SMOS L-VOD Retrieved by Level 2 Algorithm and its Correlation With GEDI LIDAR Products

In this article, L-band vegetation optical depth (L-VOD) retrieved by Soil Moisture and Ocean Salinity (SMOS) in four large continents is compared against vegetation parameters (RH100 and PAI) retrieved by Global Ecosystem Dynamics Investigation (GEDI) LIDAR instrument, recently launched by NASA. In...

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Autores principales: Cristina Vittucci, Leila Guerriero, Paolo Ferrazzoli, Philippe Richaume, Yann H. Kerr
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Lenguaje:EN
Publicado: IEEE 2021
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Acceso en línea:https://doaj.org/article/5f5d4d646d62428180aeaedcb26ea06a
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spelling oai:doaj.org-article:5f5d4d646d62428180aeaedcb26ea06a2021-12-03T00:00:18ZSMOS L-VOD Retrieved by Level 2 Algorithm and its Correlation With GEDI LIDAR Products2151-153510.1109/JSTARS.2021.3128022https://doaj.org/article/5f5d4d646d62428180aeaedcb26ea06a2021-01-01T00:00:00Zhttps://ieeexplore.ieee.org/document/9615019/https://doaj.org/toc/2151-1535In this article, L-band vegetation optical depth (L-VOD) retrieved by Soil Moisture and Ocean Salinity (SMOS) in four large continents is compared against vegetation parameters (RH100 and PAI) retrieved by Global Ecosystem Dynamics Investigation (GEDI) LIDAR instrument, recently launched by NASA. In order to manage the different spatial resolutions, GEDI parameters were averaged within SMOS pixels and a threshold to the minimum number of GEDI samples per SMOS pixel was applied. Spatial correlations between monthly averages were investigated from May 2019 to April 2020. For continents mostly covered by tropical vegetation (Africa and South America), the Pearson correlation coefficients between L-VOD and RH100 are higher than 0.8 in all months of the year. Conversely, seasonal effects are observed in North America and Asia, producing a lower correlation in colder months. RMS differences between L-VODs retrieved by SMOS and the ones obtained using a linear regression over RH100 are lower than 0.2 for all cases, and close to 0.1 for most cases. Using PAI in place of RH100 slightly lower spatial correlations are generally achieved. Overall, the obtained results confirm the good potential of L-VOD to monitor vegetation height in different environments.Cristina VittucciLeila GuerrieroPaolo FerrazzoliPhilippe RichaumeYann H. KerrIEEEarticleLIDARmicrowave radiometryvegetation heightvegetation optical depthOcean engineeringTC1501-1800Geophysics. Cosmic physicsQC801-809ENIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 14, Pp 11870-11878 (2021)
institution DOAJ
collection DOAJ
language EN
topic LIDAR
microwave radiometry
vegetation height
vegetation optical depth
Ocean engineering
TC1501-1800
Geophysics. Cosmic physics
QC801-809
spellingShingle LIDAR
microwave radiometry
vegetation height
vegetation optical depth
Ocean engineering
TC1501-1800
Geophysics. Cosmic physics
QC801-809
Cristina Vittucci
Leila Guerriero
Paolo Ferrazzoli
Philippe Richaume
Yann H. Kerr
SMOS L-VOD Retrieved by Level 2 Algorithm and its Correlation With GEDI LIDAR Products
description In this article, L-band vegetation optical depth (L-VOD) retrieved by Soil Moisture and Ocean Salinity (SMOS) in four large continents is compared against vegetation parameters (RH100 and PAI) retrieved by Global Ecosystem Dynamics Investigation (GEDI) LIDAR instrument, recently launched by NASA. In order to manage the different spatial resolutions, GEDI parameters were averaged within SMOS pixels and a threshold to the minimum number of GEDI samples per SMOS pixel was applied. Spatial correlations between monthly averages were investigated from May 2019 to April 2020. For continents mostly covered by tropical vegetation (Africa and South America), the Pearson correlation coefficients between L-VOD and RH100 are higher than 0.8 in all months of the year. Conversely, seasonal effects are observed in North America and Asia, producing a lower correlation in colder months. RMS differences between L-VODs retrieved by SMOS and the ones obtained using a linear regression over RH100 are lower than 0.2 for all cases, and close to 0.1 for most cases. Using PAI in place of RH100 slightly lower spatial correlations are generally achieved. Overall, the obtained results confirm the good potential of L-VOD to monitor vegetation height in different environments.
format article
author Cristina Vittucci
Leila Guerriero
Paolo Ferrazzoli
Philippe Richaume
Yann H. Kerr
author_facet Cristina Vittucci
Leila Guerriero
Paolo Ferrazzoli
Philippe Richaume
Yann H. Kerr
author_sort Cristina Vittucci
title SMOS L-VOD Retrieved by Level 2 Algorithm and its Correlation With GEDI LIDAR Products
title_short SMOS L-VOD Retrieved by Level 2 Algorithm and its Correlation With GEDI LIDAR Products
title_full SMOS L-VOD Retrieved by Level 2 Algorithm and its Correlation With GEDI LIDAR Products
title_fullStr SMOS L-VOD Retrieved by Level 2 Algorithm and its Correlation With GEDI LIDAR Products
title_full_unstemmed SMOS L-VOD Retrieved by Level 2 Algorithm and its Correlation With GEDI LIDAR Products
title_sort smos l-vod retrieved by level 2 algorithm and its correlation with gedi lidar products
publisher IEEE
publishDate 2021
url https://doaj.org/article/5f5d4d646d62428180aeaedcb26ea06a
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