Items where Author is "Pahlevan, N"

Lehmann, MK, Gurlin, D, Pahlevan, N, Alikas, K, Anstee, J, Balasubramanian, SV, Barbosa, CCF, Binding, CE, Bracher, A, Bresciani, M, Burtner, A, Cao, Z, Dekker, AG, Di Vittorio, C, Drayson, N, Errera, RM, Fernandez, V, Ficek, D, Fichot, CG, Gege, P, Giardino, C, Gitelson, AA, Greb, SR., Henderson, H, Higa, H, Rahaghi, AI, Jamet, C, Jiang, D, Jordan, TM, Kangro, K, Kravitz, JA, Kristoffersen, AS, Kudela, R, Li, L, Ligi, M, Loisel, H, Lohrenz, S, Ma, R, Maciel, DA, Malthus, TJ, Matsushita, B, Matthews, MW, Minaudo, C, Mishra, DR, Mishra, S, Moore, T, Moses, WJ, Nguyễn, H, Novo, EMLM, Novoa, S, Odermatt, D, O’Donnell, DM, Olmanson, LG, Ondrusek, M, Oppelt, N, Ouillon, S, Pereira Filho, W, Plattner, S, Verdu, AR, Salem, SI, Schalles, JF, Simis, SGH, Siswanto, E, Smith, B, Somlai-Schweiger, I, Soppa, MA, Spyrakos, E, Tessin, E, Van der Woerd, HJ, Vander Woude, A, Vandermeulen, RA, Vantrepotte, V, Wernand, M, Werther, M, Young, K and Yue, L 2023 GLORIA - A globally representative hyperspectral in situ dataset for optical sensing of water quality. Scientific Data, 10 (1). https://doi.org/10.1038/s41597-023-01973-y

Zolfaghari, K, Pahlevan, N, Simis, SGH, O'Shea, RE and Duguay, CR 2022 Sensitivity of remotely sensed pigment concentration via Mixture Density Networks (MDNs) to uncertainties from atmospheric correction. Journal of Great Lakes Research. https://doi.org/10.1016/j.jglr.2022.12.010

Pahlevan, N, Smith, B, Alikas, K, Anstee, J, Barbosa, CCF, Binding, CE, Bresciani, M, Cremella, B, Giardino, C, Gurlin, D, Fernandez, V, Jamet, C, Kangro, K, Lehmann, MK, Loisel, H, Matsushita, B, Hà, N, Olmanson, L, Potvin, G, Simis, SGH, VanderWoude, A, Vantrepotte, V and Ruiz-Verdu, A 2022 Simultaneous retrieval of selected optical water quality indicators from Landsat-8, Sentinel-2, and Sentinel-3. Remote Sensing of Environment, 270. 112860. https://doi.org/10.1016/j.rse.2021.112860

Zolfaghari, K, Pahlevan, N, Binding, CE, Gurlin, D, Simis, SGH, Verdu, AR, Li, L, Crawford, CJ, VanderWoude, A, Errera, R, Zastepa, A and Duguay, CR 2021 Impact of Spectral Resolution on Quantifying Cyanobacteria in Lakes and Reservoirs: A Machine-Learning Assessment. IEEE Transactions on Geoscience and Remote Sensing. 1-20. https://doi.org/10.1109/TGRS.2021.3114635

Pahlevan, N, Mangin, A, Balasubramanian, SV, Smith, BD, Alikas, K, Arai, K, Barbosa, CCF, Bélanger, S, Binding, CE, Bresciani, M, Giardino, C, Gurlin, D, Fan, Y, Harmel, T, Hunter, P, Ishikaza, J, Kratzer, S, Lehmann, MK, Ligi, M, Ma, R, Martin-Lauzer, FR, Olmanson, L, Oppelt, N, Pan, Y, Peters, S, Reynaud, N, Sander de Carvalho, LA, Simis, SGH, Spyrakos, E, Steinmetz, F, Stelzer, K, Sterckx, S, Tormos, T, Tyler, A, Vanhellemont, Q and Warren, M 2021 ACIX-Aqua: A global assessment of atmospheric correction methods for Landsat-8 and Sentinel-2 over lakes, rivers, and coastal waters. Remote Sensing of Environment, 258. 112366. https://doi.org/10.1016/j.rse.2021.112366

O'Shea, RE, Pahlevan, N, Smith, B, Bresciani, M, Egerton, T, Giardino, C, Li, L, Moore, T, Ruiz-Verdu, A, Ruberg, S, Simis, SGH, Stumpf, R and Vaiciute, D 2021 Advancing cyanobacteria biomass estimation from hyperspectral observations: Demonstrations with HICO and PRISMA imagery. Remote Sensing of Environment, 266. 112693. https://doi.org/10.1016/j.rse.2021.112693