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Improved algorithms for the measurement of total precipitable water and cloud liquid water from SARAL microwave radiometer observations / Rajput Neha Mangalsinh in Marine geodesy, vol 42 n° 4 (July 2019)  

Public [article]  inMarine geodesy > vol 42 n° 4 (July 2019) . - pp 367 - 381 Titre : Improved algorithms for the measurement of total precipitable water and cloud liquid water from SARAL microwave radiometer observations Type de document : Article/Communication Auteurs : Rajput Neha Mangalsinh, Auteur ; Atul Kumar Varma, Auteur Année de publication : 2019 Article en page(s) : pp 367 - 381 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes descripteurs IGN] cryosphère [Termes descripteurs IGN] données altimétriques [Termes descripteurs IGN] hauteurs de mer [Termes descripteurs IGN] image GPM [Termes descripteurs IGN] image SSMIS [Termes descripteurs IGN] image TRMM-MI [Termes descripteurs IGN] nuage [Termes descripteurs IGN] précipitation [Termes descripteurs IGN] radiomètre à hyperfréquence [Termes descripteurs IGN] température de luminance [Termes descripteurs IGN] vapeur d'eau Résumé : (auteur) SARAL carried onboard a radar altimeter that provides very precise measurements of the sea surface height (SSH). Like other altimetric missions, SARAL carries a passive microwave radiometer (PMR) for wet tropospheric correction to SSH. In the present study, new algorithms are developed for the retrieval of cloud liquid water (CLW) and total precipitable water vapor (TPW) over the global oceans from PMR measurements of the brightness temperatures. A radiative transfer and genetic algorithm based retrieval scheme is proposed for the estimation of CLW and TPW from SARAL PMR. The comparisons of CLW from PMR with independent measurements from GPM-GMI and SSMIS within and outside ±40° latitudes show correlation (R) of 0.86 and 0.83, bias of 0.7 and −3.61 mg/cm2, and root mean square error (RMSE) of 8.42 and 8.07 mg/cm2, respectively. Similarly, TPW from PMR with GPM-GMI and SSMIS show R of 0.99 and 0.98, bias of −0.04 and −0.03 g/cm2 and RMSE of 0.17 and 0.17 g/cm2, respectively. The retrieval accuracy of CLW and TPW from the new algorithms is compared with these parameters provided in the SARAL geophysical data records as finished products, which showed substantial improvement in the quality of the parameters from the new algorithm. Numéro de notice : A2019-282 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01490419.2019.1624662 date de publication en ligne : 12/06/2019 En ligne : https://doi.org/10.1080/01490419.2019.1624662 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93116 [article]

Improving the spatial bias correction algorithm in SMOS image reconstruction processor : validation of soil moisture retrievals with in situ data / Ali Khazaal in IEEE Transactions on geoscience and remote sensing, vol 57 n° 1 (January 2019)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 57 n° 1 (January 2019) . - pp 277 - 290 Titre : Improving the spatial bias correction algorithm in SMOS image reconstruction processor : validation of soil moisture retrievals with in situ data Type de document : Article/Communication Auteurs : Ali Khazaal, Auteur ; Philippe Richaume, Auteur ; François Cabot, Auteur ; Eric Anterrieu, Auteur ; Arnaud Mialon, Auteur ; Yann H. Kerr, Auteur Année de publication : 2019 Article en page(s) : pp 277 - 290 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes descripteurs IGN] correction d'image [Termes descripteurs IGN] erreur systématique [Termes descripteurs IGN] humidité du sol [Termes descripteurs IGN] image SMOS [Termes descripteurs IGN] résidu [Termes descripteurs IGN] télédétection en hyperfréquence [Termes descripteurs IGN] température de luminance Résumé : (Auteur) SMOS is a space mission led by the European Space Agency and designed to provide global maps of Soil Moisture and Ocean salinity, two important geophysical parameters for understanding the water cycle variations and climate change. The SMOS payload is a 2-D interferometer operating at L-band that consists of 69 elementary antennas located along a Y-shaped structure. Important spatial biases persist in the retrieved brightness temperature (BT) images mainly due to the phenomenon of aliasing inside the field of view of SMOS but also due to the Gibbs oscillations near land/ocean transitions. To minimize these biases, a differential image reconstruction algorithm is used in the operational processor that reduces the contrast of the image to be retrieved. To do that, the contribution of a constant artificial temperature map is removed from the measurements prior to reconstruction and then added back after the reconstruction. In this paper, we show that strong residual biases are still present in the retrieved images. To reduce them, we propose to improve the bias correction algorithm by using a more realistic artificial temperature scene based on separating the land and ocean regions and assigning a constant temperature over land and a Fresnel BT model over the ocean. The artificial scene is also improved by means of representing each pixel by its water fraction percentage to smooth the land/ocean transitions. The improved algorithm is validated over the ocean by comparing the retrieved temperatures to a forward geophysical model but also over land by comparing the retrieved soil moisture to in situ measurements. Numéro de notice : A2019-106 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2018.2853619 date de publication en ligne : 09/08/2018 En ligne : https://doi.org/10.1109/TGRS.2018.2853619 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92412 [article]

