Kalifa Goïta

Thématiques de recherche

Je suis un géomaticien spécialisé en télédétection des paramètres biogéophysiques. Mes centres d’intérêt portent sur la télédétection et la géomatique appliquée à l’environnement, aux ressources naturelles et aux risques naturels. J’interviens spécifiquement dans le développement de méthodes d’estimation de paramètres à partir des micro-ondes passives, l’altimétrie radar et lidar pour l’eau dans le sol, dans la neige ou dans le couvert végétal; les variations de niveaux d’eau de surface, la biomasse et le carbone des formations forestières et des milieux agricoles; la géomatique de la propagation des feux et des inondations; l’exploration minière, les applications cadastrales et la mise à jour cartographique.

 
Kalifa.Goita@USherbrooke.ca
 
Étude des variations de niveaux d’eau de surface en milieu hétérogène par altimétrie satellitaire (Topex-Poseidon, Jason, Envisat, Icesat)

Estimation de l’humidité du sol au moyen de mesures au sol et de données micro-ondes passives aéroportées et satellitaires dans le cadre de la validation de données SMOS
Estimation du contenu en eau de la végétation et intégration de la télédétection dans les modèles de propagation des feux de forêts
Utilisation des micro-ondes passives et de l’altimétrie par satellite pour l’estimation de l’épaisseur et du contenu en eau de la neige
Biomasse et carbone des formations forestières tropicales
Analyse de données géoscientifiques et de télédétection multisources combinés à des relevés conventionnels, pour des fins d’exploration minière
Synergie des mesures spectrales pour l’aide à la décision en viabilité hivernale (conditions de la chaussée)

 

