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Data from Phenocam (PHE) measurements of in-canopy vegetation (hartheim2) at Hartheim Forest Research Site (DE-Har) from 2018-11-05 to 2018-12-31 [RAW]

<p>Phenocam images from "hartheim2" at DE-Har separated into near-infrared (NIR) and visible (VIS) for the year 2022. The phenocam "hartheim2" was put into operation on November 5, 2018. There are no phenocam images before that date at this site.</p> <p>Phenocam "hartheim2" shows the view from the main tower at 8.4 m 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 in-canopy vegetation.</p>

Data from Phenocam (PHE) measurements of in-canopy vegetation (hartheim2) at Hartheim Forest Research Site (DE-Har) from 2020-01-01 to 2020-12-31 [RAW]

<p>Phenocam images from "hartheim2" at DE-Har separated into near-infrared (NIR) and visible (VIS) for the year 2020. </p> <p>Phenocam "hartheim2" shows the view from the main tower at 8.4 m 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 in-canopy vegetation.</p>

Data from Phenocam (PHE) measurements of in-canopy vegetation (hartheim2) at Hartheim Forest Research Site (DE-Har) from 2021-01-01 to 2021-12-31 [RAW]

<div> <p>Phenocam images from "hartheim2" at DE-Har separated into near-infrared (NIR) and visible (VIS) for the year 2021. </p> <p>Phenocam "hartheim2" shows the view from the main tower at 7m 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 in-canopy vegetation.</p> </div>

Data from Phenocam (PHE) measurements of in-canopy vegetation (hartheim2) at Hartheim Forest Research Site (DE-Har) from 2022-01-01 to 2022-12-31 [RAW]

<div> <p>Phenocam images from "hartheim2" at DE-Har separated into near-infrared (NIR) and visible (VIS) for the year 2022. </p> <p>Phenocam "hartheim2" shows the view from the main tower at at 8.4 m 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 in-canopy vegetation.</p> <p> </p> </div>

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SEV LTER: Tracking Vegetation Phenology Using PhenoCam Imagery at the Sevilleta National Wildlife Refuge, New Mexico, 2014-2024

As of 03/03/2024, the Sevilleta Long-Term Ecological Research Program is equipped with a total of 65 digital RGB cameras, or PhenoCams, across the Sevilleta National Wildlife Refuge. These cameras are installed on eddy covariance flux towers and at a number of precipitation manipulation experiments to track vegetation phenology and productivity across dryland ecotones. PhenoCams have been paired with eddy covariance flux tower data at the site since 2014, while some Mean-Variance Experiment PhenoCams were installed as recently as June 2023. For information on PhenoCam data processing and formatting, see Richardson et al., 2018, Scientific Data (https://doi.org/10.1038/sdata.2018.28), Seyednasrollah et al., 2019, Scientific Data (https://doi.org/10.1038/s41597-019-0229-9), and the PhenoCam Network web page (https://phenocam.nau.edu/webcam/). The PhenoCam Network uses imagery from digital cameras to track vegetation phenology and seasonal changes in vegetation activity in diverse ecosystems across North America and around the world. Imagery is uploaded to the PhenoCam server hosted at Northern Arizona University, where it is made publicly available in near-real time, every 30 minutes from sunrise to sunset, 365 days a year. The data are processed using simple image analysis tools to yield a measure of canopy greenness, from which phenological metrics are extracted, characterizing the start and end of the growing season. These transition dates have been shown to align well with on-the-ground observations at various research sites. Long-term PhenoCam data can be used to track the impact of climate variability and change on the rhythm of the seasons.

PhenoCam Dataset v2.0: Vegetation Phenology from Digital Camera Imagery, 2000-2018

This data set provides a time series of vegetation phenological observations for 393 sites across diverse ecosystems of the world (mostly North America) from 2000-2018. The phenology data were derived from conventional visible-wavelength automated digital camera imagery collected through the PhenoCam Network at each site. From each acquired image, RGB (red, green, blue) color channel information was extracted and means and other statistics calculated for a region-of-interest (ROI) that delineates an area of specific vegetation type. From the high-frequency (typically, 30 minute) imagery collected over several years, time series characterizing vegetation color, including canopy greenness, plus greenness rising and greenness falling transition dates, were summarized over 1- and 3-day intervals.

