Hamid Dashti

Hamid Dashti

Postdoctoral Research Associate at UW-Madison Remote Sensing | Geospatial Data Science | Climate Change |

My Publications

  1. Dashti, H., Chen, M., Smith, W. K., Zhao, K., & Moore, D. J. P. (2023). Rethinking Ecosystems Disturbance Recovery: what it was or what it could have been? Global Change Biology. Manuscript under review.
  2. Dashti, H., Smith, W. K., Huo, X., Fox, A., Javadian, M., Devine, C. J., Behrangi, A., & Moore, D. J. P. (2023). Underestimation of the impact of land cover change on the biophysical environment of the Arctic and Boreal Region of North America. Environmental Research Letters. Manuscript under review.
  3. Enterkine, J., Dashti, H., Caughlin, T. T., & Glenn, N. F. (2023). Applied soft classes and fuzzy confusion in a patchwork semi-arid ecosystem: Stitching together classification techniques to preserve ecologically-meaningful information. Remote Sensing of Environment. Manuscript accepted for publication.
  4. Luo, M., Li, F., Hao, D., Zhu, Q., Dashti, H., & Chen, M. (2023). Uncertain spatial pattern of future land use and land cover change and its impacts on terrestrial carbon cycle over the Arctic–Boreal region of North America. Earth's Future, 11, e2023EF003648. https://doi.org/10.1029/2023EF003648
  5. Dashti, H., Smith, W. K., Huo, X., Fox, A., Javadian, M., Devine, C. J., Behrangi, A., & Moore, D. J. P. (2022). Underestimation of the impact of land cover change on the biophysical environment of the Arctic and Boreal Region of North America. Environmental Research Letters. https://doi.org/10.1088/1748-9326/ac8da7
  6. Fox, A. M., Huo, X., Hoar, T. J., Dashti, H., Smith, W. K., MacBean, N., et al. (2022). Assimilation of global satellite leaf area estimates reduces modeled global carbon uptake and energy loss by terrestrial ecosystems. Journal of Geophysical Research: Biogeosciences, 127, e2022JG006830. https://doi.org/10.1029/2022JG006830
  7. Ilangakoon, N., Glenn, N. F., Schneider, F. D., Dashti, H., Hancock, S., Spaete, L., & Goulden, T. (2021). Airborne and spaceborne lidar reveal trends and patterns of functional diversity in a semi-arid ecosystem. Frontiers in Remote Sensing, 2. https://doi.org/10.3389/frsen.2021.743320
  8. Cawse-Nicholson, K., Townsend, P. A., Schimel, D., Assiri, A. M., Blake, P. L., Buongiorno, M. F., et al. (2021). NASA’s Surface Biology and Geology Designated Observable: A perspective on surface imaging algorithms. Remote Sensing of Environment, 257, 112349. https://doi.org/10.1016/j.rse.2021.112349
  9. Pandit, K., Dashti, H., Hudak, A. T., Glenn, N. F., Flores, A. N., & Shinneman, D. J. (2021). Understanding the effect of fire on vegetation composition and gross primary production in a semi-arid shrubland ecosystem using the Ecosystem Demography (EDv2.2) model. Biogeosciences Discuss., 2021, 1–20.
  10. Dashti, H., Pandit, K., Glenn, N.F., Shinneman, D.J., Flerchinger, G.N., Hudak, A.T., de Graaf, M.A., Flores, A., Ustin, S., Ilangakoon, N., & Fellows, A.W. (2021). Performance of the ecosystem demography model (EDv2.2) in simulating gross primary production capacity and activity in a dryland study area. Agricultural and Forest Meteorology, 297, 108270.
  11. Dashti, H., Spaete, L., Roberts, D., Enterkine, J., Flores, A. N., Ustin, S. L., & Mitchell, J. J. (2019). Regional-scale dryland vegetation classification with an integrated lidar-hyperspectral approach. Remote Sensing, 11(18).
  12. Pandit, K., Dashti, H., Glenn, N. F., Flores, A. N., Maguire, K. C., Shinneman, D. J., Fellows, A. W. (2019). Developing and optimizing shrub parameters representing sagebrush (Artemisia spp.) ecosystems in the northern Great Basin using the Ecosystem Demography (EDv2.2) model. Geoscientific Model Development, 12(11), 4585–4601. https://doi.org/10.5194/gmd-12-4585-2019
  13. Ilangakoon, N. T., Glenn, N. F., Dashti, H., Painter, T. H., Mikesell, T. D., Spaete, L. P., Mitchell, J. J., & Shannon, K. (2018). Constraining plant functional types in a semi-arid ecosystem with waveform lidar. Remote Sensing of Environment, 209, 497–509.
  14. Darvishzadeh, R., Matkan, A. A., & Dashti, A. (2011). Inversion of a radiative transfer model for estimation of rice canopy chlorophyll content. IEEE Journal of Selected Topics in Earth Observations and Remote Sensing, 5(4), 1222–1230.