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691 results for “Vegetation Data”

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edi64/100

Spartina alterniflora marsh vegetation data along the Georgia coast used in the Belowground Ecosystem Resiliency Model version 2.0

Study plots (1-m2) were established in eight Spartina alterniflora-dominated marshes (7 on Sapelo Island, Georgia, and 1 on Skidaway Island, Georgia). At three sites, plots were sampled once each during May, July, August, September, and October of 2016. At all sites, plots were sampled once each during June, August, and November of 2021, February, May, August, and November of 2022, and February of 2023. One long-term (quarterly 2013 to 2023) GCE LTER sampling site is also included. Nine replicate plots were placed in vegetated marsh along transects that spanned 3 Landsat-8 and -9 pixel footprints, with 3 plots per pixel footprint. In each plot, measurements included plant biomass, plant species, stem density, and height. Aboveground biomass was calculated using allometric relationships between plant height and mass from plant clipping studies. During these surveys, destructive core sampling was also performed in the proximity of the plots (n = 1 per plot) to measure above and below ground biomass. Chlorophyll, foliar N, and Leaf Area Index measurements were taken in the proximity of the plots. This dataset reflects an update to the "PLT-GCED-2106" dataset (doi: 10.6073/pasta/03f4f78c6498aecca34faf4339591129). This project also utilized data from the "PLT-GCEM-1610" dataset doi: 10.6073/pasta/9746c71b35e9f8c544ea12c601c33949). Those data utilized in this project are duplicated here for completeness.

openCC (other)Jan 2026View details →
edi60/100

Cooperative Alaska Forest Inventory (CAFI): III - Vegetation Data 1994-2024

The CAFI is a repeated forest measurement project established in forest stands throughout interior and southcentral Alaska. The CAFI was launched in 1994 and measurements were done at a 5-year interval until 2015. The project was on hiatus between 2016 and 2019 but picked back up again in 2020 and will continue at a 10-year interval. Total of 205 permanent plots have been established and each plot has been measured up to 6 times. The CAFI is the most extensive forest monitoring program, both in spatial and temporal scale, in interior and southcentral Alaska today. This is the vegetation data of the CAFI. The protocol has been changed in 2021. The CAFI is a repeated forest measurement project established in forest stands throughout interior and southcentral Alaska. The CAFI was launched in 1994 and measurements were done at a 5-year interval until 2015. The project was on hiatus between 2016 and 2019 but picked back up again in 2020 and will continue at a 10-year interval. Total of 205 permanent plots have been established and each plot has been measured up to 6 times. The CAFI is the most extensive forest monitoring program, both in spatial and temporal scale, in interior and southcentral Alaska today.

openOpenApr 2025View details →
edi60/100

Spectral Vegetation Indices from Harmonized Landsat and Sentinel-2 Data for Harvard Forest 2015-2020

The goal of this work is to exploit time series of remotely sensed data sets with ground observations to improve our understanding of how seasonal variation in canopy and environmental conditions affect the relationship between vegetation indices and leaf area index (LAI) and fraction of absorbed photosynthetically active radiation (fAPAR). Using three different common vegetation indices (EVI2, NDVI, NIRV), we can estimate LAI, fAPAR, and daily absorbed photosynthetically active radiation (APAR) using a semi-empirical model.

openCC0Dec 2023View details →
edi56/100

Normalized Difference Vegetation Index (NDVI) derived from 2019 National Agriculture Imagery Program (NAIP) data for the central Arizona region

This project calculates two vegetation indices—Normalized Difference Vegetation Index (NDVI) and Soil Adjusted Vegetation Index (SAVI) from the National Agriculture Imagery Program (NAIP) remotely sensed imagery. The intent is to make remotely sensed variables and visualizations accessible to stakeholders and researchers studying the Phoenix metropolitan area. NDVI and SAVI are calculated from the 2019 NAIP imagery (1m resolution). This dataset extends the 2010, 2013, 2015, and 2017 NDVI and SAVI products derived from NAIP imagery (also 1m resolution). All images are cropped to the CAP study area boundary.

openCC0May 2023View details →
edi56/100

Soil-Adjusted Vegetation Index (SAVI) derived from 2019 National Agriculture Imagery Program (NAIP) data for the central Arizona region

