Dr. Heather McNairn

Image Heather McNairn
Chercheuse

Mes recherches portent sur l’élaboration de méthodes, de modèles et d’algorithmes pour surveiller l’état de nos sols et de nos cultures à l’aide de données provenant de satellites équipés de capteurs multispectraux, de capteurs hyperspectraux et d’un radar à synthèse d’ouverture (RSO).

Recherche et / ou projets en cours

Je dirige actuellement deux projets de recherche :

« Comparaison internationale des méthodes basées sur l’imagerie de radar à synthèse d’ouverture (RSO) pour la surveillance des types de culture et de l’état des cultures : mise au point d’une capacité de surveillance opérationnelle pour le Canada et au-delà » 

« Quantifier la productivité des cultures depuis l’espace : Un nouveau système radar par satellite pour mesurer la réponse des cultures »

 

Énoncés de recherches/projets

Champs scientifiques

Renseignez-vous sur mes recherches et ce qu’elles signifient pour vous en visitant Champs scientifiques, une campagne mettant en vedette 11 scientifiques d’Agriculture et Agroalimentaire Canada établis d’un océan à l’autre.

Principales publications

  1. Arcand, Y., Bittman, S., Britten, M., Champagne, C., Daneshfar, B., David, S., Davidson, A., Derdall, E. Drury, C., Eden, J., Handyside, P., Hung, Y., Javorek, S., Jiang, Y., Jingui, Y., Jordan, C., Joosse, P., Li, S., McAuley, E., McNairn, H., MacDonald, D., Pacheco, A., Powers, J., Reid, K., Smith, E. L., Topp, E., Vanrobaeys, J., Villeneuve, S., Wilson, H., Yang, J. Agricultural Land Use. Synthesis of Science. Canada Water Agency Report. Freshwater Science Assessment-Line of Inquiry. Nov. 20, 2020.

    2020 - View publication details

  2. Dey, S., Bhattacharya, A., Ratha, D., Mandal, D., McNairn, H., Lopez-Sanchez, J.M., Rao, Y.S. (2020). Novel clustering schemes for full and compact polarimetric SAR data: An application for rice phenology characterization. ISPRS Journal of Photogrammetry and Remote Sensing, [online] 169 135-151. http://dx.doi.org/10.1016/j.isprsjprs.2020.09.010

    2020 - View publication details

  3. Mandal, D., Ratha, D., Bhattacharya, A., Kumar, V., McNairn, H., Rao, Y.S., Frery, A.C. (2020). A Radar vegetation index for crop monitoring using compact polarimetric sar data. IEEE Transactions on Geoscience and Remote Sensing, [online] 58(9), 6321-6335. http://dx.doi.org/10.1109/TGRS.2020.2976661

    2020 - View publication details

  4. Mandal, D., Kumar, V., Lopez-Sanchez, J.M., Bhattacharya, A., McNairn, H., Rao, Y.S. (2020). Crop biophysical parameter retrieval from Sentinel-1 SAR data with a multi-target inversion of Water Cloud Model. International Journal of Remote Sensing, [online] 41(14), 5503-5524. http://dx.doi.org/10.1080/01431161.2020.1734261

    2020 - View publication details

  5. Laamrani, A., Joosse, P., McNairn, H., Berg, A.A., Hagerman, J., Powell, K., Berry, M. (2020). Assessing soil cover levels during the non-growing season using multitemporal satellite imagery and spectral unmixing techniques, 12(9), http://dx.doi.org/10.3390/rs12091397

    2020 - View publication details

  6. McNairn, H., Jiao, X., Pacheco, A., Sinha, A., Tan, W., Li, Y. (2018). Estimating canola phenology using synthetic aperture radar. Remote Sensing of Environment, [online] 219 196-205. http://dx.doi.org/10.1016/j.rse.2018.10.012

    2018 - View publication details

  7. Zhang, H., Li, Q., Liu, J., Du, X., Dong, T., McNairn, H., Champagne, C., Liu, M., Shang, J. (2018). Object-based crop classification using multi-temporal SPOT-5 imagery and textural features with a Random Forest classifier. Geocarto International, [online] 33(10), 1017-1035. http://dx.doi.org/10.1080/10106049.2017.1333533

    2018 - View publication details

  8. Zwieback, S., Colliander, A., Cosh, M.H., Martínez-Fernández, J., McNairn, H., Starks, P.J., Thibeault, M., Berg, A. (2018). Estimating time-dependent vegetation biases in the SMAP soil moisture product. Hydrology and Earth System Sciences, [online] 22(8), 4473-4489. http://dx.doi.org/10.5194/hess-22-4473-2018

    2018 - View publication details

  9. Niazmardi, S., Homayouni, S., Safari, A., Shang, J., McNairn, H. (2018). Multiple kernel representation and classification of multivariate satellite-image time-series for crop mapping. International Journal of Remote Sensing, [online] 39(1), 149-168. http://dx.doi.org/10.1080/01431161.2017.1381351

