10 research outputs found
Arctic Tundra Vegetation Functional Types Based on Photosynthetic Physiology and Optical Properties
Non-vascular plants (lichens and mosses) are significant components of tundra landscapes and may respond to climate change differently from vascular plants affecting ecosystem carbon balance. Remote sensing provides critical tools for monitoring plant cover types, as optical signals provide a way to scale from plot measurements to regional estimates of biophysical properties, for which spatial-temporal patterns may be analyzed. Gas exchange measurements were collected for pure patches of key vegetation functional types (lichens, mosses, and vascular plants) in sedge tundra at Barrow, AK. These functional types were found to have three significantly different values of light use efficiency (LUE) with values of 0.013 plus or minus 0.0002, 0.0018 plus or minus 0.0002, and 0.0012 plus or minus 0.0001 mol C mol (exp -1) absorbed quanta for vascular plants, mosses and lichens, respectively. Discriminant analysis of the spectra reflectance of these patches identified five spectral bands that separated each of these vegetation functional types as well as nongreen material (bare soil, standing water, and dead leaves). These results were tested along a 100 m transect where midsummer spectral reflectance and vegetation coverage were measured at one meter intervals. Along the transect, area-averaged canopy LUE estimated from coverage fractions of the three functional types varied widely, even over short distances. The patch-level statistical discriminant functions applied to in situ hyperspectral reflectance data collected along the transect successfully unmixed cover fractions of the vegetation functional types. The unmixing functions, developed from the transect data, were applied to 30 m spatial resolution Earth Observing-1 Hyperion imaging spectrometer data to examine variability in distribution of the vegetation functional types for an area near Barrow, AK. Spatial variability of LUE was derived from the observed functional type distributions. Across this landscape, a fivefold variation in tundra LUE was observed. LUE calculated from the functional type cover fractions was also correlated to a spectral vegetation index developed to detect vegetation chlorophyll content. The concurrence of these alternate methods suggest that hyperspectral remote sensing can distinguish functionally distinct vegetation types and can be used to develop regional estimates of photosynthetic LUE in tundra landscapes
Estimation and Validation of Land Surface Broadband Albedos and Leaf Area Index From EO-1 ALI Data
The Advanced Land Imager (ALI) is a multispectral
sensor onboard the National Aeronautics and Space
Administration Earth Observing 1 (EO-1) satellite. It has similar
spatial resolution to Landsat-7 Enhanced Thematic Mapper Plus
(ETM+), with three additional spectral bands. We developed
new algorithms for estimating both land surface broadband
albedo and leaf area index (LAI) from ALI data. A recently
developed atmospheric correction algorithm for ETM+ imagery
was extended to retrieve surface spectral reflectance from ALI
top-of-atmosphere observations. A feature common to these
algorithms is the use of new multispectral information from ALI.
The additional blue band of ALI is very useful in our atmospheric
correction algorithm, and two additional ALI near-infrared
bands are valuable for estimating both broadband albedo and
LAI. Ground measurements at Beltsville, MD, and Coleambally,
Australia, were used to validate the products generated by these
algorithms.This work
was supported in part by the National Aeronautics and Space Administration
under Grant NCC5462 and by funding provided by the Australian Federal Government
to the Commonwealth Scientific and Industrial Research Organization
and the Cooperative Research Centre for Sustainable Rice Production, Project
1105
Relationship between fraction of radiation absorbed by photosynthesizing maize and soybean canopies and NDVI from remotely sensed data taken at close range and from MODIS 250 m resolution data
The fraction of incident photosynthetically active radiation absorbed by the photosynthesizing tissue in a canopy (fAPAR) is a key variable in the assessment of vegetation productivity. It also plays tremendous role in accurate retrieval of light use efficiency, which is essential for assessing vegetation health status. The main goal of this work was to study in detail relationships of fAPAR absorbed by photosynthetically active vegetation (fAPARgreen) and Normalized Difference Vegetation Index (NDVI) for two crops with contrasting leaf structures (C3 vs. C4) and canopy architectures, using close range (6 m above the canopy) radiometric data and daily MODIS data taken during eight growing seasons over three irrigated and rainfed maize and soybean sites. Our specific goal was to understand differences in fAPARgreen/NDVI relationshipwhen crop canopy was almost vertically homogeneous (with respect to leaf area and leaf chlorophyll content), as in vegetative stage, and vertically heterogeneous