Three-dimensional urban slum reconstruction from ENVISAT ASAR data

This study aims to investigate the probable of ENVISAT ASAR satellite and Google Earth data for three-dimensional (3-D) urban slum reform. The major objective of this study is to exploit 3-D automatic detection algorithm for urban slum in ENVISAT ASAR and Google Erath images using Fuzzy B-spline algorithm. The results present that the fuzzy algorithm is excellent for automatic detection of chaotic urban slum from its surrounding environment. The results expose that urban slums, road network, and infrastructures are impeccably categorized. The fuzzy B-spline delivers high accuracy with standard error of 0.0005 compared to Digital Train Data (DTM). The permutation of Fuzzy and B-spline is to reconstruct 3-D of urban slum. In conclusion, the fuzzy algorithm is the proper algorithm for chaotic urban slum automatic detection in ENVSIAT ASAR and Google Earth data.