    2018 - View publication details

  10. Zhang, H., Li, Q., Liu, J., Shang, J., Du, X., McNairn, H., Champagne, C., Dong, T., Liu, M. (2017). Image Classification Using RapidEye Data: Integration of Spectral and Textual Features in a Random Forest Classifier. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, [online] 10(12), 5334-5349. http://dx.doi.org/10.1109/JSTARS.2017.2774807

    2017 - View publication details

  11. Manns, H.R., Berg, A.A., Bullock, P.R., McNairn, H., Groenevelt, P., Yang, W. (2017). Importance of soil organic carbon in near-surface soil water content estimation: A simple model comparison in dry-end Canadian Prairie soils. Canadian Water Resources Journal, [online] 42(4), 364-377. http://dx.doi.org/10.1080/07011784.2017.1383188

    2017 - View publication details

  12. Global Strategy to improve Agricultural and Rural Statistics (GSARS). 2017. Handbook on Remote Sensing for Agricultural Statistics. GSARS Handbook: Rome.

    Davidson, A.M., Fisette, T., Mcnairn, H. & Daneshfar, B. 2017. Detailed crop mapping using remote sensing data (Crop Data Layers). In: J. Delincé (ed.), Handbook on Remote Sensing for Agricultural Statistics (Chapter 4). Handbook of the Global Strategy to improve Agricultural and Rural Statistics (GSARS): Rome.

    2017 - View publication details

  13. Hosseini, M. and McNairn, H. Using multi-polarization C- and L-band synthetic aperture radar to estimate biomass and soil moisture of wheat fields, International Journal of Applied Earth Observation and Geoinformation 58(2017) 50-64.

    2017 - View publication details

  14. Tamiminia, H., Homayouni, S., McNairn, H., Safari, A. (2017). A particle swarm optimized kernel-based clustering method for crop mapping from multi-temporal polarimetric L-band SAR observations. International Journal of Applied Earth Observation and Geoinformation, [online] 58 201-212. http://dx.doi.org/10.1016/j.jag.2017.02.010

    2017 - View publication details

  15. Colliander, A., Jackson, T.J., Bindlish, R., Chan, S., Das, N., Kim, S.B., Cosh, M.H., Dunbar, R.S., Dang, L., Pashaian, L., Asanuma, J., Aida, K., Berg, A., Rowlandson, T., Bosch, D., Caldwell, T., Caylor, K., Goodrich, D., al Jassar, H., Lopez-Baeza, E., Martínez-Fernández, J., González-Zamora, A., Livingston, S., McNairn, H., Pacheco, A., Moghaddam, M., Montzka, C., Notarnicola, C., Niedrist, G., Pellarin, T., Prueger, J., Pulliainen, J., Rautiainen, K., Ramos, J., Seyfried, M., Starks, P., Su, Z., Zeng, Y., van der Velde, R., Thibeault, M., Dorigo, W., Vreugdenhil, M., Walker, J.P., Wu, X., Monerris, A., O'Neill, P.E., Entekhabi, D., Njoku, E.G., Yueh, S. (2017). Validation of SMAP surface soil moisture products with core validation sites. Remote Sensing of Environment, [online] 191 215-231. http://dx.doi.org/10.1016/j.rse.2017.01.021

    2017 - View publication details

  16. Haifa Tamiminia a, Saeid Homayouni b, Heather McNairn c, Abdoreza Safari a

    2017 - View publication details

  17. Bhuiyan, H.A.K.M., McNairn, H., Powers, J., and Merzouki, A. HEC-HMS in a cold region watershed and use of RADARSAT-2 soil moisture in initializing the model, Hydrology, 2017, 4, 9:1-19.

    2017 - View publication details

  18. Garnaud, C., Bélair, S., Carrera, M.L., McNairn, H., and Pacheco. A. Field-scale spatial variability of soil moisture and L-Band brightness temperature from land surface modeling, Journal of Hydrometeorology, 2017, 18: 573-589.

    2017 - View publication details

  19. Champagne, C., Rowlandson, T.L., Berg, A.A., Burns, T., L'Heureux, J., Tetlock, E., Adams, J.R., McNairn, H., Toth, B.M., et Itenfisu, D. (2016). « Satellite Surface Soil Moisture from SMOS and Aquarius: Assessment for Applications in Agricultural Landscapes. », International Journal of Applied Earth Observation and Geoinformation, 45(Part B), p. 143-154. doi : 10.1016/j.jag.2015.09.004

    2016 - View publication details

  20. "From fields to regions: Improving crop model predictions, using remote sensing-derived biophysical descriptors and climate data." Pattey, E.,Jégo, G. ,A. Vanderzaag, J. Liu, B. Qian, X. Geng; Res. Team: S. Admiral, M. Mesbah, D. Dow, T. HotteF. Baret, M. Weiss, R. Lacaze, F. Camacho, N. Beaudoin, R. Desjardins, T. Huffman, H. McNairn 2016. 2016 Canadian JECAM Site Update: CFIA-Ottawa. JECAM Science Meeting Kyiv, 11-12 Oct 2016 (poster).

    2016 - View publication details

Installation de recherche

960, avenue Carling
Ottawa, ON K1A 0C6
Canada

Language

Anglais
Français