@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 = "04 maio 2024"
}