This project calculates two vegetation indices—Normalized Difference Vegetation Index (NDVI) and Soil Adjusted Vegetation Index (SAVI) from the National Agriculture Imagery Program (NAIP) remotely sensed imagery. The intent is to make remotely sensed variables and visualizations accessible to stakeholders and researchers studying the Phoenix metropolitan area. NDVI and SAVI are calculated from the 2019 NAIP imagery (1m resolution). This dataset extends the 2010, 2013, 2015, and 2017 NDVI and SAVI products derived from NAIP imagery (also 1m resolution). All images are cropped to the CAP study area boundary.

openCC0May 2023View details →
edi52/100

Pre- and post-fire vegetation and fuel loading data from mixed conifer plots in Arizona and New Mexico: 2010-2023

A permanent plot network was installed in mixed conifer stands across the U.S. Southwest (Arizona and New Mexico) between 2010-2013, primarily to monitor the spread and severity of white pine blister rust (WPBR), a disease caused by the fungal pathogen Cronartium ribicola on southwestern white pine (Pinus strobiformis). Study sites were mid-to-high elevation mixed conifer stands composed of southwestern white pine, Douglas-fir (Pseudotsuga menziesii), white fir (Abies concolor), ponderosa pine (Pinus ponderosa), quaking aspen (Populus tremuloides), Gambel oak (Quercus gambelii), blue spruce (Picea pungens), Engelmann spruce (Picea engelmannii), corkbark fir (Abies latifolia var. arizonica), Rocky Mountain bristlecone pine (Pinus aristata), and New Mexico locust (Robinia neomexicana). After plot installation, 6 fires occurred in the study area, burning an estimated total of 489,390 acres and 30 plots. We remeasured plots at 1-, 5- and 10-year intervals post-fire, quantifying burn severity via a composite burn index (CBI) at the first year post-fire. We also assessed regeneration, overstory mortality, and fuel loading. Overstory variables collected included tree species, status, diameter at breast height (DBH), and mortality, as well as height, height to live crown base, strata, and crown class on a subset of trees. Understory trees were tallied by species. Fuel load was measured via transect and calculated in megagrams per hectare categorically based on fuel type. Other variables such as basal area and trees per hectare were derived and calculated. This dataset was utilized in the manuscript "Climate, fire, and the future of mixed conifer ecosystems in the U.S. Southwest" (currently in review), and R code used for analyses is included in the dataset.

openCC0May 2025View details →
edi52/100

Marsh vegetation data in Spartina alterniflora and Distichlis spicata marshes along the Texas coast, 2022 - 2024

We measured plant biomass and plant physiological metrics in two salt marshes in Bayside, Texas, and Port Aransas, Texas, from 2022 - 2024. Study plots (1-m2) were established in two Spartina alterniflora and Distichlis spicata-dominated salt marshes in the Texas Coastal Bend. At one site, S. alterniflora and D. spicata occurred in monoculture cover, and we established six study plots per species cover. Transects of plots encompassed two Landsat-8 and -9 pixel footprints, with a plot density of 3 plots per satellite pixel footprint. At the second site, both species occurred in intermixed stands. At this site we established seven study plots, and plots were not intentionally co-located with satellite pixel footprints. All plots were sampled once each during August and November of 2022, February, May, August, and November of 2023, and February and May of 2024. In each plot, measurements included plant biomass, plant species, stem density, and stem height. Aboveground biomass was calculated using allometric relationships between plant height and mass from plant clipping studies. During these surveys, destructive core sampling was also performed in the proximity of the plots (n = 1 per plot per species) to measure above- and belowground biomass. We measured plant physiological metrics as foliar chlorophyll, foliar N, and Leaf Area Index. Foliar chlorophyll and foliar N were assessed per species present, and Leaf Area Index was measured once per plot. These measurements were taken in the proximity of the plots. We also measured elevation once at each plot at the start of the study period. At each site, we measured water level with HOBO U20L pressure transducers. We installed a stilling well and placed one transducer above the marsh surface to measure ambient pressure, and one transducer at depth. We used the HOBOware software to calculate water level. Measurements were collected at 15 minute intervals. In instances of ambient pressure equipment failure, ambient pressure

openCC (other)May 2025View details →
edi52/100

Landscape Ecosystem Classification Soils and Vegetation Plots Data at the University of Michigan Biological Station, Pellston, Michigan from 1987 to 2015 remeasurements

