Descripteur



Etendre la recherche sur niveau(x) vers le bas
A deep learning approach to improve the retrieval of temperature and humidity profiles from a ground-based microwave radiometer / Xing Yan in IEEE Transactions on geoscience and remote sensing, Vol 58 n° 12 (December 2020)
![]()
[article]
Titre : A deep learning approach to improve the retrieval of temperature and humidity profiles from a ground-based microwave radiometer Type de document : Article/Communication Auteurs : Xing Yan, Auteur ; Chen Liang, Auteur ; Yize Jiang, Auteur Année de publication : 2020 Article en page(s) : pp 8427 - 8437 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes descripteurs IGN] analyse diachronique
[Termes descripteurs IGN] apprentissage profond
[Termes descripteurs IGN] changement climatique
[Termes descripteurs IGN] classification par réseau neuronal
[Termes descripteurs IGN] humidité du sol
[Termes descripteurs IGN] modèle atmosphérique
[Termes descripteurs IGN] radiomètre à hyperfréquence
[Termes descripteurs IGN] température au solRésumé : (auteur) The ground-based microwave radiometer (MWR) retrieves atmospheric profiles with a high temporal resolution for temperature and humidity up to a height of 10 km. Such profiles are critical for understanding the evolution of climate systems. To improve the accuracy of profile retrieval in MWR, we developed a deep learning approach called batch normalization and robust neural network (BRNN). In contrast to the traditional backpropagation neural network (BPNN), which has previously been applied for MWR profile retrieval, BRNN reduces overfitting and has a greater capacity to describe nonlinear relationships between MWR measurements and atmospheric structure information. Validation of BRNN with the radiosonde demonstrates a good retrieval capability, showing a root-mean-square error of 1.70 K for temperature, 11.72% for relative humidity (RH), and 0.256 g/m 3 for water vapor density. A detailed comparison with various inversion methods (BPNN, extreme gradient boosting, support vector machine, ridge regression, and random forest) has also been conducted in this research, using the same training and test data sets. From the comparison, we demonstrated that BRNN significantly improves retrieval accuracy, particularly for the retrieval of temperature and RH near the surface. Numéro de notice : A2020-741 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2020.2987896 date de publication en ligne : 29/04/2020 En ligne : https://doi.org/10.1109/TGRS.2020.2987896 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96371
in IEEE Transactions on geoscience and remote sensing > Vol 58 n° 12 (December 2020) . - pp 8427 - 8437[article]Challenges in flood modeling over data-scarce regions: how to exploit globally available soil moisture products to estimate antecedent soil wetness conditions in Morocco / El Mahdi El Khalk in Natural Hazards and Earth System Sciences, vol 20 n° 10 (October 2020)
![]()
[article]
Titre : Challenges in flood modeling over data-scarce regions: how to exploit globally available soil moisture products to estimate antecedent soil wetness conditions in Morocco Type de document : Article/Communication Auteurs : El Mahdi El Khalk, Auteur ; Yves Tramblay, Auteur ; Christian Massari, Auteur Année de publication : 2020 Article en page(s) : pp 2591 - 2607 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes descripteurs IGN] Advanced scatterometer
[Termes descripteurs IGN] Atlas marocain
[Termes descripteurs IGN] bassin hydrographique
[Termes descripteurs IGN] crue
[Termes descripteurs IGN] humidité du sol
[Termes descripteurs IGN] image SMOS
[Termes descripteurs IGN] inondation
[Termes descripteurs IGN] Maroc
[Termes descripteurs IGN] modèle hydrographique
[Termes descripteurs IGN] modélisation
[Termes descripteurs IGN] variation saisonnière
