ABSTRACT
The surface slopes of planetary bodies must be considered when carrying out exploratory missions such as landing site selection and rover manoeuvres. Generally, high-resolution digital elevation models (DEMs) such as those generated from High Resolution Imaging Science Experiment (HiRISE) images on Mars are favoured, as they result in detailed slopes with high-fidelity terrain features. However, high- resolution datasets normally only cover small areas and are not always available, whereas lower-resolution datasets, such as those obtained using the Mars Orbiter Laser Altimeter (MOLA), provide global coverage of the Martian surface. Slopes generated from low-resolution DEMs are based on a large baseline and have been smoothed relative to the real situation. To alleviate the slope smoothness problem to carry out large-scale slope analysis of the Martian surface using low-resolution data, this chapter presents correlated slope analysis at different scales using multiple-source DEMs. DEMs from different sources often show inconsistencies due to differences in sensor configurations, data acquisition periods and production techniques. Therefore, this chapter first presents a co-registration method for multiple-source DEMs. Next, slope correlation analysis is carried out using DEMs with different resolutions, and a slope correlation function with respect to different baselines is proposed. The validity and feasibility of the slope correlation function are verified using multiple-source datasets containing HiRISE, Context Camera (CTX), High Resolution Stereo Camera (HRSC) and MOLA data. The results indicate that the proposed slope function improves the accuracy of the slopes generated from low-resolution DEMs by about 50%.
