Multi-Temporal Speckle Filtering of Polarimetric P-Band SAR Data over Dense Tropical Forests: Study Case in French Guiana for the BIOMASS Mission
Abstract
:1. Introduction
2. Data Selection
3. Multi Temporal and Multi Channel Speckle Filter
3.1. Intensity-Based Multi-Temporal Filtering Techniques
3.2. Extension to SLC Data
3.2.1. General Form
3.2.2. Application to Polarimetric SAR Data
4. Results
4.1. Implementation
4.2. Preservation of the Average
4.3. Analysis in Terms of Speckle Reduction
4.3.1. The Equivalent Number of Looks (ENL)
4.3.2. Estimation of the Polarimetric Orientation Angle ()
5. Discussion
6. Conclusions and Further Prospects
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Abbreviations
MCMT | Multi Channel and Multi Temporal |
POA | Polarization Orientation Angle |
AGB | Above Ground Biomass |
DEM | Digital Elevation Model |
SRTM | Shuttle Radar Topography Mission |
ENL | Equivalent Number of Looks |
RMSE | Root Mean Squared Error |
SLC | Single Look Complex |
References
- D’Alessandro, M.M.; Tebaldini, S.; Quegan, S.; Soja, M.; Ulander, L.M.H. Interferometric Ground Notching of SAR Images for Estimating Forest Above Ground Biomass. In Proceedings of the IGARSS 2018—2018 IEEE International Geoscience and Remote Sensing Symposium, Valencia, Spain, 22–27 July 2018; pp. 8798–8800. [Google Scholar]
- Global Climat Observing System (GCOS). Systematic Observation Requirements for sAtellite-Based Products for Climate, Supplemental Details to the Satellite-Based Component of the Implemention Plan for the Global Observing System for Climate in Support of the UNFCCC. WMO/TD No 1338; 2006. Available online: https://climate.esa.int/sites/default/files/gcos-154.pdf (accessed on 20 September 2020).
- Hamadi, A.; Villard, L.; Borderies, P.; Albinet, C.; Koleck, T.; Le Toan, T. Comparative Analysis of Temporal Decorrelation at P-Band and Low L-Band Frequencies Using a Tower-Based Scatterometer Over a Tropical Forest. IEEE Geosci. Remote Sens. Lett. 2017, 14, 1918–1922. [Google Scholar] [CrossRef]
- Agency, E.S. Biomass Coreh2o Premier: Report for Mission Selection. An Earth Explorer to Observe Forest Biomass; European Space Agency (ESA): Paris, France, 2012. [Google Scholar]
- Lee, J.-S.; Schuler, D.L.; Ainsworth, T.L. Polarimetric SAR data compensation for terrain azimuth slope variation. IEEE Trans. Geosci. Remote Sens. 2000, 38, 2153–2163. [Google Scholar]
- Lee, J.-S.; Jurkevich, L.; Dewaele, P.; Wambacq, P.; Oosterlinck, A. Speckle filtering of synthetic aperture radar images: A review. Remote Sens. Rev. 1994, 8, 313–340. [Google Scholar] [CrossRef]
- Dubois-Fernandez, P.; Le Toan, T.; Chave, J.; Blanc, J.; Daniel, S.; Oriot, H.; Arnaubec, A.; Rejou-Mechain, M.; Villard, L.; Lasne, Y.; et al. Technical Assistance for the Development of Airbone SAR and Geophysical Measurments during the TropiSAR 2009 Experiment (Report); European Space Agency: Paris, France, 2011. [Google Scholar] [CrossRef]
- Hamadi, A.; Borderies, P.; Albinet, C.; Koleck, T.; Villard, L.; Minh, D.H.T.; Le Toan, T.; Burban, B. Temporal coherence of tropical forests at P-band: Dry and rainy seasons. IEEE Geosci. Remote Sens. Lett. 2015, 12, 557–561. [Google Scholar] [CrossRef]
- Villard, L.; Le Toan, T. Relating P-Band SAR Intensity to Biomass for Tropical Dense Forest in Hilly Terrain: γ0 et t0? IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 2015, 8, 214–223. [Google Scholar] [CrossRef]
