The Biophysical Properties of the Vegetation Data Set were collected as part of the larger FIFE Science effort to characterize the physical and biological properties of the sites within the FIFE study area over the life of the field experiment. These data were collected at 43 locations scattered throughout the FIFE study area between May 1987 and August 1989. The measurements of leaf area were based on an optical technique in which the area of the light beam obscured by the material under the beam is a measure of the surface area of that material relative to the total surface area that the beam covers. The resulting Leaf Area Indices (LAI) provide a relative measure of leaf area. These indices, when compared between plant samples provide an indirect and relative measure of plant biomass.

This data set documentation is currently in work. In the interim, an abstract of the entire Superior National Forest (SNF) data collection activity from which the SNF Vegetation Cover Data: C. Jarvis Data Set is a product is being provided. During the summers of 1983 and 1984, the National Aeronautics and Space Administration (NASA) conducted an intensive experiment in a portion of the Superior National Forest (SNF) near Ely, Minnesota, USA. The purpose of the experiment was to investigate the ability of remote sensing to provide estimates of biophysical properties of ecosystems, such as leaf area index (LAI), biomass and net primary productivity (NPP). The study area covered a 50 x 50 km area centered at approximately 48 degrees North latitude and 92 degrees West longitude in northeastern Minnesota at the southern edge of the North American boreal forest. The SNF is mostly covered by boreal forest. Boreal forests were chosen for this project because of their relative taxonomic simplicity, their great extent, and their potential sensitivity to climatic change. Satellite, aircraft, helicopter and ground observations were obtained for the study area. These data comprise a unique dataset for the investigation of the relationships between the radiometric and biophysical properties of vegetated canopies. This is perhaps the most complete dataset of its type ever collected over a forested region.

This data set provide local LAI maps for the Larose (Ontario) site in Canada. These derived maps may also be useful for validating other LAI maps over this same site given that the area is protected from disturbance. The maps should be used for the given period of validity. The LAI data are suitable for use in modeling the carbon, water, energy, energy and trace gas exchange between the land surface and the atmosphere at regional scales. The dataset may also be useful for monitoring changes in the land surface. A complete description of producing the maps for the Larose site and the ground measurement campaign is provide in the companion document (Larose2003FTReport.pdf (link)).The Leaf Area Index (LAI) maps are at 30-m resolution for the 3x3-km Larose site. LAI is defined here as half the total (all-sided) live foliage area per unit horizontal projected ground surface area. Overstory LAI corresponds to all tree foliage except for treeless areas where it corresponds to total foliage. The algorithms were developed from ground measurements and Landsat TM and ETM+ images (Fernandes et. al., 2003). A mask was developed using the Landsat ETM+/TM5 image and available land cover maps to identify only those areas with land cover belonging to the sample land cover classes and with Landsat ETM+/TM5 spectral reflectance values that fell within the convex hull of the spectral reflectance values over the plots. LAI was mapped within the masked region using the Landsat ETM+/TM5 image and the developed transfer function. The final LAI map was scaled by a factor of 20 (offset 0). The LAI maps are in Tagged Image File Format (TIFF).The VALERI project (Validation of Land European Remote sensing Instruments) is dedicated to the validation of the products derived from medium resolution satellite sensors ( http://www.avignon.inra.fr/valeri/ ). The objectives of the VALERI project are: (1) to evaluate the absolute accuracy of the biophysical products (LAI, fAPAR, fCover) derived from large swath sensors (e.g., AVHRR, POLDER, VEGETATION, SEAWIFS, MSG, MERIS, AATSR, MODIS, MISR, GLI) using a range of possible algorithms; and (2) to inter-compare the products derived from different sensors and algorithms. For this purpose, the VALERI project has developed a network of sites distributed over the Earth’s surface and a methodology designed to directly measure the biophysical variables of interest at proper spatial and temporal scales.

This dataset provides a global 0.25 degree x 0.25 degree gridded monthly mean leaf area index (LAI) climatology as averaged over the period from August 1981 to August 2015. The data were derived from the Advanced Very High Resolution Radiometer (AVHRR) Global Inventory Modeling and Mapping Studies (GIMMS) LAI3g version 2, a bi-weekly data product from 1981 to 2015 (GIMMS-LAI3g version 2). The LAI3g version 2 (raw) data were first regridded from 1/12 x 1/12 degree to 0.25 x 0.25 degree resolution, then processed to remove missing and unreasonable values, scaled to obtain LAI values, and the bi-weekly LAI values were averaged for every month. Finally, the monthly long-term mean LAI (1981-2015) was calculated.

