Performance of GNSS-R GLORI data for biomass estimation over the Landes forest

Zribi, Mehrez Guyon, Dominique Motte, Erwan Dayau, Sylvia Wigneron, Jean Pierre Baghdadi, Nicolas Pierdicca, Nazzareno

Performance of GNSS-R GLORI data for biomass estimation over the Landes forest

Zribi, Mehrez 1Guyon, Dominique 2Motte, Erwan 1Dayau, Sylvia 2Wigneron, Jean Pierre 2Baghdadi, Nicolas 3Pierdicca, Nazzareno4
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作者信息

  • 1. CNES, IRD, UPS, CESBIO,CNRS, 18 Av Edouard Belin,Bpi 2801, F-31401 Toulouse 9, France
  • 2. INRA, ISPA, F-33140 Villenave Dornon, France
  • 3. Univ Montpellier, IRSTEA, TETIS, Montpellier, France
  • 4. Sapienza Univ Rome, DIET, Via Eudossiana 18, I-00184 Rome, Italy
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Abstract

The Above-Ground Biomass (AGB) is a key parameter used for the modeling of the carbon cycle. The aim of this study is to make an experimental assessment of the sensitivity of Global Navigation Satellite System (GNSS) reflected signals to forest AGB. This is based on the analysis of the data recorded during several GLORI airborne campaigns in June and July 2015, over the Landes Forest (France). Ground truth measurements of tree height, density and diameter at breast height (DBH), as well as AGB, were carried out for 100 maritime pine forest plots of various ages. The GNSS-R data were used to obtain the right-left (Gamma(RL) and right-right (Gamma(RR)) reflectivity observables, which are geo-referenced in accordance with the known positions of relevant GPS satellites and the airborne receiver. The correlations between forest AGB and the GNSS-R observables yield the highest sensitivity at high elevation angles (70 degrees-90 degrees). In this case, for (Gamma(RL).) and the reflectivity polarization ratio (PR = Gamma(RL)/Gamma(RR)) estimated with a coherent integration time Tc = 20 ms, the coefficients of determination R-2 are equal to 0.67 and 0.51, with a sensitivity of-0.051 dB/[10(6)g (Mg) ha(-1)], and - 0.053 dB/[Mg ha(-1)], respectively. The relationships between AGB and the observables are confirmed through the use of a 5-fold cross validation approach, with several different coherent integration times.

Key words

GNSS-R/Forest/Above ground biomass/Landes forest/Maritime pine

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出版年

2019
International journal of applied earth observation and geoinformation

International journal of applied earth observation and geoinformation

SCI
ISSN:0303-2434
被引量10
参考文献量51
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