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- 저자 : Migliavacca, Mirco (검색결과 2 건)
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Filippa, Gianluca,Cremonese, Edoardo,Migliavacca, Mirco,Galvagno, Marta,Sonnentag, Oliver,Humphreys, Elyn,Hufkens, Koen,Ryu, Youngryel,Verfaillie, Joseph,Morra di Cella, Umberto,Richardson, Andrew D. Elsevier 2018 Agricultural and forest meteorology Vol.249 No.-
<P><B>Abstract</B></P> <P>Time series of vegetation indices (e.g. normalized difference vegetation index [NDVI]) and color indices (e.g. green chromatic coordinate [<I>G</I> <SUB> <I>CC</I> </SUB>]) based on radiometric measurements are now available at different spatial and temporal scales ranging from weekly satellite observations to sub-hourly <I>in situ</I> measurements by means of near-surface remote sensing (e.g. spectral sensors or digital cameras). <I>In situ</I> measurements are essential for providing validation data for satellite-derived vegetation indices. In this study we used a recently developed method to calculate NDVI from near-infrared (NIR) enabled digital cameras (NDVI<SUB> <I>C</I> </SUB>) at 17 sites (for a total of 74 year-sites) encompassing six plant functional types (PFT) from the PhenoCam network.</P> <P>The seasonality of NDVI<SUB> <I>C</I> </SUB> was comparable to both NDVI measured by ground spectral sensors and by the moderate resolution imaging spectroradiometer (MODIS). We calculated site- and PFT-specific scaling factors to correct NDVI<SUB> <I>C</I> </SUB> values and recommend the use of site-specific NDVI from MODIS in order to scale NDVI<SUB> <I>C</I> </SUB>. We also compared <I>G</I> <SUB> <I>CC</I> </SUB> extracted from red-green-blue images to NDVI<SUB> <I>C</I> </SUB> and found PFT-dependent systematic differences in their seasonalities. During senescence, NDVI<SUB> <I>C</I> </SUB> lags behind <I>G</I> <SUB> <I>CC</I> </SUB> in deciduous broad-leaf forests and grasslands, suggesting that <I>G</I> <SUB> <I>CC</I> </SUB> is more sensitive to changes in leaf color and NDVI<SUB> <I>C</I> </SUB> is more sensitive to changes in leaf area. In evergreen forests, NDVI<SUB> <I>C</I> </SUB> peaks later than <I>G</I> <SUB> <I>CC</I> </SUB> in spring, probably tracking the processes of shoot elongation and new needle formation. Both <I>G</I> <SUB> <I>CC</I> </SUB> and NDVI<SUB> <I>C</I> </SUB> can be used as validation tools for the MODIS Land Cover Dynamics Product (MCD12Q2) for deciduous broad-leaf spring phenology, whereas NDVI<SUB> <I>C</I> </SUB> is more comparable than <I>G</I> <SUB> <I>CC</I> </SUB> with autumn phenology derived from MODIS. For evergreen forests, we found a poor relationship between MCD12Q2 and camera-derived phenology, highlighting the need for more work to better characterize the seasonality of both canopy structure and leaf biochemistry in those ecosystems.</P> <P>Our results demonstrate that NDVI<SUB> <I>C</I> </SUB> is in excellent agreement with NDVI obtained from spectral measurements, and that NDVI<SUB> <I>C</I> </SUB> and <I>G</I> <SUB> <I>CC</I> </SUB> can complement each other in describing ecosystem phenology. Additionally, NDVI<SUB> <I>C</I> </SUB> allows the detection of structural changes in the canopy that cannot be detected by visible-wavelength imagery.</P> <P><B>Highlights</B></P> <P> <UL> <LI> We analyze 74 site-years of green chromatic coordinate (GCC) and camera NDVI data. </LI> <LI> Camera NDVI is comparable to traditional NDVI measurements. </LI> <LI> Camera NDVI and GCC can complement each other in describing ecosystem phenology. </LI> <LI> Both can be used as validation tools for satellite phenology products. </LI> </UL> </P>
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Tagliabue, Giulia,Panigada, Cinzia,Dechant, Benjamin,Baret, Fré,dé,ric,Cogliati, Sergio,Colombo, Roberto,Migliavacca, Mirco,Rademske, Patrick,Schickling, Anke,Schü,ttemeyer, Dirk,Verre Elsevier 2019 Remote sensing of environment Vol.231 No.-
<P><B>Abstract</B></P> <P>Terrestrial gross primary productivity (GPP) plays an essential role in the global carbon cycle, but the quantification of the spatial and temporal variations in photosynthesis is still largely uncertain. Our work aimed to investigate the potential of remote sensing to provide new insights into plant photosynthesis at a fine spatial resolution. This goal was achieved by exploiting high-resolution images acquired with the FLuorescence EXplorer (FLEX) airborne demonstrator <I>HyPlant</I>. The sensor was flown over a mixed forest, and the images collected were elaborated to obtain two independent indicators of plant photosynthesis. First, maps of sun-induced chlorophyll fluorescence (F), a novel indicator of plant photosynthetic activity, were successfully obtained at both the red and far-red peaks (r<SUP>2</SUP> = 0.89 and <I>p</I> < 0.01, r<SUP>2</SUP> = 0.77 and p < 0.01, respectively, compared to top-of-canopy ground-based measurements acquired synchronously with the overflight) over the forested study area. Second, maps of GPP and absorbed photosynthetically active radiation (APAR) were derived using a customised version of the coupled biophysical model Breathing Earth System Simulator (BESS). The model was driven with airborne-derived maps of key forest traits (i.e., leaf chlorophyll content (LCC) and leaf area index (LAI)) and meteorological data providing a high-resolution snapshot of the variables of interest across the study site. The LCC and LAI were accurately estimated (RMSE = 5.66 μg cm<SUP>−2</SUP> and RMSE = 0.51 m<SUP>2</SUP> m<SUP>−2</SUP>, respectively) through an optimised Look-Up-Table-based inversion of the PROSPECT-4-INFORM radiative transfer model, ensuring the accurate representation of the spatial variation of these determinants of the ecosystem's functionality. The spatial relationships between the measured F and modelled BESS outputs were then analysed to interpret the variability of ecosystem functioning at a regional scale. The results showed that far-red F is significantly correlated with the GPP (r<SUP>2</SUP> = 0.46, <I>p</I> < 0.001) and APAR (r<SUP>2</SUP> = 0.43, p < 0.001) in the spatial domain and that this relationship is nonlinear. Conversely, no statistically significant relationships were found between the red F and the GPP or APAR (<I>p</I> > 0.05). The spatial relationships found at high resolution provide valuable insight into the critical role of spatial heterogeneity in controlling the relationship between the far-red F and the GPP, indicating the need to consider this heterogeneity at a coarser resolution.</P> <P><B>Highlights</B></P> <P> <UL> <LI> High-resolution LCC and LAI maps were obtained from <I>HyPlant</I> through RTM inversion. </LI> <LI> High-resolution GPP and APAR maps were obtained driving BESS with <I>HyPlant</I> data. </LI> <LI> High-resolution F<SUB>687</SUB> and F<SUB>760</SUB> maps were obtained from <I>HyPlant</I> using SFM in a forest. </LI> <LI> F<SUB>687</SUB> showed a non-significant relation with GPP and APAR in the spatial domain. </LI> <LI> F<SUB>760</SUB> showed a positive nonlinear relation with GPP and APAR in the spatial domain. </LI> </UL> </P>
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