From CEF

Membres: SiddharthaKhare

Dr. Siddhartha Khare

Postdoctorat
The spatial characterization of tree growth by the integration of spatially-continuous variables
University of Quebec at Chicoutimi

Director: Sergio Rossi

ResearchGate Profile' ,

Research Interest

My current research interests focus on the potential application of satellite remote sensing, GIS and machine learning technology in the domains of smart agriculture, forest phenology, biodiversity and climate change. Currently, I am working on Canadian Boreal and Indian Himalayan forest ecosystems. I am very curious to explore new technologies such as Google Earth Engine (GEE) and R programming for satellite remote sensing based analysis. Over the period of 4 years, I have developed several automatic routines on GEE and R platforms to address various research problems especially for challenging areas where field based collection methods are both expensive and time consuming.

Work Experience

Foreign Research Visits

Awards and Honors

Education

Research Projects

Peer Reviewed Articles

  1. Khare, S. , Latifi, H., & Rossi, S., 2020. A 15-year spatio-temporal analysis of plant β-diversity using Landsat time series derived Rao's Q index. Ecological Indicators (minor revisions submitted).
  2. Jain, P., Khare, S. , Sylvain, J-D., Patricia, R., Rossi, S. 2020. Predicting the location of maple stands under warming scenarios in two regions at the northern range in Quebec, Canada. Forest Ecosystems. (Under review)
  3. Silva, J. R. D., Rossi, S., Khare, S. , Longui, E.L., and Marcati, C.R. 2020. Disentangling the effects of genotype and 2 environment on growth and wood features of Balfourodendron riedelianum trees by common 4 garden experiments in Brazil. Forest, , 11(9), pp.905.DOI: 10.3390/f11090905 
  4. Guo,X., Khare, S. , Silvestro, R., Huang, J., Sylvain, J-D., Delagrange, S., Rossi, S., 2020. Minimum spring temperatures at the provenance origin drive leaf phenology in sugar maple populations, tpaa096. Tree physiology. DOI: 10.1093/treephys/tpaa096 
  5. Zhang, S., Buttò, V., Khare, S. , Deslauriers, A., Morin, H., Huang, J.-G., Ren, H., Rossi, S., 2020. Calibrating phenocam data with phenological observations in black spruce. Canadian Journal of Remote Sensing.DOI: 10.1080/07038992.2020.1761251 
  6. Khare, S. , Drolet, G., Sylvain, J-D., Paré, M.C., & Rossi, S., 2019. Assessment of Spatio-Temporal Patterns of Black Spruce Bud Phenology across Quebec Based on MODIS-NDVI Time Series and Field Observations. Remote Sensing, 11, pp.2745.DOI: https://doi.org/10.3390/rs11232745 
  7. Khare, S. , Latifi, H., & Rossi, S., 2019. Forest beta-diversity analysis by remote sensing: How scale and sensors affect the Rao’s Q index. Ecological Indicators, 106, pp.105520.DOI: https://doi.org/10.1016/j.ecolind.2019.105520 
  8. Khare, S. , Latifi, H., Rossi, S. and Ghosh, S.K., 2019. Fractional Cover Mapping of Invasive Plant Species by Combining Very High-Resolution Stereo and Multi-Sensor Multispectral Imageries. Forests, 10(7), pp.540.DOI: https://doi.org/10.3390/f10070540 
  9. Khare, S. , Latifi, H. and Ghosh, S.K., 2018. Multi-scale assessment of invasive plant species diversity using Pléiades 1A, RapidEye and Landsat-8 data. Geocarto international, 33(7), pp.681-698.DOI: 10.1080/10106049.2017.1289562 
  10. Khare, S. , Ghosh, S.K., Latifi, H., Vijay, S. and Dahms, T., 2017. Seasonal-based analysis of vegetation response to environmental variables in the mountainous forests of Western Himalaya using Landsat 8 data. International Journal of Remote Sensing, 38(15), pp.4418-4442.DOI: 10.1080/01431161.2017.1320450 
  11. Khare, S.  and Ghosh, S.K., 2016. “Satellite Remote Sensing Technologies for Biodiversity Monitoring and Its Conservation”, International Journal of Advanced Earth Science and Engineering, 5(1), pp.375-389.DOI: 10.23953/cloud.ijaese.213 

Peer Reviewed International Conference

  1. Khare, S. , and Rossi, S., 2019. Phenology analysis of moist deciduous forest using time series Landsat-8 remote sensing data. IEEE International Workshop on Metrology for Agriculture and Forestry (MetroAgriFor), 24-26 Oct. 2019.
    DOI: 10.1109/MetroAgriFor.2019.8909249 
  2. Rossi, S., Zhang, S., Deslauriers, A., Butto, V., Morin, H., Huang, J.-G., Ren, H., and Khare, S. , 2019. Linking phenocam derived phenology with field observations in the boreal forest. IEEE International Workshop on Metrology for Agriculture and Forestry (MetroAgriFor), 24-26 Oct. 2019.
    DOI: 10.1109/MetroAgriFor.2019.8909272 
  3. Fakhri, S. A., Sayadi, S., Latifi, H., Khare, S. , 2019. An optimized Enhanced Vegetation Index for Sparse Tree Cover Mapping across a Mountainous Region. IEEE International Workshop on Metrology for Agriculture and Forestry (MetroAgriFor), 24-26 Oct. 2019.
    DOI: 10.1109/MetroAgriFor.2019.8909259 
  4. Khare, S. , Latifi, H. and Ghosh, S.K., 2018. Full satellite remote sensing based approach to assess the plant and tree species diversity using high and very spatial resolution multi-spectral data. EGU General Assembly 2018(Vienna | Austria | 8–13 April 2018).
    DOI: https://meetingorganizer.copernicus.org/EGU2018/EGU2018-665.pdf 
  5. Khare, S. , Latifi, H. and Ghosh, S. K., 2016. “Phenology Analysis of Forest Vegetation to Environmental Variables during-and Post-Monsoon Seasons in Western Himalayan Region of India”. ISPRS-International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, pp.15-19.
    DOI: 10.5194/isprs-archives-XLI-B2-15-2016 

Workshops and Lectures

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