Research
My research program extracts, monitors, and analyzes impervious surfaces (IS) from remotely sensed imagery. Under global urbanization (i.e. physical growth of urban land areas), evidence indicates anthropogenic IS, such as concrete and asphalt, are expanding at increasing rates under low density land development. IS modify natural fluxes and flows of water, air and other elements upon and through the pedosphere (i.e. earth’s outermost layer) with associated negative physical, chemical and biological effects documented upon the atmos-, bio-, and hydro-spheres. Accordingly, IS area/coverage is a key environmental indicator and critically sensitive input parameter within models predicting urbanization effects – both of which form the basis of environmental policy attempting to sustain natural systems perturbed by on-going urbanization. Further understanding the dynamics through time and space of IS and related phenomena is requisite to optimize, improve the certainty and ultimately the efficacy of such policy. My PhD dissertation contributes to this mandate by developing and assessing IS extraction and change detection methods, techniques and algorithms striving to improve synoptic and accurate monitoring of IS. Applied and pure research integrates object- and sub-pixel-based image and geospatial analyses with satellite sensor imagery and datasets at varying scales and resolutions under germane factors of land cover/use context, scale, accuracy, and image structure. Geo-spatial technologies of remote sensing analyses, geographic information science/systems (GIS), geomatic computation/statistics, and decision support system science are employed.
Concurrent Research Themes
Down and up scaling-based digital image extraction of land covers, uses, and features.
Hybrid object-oriented and sub-pixel land cover classification.
Digital image structure effects upon sub-pixel mapping accuracies.
Geomatics/geo-spatial analyses for bio-energy resource assessment and quantification.
Select Peer-Reviewed Publications
Luciani, P.D. and Chen, D. Context-based impervious surface extraction incorporating regression tree models and textural transformations. Remote Sensing of Environment. Submitted.
Luciani, P.D., Li, J.Y. and Banting, D. (2011). Distributed urban stormwater modeling within GIS integrating analytical probabilistic hydrologic models and remote sensing digital image analysis. Water Quality Research Journal of Canada. 46 (3): 183–199
Luciani, P.D. and Chen, D. 2011. The impact of image and class structure upon sub-pixel mapping accuracy using the pixel-swapping algorithm. Annals of GIS. 17 (1): 31–42. http://dx.doi.org/10.1080/19475683.2011.558022
Chen, D., Liu, W., Tian, J., and Luciani, P.D. 2009. Evaluating ecological and environmental impact of urbanization in the Greater Toronto Area through multi-temporal remotely sensed data and landscape ecological measures. In B. Jiang and X. Yao. Ed. Geospatial Analysis and Modeling of Urban Environment. Springer Press: New York, NY. http://personal.georgiasouthern.edu/~jtian/Geospatial_Analysis_Modeling.pdf
James Y. Li, Ching Lo, Peter D. Luciani, Angelune Des Lauriers, Kevin Sze, Jiang Shao, Wayne Komer, Ken Wilkinson, David Truen, and Rod Anderton. 2009. Environmental Factors Affecting Methoprene Concentrations for West Nile Virus Control in a Storm Sewer System. Water Quality Research Journal of Canada. 44 (2): 141–150. http://www.cawq.ca/journal/temp/article/422.pdf
Teaching Interests
I enjoy conveying, sharing and incubating knowledge and wisdom in the domains of: Geographic information science/systems; remote sensing analyses; water resource management; and environmental planning, impact assessment and analyses.
Teaching Dossier
Introduction to Geographic Information Science (GPHY 243) - Winter 2011.
Supervisor: Dr. Dongmei Chen
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