Articles | Volume 15, issue 1
https://doi.org/10.5194/essd-15-345-2023
https://doi.org/10.5194/essd-15-345-2023
Data description paper
 | 
19 Jan 2023
Data description paper |  | 19 Jan 2023

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

Ricardo Dalagnol, Lênio Soares Galvão, Fabien Hubert Wagner, Yhasmin Mendes de Moura, Nathan Gonçalves, Yujie Wang, Alexei Lyapustin, Yan Yang, Sassan Saatchi, and Luiz Eduardo Oliveira Cruz Aragão

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Cited articles

Anderson, L. O., Ribeiro Neto, G., Cunha, A. P., Fonseca, M. G., Mendes de Moura, Y., Dalagnol, R., Wagner, F. H., and Aragão, L.: Vulnerability of Amazonian forests to repeated droughts, Philos. T. Roy. Soc. B, 373, 20170411, https://doi.org/10.1098/rstb.2017.0411, 2018. 
Bhandari, S., Phinn, S., and Gill, T.: Assessing viewing and illumination geometry effects on the MODIS vegetation index (MOD13Q1) time series: implications for monitoring phenology and disturbances in forest communities in Queensland, Australia, Int. J. Remote Sens., 32, 7513–7538, https://doi.org/10.1080/01431161.2010.524675, 2011. 
Bi, J., Knyazikhin, Y., Choi, S., Park, T., Barichivich, J., Ciais, P., Fu, R., Ganguly, S., Hall, F., Hilker, T., Huete, A., Jones, M., Kimball, J., Lyapustin, A. I., Mõttus, M., Nemani, R. R., Piao, S., Poulter, B., Saleska, S. R., Saatchi, S. S., Xu, L., Zhou, L., and Myneni, R. B.: Sunlight mediated seasonality in canopy structure and photosynthetic activity of Amazonian rainforests, Environ. Res. Lett., 10, 064014, https://doi.org/10.1088/1748-9326/10/6/064014, 2015. 
Bontempo, E., Dalagnol, R., Ponzoni, F., and Valeriano, D.: Adjustments to SIF aid the interpretation of drought responses at the caatinga of Northeast Brazil, Remote Sens., 12, 1–29, https://doi.org/10.3390/rs12193264, 2020. 
Chen, J. M., Liu, J., Leblanc, S. G., Lacaze, R., and Roujean, J. L.: Multi-angular optical remote sensing for assessing vegetation structure and carbon absorption, Remote Sens. Environ., 84, 516–525, https://doi.org/10.1016/S0034-4257(02)00150-5, 2003. 
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The AnisoVeg dataset brings 22 years of monthly satellite data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor for South America at 1 km resolution aimed at vegetation applications. It has nadir-normalized data, which is the most traditional approach to correct satellite data but also unique anisotropy data with strong biophysical meaning, explaining 55 % of Amazon forest height. We expect this dataset to help large-scale estimates of vegetation biomass and carbon.
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