Evaluation of digital elevation model using rational polynomial coefficient based on HR Pleiades satellite stereo imagery

In this paper, we analysed the geometric model characteristics based on rational polynomial coefficient (RPC) model using high resolution Pleiades satellite stereo images i.e., Pleiades 1A and 1B satellite sensors. 3D maps were generated for objects like trees near poles of power transmission lines using satellite stereo images. This study was very challenging due to weather condition, hilly and non-uniform terrain at Kota kina balu in East Malaysia. First we require the geometric accuracy of these two sensors for 3D mapping of the area of interest. Also we require accurate Digital elevation model for better height calculation of vegetation/trees near power poles. For these purposes, we evaluated the geometric accuracy of both Pleiades sensors i.e., 1A and 1B which is based on direct rational function model and inverse Rational Function model (RFM). The comparison was made based on RPC coefficients. Results shown that values of RPC coefficients for Pleiades 1A sensor are less as compared to the Pleiades 1B sensor. This shows that Pleiades 1A sensor can be used for monitoring the vegetation near poles of high transmission power lines based on the satellite stereo images.