IMPROVED LARGE-SCALE SLOPE ANALYSIS ON MARS BASED ON CORRELATION OF SLOPES DERIVED WITH DIFFERENT BASELINES
The surface slopes of planetary bodies are important factors for exploration missions, such as landing site selection and rover manoeuvre. Generally, high-resolution digital elevation models (DEMs) such as those generated from the HiRISE images on Mars are preferred to generate detailed slopes with a better fidelity of terrain features. Unfortunately, high-resolution datasets normally only cover small area and are not always available. While lower resolution datasets, such as MOLA, provide global coverage of the Martian surface. Slopes generated from the low-resolution DEM will be based on a large baseline and be smoothed from the real situation. In order to carry out slope analysis at large scale on Martian surface based low-resolution data such as MOLA data, while alleviating the smoothness problem of slopes due to its low resolution, this paper presents an amplifying function of slopes derived from low-resolution DEMs based on the relationships between DEM resolutions and slopes. First, slope maps are derived from the HiRISE DEM (meter-level resolution DEM generated from HiRISE images) and a series of down-sampled HiRISE DEMs. The latter are used to simulate low-resolution DEMs. Then the high-resolution slope map is down- sampled to the same resolution with the slope map from the lower-resolution DEMs. Thus, a comparison can be conducted pixel-wise. For each pixel on the slope map derived from the lower-resolution DEM, it can reach the same value with the down-sampled HiRISE slope by multiplying an amplifying factor. Seven sets of HiRISE images with representative terrain types are used for correlation analysis. It shows that the relationship between the amplifying factors and the original MOLA slopes can be described by the exponential function. Verifications using other datasets show that after applying the proposed amplifying function, the updated slope maps give better representations of slopes on Martian surface compared with the original slopes.