[Termes descripteurs IGN] zone semi-arideRésumé : (auteur) The Mediterranean region is characterized by intense rainfall events giving rise to devastating floods. In Maghreb countries such as Morocco, there is a strong need for forecasting systems to reduce the impacts of floods. The development of such a system in the case of ungauged catchments is complicated, but remote-sensing products could overcome the lack of in situ measurements. The soil moisture content can strongly modulate the magnitude of flood events and consequently is a crucial parameter to take into account for flood modeling. In this study, different soil moisture products (European Space Agency Climate Change Initiative, ESA-CCI; Soil Moisture and Ocean Salinity, SMOS; Soil Moisture and Ocean Salinity by the Institut National de la Recherche Agronomique and Centre d'Etudes Spatiales de la Biosphère, SMOS-IC; Advanced Scatterometer, ASCAT; and ERA5 reanalysis) are compared to in situ measurements and one continuous soil-moisture-accounting (SMA) model for basins located in the High Atlas Mountains, upstream of the city of Marrakech. The results show that the SMOS-IC satellite product and the ERA5 reanalysis are best correlated with observed soil moisture and with the SMA model outputs. The different soil moisture datasets were also compared to estimate the initial soil moisture condition for an event-based hydrological model based on the Soil Conservation Service curve number (SCS-CN). The ASCAT, SMOS-IC, and ERA5 products performed equally well in validation to simulate floods, outperforming daily in situ soil moisture measurements that may not be representative of the whole catchment soil moisture conditions. The results also indicated that the daily time step may not fully represent the saturation state before a flood event due to the rapid decay of soil moisture after rainfall in these semiarid environments. Indeed, at the hourly time step, ERA5 and in situ measurements were found to better represent the initial soil moisture conditions of the SCS-CN model by comparison with the daily time step. The results of this work could be used to implement efficient flood modeling and forecasting systems in semiarid regions where soil moisture measurements are lacking. Numéro de notice : A2020-610 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.5194/nhess-20-2591-2020 date de publication en ligne : 05/10/2020 En ligne : https://doi.org/10.5194/nhess-20-2591-2020 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95974
in Natural Hazards and Earth System Sciences > vol 20 n° 10 (October 2020) . - pp 2591 - 2607[article]Improved SMAP dual-channel algorithm for the retrieval of soil moisture / Mario Julian Chaubell in IEEE Transactions on geoscience and remote sensing, vol 58 n° 6 (June 2020)
![]()
[article]
Titre : Improved SMAP dual-channel algorithm for the retrieval of soil moisture Type de document : Article/Communication Auteurs : Mario Julian Chaubell, Auteur ; Simon H. Yueh, Auteur ; R. Scott Dunbar, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 3894 - 3905 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes descripteurs IGN] bande L
[Termes descripteurs IGN] humidité du sol
[Termes descripteurs IGN] mission SMAP
[Termes descripteurs IGN] polarisation
[Termes descripteurs IGN] radiomètre
[Termes descripteurs IGN] rugosité
[Termes descripteurs IGN] teneur en eau de la végétationRésumé : (auteur) The soil moisture active passive (SMAP) mission was designed to acquire L-band radiometer measurements for the estimation of soil moisture (SM) with an average ubRMSD of not more than 0.04 m3/m3 volumetric accuracy in the top 5 cm for vegetation with a water content of less than 5 kg/ m2 . Single-channel algorithm (SCA) and dual-channel algorithm (DCA) are implemented for the processing of SMAP radiometer data. The SCA using the vertically polarized brightness temperature (SCA-V) has been providing satisfactory SM retrievals. However, the DCA using prelaunch design and algorithm parameters for vertical and horizontal polarization data has a marginal performance. In this article, we show that with the updates of the roughness parameter h and the polarization mixing parameters Q , a modified DCA (MDCA) can achieve improved accuracy over DCA; it also allows for the retrieval of vegetation optical depth (VOD or τ ). The retrieval performance of MDCA is assessed and compared with SCA-V and DCA using four years (April 1, 2015 to March 31, 2019) of in situ data from core validation sites (CVSs) and sparse networks. The assessment shows that SCA-V still outperforms all the implemented algorithms. Numéro de notice : A2020-282 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2019.2959239 date de publication en ligne : 15/01/2020 En ligne : https://doi.org/10.1109/TGRS.2019.2959239 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95104