This global data set of photosynthetic rates and leaf nutrient traits was compiled from a comprehensive literature review. It includes estimates of Vcmax (maximum rate of carboxylation), Jmax (maximum rate of electron transport), leaf nitrogen content (N), leaf phosphorus content (P), and specific leaf area (SLA) data from both experimental and ambient field conditions, for a total of 325 species and treatment combinations. Both the original published Vcmax and Jmax values as well as estimates at standard temperature are reported. The maximum rate of carboxylation (Vcmax) and the maximum rate of electron transport (Jmax) are primary determinants of photosynthetic rates in plants, and modeled carbon fluxes are highly sensitive to these parameters. Previous studies have shown that Vcmax and Jmax correlate with leaf nitrogen across species and regions, and locally across species with leaf phosphorus and specific leaf area, yet no universal relationship suitable for global-scale models is currently available. These data are suitable for exploring the general relationships of Vcmax and Jmax with each other and with leaf N, P and SLA. This data set contains one *.csv file.

This data set provides local LAI maps for the selected measured sites in Canada. These derived maps may also be useful for validating other LAI maps over these same sites given that the areas are protected from disturbance. The maps should be used for the given period of validity. The LAI data are suitable for use in modeling the carbon, water, energy, energy and trace gas exchange between the land surface and the atmosphere at regional scales. The data set may also be useful for monitoring changes in the land surface.The Leaf Area Index (LAI) maps are at 30-m resolution for the selected sites. LAI is defined here as half the total (all-sided) live foliage area per unit horizontal projected ground surface area. Overstory LAI corresponds to all tree foliage except for treeless areas where it corresponds to total foliage. The algorithms were developed from ground measurements and Landsat TM and ETM+ images (Fernandes et. al., 2003). A mask was developed using the Landsat ETM+/TM5 image and available land cover map to identify only those areas with land cover belonging to the sample land cover classes and with Landsat ETM+/TM5 spectral reflectance values that fell within the convex hull of the spectral reflectance values over the plots. LAI was mapped within the masked region using the Landsat ETM+/TM5 image and the developed transfer function. The final LAI map was scaled by a factor of 20 (offset 0). The LAI maps are in Tagged Image File Format (TIFF).

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.

This data set provides global leaf area index (LAI) values for woody species. The data are a compilation of field-observed data from 1,216 locations obtained from 554 literature sources published between 1932 and 2011. Only site-specific maximum LAI values were included from the sources; values affected by significant artificial treatments (e.g. continuous fertilization and/or irrigation) and LAI values that were low due to drought or disturbance (e.g. intensive thinning, wildfire, or disease), or because vegetation was immature or old/declining, were excluded (Lio et al., 2014). To maximize the generic applicability of the data, original LAI values from source literature and values standardized using the definition of half of total surface area (HSA) are included. Supporting information, such as geographical coordinates of plot, altitude, stand age, name of dominant species, plant functional types, and climate data are also provided in the data file. There is one data file in comma-separated (.csv) format with this data set and one companion file which provides the data sources.

The BOREAS TE-09 team collected several data sets related to chemical and photosynthetic properties of leaves. This data set contains canopy biochemistry data collected in 1994 in the NSA at the YJP, OJP, OBS, BS and OA sites including biochemistry lignin, nitrogen, cellulose, starch, and fiber concentrations. These data were collected to study the spatial and temporal changes in the canopy biochemistry of boreal forest cover types and how a high-resolution radiative transfer model in the mid-infrared could be applied in an effort to obtain better estimates of canopy biochemical properties using remote sensing.

This dataset includes footprint-level canopy structure products derived from data collected using NASA's Land, Vegetation, and Ice Sensor (LVIS) during flights over five forested sites in Gabon during February and March 2016. Three types of canopy structure information are included for each flight: 1) vertical profiles of canopy cover fraction in 1-meter bins, 2) vertical profiles of plant area index (PAI) in 1-meter bins, and 3) footprint summary data of total recorded energy, leaf area index, canopy cover fraction, and vertical foliage profiles in 10-meter bins. Canopy structure metrics are provided for each waveform (20-m footprint) collected by the LVIS instrument. These data were collected by NASA as part of the AfriSAR project. AfriSAR is a NASA collaboration with the European Space Agency (ESA), German Aerospace Center (DLR), and the Gabonese Space Agency (AGEOS) that is collecting data useful for deriving forest canopy structure and will help prepare for and calibrate current and upcoming spaceborne missions that aim to gauge the role of forests in Earth's carbon cycle.