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Anderson, DM, SFE Boerlage, MB Dixon (Eds). Harmful Algal Blooms (HABs) and Desalination: A Guide to Impacts, Monitoring, and Management. Paris, Intergovernmental Oceanographic Commission of UNESCO, 2017. 538pp. (IOC Manuals and Guides #78)

Kudela RM, Palacios SL, Austerberry DC, Accorsi EK, Guild LS, Torres-Perez, J, 2015 . Application of hyperspectral remote sensing to cyanobacterial blooms in inland waters. Remote Sensing of Environment 167 (2015) 196–205.

Palacios, SL, Kudela RM, Guild LS, Negrey KH, Torres-Perez J, and Broughton J, 2015. Remote sensing of phytoplankton functional types in the coastal ocean from the HyspIRI Preparatory Flight Campaign. Remote Sensing Environment, 167: 269-280.

Thompson, D. R., Seidel, F. C., Gao, B. C., Gierach, M. M., Green, R. O., Kudela, R. M., & Mouroulis, P. 2015. Optimizing Irradiance Estimates for Coastal and Inland Water Imaging Spectroscopy. Geophysical Research Letters 42(10): 4116-4123.

Jacox, MG, CA Edwards, M Kahru, DL Rudnick, and RM Kudela. 2014. Improving remote estimation of primary productivity in the southern California Current System.  Deep-Sea Research II, doi:10.1016/j.dsr2.2013.12.008

Kahru, Mati, et al. 2014. Evaluation of satellite retrievals of chlorophyll-a in the California Current. Remote Sensing 2014, 6, 8524-8540.

Kahru, M, MG Jacox, ZP Lee, RM Kudela, M Manzano-Sarabia, and BG Mitchell. 2014. Optimized multi-satellite merger of primary production estimates in the California Current using inherent optical properties. J. Marine Systems, http://dx.doi.org/10.1016/j.marsys.2014.06.003.

Ryan, JP, et al. 2014. Application of the hyperspectral imager for the coastal ocean to phytoplankton ecology studies in Monterey Bay, CA, USA. Remote Sensing 2014, 6, 1007-1025; doi:10.3390/rs6021007

Seltenrich, N. Remote sensing applications for environmental health research. Environmental Health Perspectives, October 2014, vol 122 No. 10.

Jacox, M. G., C. A. Edwards, M. Kahru, D. L. Rudnick, and R. M. Kudela (2013), The potential for improving remote primary productivity estimates through subsurface chlorophyll and irradiance measurement, Deep-Sea Res. II, doi:10.1016/j.dsr2.2013.12.008.

Harvey, J, et al, 2012. Robotic sampling, in situ monitoring and molecular detection of marine zooplankton. Journal of Experimental Marine Biology and Ecology 413 (2012), 60-70.

Peacock, MB, and RM Kudela, 2012. A method for determining alkaline phosphatase activity in marine phytoplankton using spectrofluorometry. Journal of Microbiological Methods. doi:10.1016/j.mimet.2012.03.007

McGaraghan, AR, and RM Kudela, 2012. Estimating labile particulate iron concentrations in coastal waters from remote sensing data. Journal of Geophysical Research 117, C02004, doi:10,1029/2011JC006977

Anderson, CR, et al., 2011. Detecting toxic diatom blooms from ocean color and a regional ocean model. Geophysical Research Letter 38, L04603, doi:10.1029/2010GL045858. Aux 1, aux 2, aux 3.

Benoit, MD, Kudela RM, and AR Flegal, 2010. Modeled trace element concentrations and partitioning in the San Francisco Estuary, based on suspended solids concentrations. Environmental Science and Technology.

Palacios, S., T. Peterson, and R. Kudela, 2009. Development of synthetic salinity from remote sensing for the Columbia River plume, Journal of Geophysical Research, 114, C00B05, doi: 10.1029/2008JC004895.

Lane, J., P Raimondi, and RM Kudela, 2009. Development of a logistic regression model for the prediction of toxigenic Pseudo-nitzschia blooms in Monterey Bay, California. Marine Ecology Progress Series, 383, 37-51.

Anderson, CR, Siegel, DA, Kudela, RM and MA Brzezinski, 2009. Empirical models of toxigenic Pseudo-nitzschia blooms: Potential use as a remote detection tool in the Santa Barbara Channel. Harmful Algae, 8, 478-492