LAI estimates computed from unweighted openness by the CANOPY program from digitized canopy photographs

Data from the Tracing Radiation and Architecture of Canopies (TRAC) instrument were collected at five sites along the International Geosphere-Biosphere Programme (IGBP) Kalahari Transect, including Mongu in Zambia and Pandamatenga, Maun, Okwa River Crossing, and Tshane in Botswana, during the 2000 wet season field campaign (March-April) of SAFARI 2000. At the Mongu site, TRAC measurements began in August of 1999 and continued beyond the 2000 wet season field campaign, about every month for the rest of 2000.The TRAC instrument contains pyranometers that are sensitive to photosynthetically active radiation (PAR) at 400-700 nm. The TRAC measures the PAR flux transmitted through the overstory canopy continuously at 32 Hz. The parameters derived from the TRAC instrument include estimates of plant or leaf area index (PAI, LAI), overstory gap fraction, and clumping index.At each site, the TRAC instrument was carried along three parallel transects, each 750 m long and spaced 250 m apart. Measurements were made every 25 m along the transects. The length and spacing of the transects were chosen to sample an area large enough to be representative of a 1 km MODIS pixel.The data files are stored as ASCII text files, one file per transect, site, and date, with column headers. There are also summary files (ASCII text) containing mean values of each derived parameter over an entire transect for each collection date.

This data set contains leaf area index (LAI), leaf inclination angle, and canopy dimension data from study sites along the Kalahari Transect in southwest Botswana. The data were collected during the 2001 wet season field campaign of the SAFARI 2000 at a total of seven plots of 200 x 150 meter dimensions; two plots each at Tshane and Mabuasehube, and three plots at Tsabong. The data set consists of measurements of leaf angle for plot dominant woody species, LAI calculated from overstory and understory photosynthetically active radiation (PAR) measurements, and canopy dimension data (i. e., crown height, crown width, and height to crown) for grass and woody vegetation, for use in the parameterization of plant canopy reflectance models.Measurements of LAI were made with a plant canopy analyzer which records direct and diffuse PAR at the top of the canopy using a beam fraction sensor. PAR beneath the canopy was measured simultaneously with a one-meter long probe held horizontally beneath the canopy. Leaf inclination angle measurements were made using a clinometer. Measurements of tree height, crown height, height-to-crown, and crown width were made for 10 to 20 individual trees of the dominant species at each field plot using a tape measure or simple trigonometry, and calculations based on these data.The data files are stored as ASCII table files, in comma-separated-value (.csv) format, with column headers. Photographs (.jpg) are provided of each plot to provide an idea of site conditions. The photographs can be viewed on the S2K Photo Gallery pages.

Leaf Area Index (LAI) data from the scientific literature, covering the period from 1932-2000, have been compiled at the Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC) to support model development and validation for products from the MODerate Resolution Imaging Spectroradiometer (MODIS) instrument. There is one data file which consists of a spreadsheet table, together with a bibliography of more than 300 original-source references. Although the majority of measurements are from natural or semi-natural ecosystems, some LAI values have been included from crops (limited to a sub-set representing different crops at different stages of development under a range of treatments). Like Net Primary Productivity (NPP), Leaf Area Index (LAI) is a key parameter for global and regional models of biosphere/atmosphere exchange. Modeling and validation of coarse scale satellite measurements both require field measurements to constrain LAI values for different biomes (typical minimum, maximum values, phenology, etc.). Maximum values for point measurements are unlikely to be approached or exceeded by area-weighted LAI, which is what satellites and true spatial models are estimating.

