Publications

Google Scholar: https://scholar.google.com/citations?user=5vSzixcAAAAJ&hl=en

PDFs available or email me directly for a reprint

Lin, Y., Meerdink, S.K., & Gader, P.D. (2022). Spectral Transformations for Multi-Temporal Hyperspectral Classification. IEEE Geoscience and Remote Sensing Letters, 19: 1-5. https://doi.org/10.1109/LGRS.2021.3136569

Miller, D.L., Alonzo, M., Meerdink, S.K., Allen, M.A., Tague, C.L., Roberts, D.A., & McFadden, J.P. (2022). Seasonal and interannual drought responses of vegetation in a California urbanized area measured using complementary remote sensing indices. ISPRS Journal of Photogrammetry and Remote Sensing, 183, 178–195. https://doi.org/10.1016/j.isprsjprs.2021.11.002

Meerdink, S., Bocinsky, J., Zare, A., Kroeger, N., McCurley, C., Shats, D., & Gader, P. (2021). Multitarget Multiple-Instance Learning for Hyperspectral Target Detection. IEEE Transactions on Geoscience and Remote Sensing, doi: 10.1109/TGRS.2021.3060966

Kibler, C. L., Parkinson, A. L., Peterson, S. H., Roberts, D. A., Antonio, C. M. D., Meerdink, S. K., & Sweeney, S. H. (2019). Monitoring post-fire recovery of chaparral and conifer species using field surveys and Landsat time series. Remote Sensing, 11(2963), 1–25. https://doi.org/10.3390/rs11242963 Open Access

Meerdink, S., Bocinsky, J., Wetherley, E., Zare, A., Mccurley, C., & Gader, P. (2019). Developing spectral libraries using multiple target multiple instance adapative cosine/coherence estimator. 2019 10th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS), 1–5. https://doi.org/10.1109/WHISPERS.2019.8920989

Fick, R., Gader, P., Zare, A., & Meerdink, S. (2019). Temporal mapping of hyperspectral data. 2019 10th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS), 1–4. https://doi.org/10.1109/WHISPERS.2019.8921373

Dennison, P. E., Qi, Y., Meerdink, S. K., Kokaly, R. F., Thompson, D. R., Daughtry, C. S. T., Quemada, M., Roberts, D.A., Gader, P.D., Wetherley, E.B., Numata, I., & Roth, K. L. (2019). Comparison of methods for modeling fractional cover using simulated satellite hyperspectral imager spectra. Remote Sensing, 11(2072), 1–23. https://doi.org/10.3390/rs11182072

Meerdink, S.K., Roberts, D.A., Roth, K.L., King, J.Y., Gader, P.D., & Koltunov, A. (2019). Classifying California plant species temporally using airborne hyperspectral imagery. Remote Sensing of Environment, 232, 111308. https://doi.org/10.1016/j.rse.2019.111308

Meerdink, S. K., Hook, S. J., Roberts, D. A., & Abbott, E. A. (2019). The ECOSTRESS spectral library version 1.0. Remote Sensing of Environment, 230(111196), 1–8. https://doi.org/10.1016/j.rse.2019.05.015

Meerdink, S.K., Roberts, D. A., Hulley, G., Pisek, J., Raabe, K., King, J., & Hook, S. J. (2019). Plant species’ spectral emissivity and temperature using the Hyperspectral Thermal Emission Spectrometer (HyTES) sensor. Remote Sensing of Environment, 224, 421–435. https://doi.org/10.1016/j.rse.2019.02.009

Roberts, D.A., Roth, K.L, Wetherley, E.B., Meerdink, S.K., & Perroy, R.L. (2018). Chapter 1: Hyperspectral Vegetation Indices, in: Hyperspectral Remote Sensing of Vegetation.

Meerdink, S. K., Roberts, D. A., King, J. Y., Roth, K. L., Dennison, P. E., Amaral, C. H., & Hook, S. J. (2016). Linking seasonal foliar traits to VSWIR-TIR spectroscopy across California ecosystems. Remote Sensing of Environment, 186, 322-338. http://dx.doi.org/10.1016/j.rse.2016.08.003