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A new proliferation of optical instruments that can be attached to towers over or within ecosystems, a.k.a. ‘proximal’ remote sensing, enables a comprehensive characterization of terrestrial ecosystem structure, function, and fluxes of energy, water, and carbon. Proximal remote sensing bridges the gap between individual plants, site-level eddy-covariance fluxes, and air- and space-borne remote sensing by providing continuous data at a high-spatiotemporal resolution. Specifically the PIE lab uses proximal remote sensing to address:
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Related Publications |
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*The following publications are focused on the utility of proximal remote sensing and instrument development. Please see other research themes for research that uses proximal remote sensing for answering ecological questions.
Pierrat, Z. A., Magney, T. S., Richardson, W. P., Runkle, B. R. K., Diehl, J., Yang, X., Woodgate, W., Smith, W. K., Johnston, M. R., Ginting, Y. R. S., Koren, G., Albert, L. P., Kibler, C. L., Morgan, B. E., Barnes, M., Uscanga, A., Devine, C., Javadian, M., Meza, K., Julitta, T., Tagliabue, G., Dannenberg, M. P., Antala, M., Wong, C. Y. S., Santos, A. L. D., Hufkens, K., Marrs, J. K., Stovall, A. E. L., Liu, Y., Fisher, J. B., Gamon, J, A., Cawse-Nicholson, K. (2025). Proximal Remote Sensing: An essential tool for bridging the gap between high resolution ecosystem monitoring and global ecology. New Phytologist Tansley Review. https://doi.org/10.1111/nph.20405 Runkle, B. R. K., Barnes, M., Dannenberg, M., Gamon, J. A., Magney, T., Pierrat, Z. A, Southwick, C. D., Still, C., & Woodgate, W. (2025). Near-surface remote sensing applications for a robust, climate-smart measurement, monitoring, and information system (MMIS). Carbon Management, 16(1), 2465361. https://doi.org/10.1080/17583004.2025.2465361 Magney, T. S., Pierrat, Z. A., Wong, C. Y. S. Scaling Forest Ecophysiology from the Leaf to the Satellite. Book Chapter in “Following Photons Through Forests - A Radiation Ecology”. Springer Nature. (in review). ESS Open Archive. https://doi.org/10.22541/essoar.172978609.92915710/v1 Pierrat, Z., Magney, T., Yang, X., Khan, A., Albert, L. (2023). Ecosystem observations from every angle, Eos, 104, https://doi.org/10.1029/2023EO230483. Published on 14 December 2023. Runkle, B., Barnes, M., Pierrat, Z. A., and Members of the Fluxnet Linking Optical and Energy Fluxes Workshop, Nederland, Colorado, July 12-15, 2023. Public response on the Federal Strategy to Advance Measurement and Monitoring Greenhouse Gas Measurement and Monitoring for the Agriculture and Forest Sectors (2023). Published on August 10, 2023. |
Pierrat, Z. (2023). Evergreen needleleaf forest pigment, MONI-PAM, eddy-covariance, and tower-scale remote sensing data across four different sites [Data set]. In BioScience. Zenodo. https://doi.org/10.5281/zenodo.10048770
Pierrat, Z., Troy Magney, David R. Bowling, Bruce Johnson, Alan Barr, & Jochen Stutz. (2022). Boreal forest tower-based remote sensing data (solar-induced fluorescence and reflectance-based vegetation indices) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.7231157 Pierrat, Z., & Jochen Stutz. (2022). Tower-based solar-induced fluorescence and vegetation index data for Southern Old Black Spruce forest (Version 2) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.7596931 Pierrat, Z., Johnson, B., Helgason, W., Barr, A., Stutz, J. (2022). Gross primary production and environmental observations for a mature black spruce site located in central Saskatchewan, Canada, for the period Sep-2018 to Dec-2020. Federated Research Data Repository. https://doi.org/10.20383/102.0550 Pierrat, Z., Troy Magney, & Jochen Stutz. (2021). Tower-based remote sensing data for understory vegetation at Delta Junction, Alaska 2019-2020 [Data set]. Zenodo. https://doi.org/10.5281/zenodo.5806488 Pierrat, Z., Johnson, B., Helgason, W., Barr, A., Stutz, J. (2021). Environmental and gross primary production observations for a mature black spruce site located in central Saskatchewan, Canada. Federated Research Data Repository. https://doi.org/10.20383/101.0300 Pierrat, Z., & Stutz, J. (2021). Tower-based remote sensing data for mixed-species boreal forest spring transition 2019 and 2020 [Data set]. Zenodo. https://doi.org/10.5281/zenodo.4637567 |