Three-dimensional building change detection using object-based image analysis (case study: Tehran)

Natural disasters such as earthquakes and floods together with the urban sprawl conducted by increasing the population make multi-temporal changes in building areas. Destruction, buildings' renovation, and constructing new buildings are the main changes of the urban areas that should be detected to update three-dimensional city models. The results of performing three-dimensional changes detecting of high altitude objects such as buildings are more close to reality than the two-dimensional methods. In this study, a three-dimensional changes detection method is proposed based on digital elevation models (DEMs). In the first step of this proposed method, the normalized digital surface model (nDSM) is generated for timely datasets. Then, object-based image analysis is utilized by performing segmentation followed by the structural classification of DEMs. Differencing and comparing the multi-temporal classification maps as the third step of the proposed algorithm led to analyzing the occurred changes. The obtained results are evaluated in an urban area in Tehran, Iran, in a 9-year time interval. These results represent -9.7% decreasing rate in low-rise buildings and also -1.37% decreases in the ground. Moreover, the class of high-rise buildings increased for +16.4% which conforms to making new constructions in addition to the renovation of low-rise buildings. According to the area analyzing of the changes, 4.8% of the investigated study area has new constructions, 3.05% has buildings' renovation, and 3.89% has destruction in that 9-year period.