DART: Recent Advances in Remote Sensing Data Modeling With Atmosphere, Polarization, and Chlorophyll Fluorescence

Gastellu-Etchegorry, Jean-Philippe; Lauret, Nicolas; Yin, Tiangang; Landier, Lucas; Kallel, A.; Malenovský, Zbyněk; Bitar, Ahmad Al; Aval, Josselin; Benhmida, Sahar; Qi, Jianbo; Medjdoub, Ghania; Guilleux, J.; Chavanon, Eric; Cook, Bruce D.; Morton, Douglas C.; Chrysoulakis, Nektarios; Mitraka, Zina

doi:10.1109/jstars.2017.2685528

Cited by 155 publications

(77 citation statements)

References 35 publications

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“…This index is not particularly suited for fragmented agricultural landscapes with different crops within the same pixel or for complex mixed forests, and therefore additional studies are needed to define strategies for global scale applications. Moreover, further studies exploiting new emerging 3‐D radiative transfer models incorporating fluorescence, like FluorWPS (Zhao et al., ), FluorFLIGHT (Hernández‐Clemente et al., ) and DART (Gastellu‐Etchegorry et al., ) will help to test the performance of CCFI and the effects caused by the canopy structure on the fluorescence signal recorded from mixed pixels. In summary, the CCFI index can be applied, under certain conditions, to coarse spatial resolution data to minimize confounding factors due to the spatial variability of canopy structure, and it is expected to be suitable for applications assessing vegetation function in future Earth Observations in the fluorescence era.…”

Section: Discussionmentioning

confidence: 99%

Variability of sun‐induced chlorophyll fluorescence according to stand age‐related processes in a managed loblolly pine forest

Colombo

Celesti

Bianchi

et al. 2018

Global Change Biology

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Leaf fluorescence can be used to track plant development and stress, and is considered the most direct measurement of photosynthetic activity available from remote sensing techniques. Red and far-red sun-induced chlorophyll fluorescence (SIF) maps were generated from high spatial resolution images collected with the HyPlant airborne spectrometer over even-aged loblolly pine plantations in North Carolina (United States). Canopy fluorescence yield (i.e., the fluorescence flux normalized by the light absorbed) in the red and far-red peaks was computed. This quantifies the fluorescence emission efficiencies that are more directly linked to canopy function compared to SIF radiances. Fluorescence fluxes and yields were investigated in relation to tree age to infer new insights on the potential of those measurements in better describing ecosystem processes. The results showed that red fluorescence yield varies with stand age. Young stands exhibited a nearly twofold higher red fluorescence yield than mature forest plantations, while the far-red fluorescence yield remained constant. We interpreted this finding in a context of photosynthetic stomatal limitation in aging loblolly pine stands. Current and future satellite missions provide global datasets of SIF at coarse spatial resolution, resulting in intrapixel mixture effects, which could be a confounding factor for fluorescence signal interpretation. To mitigate this effect, we propose a surrogate of the fluorescence yield, namely the Canopy Cover Fluorescence Index (CCFI) that accounts for the spatial variability in canopy structure by exploiting the vegetation fractional cover. It was found that spatial aggregation tended to mask the effective relationships, while the CCFI was still able to maintain this link. This study is a first attempt in interpreting the fluorescence variability in aging forest stands and it may open new perspectives in understanding long-term forest dynamics in response to future climatic conditions from remote sensing of SIF.

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Section: Discussionmentioning

confidence: 99%

Variability of sun‐induced chlorophyll fluorescence according to stand age‐related processes in a managed loblolly pine forest

Colombo

Celesti

Bianchi

et al. 2018

Global Change Biology

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“…Overall, our results indicate that leaf level correlations observed over diurnal time scales may not be present in seasonal trends, where longer term changes in plant pigments, temperature and irradiance become influential. However, the extent to which the observed leaf level correlations can be scaled to the top of canopy (TOC) using, for instance, a combination of an airborne variant of LIFT [49,50] and canopy radiative transfer modelling [51,52], requires further investigation. At TOC we would expect lower SIF red due to reabsorption by canopy elements containing PAR absorbing pigments [53].…”

Section: Discussionmentioning

confidence: 99%

Do Daily and Seasonal Trends in Leaf Solar Induced Fluorescence Reflect Changes in Photosynthesis, Growth or Light Exposure?