  • Fatolazadeh, F., & Goïta, K. (2022). Reconstructing groundwater storage variations from GRACE observations using a new Gaussian-Han-Fan (GHF) smoothing approach. Journal of Hydrology, 127234.
  • Tong, C., Wang, H., Magagi, R., Goïta, K., & Wang, K. (2021). Spatial Gap-Filling of SMAP Soil Moisture Pixels Over Tibetan Plateau via Machine Learning Versus Geostatistics. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 14, 9899-9912.
  • Diaby, I., Germain, M., & Goïta, K. (2021). Evidential Data Fusion for Characterization of Pavement Surface Conditions during Winter Using a Multi-Sensor Approach. Sensors, 21(24), 8218.
  • Bahrami, A., Goïta, K., Magagi, R., Davison, B., Razavi, S., Elshamy, M., & Princz, D. (2021). Data assimilation of satellite-based terrestrial water storage changes into a hydrology land-surface model. Journal of Hydrology, 597, 125744.
  • Wang, H., Magagi, R., Goïta, K., Colliander, A., Jackson, T., McNairn, H., & Powers, J. (2021). Soil moisture retrieval over a site of intensive agricultural production using airborne radiometer data. International Journal of Applied Earth Observation and Geoinformation, 97, 102287.
  • Fatolazadeh, F., & Goïta, K. (2021). Mapping terrestrial water storage changes in Canada using GRACE and GRACE-FO. Science of The Total Environment, 146435.
  • Hamdi, M., Goïta, K., Karaouli, F., & Zagrarni, M. F. (2021). Hydrodynamic groundwater modeling and hydrochemical conceptualization of the mining area of Moulares Redeyef (southwestern of Tunisia): New local insights. Physics and Chemistry of the Earth, Parts A/B/C, 121, 102974.
  • Hamdi, M., Goita, K., & Zagrarni, M. F. (2021). Integrated 3D geological and hydrodynamic modeling for the water budget estimation: Sisseb El Alem Nadhour Saouaf case study. International Journal of Innovation and Scientific Research, Vol. 52, No. 2, pp. 185-192
  • Siebels, K., Goïta, K., & Germain, M. (2021) A semi-empirical approach to quantify and handle the effect of moisture on spectral unmixing. International Journal of Applied Earth Observation and Geoinformation, 96, 102259.
  • Bahrami, A., Goïta, K., & Magagi, R. (2020). Analysing the contribution of snow water equivalent to the terrestrial water storage over Canada. Hydrological Processes, 34(2), 175-188.
  • Fatolazadeh, F., Goïta, K., & Azar, R. J. (2020). Determination of earthquake epicentres based upon invariant quantities of GRAce strain gravity tensors. Scientific Reports, 10(1), 1-14.
  • Wang, H., Magagi, R., Goïta, K., & Wang, K. (2020). Soil moisture retrievals using ALOS2-ScanSAR and MODIS synergy over Tibetan Plateau. Remote Sensing of Environment, 251, 112100.
  • Migolet, P., Goïta, K., Ngomanda, A., & Mekui Biyogo, A. P. (2020). Estimation of Aboveground Oil Palm Biomass in a Mature Plantation in the Congo Basin. Forests, 11(5), 544.
  • Sogoba, B., Traoré, B., Safia, A., Samaké, O. B., Dembélé, G., Diallo, S., … & Goïta, K. (2020). On-Farm Evaluation on Yield and Economic Performance of Cereal-Cowpea Intercropping to Support the Smallholder Farming System in the Soudano-Sahelian Zone of Mali. Agriculture, 10(6), 214.
  • Hamdi, M., Goïta, K., Jerbi, H., & Zagrarni, M. F. (2020). Modeling of the natural groundwater recharge under climate change: Sisseb El Alem Nadhour Saouaf basin (Central Tunisia) case study. Environmental Earth Sciences, 79, 1-25.
  • Clabaut, E., Germain, M., Goïta, K., Morisset, C.-E., Plante, B., Tessier, C., Lemelin, M., Hébert, R., and Siebels, K. (2020) Mineralogical and lithological unmixing with radiative transfer modelling in the open-pit context of Mine Canadian Malartic, Journal of Quantitative Spectroscopy and Radiative Transfer, vol. 241, 106707.
  • Siebels, K., K. Goïta, M. Germain, (2020) Estimation of Mineral Abundance From Hyperspectral Data Using a New Supervised Neighbor-Band Ratio Unmixing Approach. IEEE Transactions on Geoscience and Remote Sensing, doi: 10.1109/TGRS.2020.2969577.
  • Tong, C., Wang, H., Magagi, R., Goïta, K., Zhu, L., Yang, M., & Deng, J. (2020). Soil Moisture Retrievals by Combining Passive Microwave and Optical Data. Remote Sensing, 12(19), 3173.