Vegetation effects modeling in soil moisture retrieval using MSVI / Mina Moradizadeh in Photogrammetric Engineering & Remote Sensing, PERS, vol 82 n° 10 (October 2016)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 82 n° 10 (October 2016) . - pp 803 - 810 Titre : Vegetation effects modeling in soil moisture retrieval using MSVI Type de document : Article/Communication Auteurs : Mina Moradizadeh, Auteur ; Mohammad R. Saradjian, Auteur Année de publication : 2016 Article en page(s) : pp 803 - 810 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes descripteurs IGN] humidité du sol [Termes descripteurs IGN] image multicapteur [Termes descripteurs IGN] indice de végétation [Termes descripteurs IGN] itération [Termes descripteurs IGN] température au sol [Termes descripteurs IGN] température de luminance Résumé : (Auteur) Brightness temperature (BT) measured by passive microwave sensors is usually affected by soil moisture, vegetation cover, and soil roughness. Soil moisture estimates have been limited to regions that had either bare soil or low to moderate amounts of vegetation cover. In this study, Simultaneous Land Parameters Retrieval Model (SLPRM) as an iterative least-squares minimization method has been used. This algorithm retrieves surface soil moisture, land surface temperature, and canopy temperature simultaneously using brightness temperature data in bare soil, low to moderate and higher amounts of vegetation cover. Furthermore, a new index called MSVI (Multi Sensor Vegetation Index) has been introduced to approximate vegetation effects on properly observed brightness temperatures. The algorithm includes model construction, calibration, and validation using observations carried out for the SMEX03 (Soil Moisture Experiment 2003) region in the South and North of Oklahoma. The results indicated about 0.9 percent improvement on soil moisture estimation accuracy using the MSVI. Numéro de notice : A2016-935 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article En ligne : http://dx.doi.org/10.14358/PERS.82.10.803 Format de la ressource électronique : URL artilce Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83349 [article]

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A physics-based unmixing method to estimate subpixel temperatures on mixed pixels / Manuel Cubero-Castan in IEEE Transactions on geoscience and remote sensing, vol 53 n° 4 (April 2015)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 53 n° 4 (April 2015) . - pp 1894 - 1906 Titre : A physics-based unmixing method to estimate subpixel temperatures on mixed pixels Type de document : Article/Communication Auteurs : Manuel Cubero-Castan, Auteur ; Jocelyn Chanussot, Auteur ; Véronique Achard, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 1894 - 1906 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes descripteurs IGN] analyse linéaire des mélanges spectraux [Termes descripteurs IGN] emissivité [Termes descripteurs IGN] image aérienne [Termes descripteurs IGN] image hyperspectrale [Termes descripteurs IGN] image TASI [Termes descripteurs IGN] méthode des moindres carrés [Termes descripteurs IGN] rayonnement infrarouge thermique [Termes descripteurs IGN] température de luminance Résumé : (Auteur) This paper presents a new algorithm for the analysis of linear spectral mixtures in the thermal infrared domain, with the goal to jointly estimate the abundance and the subpixel temperature in a mixed pixel, i.e., to estimate the relative proportion and the temperature of each material composing the mixed pixel. This novel approach is a two-step procedure. First, it estimates the emissivity and the temperature over pure pixels using the standard temperature and emissivity separation (TES) algorithm. Second, it estimates the abundance and the subpixel temperature using a new unmixing physics-based model, called Thermal Remote sensing Unmixing for Subpixel Temperature (TRUST). This model is based on an estimator of the subpixel temperature obtained by linearizing the black body law around the mean temperature of each material. The abundance is then retrieved by minimizing the reconstruction error with the estimation of the subpixel temperatures. The TRUST method is benchmarked on simulated scenes against the fully constrained least squares unmixing applied on the radiance and on the estimation of surface emissivity using the TES algorithm. The TRUST method shows better results on pure and mixed pixels composed of two materials. TRUST also shows promising results when applied on thermal hyperspectral data acquired with the Thermal Airborne Spectrographic Imager during the Detection in Urban scenario using Combined Airborne imaging Sensors campaign and estimates coherent localization of mixed-pixel areas. Numéro de notice : A2015-172 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2014.2350771 date de publication en ligne : 15/09/2014 En ligne : https://doi.org/10.1109/TGRS.2014.2350771 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=75890 [article]