Landscape ecosystems are a means of understanding the spatial patterns of and the functional interrelationships in forest ecosystems. Landscape ecosystem research is a multifactor, holistic approach to identifying, classifying, describing, and mapping terrain ecosystems. Abiotic and biotic factors are integrated in the field to distinguish repeating units similar in ecological structure and function. Landscape ecosystems are identified by simultaneous integration of physiographic, soil, and vegetation information. The more stable components--physiography and soil--largely determine local climate, and water and nutrient relations, and thus the interrelationships of physiography and soil form the foundation of a landscape ecosystem classification. Vegetation is seen as a phytometer that integrates the many abiotic factors and their interactions, and therefore reflects differences in ecosystem structure and function. When the three main ecosystem factors are analyzed simultaneously, one can perceive interrelationships that result in ecologically meaningful differences among segments of the ecosphere. Landscape ecosystems are spatial; they are volumetric, multi-dimensional segments of earth, whose components include soil, water, atmosphere, solar radiation, and biota. These segments can be identified, classified, described, and mapped at various scales. From the years of 1988 to 2001, various graduate students of Burton V. Barnes completed their masters thesis and dissertations in this pursuit. The attached data set is a culmination of these individual work. Each plot has measurements at various scales within the 10 by 30 meet plot. A stratified random design was used to locate plot locations. The random design was stratified by major and minor landforms in the region. All trees within the plot where identified and dbh was measured. All individual shrubs where identified and abundance was counted within the entire plot. Soils pits locations for each plot where selected

openCC (other)Apr 2025View details →
edi52/100

Vegetation Data Collected with Point Frame for 83 Locations of 6-163 Years Old Black Spruce, Alaska Paper Birch, and Aspen Stands Across Interior Alaska. Sampled in 2008-2010 and 2013-2015.

This dataset contains point frame data for vegetation less than 1.3 m, including vascular plants, bryophytes, lichens, leaf litter and bare ground, as well as species codes used, as described in Jean et al. 2017 Canadian Journal of Forest Research. Samples of all encountered unknown species were collected for identification in the lab. Bryophyte nomenclature followed Anderson et al. (1990).

openOpenNov 2022View details →
edi52/100

Normalized Difference Vegetation Index (NDVI) derived from 2021 National Agriculture Imagery Program (NAIP) data for the central Arizona region

This project calculates two vegetation indices —Normalized Difference Vegetation Index (NDVI) and Soil Adjusted Vegetation Index (SAVI)— from the National Agriculture Imagery Program (NAIP) remotely sensed imagery. The intent is to make remotely sensed variables and visualizations accessible to stakeholders and researchers studying the Phoenix metropolitan area. NDVI and SAVI are calculated from the 2021 NAIP imagery (1m resolution). This dataset extends the 2010, 2013, 2015, 2017, and 2019 NDVI and SAVI products derived from NAIP imagery (also 1m resolution). All images are cropped to the CAP LTER study area boundary of central Arizona, USA. The materials presented here include NDVI data with SAVI data presented in a companion dataset that is also available through the EDI.

openCC0Jan 2023View details →
edi52/100

Soil-Adjusted Vegetation Index (SAVI) derived from 2021 National Agriculture Imagery Program (NAIP) data for the central Arizona region

This project calculates two vegetation indices —Normalized Difference Vegetation Index (NDVI) and Soil Adjusted Vegetation Index (SAVI)— from the National Agriculture Imagery Program (NAIP) remotely sensed imagery. The intent is to make remotely sensed variables and visualizations accessible to stakeholders and researchers studying the Phoenix metropolitan area. NDVI and SAVI are calculated from the 2021 NAIP imagery (1m resolution). This dataset extends the 2010, 2013, 2015, 2017, and 2019 NDVI and SAVI products derived from NAIP imagery (also 1m resolution). All images are cropped to the CAP LTER study area boundary of central Arizona, USA. The materials presented here include SAVI data with NDVI data presented in a companion dataset that is also available through the EDI.

openCC0Jan 2023View details →
edi52/100

Consumer Stocks: Fish, Vegetation, and other Non-physical Data from Everglades National Park (FCE LTER), South Florida, USA from February 2000 to April 2005

We hypothesize that standing crops of consumers reflect patterns of allochthonous nutrient transport along the estuarine interface at the Florida Coastal Everglades (FCE) LTER. Our goal is to investigate how variation in hydrology, water quality, and disturbance influence secondary production. This data set represents the numeric count data of fish, plants, and other fauna.