  • Fatolazadeh, F., Eshagh, M., & Goïta, K. (2020). A new approach for generating optimal GLDAS hydrological products and uncertainties. Science of The Total Environment, 138932.
  • Ziyad, J., Goïta, K., Magagi, R., Blarel, F., & Frappart, F. (2020). Improving the Estimation of Water Level over Freshwater Ice Cover using Altimetry Satellite Active and Passive Observations. Remote Sensing, 12(6), 967.
  • Monsiváis-Huertero, A., Hernández-Sánchez, J. C., Jiménez-Escalona, J. C., Galeana-Pizaña, J. M., Constantino-Recillas, D. E., Torres-Gómez, A. C., … & Couturier, S. (2020). Impact of temporal variations in vegetation optical depth and vegetation temperature on L-band passive soil moisture retrievals over a tropical forest using in-situ information. International Journal of Remote Sensing, 41(6), 2098-2139.
  • Ziyad, J., Goïta, K., & Magagi, R. (2020). Incertitudes des niveaux d’eau dérivés de l’altimétrie satellitaire pour des étendues d’eau soumises à l’action de la glace. Canadian Journal of Remote Sensing, 46(4), 429-453.
  • Migolet, P., & Goïta, K. (2020). Evaluation of formosat-2 and planetscope imagery for aboveground oil palm biomass estimation in a mature plantation in the congo basin. Remote Sensing, 12(2926). https://doi.org/10.3390/rs12182926
  • Goïta, K., Mouloungou, J., & Bénié, G. B. (2019). Estimation of aboveground biomass and carbon in a tropical rain forest in Gabon using remote sensing and GPS data. Geocarto International, 34(3), 243-259.
  • Abbes, A. B., Magagi, R., & Goita, K. (2019, July). Soil Moisture Estimation From Smap Observations Using Long Short-Term Memory (LSTM). In IGARSS 2019-2019 IEEE International Geoscience and Remote Sensing Symposium (pp. 1590-1593). IEEE.
  • Bahrami, A., Goïta, K., Magagi, R. (2019). Analyzing the contribution of snow waterequivalent to the terrestrial water storage over Canada. Hydrological Processes, (Article sous presse).
  • Wang, H., Magagi, R., Goïta, K., Trudel, M., McNairn, H., Powers, J. (2019). Crop phenology retrieval via polarimetric SAR decomposition and Random Forest algorithm. Remote Sensing of Environment, 231, 1-15. DOI. (Article publié).
  • Hongquan Wang, Ramata Magagi, Kalifa Goïta, Member, IEEE and Thomas Jagdhuber. (2019). Refining a Polarimetric Decomposition of Multi-Angular UAVSAR Time Series for Soil Moisture Retrieval over Low and High Vegetated Agricultural Fields. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 12(5), 1431-1450. DOI. (Article publié).
  • Najib Djamai, Richard Fernandes, Marie Weiss, Heather McNairn, Kalifa Goïta. (2019). Validation of the Sentinel Simplified Level 2 Product Prototype Processor (SL2P) for mapping cropland biophysical variables using Sentinel-2/MSI and Landsat-8/OLI data. Remote Sensing of Environment, 225, 416-430. (Article publié).
  • Monsiváis-Huertero, A., Hernández-Sánchez, J.C., Jiménez-Escalona, J.C., Galeana-Pizaña, J.M., Constantino-Recillas, D.E., Torres-Gómez, A.C., Magagi, R., Goïta, K., Couturier, S. (2019). in-situImpact of temporal variations in vegetation optical depth and vegetation temperature on L-band passive soil moisture retrievals over a tropical forest using information. International Journal of Remote Sensing, 1-42. DOI. (Article publié).
  • Hamdi, M., Zagrarni, M.F., Djamai, N., Jerbi, H., Goita, K.,Tarhouni, J. (2018). 3D geological modeling for complex aquifer system conception and groundwater storage assessment: Case of Sisseb El Alem Nadhour Saouaf basin, northeastern Tunisia. Journal of African Earth Sciences, 143, 178-186. DOI. (Article publié).
  • Wang, H., Magagi, R., Goïta, K. (2018). Potential of a two-component polarimetric decomposition at C-band for soil moisture retrieval over agricultural fields. Remote Sensing of Environment, (Article accepté).
  • Badreddine, S. F., Goïta, K., & Vachon, F. (2018, July). Comparison of Quebec Snow Grid Data and Globsnow Products Over the LA Grande and Manicouagan Watersheds in Canada from 2006 to 2010. In IGARSS 2018-2018 IEEE International Geoscience and Remote Sensing Symposium (pp. 5216-5219). IEEE.
