SMOS Level 2 Retrieval Algorithm Over Forests: Description and Generation of Global Maps

Rahmoune, R.; Ferrazzoli, P.; Kerr, Yann H.; Richaume, Philippe

doi:10.1109/jstars.2013.2256339

Cited by 61 publications

(42 citation statements)

References 36 publications

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“…4.1 were obtained with SMOS-IC L-VOD, only the latter is considered in the following. The relationship between tree height and IC L-VOD was found to be close to linear with a high Pearson 5 correlation coefficient (R = 0.87, Table 1), in agreement with previous findings using SMOS L2 data Rahmoune et al (2013).…”

Section: Comparison Of Smos Ic L-vod To Other Data Setssupporting

confidence: 91%

The high sensitivity of SMOS L-Band vegetation optical depth to biomass

Rodriguez‐fernandez¹,

Mialon²,

Mermoz³

et al. 2018

Preprint

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Abstract. The vegetation optical depth (VOD) measured at microwave frequencies is related to the vegetation water content and provides information complementary to visible/infra-red vegetation indices. This study is devoted to the characterisation of a new VOD data set obtained from SMOS (Soil Moisture and Ocean Salinity) satellite observations at L-band (1.4 GHz).Three different SMOS L-band VOD (L-VOD) data sets (SMOS Level 2, Level 3 and SMOS-IC) were compared with data sets on tree height, visible/infra-red indexes (NDVI, EVI), cumulated precipitation, and above ground biomass (AGB) for the 5 African continent. For all relationships, SMOS-IC showed the lowest dispersion and highest correlation. Overall, we found a strong (R > 0.85) correlation with no clear sign of saturation between L-VOD and four AGB data sets. The relationship linking L-VOD to tree height (R = 0.87) and Baccini's AGB (R = 0.94) was strong and linear. The relationships between L-VOD and three other AGB data sets were linear per land cover class, but with a changing slope depending on the land cover type. For low vegetation classes, the annual mean of L-VOD spans a range from 0 to 0.7 and it is linearly correlation with the amount of 10 the average annual precipitations. SMOS L-VOD showed a higher sensitivity to AGB as compared to NDVI and K/X/C-VOD (VOD measured, respectively, at 19, 10.7, and 6.9 GHz). The results showed that although the spatial resolution of L-VOD is coarse (∼ 40 km), the high temporal frequency and sensitivity to AGB makes SMOS L-VOD a very promising index for large scale monitoring of the vegetation status, in particular biomass.

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Section: Comparison Of Smos Ic L-vod To Other Data Setssupporting

confidence: 91%

The high sensitivity of SMOS L-Band vegetation optical depth to biomass

Rodriguez‐fernandez¹,

Mialon²,

Mermoz³

et al. 2018

Preprint

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“…The r 2 correlation coefficient computed for Africa is slightly lower than for South America, probably due to the heterogeneity of the African landscape compared to the South American one, with the former characterized by high fragmentation of land cover types and presence of several water bodies. We remark that in the previous versions of the algorithm, the water presence caused retrieval failures in extended areas of Congo (Rahmoune, Ferrazzoli, Kerr, & Richaume, 2013). Discrepancies in New Guinea, already observed in Fig.…”

Section: Comparison With Forest Heightmentioning

confidence: 58%

SMOS retrieval over forests: Exploitation of optical depth and tests of soil moisture estimates

Vittucci

Ferrazzoli

Kerr

et al. 2016

Remote Sensing of Environment

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This research aims to test data obtained by level 2 retrieval algorithm of SMOS over land, in order to provide information regarding vegetation and soil moisture over forested areas. Results presented in this paperwere obtained using the last 620 version of the algorithm. The correlation between the new vegetation optical depth (VOD) product and the height of the forest estimated by ICES at GLAS lidar on a global scale is investigated. Over South American and African forests a good correspondence between the two variables is observed, with saturation occurring above about 30 m height. Moreover, the comparison between the VOD and the height of the forest shows good spatial and temporal stability, and the r2 correlation coefficient is within a 0.59–0.69 range. Conversely, discrepancies are observed in some Indonesian islands, particularly New Guinea. Over specific areas, the trends vs. forest height obtained with SMOS VOD are compared with the corresponding trends of AMSR-E VOD. Results are also validated at country-level scale. To this aim, accurate estimates of forest biomass derived from airborne lidar over selected forests of Peru, Columbia and Panama are used. Finally, the soil moisture retrieved over forests is investigated, reporting continental maps for Tropical areas and comparisons with ground measurements in selected forests of the US. Continental maps obtained with the new level 2 V620 algorithm cover almost all forest areas, and show seasonal variations which are dependent on climatic zones. Comparisons between soil moisture retrievals in forests and ground measurements of the US SCAN network produce worseRMSE valueswith respect to lowvegetation areas. Significant improvements however are achieved after averaging among close nodes of the ground network

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“…For the specific case of developed forests, the optical depth is relatively high (in the range 0.6-1.2) which makes the retrieval of SM difficult. In fact, for equal to 0.6, the sensitivity of brightness temperature to variations of SM ( ) is in the range ), depending on angle and polarization [3]. An SM variation equal to corresponds to a brightness temperature variation in a range of 2.4-3.0 K, which can be comparable with the noise in the measurements.…”

Section: Introductionmentioning

confidence: 83%

SMOS Retrieval Results Over Forests: Comparisons With Independent Measurements

Rahmoune

Ferrazzoli

Singh

et al. 2014

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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This paper shows results obtained by using SMOS Level 2 retrieval algorithm, run at prototype stage, over forests. For each SMOS pixel, the algorithm estimates the soil moisture (SM) and the vegetation optical depth (τ). Average τ values retrieved in 4 days of July 2011 over forest pixels are shown and compared against forest height estimated by GLAS Lidar on board ICEsat satellite. Results of the comparison show a significantly increasing trend of τ with respect to forest height. For each 1-m interval of forest height estimated by Lidar, the standard deviation of optical depth is slightly higher than 0.1. The analysis is made again considering forest τ retrieved in 4 days of February, May, and November 2011, and it is observed that seasonal effects over optical depth are low. As an insight, it is shown that the increasing trend is still observed after subdividing world forests into Coniferous, Deciduous Broadleaf, and Evergreen Broadleaf. Comparisons with independent information about biomass are also shown at regional level for the U.S. The increasing trend is still observed, but with a reduced range of values. For SM, 14 nodes of the SCAN/SNOTEL network in the U.S. are considered. Over 2 years of data, retrieved values of SM are compared against ground measurements. Obtained values of correlation coefficient, rms error, and bias are reported.

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SMOS Level 2 Retrieval Algorithm Over Forests: Description and Generation of Global Maps

Cited by 61 publications

References 36 publications

The high sensitivity of SMOS L-Band vegetation optical depth to biomass

The high sensitivity of SMOS L-Band vegetation optical depth to biomass

SMOS retrieval over forests: Exploitation of optical depth and tests of soil moisture estimates

SMOS Retrieval Results Over Forests: Comparisons With Independent Measurements

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