et al. 2017

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Solar induced chlorophyll fluorescence (SIF) emissions of photosynthetically active plants retrieved from space-borne observations have been used to improve models of global primary productivity. However, the relationship between SIF and photosynthesis in diurnal and seasonal cycles is still not fully understood, especially at large spatial scales, where direct measurements of photosynthesis are unfeasible. Motivated by up-scaling potential, this study examined the diurnal and seasonal relationship between SIF and photosynthetic parameters measured at the level of individual leaves. We monitored SIF in two plant species, avocado (Persea Americana) and orange jasmine (Murraya paniculatta), throughout 18 diurnal cycles during the Southern Hemisphere spring, summer and autumn, and compared them with simultaneous measurements of photosynthetic yields, and leaf and global irradiances. Results showed that at seasonal time scales SIF is principally correlated with changes in leaf irradiance, electron transport rates (ETR) and constitutive heat dissipation (YNO; p < 0.001). Multiple regression models of correlations between photosynthetic parameters and SIF at diurnal time scales identified leaf irradiance as the principle predictor of SIF (p < 0.001). Previous studies have identified correlations between photosynthetic yields, ETR and SIF at larger spatial scales, where heterogeneous canopy architecture and landscape spatial patterns influence the spectral and photosynthetic measurements. Although this study found a significant correlation between leaf-measured YNO and SIF, future dedicated up-scaling experiments are required to elucidate if these observations are also found at larger spatial scales.

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“…The basic principle is that SIF-photosynthesis mechanisms are first calculated at the leaf scale and then propagated throughout the canopy. Based on this principle, similar SIF leaf-to-canopy mechanisms have been recently introduced into even more advanced RTMs that explicitly account for canopy structure, such as DART [18] and FLIGHT [19].…”

Section: Introductionmentioning

confidence: 99%

SCOPE-Based Emulators for Fast Generation of Synthetic Canopy Reflectance and Sun-Induced Fluorescence Spectra

et al. 2017

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Progress in advanced radiative transfer models (RTMs) led to an improved understanding of reflectance (R) and sun-induced chlorophyll fluorescence (SIF) emission throughout the leaf and canopy. Among advanced canopy RTMs that have been recently modified to deliver SIF spectral outputs are the energy balance model SCOPE and the 3D models DART and FLIGHT. The downside of these RTMs is that they are computationally expensive, which makes them impractical in routine processing, such as scene generation and retrieval applications. To bypass their computational burden, a computationally effective technique has been proposed by only using a limited number of model runs, called emulation. The idea of emulation is approximating the original RTM by a surrogate machine learning model with low computation time. However, a concern is whether the emulator reaches sufficient accuracy. To this end, we analyzed key aspects of emulator development that may impact the precision of emulating SCOPE-like R and SIF spectra, being: (1) type of machine learning, (2) type of dimensionality reduction (DR) method, and (3) number of components and lookup table (LUT) size. The machine learning family of Gaussian processes regression and neural networks were found best suited to function as emulators. The classical principal component analysis (PCA) remains a robust DR method, but the number of components needs to be optimized depending on the complexity of the spectral data. Based on a small Latin hypercube sampling LUT of 500 samples (70% used for training) covering a selection of SCOPE input variables, the best-performing emulators can reconstruct any combination for the selected SCOPE input variables with relative errors along the spectral range below 2% for R and 4% for SIF. That is sufficient for a precise reconstruction for the large majority of possible combinations, and errors can be further reduced when increasing LUT size for training. As a proof of concept, we imported the best-performing emulators into a newly developed Automated Scene Generator Module (A-SGM) to generate a R and SIF synthetic scene of a vegetated surface. Using emulators as alternative of SCOPE reduced the processing time from the order of days to the order of minutes while preserving sufficient accuracy.

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DART: Recent Advances in Remote Sensing Data Modeling With Atmosphere, Polarization, and Chlorophyll Fluorescence

Cited by 155 publications

References 35 publications

Variability of sun‐induced chlorophyll fluorescence according to stand age‐related processes in a managed loblolly pine forest

Variability of sun‐induced chlorophyll fluorescence according to stand age‐related processes in a managed loblolly pine forest

Do Daily and Seasonal Trends in Leaf Solar Induced Fluorescence Reflect Changes in Photosynthesis, Growth or Light Exposure?

SCOPE-Based Emulators for Fast Generation of Synthetic Canopy Reflectance and Sun-Induced Fluorescence Spectra

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