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@Article{BontempoDalaPonzVale:2020:AdSiAi,
               author = "Bontempo, Edgard and Dalagnol da Silva, Ricardo and Ponzoni, 
                         Fl{\'a}vio Jorge and Valeriano, Dalton de Morisson",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de 
                         Pesquisas Espaciais (INPE)} and {Instituto Nacional de Pesquisas 
                         Espaciais (INPE)}",
                title = "Adjustments to sif aid the interpretation of drought responses at 
                         the caatinga of Northeast Brazil",
              journal = "Remote Sensing",
                 year = "2020",
               volume = "12",
               number = "19",
                pages = "1--29",
                month = "Oct",
             keywords = "chlorophyll fluorescence, SIF, drought, spectral vegetation 
                         indices, Caatinga, GOME-2, abiotic stress.",
             abstract = "Sun-Induced chlorophyll Fluorescence (SIF) relates directly to 
                         photosynthesis yield and stress but there are still uncertainties 
                         in its interpretation. Most of these uncertainties concern the 
                         influences of the emitting vegetations structure (e.g., leaf 
                         angles, leaf clumping) and biochemistry (e.g., chlorophyll 
                         content, other pigments) on the radiative transfer of fluorescent 
                         photons. The Caatinga is a large region in northeast Brazil of 
                         semiarid climate and heterogeneous vegetation, where such 
                         biochemical and structural characteristics can vary greatly even 
                         within a single hectare. With this study we aimed to characterize 
                         eleven years of SIF seasonal variation from Caatinga vegetation 
                         (2007 to 2017) and to study its responses to a major drought in 
                         2012. Orbital SIF data from the instrument GOME-2 was used along 
                         with MODIS MAIAC EVI and NDVI. Environmental data included 
                         precipitation rate (TRMM), surface temperature (MODIS) and soil 
                         moisture (ESA CCI). To support the interpretation of SIF responses 
                         we used red and far-red SIF adjusted by the Suns zenith angle 
                         (SIF-SZA) and by daily Photosynthetically Active Radiation (dSIF). 
                         Furthermore, we also adjusted SIF through two contrasting 
                         formulations using NDVI data as proxy for structure and 
                         biochemistry, based on previous leaf-level and landscape level 
                         studies: SIF-Yield and SIF-Prod. Data was tested with time-series 
                         decomposition, rank correlation, spatial correlation and Linear 
                         Mixed Models (LMM). Results show that GOME-2 SIF and adjusted SIF 
                         formulations responded consistently to the observed environmental 
                         variation and showed a marked decrease in SIF emissions in 
                         response to a 2012 drought that was generally larger than the 
                         corresponding NDVI and EVI decreases. Drought sensitivity of SIF, 
                         as inferred from LMM slopes, was correlated to land cover at 
                         different regions of the Caatinga. This is the first study to show 
                         correlation between landscape-level SIF and an emergent property 
                         of ecosystems (i.e., resilience), showcasing the value of remotely 
                         sensed fluorescence for ecological studies.",
                  doi = "10.3390/rs12193264",
                  url = "http://dx.doi.org/10.3390/rs12193264",
                 issn = "2072-4292",
             language = "en",
           targetfile = "bontempo2020.pdf",
        urlaccessdate = "28 nov. 2020"
}


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