The data set consists of a southern Africa subset of the 1km Global Tree Cover Data Set developed at the Laboratory for Global Remote Sensing Studies (LGRSS) at the University of Maryland. Data are available in both ASCII GRID and binary image files formats. Characterization of terrestrial vegetation from the Advanced Very High Resolution Radiometer (AVHRR) on the global to regional scale has traditionally been accomplished using classification schemes with discrete numbers of vegetation classes. Representation of vegetation into a limited number of homogeneous classes does not account for the variability within land cover, nor does the portrayal recognize transition zones between adjacent cover types. An alternative paradigm to describing land cover as discrete classes is to represent land cover as continuous fields of vegetation characteristics using a linear mixture model approach. This prototype data set, created by researchers at the Laboratory for Global Remote Sensing Studies (LGRSS) at the University of Maryland, contains 1-km cells estimating: 1) Percent tree cover; 2) Percentage cover for two layers representing leaf longevity (evergreen and deciduous); and 3) Percentage cover for two layers estimating leaf type (broadleaf and needleleaf). Data acquired in 1992-93 from NOAA's AVHRR at a 1-km spatial resolution and processed under the guidance of the International Geosphere Biosphere Programme (IGBP) were used to derive the tree cover, leaf type and leaf longevity maps. Each pixel in the layers has a value between 10 and 80 percent. These layers can be directly used as parameters in models or aggregated into more conventional land cover maps. For the latter, the product offers the flexibility to derive land cover maps based on user's requirements for a particular application. The product is intended for use in terrestrial carbon cycle models, in conjunction with other spatial data sets such as climate and soil type, to obtain more consistent and reliable estimates of carbon stocks. More information can be found at: ftp://daac.ornl.gov/data/safari2k/vegetation_wetlands/tree_cover-1km/comp/glcftree_readme.pdf.

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.

Approximately 1000 published estimates of leaf area index (LAI) from nearly 400 unique field sites, covering the period 1932-2000, have been compiled into a single data set. LAI is a key parameter for global and regional models of biosphere/atmosphere exchange of carbon dioxide, water vapor, etc. This data set provides a benchmark of typical values and ranges of LAI for a variety of biomes and land cover types, in support of model development and validation of satellite-derived remote sensing estimates of LAI and other vegetation parameters. The LAI data are linked to a bibliography of over 300 original-source references. These historical LAI data are mostly from natural and semi-natural (managed) ecosystems, although some agricultural estimates are also included. Caution is advised in using these data; they were collected using a wide range of methodologies and assumptions and may not be comparable among sites. Some attempts have been made to detect and flag the outliers in this data set, according to different biome/land cover classes. Needleleaf (coniferous) forests are by far the most commonly measured biome/land cover types in this compilation, with 22% of the measurements from temperate evergreen needleleaf forests, and boreal evergreen needleleaf forests and crops the next most common (about 9% each). About 40% of the records in the data set were published in the past 10 years (1991-2000), with a further 20% collected between 1981 and 1990. Mean LAI (+/- standard deviation), distributed between 15 biome/land cover classes, ranged from 1.31 +/- 0.85 for deserts to 8.72 +/- 4.32 for tree plantations, with evergreen forests (needleleaf and broadleaf) displaying the highest LAI among the natural vegetation classes. Further information on this data set is available from the link below: Leaf Area Index Data Citation: Cite this data set as follows: Scurlock, J. M. O., G. P. Asner, and S. T. Gower. 2001. Global Leaf Area Index from Field Measurements, 1932-2000. Available on-line [http://www.daac.ornl.gov] from Oak Ridge National Laboratory Distributed Active Archive Center, Oak Ridge, Tennessee, U.S.A.

A newly developed ground-based canopy imaging system called an MVI was tested and used by the BOREAS TE-06 team to collect measurements of the canopy gap fraction (sky fraction), canopy gap-size distribution (size and frequency of gaps between foliage in canopy), branch architecture, and leaf angle distribution (fraction of leaf area in specific leaf inclination classes assuming azimuthal symmetry). Measurements of the canopy gap-size distribution are used to derive canopy clumping indices that can be used to adjust indirect LAI measurements made in nonrandom forests. These clumping factors will also help to describe the radiation penetration in clumped canopies more accurately by allowing for simple adjustments to Beer's law. Measurements of the above quantities were obtained at BOREAS NSA OJP site in IFC-2 in 1994, at the SSA OA in July 1995, and at the SSA OBS and SSA OA sites in IFC-2 in 1996. Modeling studies were also performed to further validate MVI measurements and to gain a more complete understanding of boreal forest canopy architecture. By using MVI measurements and Monte Carlo simulations, clumping indices as a function of zenith angle were derived for the three main boreal species studied during BOREAS.

Measurements of leaf area index and biomass of different canopy components