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Sentinel-1 sensitivity to soil moisture at high incidence angle and the impact on retrieval over seasonal crops / Davide Palmisano in IEEE Transactions on geoscience and remote sensing, Vol 59 n° 9 (September 2021)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > Vol 59 n° 9 (September 2021) . - pp 7308 - 7321 Titre : Sentinel-1 sensitivity to soil moisture at high incidence angle and the impact on retrieval over seasonal crops Type de document : Article/Communication Auteurs : Davide Palmisano, Auteur ; Francesco Mattia, Auteur ; Anna Balenzano, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 7308 - 7321 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] analyse de sensibilité [Termes IGN] angle d'incidence [Termes IGN] bande C [Termes IGN] carte agricole [Termes IGN] Castille-et-Leon (Espagne) [Termes IGN] corrélation temporelle [Termes IGN] cultures [Termes IGN] humidité du sol [Termes IGN] image Sentinel-SAR [Termes IGN] Pouilles (Italie) [Termes IGN] réseau hydrographique [Termes IGN] rétrodiffusion [Termes IGN] transfert radiatif Résumé : (auteur) Approximately, 30% of the Sentinel-1 (S-1) swath over land is imaged with incidence angles higher than 40°. Still, the interplay among the scattering mechanisms taking place at such a high incidence and their implications on the backscatter information content is often disregarded. This article investigates, through an experimental and numerical study, the S-1 sensitivity to the surface soil moisture (SSM) over agricultural fields observed at low (~33°) and high (~43°) incidence angles and quantifies the impact of the incidence angle on the SSM retrieval accuracy. The study sites are the Apulian Tavoliere (Italy) and REd de MEDición de la HUmedad del Suelo (REMEDHUS) (Spain), which are both instrumented with a hydrologic network continuously measuring SSM. At low incidence angles, results confirm that for crops such as wheat and barley, dominated in C-band by surface scattering, there exists a good sensitivity of S-1 VV to SSM. At high incidence angles, the sensitivity to SSM holds through the combination of the soil attenuated and double bounce scattering. Conversely, over crops dominated by volume scattering, such as sugar beet, the S-1 VV signal is not correlated with the in situ SSM observations, neither at low nor at high incidence. For all the crops, the sensitivity of S-1 to SSM in VH is found significantly lower than in VV. The impact of the incidence angle on the SSM retrieval has been studied with a recursive algorithm based on a short-term change detection approach. An upper and lower bounds for the worsening of the S-1 VV retrieval performance at far versus near range observations have been estimated. In the worst-case scenario, the root mean square error (RMSE) increases from ~0.056 m 3 /m 3 , at low incidence, to ~0.071 m 3 /m 3 , at high incidence. The mechanism that lowers the retrieval accuracy at high incidence angles is further investigated in the synthetic experiment and its impact on the RMSE is estimated in terms of the volume scattering contribution. Numéro de notice : A2021-646 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2020.3033887 Date de publication en ligne : 10/11/2020 En ligne : https://doi.org/10.1109/TGRS.2020.3033887 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98351 [article]

A time-series approach to estimating soil moisture from vegetated surfaces using L-band radar backscatter / Jeffrey D. Ouellette in IEEE Transactions on geoscience and remote sensing, vol 55 n° 6 (June 2017)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 55 n° 6 (June 2017) . - pp 3186 - 3193 Titre : A time-series approach to estimating soil moisture from vegetated surfaces using L-band radar backscatter Type de document : Article/Communication Auteurs : Jeffrey D. Ouellette, Auteur ; Joel T. Johnson, Auteur ; Anna Balenzano, Auteur ; et al., Auteur Année de publication : 2017 Article en page(s) : pp 3186 - 3193 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] couvert végétal [Termes IGN] détection de changement [Termes IGN] humidité du sol [Termes IGN] image radar [Termes IGN] radiométrie [Termes IGN] rétrodiffusion [Termes IGN] série temporelle [Termes IGN] traitement d'image radar Résumé : (Auteur) Many previous studies have shown the sensitivity of radar backscatter to surface soil moisture content, particularly at L-band. Moreover, the estimation of soil moisture from radar for bare soil surfaces is well-documented, but estimation underneath a vegetation canopy remains unsolved. Vegetation significantly increases the complexity of modeling the electromagnetic scattering in the observed scene, and can even obstruct the contributions from the underlying soil surface. Existing approaches to estimating soil moisture under vegetation using radar typically rely on a forward model to describe the backscattered signal and often require that the vegetation characteristics of the observed scene be provided by an ancillary data source. However, such information may not be reliable or available during the radar overpass of the observed scene (e.g., due to cloud coverage if derived from an optical sensor). Thus, the approach described herein is an extension of a change-detection method for soil moisture estimation, which does not require ancillary vegetation information, nor does it make use of a complicated forward scattering model. Novel modifications to the original algorithm include extension to multiple polarizations and a new technique for bounding the radar-derived soil moisture product using radiometer-based soil moisture estimates. Soil moisture estimates are generated using data from the Soil Moisture Active/Passive (SMAP) satellite-borne radar and radiometer data, and are compared with up-scaled data from a selection of in situ networks used in SMAP validation activities. These results show that the new algorithm can consistently achieve rms errors less than 0.07 m3/m3 over a variety land cover types. Numéro de notice : A2017-475 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2017.2663768 En ligne : https://doi.org/10.1109/TGRS.2017.2663768 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86400 [article]