anders_knudby_profile
Anders Knudby
Assistant Professor

Department of Geography
Robert C. Brown Hall (RCB 6228)
Phone: 778.782.4556

aknudby@sfu.ca

Education


Visiting Fellow (2010-2011), CCRS, Ottawa

Ph.D. Geography (2009), University of Waterloo

M.Sc. Geography (2001), University of Copenhagen

B.Sc. Geomatics (1998), University of Copenhagen

Research Interests


My interests include a broad mix of basic and applied remote sensing, spatial ecology and predictive modeling. Recent and ongoing work includes:

Automated processing of coarse-scale remote sensing data for the production of global environmental data sets. Due to the very large volume of remote sensing data produced today, highly automated processing is essential in order to turn all this valuable information into knowledge. My recent work for the Canadian government in this area has focused on automated detection of clouds in AATSR and MERIS data. These two sensors are precursors for instruments on ESA’s Sentinel-3 satellites, to be launched in 2013.

Spatial predictive modeling works by combining two things: 1) maps of environmental variables, and 2) statistical models that quantitatively relate those variables to a subject of interest. The result of that combination is a map of that subject of interest, which often cannot otherwise be mapped. Examples of my recent and ongoing work includes mapping the species richness and biomass of coral reef fishes, as well as indicators of coral reef resilience, for the Fiji Program of the Wildlife Conservation Society, and mapping the locations of deep-sea sponges and corals in collaboration with the Canadian Department of Fisheries and Oceans.

Teaching


Geog 253 – Introduction to Remote Sensing

Geog 353 – Advanced Remote Sensing

Geog 453 – Theoretical and Applied Remote Sensing

Geog 653 – Remote Sensing of Environment

Publications


Knudby, A., Latifovic, R., and Pouliot, D., 2011, “A cloud detection algorithm for AATSR data, optimized for daytime observations in Canada“, Remote Sensing of Environment 115(12), pp. 3153-3164.

Knudby, A., Roelfsema, C., Lyons, M., Phinn, S., and Jupiter, S., 2011, “Mapping fish community variables by integrating field and satellite data, object-based image analysis and modeling in a traditional Fijian fisheries management area“, Remote Sensing 3(3), pp. 460-483.

Knudby, A. and Nordlund, L., 2011, “Remote sensing of seagrasses in a patchy multi-species environment”, International Journal of Remote Sensing 32(8), pp. 2227-2244.

Knudby, A., LeDrew, E., and Brenning, A., 2010, “Predictive mapping of reef fish species richness, diversity and biomass in Zanzibar using IKONOS imagery and machine-learning techniques”, Remote Sensing of Environment 114(6), pp. 1230-1241.

Knudby, A., Brenning, A., and LeDrew E., 2010, “New approaches to modelling fish-habitat relationships”, Ecological Modelling 221(3), pp. 503-511.

Knudby, A., Newman, C., Shaghude, Y., and Muhando, C., 2010, “Simple and effective monitoring of historic changes in nearshore environments using the free archive of Landsat imagery”, International Journal of Applied Earth Observation and Geoinformation 12, pp. S116-S122.

Knudby, A., Newman, C., and LeDrew, E., 2008, “Remote sensing for studies of the local spatial distribution of coral reef fishes”, proceedings of the International Coral Reef Symposium, 7-11 July 2008, Ft. Lauderdale, USA, pp. 631-635.

Knudby, A., LeDrew, E., and Newman, C., 2007, “Progress in the use of Remote Sensing for Coral Reef Biodiversity Studies”, Progress in Physical Geography 31(4), pp. 421-434.

Newman, C., Knudby, A., and LeDrew, E., 2007, “Assessing the effect of zonation on live coral cover using multi-date IKONOS satellite imagery”, Journal of Applied Remote Sensing, 1 (2007).

Knudby, A., and LeDrew, E., 2007, “Measuring Structural Complexity on Coral Reefs”, proceedings of the American Academy of Underwater Sciences 26th Symposium, 5-10 March 2007, Miami, USA, pp. 181-188.

Knudby, A., 2004, “An AVHRR-based model of groundnut yields in the Peanut Basin of Senegal”, International Journal of Remote Sensing, 25, 3161-3175.