@Article{DalagnolGWMGWLYSA:2023:AnNaMO,
               author = "Dalagnol, Ricardo and Galv{\~a}o, L{\^e}nio Soares and Wagner, 
                         Fabien Hubert and Moura, Yhasmin Mendes de and Gon{\c{c}}alves, 
                         Nathan and Wang, Yujie and Lyapustin, Alexei and Yang, Yan and 
                         Saatchi, Sassan and Arag{\~a}o, Luiz Eduardo Oliveira e Cruz de",
          affiliation = "{University of California} and {Instituto Nacional de Pesquisas 
                         Espaciais (INPE)} and {University of California} and {Remote 
                         Sensing Applied to Tropical Environments Group} and {Michigan 
                         State University} and {NASA Goddard Space Flight Center} and {NASA 
                         Goddard Space Flight Center} and {University of California} and 
                         {University of California} and {Instituto Nacional de Pesquisas 
                         Espaciais (INPE)}",
                title = "AnisoVeg: anisotropy and nadir-normalized MODIS multi-angle 
                         implementation atmospheric correction (MAIAC) datasets for 
                         satellite vegetation studies in South America",
              journal = "Earth System Science Data",
                 year = "2023",
               volume = "15",
               number = "1",
                pages = "345--358",
                month = "Jan.",
             abstract = "The AnisoVeg product consists of monthly 1 km composites of 
                         anisotropy (ANI) and nadir-normalized (NAD) surface reflectance 
                         layers obtained from the Moderate Resolution Imaging 
                         Spectroradiometer (MODIS) sensor over the entire South American 
                         continent. The satellite data were preprocessed using the 
                         multi-angle implementation atmospheric correction (MAIAC). The 
                         AnisoVeg product spans 22 years of observations (2000 to 2021) and 
                         includes the reflectance of MODIS bands 1 to 8 and two vegetation 
                         indices (VIs), namely the normalized difference vegetation index 
                         (NDVI) and enhanced vegetation index (EVI). While the NAD layers 
                         reduce the data variability added by bidirectional effects on the 
                         reflectance and VI time series, the unique ANI layers allow the 
                         use of this multi-angular data variability as a source of 
                         information for vegetation studies. The AnisoVeg product has been 
                         generated using daily MODIS MAIAC data from both Terra and Aqua 
                         satellites, normalized for a fixed solar zenith angle (SZA 45), 
                         modeled for three sensor view directions (nadir, forward, and 
                         backward scattering), and aggregated to monthly composites. The 
                         anisotropy was calculated by the subtraction of modeled backward 
                         and forward scattering surface reflectance. The release of the ANI 
                         data for open usage is novel, and the NAD data are at an advanced 
                         processing level. We demonstrate the use of such data for 
                         vegetation studies using three types of forests in the eastern 
                         Amazon with distinct gradients of vegetation structure and 
                         aboveground biomass (AGB). The gradient of AGB was positively 
                         associated with ANI, while NAD values were related to different 
                         canopy structural characteristics. This was further illustrated by 
                         the strong and significant relationship between EVIANI and forest 
                         height observations from the Global Ecosystem Dynamics 
                         Investigation (GEDI) lidar sensor considering a simple linear 
                         model (R20.55). Overall, the time series of the AnisoVeg product 
                         (NAD and ANI) provide distinct information for various 
                         applications aiming at understanding vegetation structure, 
                         dynamics, and disturbance patterns. All data, processing codes, 
                         and results are made publicly available to enable research and the 
                         extension of AnisoVeg products for other regions outside of South 
                         America. The code can be found at 10.5281/zenodo.6561351 (Dalagnol 
                         and Wagner, 2022), EVIANI and EVINAD can be found as assets in the 
                         Google Earth Engine (GEE; described in the data availability 
                         section), and the full dataset is available from the open 
                         repository 10.5281/zenodo.3878879 (Dalagnol et al., 2022).",
                  doi = "10.5194/essd-15-345-2023",
                  url = "http://dx.doi.org/10.5194/essd-15-345-2023",
                 issn = "1866-3508 and 1866-3516",
             language = "en",
           targetfile = "essd-15-345-2023.pdf",
        urlaccessdate = "01 maio 2024"
}