Bahram Daneshfar

Spécialiste en géostatistique

Application de méthodes quantitatives et basées sur l'observation de la Terre à la surveillance agricole

Key publications

  1. Mardian, J., Berg, A., Daneshfar, B. (2021). Evaluating the temporal accuracy of grassland to cropland change detection using multitemporal image analysis, 255 http://dx.doi.org/10.1016/j.rse.2021.112292

    2021 - View publication details

  2. 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

  3. 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

  4. Dong, T., Liu, J., Shang, J., Qian, B., Huffman, E.C., Zhang, Y., Champagne, C., et Daneshfar, B. (2016). « Assessing the Impact of Climate Variability on Cropland Productivity in the Canadian Prairies Using Time Series MODIS FAPAR. », Remote Sensing, 8(4: Article 281), p. 1-18. doi : 10.3390/rs8040281

    2016 - View publication details

  5. Chipanshi, A.C., Zhang, Y., Kouadio, L., Newlands, N.K., Davidson, A.M., Hill, H.S., Warren, R., Qian, B., Daneshfar, B., Bedard, F., et Reichert, G. (2015). « Evaluation of the Integrated Canadian Crop Yield Forecaster (ICCYF) model for in-season prediction of crop yield across the Canadian agricultural landscape. », Agricultural and Forest Meteorology, 206, p. 137-150. doi : 10.1016/j.agrformet.2015.03.007

    2015 - View publication details

  6. Qiao, C., Wang, J., Shang, J., et Daneshfar, B. (2015). « Spatial relationship-assisted classification from high-resolution remote sensing imagery. », International Journal of Digital Earth, 8(9), p. 710-726. doi : 10.1080/17538947.2014.925517

    2015 - View publication details

  7. Liu, H.J., Huffman, E.C., Liu, J., Li, Z., Daneshfar, B., et Zhang, X.L. (2015). « Integration of multi-disciplinary geospatial data for delineating agroecosystem uniform management zones. », Environmental Monitoring and Assessment, 187(1: 4102). doi : 10.1007/s10661-014-4102-1

    2015 - View publication details

  8. Du, Y., Huffman, E.C., Daneshfar, B., Green, M., Feng, F., Liu, J., Liu, T., et Liu, H. (2015). « Amélioration de la résolution spatiale et de l’écostratification des estimations du rendement agricole au Canada. », Canadian Journal of Soil Science, 95(3), p. 287-297.

    2015 - View publication details

  9. Champagne, C., McNairn, H., Daneshfar, B., et Shang, J. (2014). « A bootstrap method for assessing classification accuracy and confidence for agricultural land use mapping in Canada. », International Journal of Applied Earth Observation and Geoinformation, 29(1), p. 44-52. doi : 10.1016/j.jag.2013.12.016

    2014 - View publication details