as in reproduction stage. Firstly, we established fAPARgreen/NDVI relationships for NDVI, taken at close range, and assessed noise equivalent of fAPARgreen estimation by NDVI, and then we established relationships for NDVI retrieved from daily MODIS 250 m data. Daily MODIS data illuminated fine details of this relationship and detected effects of canopy heterogeneity on fAPARgreen/NDVI relationship. In vegetative stage, the fAPAR/NDVI relationships for contrasting in leaf structures and canopy architectures crops were almost linear allowing accurate estimation of fAPARgreen as it is below 0.7. However, very different fAPARgreen/NDVI relationships in reproductive stages for both crops were observed, showing that canopy architecture and leaf structure greatly affect the relationship as leaf chlorophyll content changes and vertical distribution of chlorophyll content and green LAI inside the canopy becomes heterogeneous.We have found fine details of the fAPARgreen/NDVI relationships with two types of hysteresis that prevent the use of a single relationship for fAPARgreen estimation by NDVI over the whole growing season and suggested mechanisms for each type of hysteresis that should be further studied using radiative transfer models
BOREAS HYD-5 Winter Surface Flux Data
The BOREAS HYD-5 team collected tower flux, surface meteorological, and surface temperature data on a frozen lake (Namekus Lake) and in a mature jack pine forest in the Beartrap Creek watershed. Both sites were located in the BOREAS SSA. The objective of this study was to characterize the winter energy and water vapor fluxes, as well as related properties (such as snow density, depth, temperature, and melt) for forested and nonforested areas of the boreal forest. Data were collected on Namekus Lake in the winters of 1994 and 1996, and at Beartrap Creek in the winter of 1994 only. The data are available in tabular ASCII files. The data files are available on a CD-ROM (see document number 20010000884) or from the Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC)
Arctic Tundra Vegetation Functional Types Based on Photosynthetic Physiology and Optical Properties
Linking foliage spectral responses to canopy-level ecosystem photosynthetic light-use efficiency at a Douglas-fir forest in Canada
The light-use efficiency (LUE) of a mature Canadian Douglas-fir forest (DF49) was studied using high-resolution in situ temporal, spatial, and spectral measurements in conjunction with fluxes acquired from an instrumented tower. We examined the photochemical reflectance index (PRI), a spectral index responsive to high light conditions that alters reflectance at 531 nm, in combination with several alternative reference bands at 551, 570, and 488 nm. These indices were derived from directional reflectance spectra acquired by a hyperspectral radiometer system mounted on the DF49 tower, viewing the canopy through almost 360° rotations multiple times an hour daily throughout the 2006 growing season. From canopy structure information, three foliage sectors within the canopy were delineated according to instantaneous illumination conditions (sunlit, shaded, and mixed shaded-sunlit). On sunny days, the PRI indices for the sunlit foliage sector captured high light-induced stress responses, expressed as significantly different PRI values for sunlit versus shaded foliage. This difference was not observed on highly diffuse or overcast days. PRIs on sunny days tracked the diurnal photoregulation responses throughout the growing season in concert with illumination intensity. We computed the effective instantaneous LUE for the three foliage groups (LUE foliage) using modeled and measured information. We provide convincing evidence that LUE foliage can be well described and strongly related to all variations of the PRI within this coniferous forest under relatively clear skies (0.59 > r 2 > 0.80, P < 0.0001). LUE foliage varied through the growing season between 0.015 and 0.075 mol C mol -1 absorbed photosynthetically active radiation (APAR), and the lowest daily values were associated with the sunlit foliage group. The mixed sunlit-shaded foliage was the only group to exhibit monthly averages close to the maximum ecosystem LUE parameter ( max) used in LUE models for evergreen needle forests (0.0196 mol C mol -1 APAR). Implications for remote sensing of carbon uptake dynamics and the interaction of canopy structure and physiology are discussed. © 2009 CASI
Evaluation of fraction of absorbed photosynthetically active radiation products for different canopy radiation transfer regimes: Methodology and results using Joint Research Center products derived from SeaWiFS against ground-based estimations
This paper discusses the quality and the accuracy of the Joint Research Center (JRC) fraction of absorbed photosynthetically active radiation (FAPAR) products generated from an analysis of Sea-viewing Wide Field-of-view Sensor (SeaWiFS) data. The FAPAR value acts as an indicator of the presence and state of the vegetation and it can be estimated from remote sensing measurements using a physically based approach