in IEEE Transactions on geoscience and remote sensing > vol 58 n° 6 (June 2020) . - pp 3894 - 3905[article]Conterminous United States land cover change patterns 2001–2016 from the 2016 National Land Cover Database / Collin Homer in ISPRS Journal of photogrammetry and remote sensing, vol 162 (April 2020)
![]()
[article]
Titre : Conterminous United States land cover change patterns 2001–2016 from the 2016 National Land Cover Database Type de document : Article/Communication Auteurs : Collin Homer, Auteur ; Jon Dewitz, Auteur ; Suming Jin, Auteur Année de publication : 2020 Article en page(s) : pp 184 - 199 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes descripteurs IGN] Advanced Very High Resolution Radiometer
[Termes descripteurs IGN] analyse diachronique
[Termes descripteurs IGN] base de données d'occupation du sol
[Termes descripteurs IGN] changement climatique
[Termes descripteurs IGN] changement d'utilisation du sol
[Termes descripteurs IGN] cultures
[Termes descripteurs IGN] détection de changement
[Termes descripteurs IGN] Etats-Unis
[Termes descripteurs IGN] forêt
[Termes descripteurs IGN] image Landsat-OLI
[Termes descripteurs IGN] image MODIS
[Termes descripteurs IGN] Medium Resolution Imaging Spectrometer
[Termes descripteurs IGN] surveillance de la végétation
[Termes descripteurs IGN] zone humideRésumé : (auteur) The 2016 National Land Cover Database (NLCD) product suite (available on www.mrlc.gov), includes Landsat-based, 30 m resolution products over the conterminous (CONUS) United States (U.S.) for land cover, urban imperviousness, and tree, shrub, herbaceous and bare ground fractional percentages. The release of NLCD 2016 provides important new information on land change patterns across CONUS from 2001 to 2016. For land cover, seven epochs were concurrently generated for years 2001, 2004, 2006, 2008, 2011, 2013, and 2016. Products reveal that land cover change is significant across most land cover classes and time periods. The land cover product was validated using existing reference data from the legacy NLCD 2011 accuracy assessment, applied to the 2011 epoch of the NLCD 2016 product line. The legacy and new NLCD 2011 overall accuracies were 82% and 83%, respectively, (standard error (SE) was 0.5%), demonstrating a small but significant increase in overall accuracy. Between 2001 and 2016, the CONUS landscape experienced significant change, with almost 8% of the landscape having experienced a land cover change at least once during this period. Nearly 50% of that change involves forest, driven by change agents of harvest, fire, disease and pests that resulted in an overall forest decline, including increasing fragmentation and loss of interior forest. Agricultural change represented 15.9% of the change, with total agricultural spatial extent showing only a slight increase of 4778 km2, however there was a substantial decline (7.94%) in pasture/hay during this time, transitioning mostly to cultivated crop. Water and wetland change comprised 15.2% of change and represent highly dynamic land cover classes from epoch to epoch, heavily influenced by precipitation. Grass and shrub change comprise 14.5% of the total change, with most change resulting from fire. Developed change was the most persistent and permanent land change increase adding almost 29,000 km2 over 15 years (5.6% of total CONUS change), with southern states exhibiting expansion much faster than most of the northern states. Temporal rates of developed change increased in 2001–2006 at twice the rate of 2011–2016, reflecting a slowdown in CONUS economic activity. Future NLCD plans include increasing monitoring frequency, reducing latency time between satellite imaging and product delivery, improving accuracy and expanding the variety of products available in an integrated database. Numéro de notice : A2020-121 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2020.02.019 date de publication en ligne : 03/03/2020 En ligne : https://doi.org/10.1016/j.isprsjprs.2020.02.019 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94746
in ISPRS Journal of photogrammetry and remote sensing > vol 162 (April 2020) . - pp 184 - 199[article]Estimation of variance and spatial correlation width for fine-scale measurement error in digital elevation model / Mikhail L. Uss in IEEE Transactions on geoscience and remote sensing, vol 58 n° 3 (March 2020)
![]()
[article]
