The fine scale prediction of Urban Density (UD) for inundation analysis using Landsat OLI image : a case study of Nakhon Sawan, Thailand

Abstract

We studied the fine scale prediction method of Urban Density (UD) for inundation analysis using Landsat OLI image, in Nakhon Sawan, Thailand. A generalized additive model (GAM) and model selection using Akaike's Information Criteria (AIC) in two different seasons (March and November) were conducted. The result showed as follows. 1) The explanation power of the models using the explanation variables calculated by Landsat OLI image in November were relatively higher than that of the models in March. 2) UD in 30m grid squares was strongly positively related to Urban Index, At-satellite Brightness Temperature, and Color Complexity which was defined as the indicator of complexity in color distribution pattern of satellite image in this paper. The coefficient of determination R² of the best model was 0.649. The result suggest that UD can be predicted in the decent accuracy for inundation analysis in Nakhon Sawan without much effort and cost. This prediction method cloud be applied the urban areas threatened with flood risk in the world.