AnisoVeg: anisotropy and nadir-normalized MODIS multi-angle implementation atmospheric correction (MAIAC) datasets for satellite vegetation studies in South America

dc.contributor.authorDalagnol, Ricardo
dc.contributor.authorGalvão, Lênio Soares
dc.contributor.authorWagner, Fabien Hubert
dc.contributor.authorMoura, Yhasmin Mendes
dc.contributor.authorGonçalves, Nathan
dc.contributor.authorWang, Yujie
dc.contributor.authorLyapustin, Alexei
dc.contributor.authorYang, Yan
dc.contributor.authorSaatchi, Sassan
dc.contributor.authorAragão, Luiz Eduardo Oliveira Cruz
dc.date.accessioned2022-09-19T15:23:21Z
dc.date.available2022-09-19T15:23:21Z
dc.date.issued2023-01-19
dc.description.abstractThe 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 (R²=0.55). 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 https://doi.org/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 https://doi.org/10.5281/zenodo.3878879 (Dalagnol et al., 2022).en_US
dc.description.sponsorshipR.D. was supported by Sao Paulo Research Foundation (FAPESP) grants 2015/22987-7 and 450 2019/21662-8. F.W. was supported by FAPESP grant 2015/50484-0. Part of this work was carried 451 out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the 452 National Aeronautics and Space Administration (NASA). The funders had no role in the study 453 design, data collection and analysis, including the decision to publish or prepare the manuscript. 454 We thank the MODIS MAIAC team from NASA for providing the freely available MODIS (MAIAC) daily dataset.en_US
dc.description.urihttps://essd.copernicus.org/articles/15/345/2023/en_US
dc.format.extent14 pagesen_US
dc.genrejournal articlesen_US
dc.identifierdoi:10.13016/m2y6gc-4rnu
dc.identifier.citationDalagnol, R., et al. "AnisoVeg: anisotropy and nadir-normalized MODIS multi-angle implementation atmospheric correction (MAIAC) datasets for satellite vegetation studies in South America" Earth Syst. Sci. Data, 15 (19 Jan 2023): 345–358. https://doi.org/10.5194/essd-15-345-2023, 2023.en_US
dc.identifier.urihttps://doi.org/10.5194/essd-15-345-2023
dc.identifier.urihttp://hdl.handle.net/11603/25730
dc.language.isoen_USen_US
dc.publisherCopernicusen_US
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.ispartofUMBC Joint Center for Earth Systems Technology
dc.relation.ispartofUMBC Faculty Collection
dc.rightsThis work was written as part of one of the author's official duties as an Employee of the United States Government and is therefore a work of the United States Government. In accordance with 17 U.S.C. 105, no copyright protection is available for such works under U.S. Law.en_US
dc.rightsPublic Domain Mark 1.0*
dc.rights.urihttp://creativecommons.org/publicdomain/mark/1.0/*
dc.titleAnisoVeg: anisotropy and nadir-normalized MODIS multi-angle implementation atmospheric correction (MAIAC) datasets for satellite vegetation studies in South Americaen_US
dc.typeTexten_US

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