- Simonetto, L.P.E. Effect of scale on the correlation between topography and canopy elevations in an airborne InSAR product over Amazonia. Procedia Technol. 2014, 16, 180–185. [Google Scholar] [CrossRef] [Green Version]
- Labriere, N.; Tao, S.; Chave, J.; Scipal, K.; Le Toan, T.; Abernethy, K.; Alonso, A.; Barbier, N.; Bissiengou, P.; Casal, T.; et al. In Situ Reference Datasets from the TropiSAR and AfriSAR Campaigns in Support of Upcoming Spaceborne Biomass Missions. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 2018, 11, 3617–3627. [Google Scholar] [CrossRef]
- Chave, J.; Réjou-Méchain, M.; Búrquez, A.; Chidumayo, E.; Colgan, M.S.; Delitti, W.B.; Duque, A.; Eid, T.; Fearnside, P.M.; Goodman, R.C.; et al. Improved allometric models to estimate the aboveground biomass of tropical trees. Glob. Chang. Biol. 2014, 20, 3177–3190. [Google Scholar] [CrossRef] [PubMed]
- Yu, S.Q.J. Filtering of Multichannel SAR Images. IEEE Trans. Geosci. Remote Sens. 2001, 39, 2373–2379. [Google Scholar]
- Lee, J.S.; Grunes, M.R.; De Grandi, G. Polarimetric SAR speckle filtering and its impact on classification. In Proceedings of the IGARSS’97, Singapore, 3–8 August 1997; pp. 1038–1040. [Google Scholar]
- Goodman, J. Some fundamental properties of speckle. J. Opt. Soc. Am. 1976, 66, 1145–1150. [Google Scholar] [CrossRef]
- Le Toan, T.; Floury, N. On the Retrieval of Forest Biomass from SAR Data. Int. J. Remote Sens. 1994. [Google Scholar] [CrossRef]
- Garestier, F.; Le Toan, T. Estimation of a forest backscatter profile at P-band using Single Baseline Pol-InSAR. IEEE Trans. Geosci. Remote Sens. 2010, 48, 3340–3348. [Google Scholar] [CrossRef]
- Casal, T.; Hajnsek, I.; Pardini, M.; Jager, M.; Horn, R.; Kim, J.S.; Papathanassiou, K.; Dubois-Fernandez, P.; Dupuis, X.; Wasik, V.; et al. Technical Assistance for the Development of Airborne SAR and Geophysical Measurements during the Afrisar Experiment—Deliverable DD-4—Final Report; European Space Agency (ESA): Paris, France, 2016. [Google Scholar] [CrossRef]
16 ROIs | a | b | RMSE | ||
REF | 5.79 | −25.51 | 0.78 | 21.84 | 5.13 |
MCMT | 5.97 | −26.0 | 0.76 | 19.37 | 5.33 |
84 ROIs | a | b | RMSE | ||
REF | 5.65 | −25.12 | 0.54 | 33.63 | 27.14 |
MCMT | 5.84 | −25.62 | 0.54 | 33.84 | 32.53 |
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Gelas, C.; Villard, L.; Ferro-Famil, L.; Polidori, L.; Koleck, T.; Daniel, S. Multi-Temporal Speckle Filtering of Polarimetric P-Band SAR Data over Dense Tropical Forests: Study Case in French Guiana for the BIOMASS Mission. Remote Sens. 2021, 13, 142. https://doi.org/10.3390/rs13010142
Gelas C, Villard L, Ferro-Famil L, Polidori L, Koleck T, Daniel S. Multi-Temporal Speckle Filtering of Polarimetric P-Band SAR Data over Dense Tropical Forests: Study Case in French Guiana for the BIOMASS Mission. Remote Sensing. 2021; 13(1):142. https://doi.org/10.3390/rs13010142
Chicago/Turabian StyleGelas, Colette, Ludovic Villard, Laurent Ferro-Famil, Laurent Polidori, Thierry Koleck, and Sandrine Daniel. 2021. "Multi-Temporal Speckle Filtering of Polarimetric P-Band SAR Data over Dense Tropical Forests: Study Case in French Guiana for the BIOMASS Mission" Remote Sensing 13, no. 1: 142. https://doi.org/10.3390/rs13010142