PhenoCam Dataset v3.0: Vegetation Phenology from Digital Camera Imagery, 2000-2023

This dataset provides vegetation phenological observations for 738 sites across diverse ecosystems of the world (mostly North America) from 2000 to 2023. The phenology data were derived from conventional visible-wavelength automated digital camera imagery collected through the PhenoCam Network at each site. From each acquired image, RGB (red, green, blue) color channel information was extracted and summary statistics were calculated for a region-of-interest (ROI) that delineates an area of specific vegetation type. From the high-frequency (typically, 30 minute) imagery collected over several years, time series characterizing vegetation color, including canopy greenness, plus greenness rising and greenness falling transition dates, were summarized over 1- and 3-day intervals. These data products, consisting of 4805.5 site-years of observations, can be used for phenological modeling, to evaluate satellite remote sensing data products, to understand relationships between canopy phenology and ecosystem processes, to study the seasonal changes in leaf-level physiology that are associated with changes in leaf color, for benchmarking earth system models, and for studies of climate change impacts on terrestrial ecosystems. The data are provided in comma separated values (CSV), TIFF image, text, JSON, and GeoJSON formats.

Phenology derived from Satellite Data and PhenoCam across CONUS and Alaska, 2019-2020

This dataset provides a reference of land surface phenology (LSP) at 30-m pixels for 78 regions of 10 x 10 km2 across a wide range of ecological and climatic regions in North America during 2019 and 2020. The data were derived by fusing the Harmonized Landsat 8 and Sentinel-2 (HLS) observations with near- surface PhenoCam time series (hereafter called HP-LSP). The HP-LSP dataset consists of two parts: (1) the 3-day synthetic gap-free EVI2 (two-band Enhanced Vegetation Index) time series and (2) four key phenological transition dates that are greenup onset, maturity onset, senescence onset, and dormancy onset (accuracy less than or equal to five days). The PhenoCam network offers near-surface observations via the RGB (Red, Green, and Blue) imagery every 30 minutes. Each RGB imagery enables us to calculate as many as 100 Green Chromatic Coordinate (GCC) for generating a collection of localized vegetation dynamics. The HLS EVI2 time series with frequent gaps was fused with the most comparable PhenoCam GCC temporal shape selected from the GCC collection using the Spatiotemporal Shape Matching Model (SSMM) to create the synthetic gap-free HLS-PhenoCam EVI2 time series, which was used to establish the physically-based hybrid piecewise logistic model (HPLM) for detecting phenological transition dates (phenometrics).

PhenoCam Dataset v2.0: Digital Camera Imagery from the PhenoCam Network, 2000-2018

This dataset provides a time series of visible-wavelength digital camera imagery collected through the PhenoCam Network at each of 393 sites predominantly in North America from 2000-2018. The raw imagery was used to derive information on phenology, including time series of vegetation color, canopy greenness, and phenology transition dates for the PhenoCam Dataset v2.0.

PhenoCam Dataset v3.0: Digital Camera Imagery from the PhenoCam Network, 2000-2023

This dataset provides a time series of visible-wavelength digital camera imagery collected through the PhenoCam Network at each of 738 sites across diverse ecosystems of the world (mostly North America) from 2000-2023. Vegetation types such as deciduous broadleaf forests, grasslands, evergreen needleleaf forests, and agriculture are the best-represented. The raw imagery was used to derive information on phenology, including time series of vegetation color, canopy greenness, and phenology transition dates for the PhenoCam Dataset v3.0. The images are provided in JPEG format organized in compressed tar.gz archives by site and date. Site locations and basic metadata are included in a GeoJSON file.