Hackthon project Overview Novel method to detect landslides & boulders on the Moon: Using Chandrayaan images Landslides are mass movement rocks, debris of material downwards along the slope under the influence of gravity triggered by multiple geological activities. On Moon, there are plenty of surface with steep slope which are vulnerable to landslides and boulder falls. The identification of landslides and boulder fall are crucial because they indicate information about the recent activities undergone. Through this project, develop a novel algorithm using the Chandrayaan 1, 2 images to detect the landslide and boulder falls. The landslide occurs in wide range of size and extent and their pattern of occurrence is unpredictable. The Chandrayaan images provides a wide range (latitude, longitude) of coverage and using those images, the landslide and boulder fall presence need to be detected. The problem statement mentions a “Novel” algorithm, to detect the landslides means: the algorithm should show some novelty in landslide detection from the conventional or previous existing landslide detection techniques. The algorithm should also detect individual boulders in the given image and provide statistics like diameter or length and other statistics. After detection, the algorithm should be capable to decode the source for the landslide and provide vital information about it. The most challenging task is to look for signature and pattern in landslide and boulder fall and use it to highlight the most active region. Overall, the algorithm should provide new information about the landslide & boulder fall once it is detected.
Objective: Identify the landslides and boulders from given Chandrayaan images. Describe the novelty in landslides identification from other conventional methods. Describe the novelty in detecting individual boulders from images. Primarily the algorithm should work on any regions on the Moon. Expected Outcomes: An annotated map/image with clear marks of landslides, boulders. Details about individual landslides – their geometry, their temporal occurrence. Details about each boulder – their length, diameter. Novelty in landslide detection from other conventional methods. Novelty in detecting boulders and classifying them. A detailed explanation for the detection of landslides and boulder falls over the given region. Dataset Required: Chandrayaan-1/2 – Terrain Mapping Camera (TMC) Chandrayaan-2 – Terrain Mapping camera derived Digital Terrain Model (DTM) Chandrayaan-2 – Optical High Resolution Camera (OHRC) Suggested Tools/Technologies: QGIS (open source) ArcMap Any other open source/licensed software’s