples. Type: Expression profiling by high throughput sequencing.
Particial Dataset to the article: Bedrock meadows: a distinct vegetation type in northwestern North America
<p>This dataset is part of the data used in the article "Bedrock meadows: a distinct vegetation type in northwestern North America" published in the Journal "Applied Vegetation Science". It includes several datasets that are already merged:</p> <ol> <li>Fairbarns, 2001-2009, Unpublished data provided by Matt Fairbarns</li> <li>Roemer, 1996/97, Unpublished data provided by Hans Roemer</li> <li>Wagner, V., Spribille, T., Abrahamczyk, S. & Bergmeier, E. (2014) Timberline meadows along a 1000-km transect in NW North America: Species diversity and community patterns. <em>Applied Vegetation Science</em>, 17: 129–141. https://doi.org/10.1111/avsc.12045</li> <li>Zapisocki, Z. (2021) <em>Patterns of </em><em>non-native plants among native grasslands in Alberta, Canada.</em> Master thesis, University of Alberta, Edmonton, Alberta, Canada.</li> <li>Zapisocki, Z., Murillo, R.A. & Wagner, V. (2022) <em>Non-native plant invasions in prairie grasslands of </em><em>Alberta, Canada</em>. <em>Rangeland Ecology & Management</em>, 83: 20–30. https://doi.org/10.1016/j.rama.2022.02.011</li> </ol> <p>Further data used in the article can be retrieved from the original sources (Damm, 2001; Waterton-Glacier National Park, 1994-2002; Hop et al., 2007). </p>
Carbon and nitrogen stocks and distributions associated with different vegetation covers and soil profile types in Abisko, northern Sweden.
<p>Dataset used to compute carbon and nitrogen stocks in the vegetation and the soil of various arctic habitats near Abisko Research Station, northern Sweden. The dataset contains vegetation inventories and soil measurements on 45 quadrats, a birch tree inventory and C and N contents of soils and dominant species.</p>
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