openCC (other)May 2022View details →
edi52/100

Vegetation data collected from Northeast Shark River Slough, Everglades National Park, Florida, USA, September 2006 - April 2025

This project was established in 2006 to document the pattern of abundance of key ecological indicators (e.g., surface water, soil, floc, periphyton and sawgrass) across the NESRS landscape. A total of 30 sites were established and monitored in 2006, 2007 and 2008. After the completion of 1-mile bridge in 2012, additional 10 new sites were established to observe the ecological impact of 1-mile bridge (known as Bridge & Census sites). In 2015, additional 40 sites were established along eight transects (T1-T8, known as near canal sites) in ENP marshes starting at, and roughly perpendicular to the L-29 canal. The purpose of these sites was to monitor the potential effects of Modified Water Deliveries (MWD) operations on changing nutrient concentrations and ratios in key ecological compartments due to increased downstream discharges from the L-29 canal beneath the 1-mile and 2.6-mile bridges and culverts along Tamiami Trail. Data collection is complete.

openCC (other)Dec 2025View details →
edi52/100

Monthly Spartina alterniflora marsh vegetation data for additional sites along the Georgia coast used in the Belowground Ecosystem Resiliency Model

Study plots (1-m2) were established in three Spartina alterniflora-dominated marshes - 2 on Sapelo Island, Georgia, and 1 on Skidaway Island, Georgia, and sampled once each during May, July, August, September, and October of 2016. Nine replicate plots were placed in vegetated marsh along transects that spanned 3 Landsat-8 pixel footprints, with 3 plots per pixel foot print. In each plot, measurements included plant biomass, plant species, stem density, and height. Aboveground biomass was calculated using allometric relationships between plant height, flowering status and mass from plant clipping studies. During these surveys, destructive core sampling was also performed in the proximity of the plots (n = 1 per plot) to measure above and below ground biomass. Chlorophyll, foliar N, and Leaf Area Index measurements were taken in the proximity of the plots.

openCC (other)Jul 2021View details →
edi52/100

Quadrat vegetation cover data on 1m x 1m plots from the long-term Small Mammal Exclusion Study (SMES) at Jornada Basin LTER, 1995-2020

This data package contains vegetation cover from plots with various levels of herbivore exclusion on the Jornada Experimental Range (JER) and Chihuahuan Desert Rangeland Research Center (CDRRC) in Dona Ana County, southern New Mexico, USA. Study sites were established in 1995; one in black grama grassland and the other in creosotebush shrubland to compare the impact of herbivores on ecosystem processes between these vegetation types. Parallel studies were established at the Sevilleta LTER site (New Mexico, USA) and Mapimi Biosphere Reserve (Durango, Mexico). Each study site is 1 km by 0.5 km in area. Four replicate experimental blocks were randomly located at the grassland study site to measure vegetation responses using exclusion treatments including a) all mammalian herbivores, including cattle, lagomorphs, and rodents, b) lagomorphs and cattle only, c) cattle only, and d) control accessible to all herbivores. Because grazing cattle are excluded from the entire creosote site, only three replicate experimental blocks were randomly located there including a) all mammalian herbivores, including lagomorphs, and rodents, b) lagomorphs only, and c) control accessible to all herbivores. Thirty-six sampling points were positioned at 5.8-meter intervals on a systematically located 6 by 6 point grid within each plot. A permanent one-meter by one-meter vegetation measurement quadrat is located at each of the 36 points. At each quadrat, percent cover by individual plant species is measured. Other measurements include height (cm) of each species in the quadrat, and plant condition (living or dead). Data were collected in the spring and fall of every year from 1995 to 2005. After 2005, sampling frequency changed to every 5 years in the fall. This study is ongoing.

openCC (other)Apr 2022View details →
edi52/100

Herbaceous vegetation size and cover data in grasshopper survey quadrats at the Jornada Basin LTER site, 1984 to 1985

This dataset contains annual herbaceous plant data collected in association with grasshopper surveys during 1984 and 1985 as part of the Jornada Basin LTER program. Annual herbaceous plant data was collected from Jornada grasshopper plots on the east bajada of the Dona Ana Mts. Three plots were situated on the bajada parallel to and 200 m south of the LTER-I transect. Two additional sets of three plots were located 5 km and 10 km south of the LTER transect. Each plot is composed of two 50 m belt transects, each divided into ten 5-meter-squared quadrats. Annual plants were measured in the northeast 1 square meter of each quadrat. All individuals of each species were counted and measured. A mean diameter, height, and the total number of individuals per 1-square-meter quadrat were recorded. Measurements were taken in May, July, and September of 1984, and in May and September of 1985. This dataset consists of the date of collection, plot number, transect number, quadrat number, plant species code, mean plant diameter, and mean plant height. This dataset is complete.

openCC (other)Dec 2021View details →
edi52/100

PIE LTER salt marsh vegetation cover data from regularly monitored quadrats along transects in Rowley, MA.

