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FOR URBAN LANDCOVER CHANGE DETECTION OVER STOCKHOLM BETWEEN 1986 AND 2004

The overall objective of this research is to detect new urban areas over Stockholm Region between 1986 and 2004 using multitemporal remote sensing. Two SPOT images acquired on 13 of June 1986 and 29 of July 2004 were used for changed detection. Three change detection methods were tested for this purpose: image differencing, principal component analysis and change vector analysis using normalised difference vegetation index and brightness index. The results showed that image differencing using the red bands and second principle components performed better in detecting new urban features than change vector analysis (the overall accuracies: 89%, 87% and 83% respectively & kappa: 0.77, 0.74 and 0.67). Even though overall accuracies are all above 80%, the kappa coefficients were much lower indicating substantial amount of omission and commission errors presented in the change maps.