Print Email Facebook Twitter Remotely sensed small reservoir monitoring: A Bayesian approach Title Remotely sensed small reservoir monitoring: A Bayesian approach Author Eilander, D.M. Contributor Van de Giesen, N.C. (mentor) Annor, F.O. (mentor) Iannini, L. (mentor) Faculty Civil Engineering and Geosciences Department Water Management Programme Water Resources Date 2013-04-25 Abstract A new semi-supervised `growing' Bayesian classifier for small reservoir delineation has been developed and is tested with Radarsat-2 data for reservoirs in the semi-arid Upper East Region of Ghana. The classifier reduces the confusion error to the land-water boundary pixels, can readily be extended with auxiliary information and has a high degree of automation. Results indicate that the algorithm is able to delineate open water from SAR imagery for different weather and environmental conditions. As such, the algorithm allows for remotely sensed operational monitoring of small reservoir storages. Subject remote sensingBayesian classificationBayesian classifiersmall reservoirsSARpolarimetry To reference this document use: http://resolver.tudelft.nl/uuid:002968b0-e81b-45a3-8aec-22fc38407308 Embargo date 2013-05-13 Part of collection Student theses Document type master thesis Rights (c) 2013 Eilander, D.M. Files PDF DMEilander_mscThesis_2013.pdf 3.52 MB Close viewer /islandora/object/uuid:002968b0-e81b-45a3-8aec-22fc38407308/datastream/OBJ/view