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An analysis of urban expansion and its associated thermal characteristics using Landsat imagery / Wei Huang in Geocarto international, vol 30 n° 1 - 2 (January - February 2015)

Public [article]  inGeocarto international > vol 30 n° 1 - 2 (January - February 2015) . - pp 93 - 103 Titre : An analysis of urban expansion and its associated thermal characteristics using Landsat imagery Type de document : Article/Communication Auteurs : Wei Huang, Auteur ; Yongnian Zeng, Auteur ; Songnian Li, Auteur Année de publication : 2015 Article en page(s) : pp 93 - 103 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes descripteurs IGN] cartographie numérique [Termes descripteurs IGN] Chine [Termes descripteurs IGN] effet thermique [Termes descripteurs IGN] ilot thermique urbain [Termes descripteurs IGN] image Landsat-ETM+ [Termes descripteurs IGN] image Landsat-TM [Termes descripteurs IGN] surveillance de l'urbanisation [Termes descripteurs IGN] température au sol [Termes descripteurs IGN] température de luminance Résumé : (auteur) There has been an increasing interest in mapping and monitoring urban land use/land cover using remote sensing techniques. However, there still exist quite a number of challenges in deriving urban extent and its expansion density from remote sensing data quantitatively. This study utilized Landsat TM/ETM+ remote sensing data to assess urban expansion and its thermal characteristics with a case study in the city of Changsha, China. We proposed a new approach for quantitatively determining built-up area, its expansion density and their respective relationship with land surface temperature (LST) patterns. An urban expansion metric was also developed using a moving window mechanism to identify urban built-up area and its expansion density based on selected threshold values. The study suggested that urban extent and its expansion density, as well as surface thermal characteristics and patterns could be identified through quantitatively derived remotely sensed indices and LST, which offer meaningful characteristics in quantifying urban expansion density and urban thermal pattern. Results from the case study demonstrated that: (1) the built-up area and urban expansion density have significantly increased in the city of Changsha from 1990 to 2001; and (2) the differences of urban expansion densities correspond to thermal effects, where a high percentage of imperviousness is usually associated with the area covered by high surface temperature. Numéro de notice : A2015-247 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE/URBANISME Nature : Article nature-HAL : ArtAvecCL-RevueIntern Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=76245 [article]

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Spatiotemporally characterizing urban temperatures based on remote sensing and GIS analysis: a case study in the city of Saskatoon (SK, Canada) / Li Shen in Open geosciences, vol 7 n° 1 (January 2015)  

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Modeling and sensing the vertical structure of the atmospheric path delay by microwave radiometry to correct SAR interferograms / Patrizia Basili in IEEE Transactions on geoscience and remote sensing, vol 52 n° 2 (February 2014)  

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A comparative analysis of low-level radio frequency interference in SMOS and Aquarius microwave radiometer measurements / Mustafa Aksoy in IEEE Transactions on geoscience and remote sensing, vol 51 n° 10 (October 2013)  

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A sky status indicator to detect rain-affected atmospheric thermal emissions observed at ground / Ada Vittoria Bosisio in IEEE Transactions on geoscience and remote sensing, vol 51 n° 9 (September 2013)  

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Improved geolocation and Earth incidence angle information for a fundamental climate data record of the SSM/I sensors / Wesley Berg in IEEE Transactions on geoscience and remote sensing, vol 51 n° 3 Tome 1 (March 2013)  

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Maintaining the long-term calibration of the Jason-2/OSTM advanced microwave radiometer through intersatellite calibration / Shannon Brown in IEEE Transactions on geoscience and remote sensing, vol 51 n° 3 Tome 1 (March 2013)  

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A new technique using infrared satellite measurements to improve the accuracy of the CALIPSO cloud-aerosol discrimination method / A. Naeger in IEEE Transactions on geoscience and remote sensing, vol 51 n° 1 Tome 2 (January 2013)  

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Mapping nighttime flood from MODIS observations using support vector machines / R. Zhang in Photogrammetric Engineering & Remote Sensing, PERS, vol 78 n° 11 (November 2012)  

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ESA's Soil Moisture and Ocean Salinity mission : mission performance and operations / S. Mecklenburg in IEEE Transactions on geoscience and remote sensing, vol 50 n° 5 Tome 1 (May 2012)  

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Overview of the first SMOS sea surface salinity products. Part 1: quality assessment for the second half of 2010 / N. Reul in IEEE Transactions on geoscience and remote sensing, vol 50 n° 5 Tome 1 (May 2012)  

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