  • Constantino-Recillas, D. E., Monsiváis-Huertero, A., Jiménez-Escalona, J. C., Zempoaltecatl-Ramirez, E., Magagi, R., & Goïta, K. (2018, July). A Semi-Empirical Model to Estimate Biophysical Parameters in Southern Mexico. In IGARSS 2018-2018 IEEE International Geoscience and Remote Sensing Symposium (pp. 5344-5347). IEEE.
  • *Wang, H., Magagi, R., Goïta, K. (2017). Comparison of different polarimetric decompositions for soil moisture retrieval over vegetation covered agricultural area. Remote Sensing of Environment, 199, 120-136. (Article publié).
  • Goïta, K., Mouloungou, J., Bénié, G.B. (2017). Estimation of aboveground biomass and carbon in a tropical rain forest in Gabon using remote sensing and GPS data. Geocarto International, doi=10.1080/10106049, 1-17. DOI. (Article publié).
  • Wang, H., Magagi, R., & Goita, K. (2017, July). Polarimetric decomposition of multi-angular SAR data for soil moisture retrieval over agricultural fields. In 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS) (pp. 4947-4950). IEEE.
  • Safia, A., & Goïta, K. (2017, July). Mapping ash trees from WorldView-2 and 3 data. In 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS) (pp. 4806-4809). IEEE.
  • Djamai, N., Goita, K., Corriveau, J. L., Lecompte, U., Lefrancois, G., Magagi, R., & Hamdi, M. (2017). Geosciences and Remote Sensing. J Geol, 6(5).
  • Wang, H., Magagi, R., Goïta, K., Jagdhuber, T., Hajnsek, I. (2016). Evaluation of simplified polarimetric decomposition for soil moisture retrieval over vegetated agricultural fields. Remote Sensing, 8(2) , art. no. 142.
  • Djamai, N., Magagi, R., Goïta, K., Merlin, O., Kerr, Y., & Roy, A. (2016). A combination of DISPATCH downscaling algorithm with CLASS land surface scheme for soil moisture estimation at fine scale during cloudy days. Remote Sensing of Environment, 184, 1-14.
  • Sun, L., Seidou, O., Nistor, I., Goïta, K., & Magagi, R. (2016). Simultaneous assimilation of in situ soil moisture and streamflow in the SWAT model using the Extended Kalman Filter. Journal of Hydrology, 543, 671-685.
  • Wang, H., Magagi, R., & Goita, K. (2016). Polarimetric decomposition for monitoring crop growth status. IEEE Geoscience and Remote Sensing Letters, 13(6), 870-874.
  • Beauregard, V., Goïta, K., & Magagi, R. (2016, July). Empirical model for surface soil moisture estimation over wheat fields using C-band polarimetric SAR. In 2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS) (pp. 1695-1698). IEEE.
  • Ramos, Y., Goïta, K., & Péloquin, S. (2016). Mapping advanced argillic alteration zones with ASTER and Hyperion data in the Andes Mountains of Peru. Journal of Applied Remote Sensing, 10(2), 026031.
  • Touré, M. Y., Goïta, K., Magagi, R., & Touré, A. M. (2016, July). Comparison of in situ and grace estimated groundwater in the Canadian prairies. In 2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS) (pp. 7639-7642). IEEE.
  • Wang, H., Magagi, R., & Goita, K. (2016, July). Assessment of the SMAP L3/AP soil moisture product using international ground observation network. In 2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS) (pp. 3082-3085). IEEE.
  • Wang, H., Magagi, R., & Goita, K. (2016, July). Polarimetric decomposition of C-band SAR data for soil moisture retrieval over agricultural fields. In 2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS) (pp. 1687-1690). IEEE.
  • Monsivais-Huertero, A., Jimenez-Escalona, J. C., Galeana-Pizaña, J. M., Torres-Gomez, A. C., Magagi, R., Goïta, K., … & Hernandez-Sanchez, J. C. (2016, July). Understanding the dynamic of a tropical forest located in Southern Mexico using remotely sensed data. In 2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS) (pp. 3826-3829). IEEE.
  • Bahrami, A., Goita, K., Razavi, S., Magagi, R., Elshamy, M., Haghnegahdar, A., … & Yassin, F. A. (2016). Assimilation of GRACE derived terrestrial water storage data into Canadian land surface and hydrology model. AGUFM, 2016, H33H-1643.
  • Ousmane, S., Goïta, K., Magagi, R., & Ali, A. (2016). Développement collaboratif d’outils d’alerte inondations pour l’Afrique de l’Ouest: rapport final (1/12/2013-30/09/2016).

Bénié, G. B., C. Müller-Poitevien, M. Yergeau, K. Goïta (2008). « La géomatique appliquée à la santé » (en préparation pour les Presses de l’Université du Québec).