Titre : Estimation of variance and spatial correlation width for fine-scale measurement error in digital elevation model Type de document : Article/Communication Auteurs : Mikhail L. Uss, Auteur ; Benoit Vozel, Auteur ; Vladimir V. Lukin, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 1941 - 1956 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique
[Termes descripteurs IGN] Advanced Spaceborne Thermal Emission and Reflection Radiometer
[Termes descripteurs IGN] analyse multivariée
[Termes descripteurs IGN] corrélation automatique de points homologues
[Termes descripteurs IGN] courbe épipolaire
[Termes descripteurs IGN] erreur de mesure
[Termes descripteurs IGN] image ALOS
[Termes descripteurs IGN] image TanDEM-X
[Termes descripteurs IGN] modèle d'erreur
[Termes descripteurs IGN] modèle numérique de surface
[Termes descripteurs IGN] mouvement brownien
[Termes descripteurs IGN] varianceRésumé : (Auteur) In this article, we borrow from the blind noise parameter estimation (BNPE) methodology early developed in the image processing field an original and innovative no-reference approach to estimate digital elevation model (DEM) vertical error parameters without resorting to a reference DEM. The challenges associated with the proposed approach related to the physical nature of the error and its multifactor structure in DEM are discussed in detail. A suitable multivariate method is then developed for estimating the error in gridded DEM. It is built on a recently proposed vectorial BNPE method for estimating spatially correlated noise using noise informative areas and fractal Brownian motion. The new multivariate method is derived to estimate the effect of the stacking procedure and that of the epipolar line error on local (fine-scale) standard deviation and autocorrelation function width of photogrammetric DEM measurement error. Applying the new estimator to Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) GDEM2 and Advanced Land Observing Satellite (ALOS) World 3D DEMs, good agreement of derived estimates with results available in the literature is evidenced. Adopted for TanDEM-X-DEM, estimates obtained agree well with the values provided in the height error map. In future works, the proposed no-reference method for analyzing DEM error can be extended to a larger number of predictors for accounting for other factors influencing remote sensing (RS) DEM accuracy. Numéro de notice : A2020-092 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2019.2951178 date de publication en ligne : 28/11/2019 En ligne : https://doi.org/10.1109/TGRS.2019.2951178 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94666
in IEEE Transactions on geoscience and remote sensing > vol 58 n° 3 (March 2020) . - pp 1941 - 1956[article]Uncertainty analysis of remotely-acquired thermal infrared data to extract the thermal Properties of active lava surfaces / James A. Thompson in Remote sensing, vol 12 n° 1 (January 2020)
PermalinkImproved 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)
PermalinkLand Surface Remote Sensing in Continental Hydrology, ch. 3. Using satellite scatterometers to monitor continental surfaces / Pierre-Louis Frison (2017)
PermalinkTélédétection pour l'observation des surfaces continentales, ch. 3. Utilisation des diffusiomètres satellitaires pour le suivi des surfaces continentales / Pierre-Louis Frison (2017)
PermalinkTélédétection pour l'observation des surfaces continentales, Volume 4. Observation des surfaces continentales par télédétection 2 / Nicolas Baghdadi (2017)
PermalinkAdaptive estimation of the stable boundary layer height using combined Lidar and microwave radiometer observations / Umar Saeed in IEEE Transactions on geoscience and remote sensing, vol 54 n° 12 (December 2016)
PermalinkA global study of NDVI difference among moderate-resolution satellite sensors / Xingwang Fan in ISPRS Journal of photogrammetry and remote sensing, vol 121 (November 2016)
PermalinkMeasure of temporal variation of P-Band radar cross section and temporal coherence of a temperate tree / Clément Albinet in IEEE Transactions on geoscience and remote sensing, vol 54 n° 11 (November 2016)
PermalinkSMAP L-Band microwave radiometer: RFI mitigation prelaunch analysis and first year on-orbit observations / Priscilla N. Mohammed in IEEE Transactions on geoscience and remote sensing, vol 54 n° 10 (October 2016)
PermalinkGNSS interferometric radio occultation / Manuel Martín-Neira in IEEE Transactions on geoscience and remote sensing, vol 54 n° 9 (September 2016)
Permalink