Marsh vegetation cover data from quadrats along transects in salt marsh sites in Rowley, MA. The transects are intended to study long term changes in marsh vegetation. Four sites ((12 transects) were originally set up to study the impact of salt marsh haying. Two of these sites (labeled McH and EPH) were regularly hayed until 2002. The other two (PUH and CC) were reference sites. Two additional sites labeled RM and RR (8 transects) were originally set up to track invasion by Phragmites australis.

openCC (other)Jan 2023View details →
edi52/100

Small Mammal Exclosure Study (SMES) Vegetation Data from the Chihuahuan Desert Grassland and Shrubland at the Sevilleta National Wildlife Refuge, New Mexico (1995-2009)

This is data for vegetation canopy cover measured from each of the SMES study plots. Vegetation canopy cover was measured from each of the 36 one-meter2 quadrats twice each year. Animal consumers have important roles in ecosystems, determining plant species composition and structure, regulating rates of plant production and nutrient, and altering soil structure and chemistry. The purpose of this study is to determine whether or not the activities of small mammals regulate plant community structure, plant species diversity, and spatial vegetation patterns in Chihuahuan Desert shrublands and grasslands. The purpose of this study is to determine whether or not the activities of small mammals regulate plant community structure, plant species diversity, and spatial vegetation patterns in Chihuahuan Desert shrublands and grasslands. What role if any do indigenous small mammal consumers have in maintaining desertified landscapes in the Chihuahuan Desert? Additionally, how do the effects of small mammals interact with changing climate to affect vegetation patterns over time? This study will provide long-term experimental tests of the roles of consumers on ecosystem pattern and process across a latitudinal climate gradient. The following questions or hypotheses will be addressed. 1) Do small mammals influence patterns of plant species composition and diversity, vegetation structure, and spatial patterns of vegetation canopy cover and biomass in Chihuahuan Desert shrublands and grasslands? Are small mammals keystone species that determine plant species composition and physiognomy of Chihuahuan Desert communities? Do small mammals have a significant role in maintaining the existence of shrub islands and spatial heterogeneity of creosotebush shrub communities? 2) Do small mammals affect the taxonomic composition and spatial pattern of vegetation similarly or differently in grassland communities as compared to shrub communities? How do patterns compare between grassland and shru

openCC0Jul 2021View details →
zenodo48/100

Data from Phenocam (PHE) measurements of above-canopy vegetation (hartheim1) at Hartheim Forest Research Site (DE-Har) from 2023-01-01 to 2023-12-31 [RAW]

<p>Phenocam images from "hartheim1" at DE-Har separated into near-infrared (NIR) and visible (VIS) for the year 2023.&nbsp;</p> <p>Phenocam "hartheim1" shows the view from the main tower at 29.6m height towards N at the <a href="https://www.meteo.uni-freiburg.de/en/infrastructure/hartheim-forest-research-site?set_language=en">ICOS Associate Ecosystem Site DE-Har, Germany</a> recording the phenology and state of the top of the canopy consisting of pinus sylverstris and pinus nigra.</p>

opencc-by-4.0Apr 2024View details →
zenodo48/100

Data from Phenocam (PHE) measurements of above-canopy vegetation (hartheim1) at Hartheim Forest Research Site (DE-Har) from 2022-01-01 to 2022-12-31 [RAW]

<p>Phenocam images from "hartheim1" at DE-Har separated into near-infrared (NIR) and visible (VIS) for the year 2022.&nbsp;</p> <p>Phenocam "hartheim1" shows the view from the main tower at 29.6m height towards N at the <a href="https://www.meteo.uni-freiburg.de/en/infrastructure/hartheim-forest-research-site?set_language=en">ICOS Associate Ecosyste Site DE-Har, Germany</a> recording the phenology and state of the top of the canopy consisting of pinus sylverstris and pinus nigra.</p>

opencc-by-4.0Apr 2024View details →

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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.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

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.

abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

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.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

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.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

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.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record