Modeling spatially distributed ecosystem flux of boreal forest using hyperspectral indices from AVIRIS imagery

Abstract

Abstract. Correct estimation of spatially distributed CO2 flux is of utmost importance for regional and global carbon balance studies. Tower-based instruments provide flux data from a small footprint area and may not be suitable for spatial extrapolation over areas not represented by the towers. In this study we developed a method of combining optical indices from remotely sensed hyperspectral images with flux data from towers covering different vegetation types to make spatially continuous maps of gross CO2 fluxes. Using a simple light-use efficiency model, we tested the ability of spectral indices derived from Airborne Visible Infrared Imaging Spectrometer (AVIRIS) imagery to estimate photosynthetic fluxes of several boreal forest stands. Because CO 2 flux from terrestrial ecosystems is dependent on both vegetation cover and physiological state, we hypothesized that measures of both forest structure and physiology were important for flux estimation. Consequently, the modeled fluxes considered both the normalized difference vegetation index (NDVI) and a scaled value of the photochemical reflectance index (PRI), both

Connection of the Photochemical Reflectance Index (PRI) with the Photosystem II Quantum Yield and Nonphotochemical Quenching Can Be Dependent on Variations of Photosynthetic Parameters among Investigated Plants: A Meta-Analysis

“…The mathematical modeling of photosynthetic processes and PRI can be potentially used for a crude guess of the photosynthetic parameters under specific conditions. Moreover, the modeling can be an additional tool for the analysis of the connection between reflectance indices and photosynthetic parameters [109,125,126]. Development of these models can be used as a solution to the fundamental and applied problems in the field of remote sensing with PRI.…”

The use of remote sensing in light use efficiency based models of gross primary production: A review of current status and future requirements

“…Second, airborne or spaceborne sensors can only provide snapshots in time determined by a given aircraft or satellite overpass , however, the temporal and spatial requirements for these observations to be representative of the physiological status of plant canopies are not well understood . Third, the relationship between PRI and is species dependent and also changes with age, canopy structure, disturbances and LAI (Rahman et al, 2001), making a spatial extrapolation of empirical findings difficult.…”

“…involved, include near surface observations using transect measurements , permanently established tower based observations of forest canopies (Leuning et al, 2006;Hilker et al, 2007), and airborne measurements (Nichol et al, 2000;Chen and Vierling, 2006;Rahman et al, 2001). A first spaceborne assessment of was introduced by Drolet et al (2005), successfully using backscatter reflectance data from MODIS Aqua over the Canadian boreal forest with a spatial resolution of 1 km 2 .…”

“…Networking approaches, such as the recently established SpecNet initiative attempt to link these observations with existing global fluxtower sites to further the understanding of relationships existing between biophysical processes and spectral reflectance data, thereby trying to overcome the fundamental scale mismatch between estimates obtained from eddy flux and remote sensing Rahman et al 2001;Cheng et al 2006;Gamon et al, 2006). Other objectives of this network are the exploration of temporal matters, derivation of flux components and the validation of satellite data products .…”

Remote sensing of ecosystem services: An opportunity for spatially explicit assessment

“…The possibility of predicting average primary productivity by its regression relationship with NDVI has been observed in the Arctic tundra (Boelman et al, 2003) and in steppe ecosystems (Wylie et al, 2003). NDVI tends to be saturated when biomass increases to a high value (Myneni et al, 1995;Hao et al, 2008), this being especially obvious in evergreen forest area (Rahman et al, 2001). Considerable efforts have been made to improve NDVI estimation.…”