492 research outputs found

    A cross‐faculty simulation model for authentic learning

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    This paper proposes a cross‐faculty simulation model for authentic learning that bridges the gap between short group‐based simulations within the classroom and longer individual placements in professional working contexts. Dissemination of the model is expected to widen the use of authentic learning approaches in higher education (HE). The model is based on a cross‐faculty project in which UK HE students acted as professional developers to produce prototype educational games for academic clients from other subject areas. Perceptions about the project were obtained from interviews with project participants. The stakeholders believed the cross‐faculty simulation to be a motivating learning experience, whilst identifying possible improvements. To evaluate whether the authenticity of the student–client relationship could be improved, the interview data were compared to four themes for authentic learning described by Rule in 2006. The data supported Rule’s themes, whilst highlighting the added value gained from meta‐awareness of the simulation as a learning opportunity

    Solutions of Higher Dimensional Gauss-Bonnet FRW Cosmology

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    We examine the effect on cosmological evolution of adding a Gauss-Bonnet term to the standard Einstein-Hilbert action for a (1 + 3)+ d dimensional Friedman-Robertson-Walker (FRW) metric. By assuming that the additional dimensions compactify as a power law as the usual 3 spatial dimensions expand, we solve the resulting dynamical equations and find that the solution may be of either de Sitter or Kasner form depending upon whether the Gauss-Bonnet term or the Einstein term dominates.Comment: 10 pages, references added/corrected, accepted for publication in General Relativity and Gravitatio

    Can a Satellite-Derived Estimate of the Fraction of PAR Absorbed by Chlorophyll (FAPAR(sub chl)) Improve Predictions of Light-Use Efficiency and Ecosystem Photosynthesis for a Boreal Aspen Forest?

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    Gross primary production (GPP) is a key terrestrial ecophysiological process that links atmospheric composition and vegetation processes. Study of GPP is important to global carbon cycles and global warming. One of the most important of these processes, plant photosynthesis, requires solar radiation in the 0.4-0.7 micron range (also known as photosynthetically active radiation or PAR), water, carbon dioxide (CO2), and nutrients. A vegetation canopy is composed primarily of photosynthetically active vegetation (PAV) and non-photosynthetic vegetation (NPV; e.g., senescent foliage, branches and stems). A green leaf is composed of chlorophyll and various proportions of nonphotosynthetic components (e.g., other pigments in the leaf, primary/secondary/tertiary veins, and cell walls). The fraction of PAR absorbed by whole vegetation canopy (FAPAR(sub canopy)) has been widely used in satellite-based Production Efficiency Models to estimate GPP (as a product of FAPAR(sub canopy)x PAR x LUE(sub canopy), where LUE(sub canopy) is light use efficiency at canopy level). However, only the PAR absorbed by chlorophyll (a product of FAPAR(sub chl) x PAR) is used for photosynthesis. Therefore, remote sensing driven biogeochemical models that use FAPAR(sub chl) in estimating GPP (as a product of FAPAR(sub chl x PAR x LUE(sub chl) are more likely to be consistent with plant photosynthesis processes

    Relating a Spectral Index from MODIS and Tower-based Measurements to Ecosystem Light Use Efficiency for a Fluxnet-Canada Coniferous Forest

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    As part of the North American Carbon Program effort to quantify the terrestrial carbon budget of North America, we have been examining the possibility of retrieving ecosystem light use efficiency (LUE, the carbon sequestered per unit photosynthetically active radiation) directly from satellite observations. Our novel approach has been to compare LUE derived from tower fluxes with LUE estimated using spectral indices computed from MODIS satellite observations over forests in the Fluxnet-Canada Research Network, using the MODIS narrow ocean bands acquired over land. We matched carbon flux data collected around the time of the MODIS mid-day overpass for over one hundred relatively clear days in five years (2001-2006) from a mature Douglas fir forest in British Columbia. We also examined hyperspectral reflectance data collected diurnally from the tower in conjunction with the eddy correlation fluxes and meteorological measurements made throughout the 2006 growing season at this site. The tower-based flux data provided an opportunity to examine diurnal and seasonal LUE processes and their relationship to spectral indices at the scale of the forest stand. We evaluated LUE in conjunction with the Photochemical Reflectance Index (PRI), a normalized difference spectral index that uses 531 nm and a reference band to capture responses to high light induced stress afforded by the xanthophyll cycle. Canopy structure information, retrieved from airborne laser scanning radar (LiDAR) observations, was used to partition the forest canopy into sunlit and shaded fractions throughout the day, on numerous days during 2006. At each observation period throughout a day, the PRI was examined for the sunlit, shaded, and intermediate canopy segments defined by their instantaneous position relative to the solar principal plane (SPP). The sunlit sector was associated with the illumination "hotspot" (the reflectance backscatter maximum), the shaded sector with the "cold or dark spot" (the reflectance forward scatter minimum), while the intermediate, mixed sunlit/shade sector was located in the cross-plane to the SPP. The PRI indices clearly captured the differences in leaf groups, with sunlit foliage exhibiting the lowest values on sunny days throughout the 2006 season. When tower-based canopy-level LUE was recalculated to estimate foliage-based values (LUE(sub foilage) for the three foliage groups under their incident light environments, a strong linear relationship for PRI:LUE(sub foilage) was demonstrated (0.6 less than or equal to r(sup 2) less than or equal to 0.8, n=822, P<0.0001). The MODIS data represent relatively large areas when acquired at nadir (approx.1 sq km) or at variable off-nadir view angles (greater than or equal to 1 sq km) looking forward or aft. Nevertheless, a similar relationship between MODIS PRI and tower-based LUE was obtained from satellite observations (r(sup 2) = 0.76, n=105, P= 0.026) when the azimuth offsets from the SPP for off-nadir observations were considered. At this relatively high latitude of 50 degrees, the MODIS directional observations were offset from the SPP by approximately 50 degrees, but still represented backscatter or forward scatter sectors of the bidirectional reflectance distribution function (BRDF). The backscatter observations sampled the sunlit forest and provided lower PRI values, in general, than the forward scatter observations from the shaded forest. Since the hotspot and darkspot were not typically directly observed, the dynamic range for MODIS PRI was less than that observed in the SPP at the canopy level; therefore, MODIS PRI values were more similar to those observed in sifu in the BRDF cross-plane. While not ideal in terms of spatial resolution or optimal viewing configuration, the MODIS observations nevertheless provide a means to monitor forest under stress using narrow spectral band indices and off-nadir observations. This research has stimulated several spin-off studies for remote sensinf LUE, and demonstrates the importance of the connection between ecosystem structure and physiological function

    Estimation of Crop Gross Primary Production (GPP)

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    Satellite remote sensing estimates of Gross Primary Production (GPP) have routinely been made using spectral Vegetation Indices (VIs) over the past two decades. The Normalized Difference Vegetation Index (NDVI), the Enhanced Vegetation Index (EVI), the green band Wide Dynamic Range Vegetation Index (WDRVIgreen), and the green band Chlorophyll Index (CIgreen) have been employed to estimate GPP under the assumption that GPP is proportional to the product of VI and photosynthetically active radiation (PAR) (where VI is one of four VIs: NDVI, EVI, WDRVIgreen, or CIgreen). However, the empirical regressions between VI*PAR and GPP measured locally at flux towers do not pass through the origin (i.e., the zero X-Y value for regressions). Therefore they are somewhat difficult to interpret and apply. This study investigates (1) what are the scaling factors and offsets (i.e., regression slopes and intercepts) between the fraction of PAR absorbed by chlorophyll of a canopy (fAPARchl) and the VIs, and (2) whether the scaled VIs developed in (1) can eliminate the deficiency and improve the accuracy of GPP estimates. Three AmeriFlux maize and soybean fields were selected for this study, two of which are irrigated and one is rainfed. The four VIs and fAPARchl of the fields were computed with the MODerate resolution Imaging Spectroradiometer (MODIS) satellite images. The GPP estimation performance for the scaled VIs was compared to results obtained with the original VIs and evaluated with standard statistics: the coefficient of determination (R2), the root mean square error (RMSE), and the coefficient of variation (CV). Overall, the scaled EVI obtained the best performance. The performance of the scaled NDVI, EVI and WDRVIgreen was improved across sites, crop types and soil/background wetness conditions. The scaled CIgreen did not improve results, compared to the original CIgreen. The scaled green band indices (WDRVIgreen, CIgreen) did not exhibit superior performance to either the scaled EVI or NDVI in estimating crop daily GPP at these agricultural fields. The scaled VIs are more physiologically meaningful than original un-scaled VIs, but scaling factors and offsets may vary across crop types and surface conditions
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