Landslides are a major class of disaster in equatorial alpine regions.2,3 Better danger zone classification ("landslide susceptibility zonation") could help keep people out of the riskier areas. Better landslide prediction could save human lives and help preserve local economic capacity. Neither problem is easy, however. The ability to fly over the same point several times per day could make it possible to consider in more detail -- and in a more timely manner -- some factors that are currently neglected or underutilized:
- local precipitation45
- hydrological changes
- "slumps" - slow earth movement that might presage faster movement
- herds of animals that could precipitate slides by grazing on unstable slopes6
One of Project Persephone's medium-term R&D activities is to support the launch of remote-sensing satellites into equatorial low Earth orbit? (ELEO) for disaster warning, environmental monitoring and emergency communications. ELEO makes it possible to overfly the same point every 90 minutes, which might significantly improve on existing landslide prediction and disaster response in remote areas. Even Cubesat-size satellites might be able to detect changes in river water color that point to an increased likelihood of mountainside mud flows.7
One of the current activities is the equatorial landslide newsfeed.
1 Two Lucky People: Memoirs, Milton and Rose Friedman, University of Chicago Press, 1999; ISBN 0226264157 ⇑
2 "Landslide deaths much higher than thought - study", 15 Aug 2012, Reuters: "identified hotspots - among them [...] Indonesia and mountains from Mexico to Chile." ⇑
4 The potential for nanosatellies in monitoring heavy rainfall in the equatorial band is being explored in recent work, see e.g., "Nanosatellites for earth environmental monitoring: The MicroMAS project", Blackwell, W. et al. IEEE Xplore DOI 10.Micro Rad?.2012.6185263 ISBN 978-1-4673-1468-8 in conf. proc of 2012 12th Specialist Meeting on Microwave Radiometry and Remote Sensing of the Environment (Micro Rad?) ⇑
6 Detection of herds might be difficult; detection of effects of grazing is, however, already being investigated, see e.g., "Identifying regional-scale self-organized patchiness in ecosystems using remote-sensing imagery", funded by Earth and Space Foundation ⇑
7 See, e.g., Charybdis: The Next Generation in Ocean Colour and Biogeochemical Remote Sensing, Christopher Lowe, Malcolm Macdonald, Steve Greenland, David Mckee, presented at Small Satellite Conference 2012 ⇑
- Clerici, A; Perego, S; Tellini, C; Vescovi, P (2002). "A procedure for landslide susceptibility zonation by the conditional analysis method". Geomorphology 48 (4): 349. doi:10.1016/S0169-555X(02)00079-X
- Metternicht, G; Hurni, L; Gogu, R (2005). "Remote sensing of landslides: An analysis of the potential contribution to geo-spatial systems for hazard assessment in mountainous environments". Remote Sensing of Environment 98 (2-3): 284. doi:10.1016/j.rse.2005.08.004
- De La Ville, Noemi; Chumaceiro Diaz, Alejandro; Ramirez, Denisse (2002). "Remote Sensing and GIS Technologies as Tools to Support Sustainable Management of Areas Devastated by Landslides". Environment, Development and Sustainability 4 (2): 221. doi:10.1023/A:1020835932757.
- Fabbri, Andrea G.; Chung, Chang-Jo F.; Cendrero, Antonio; Remondo, Juan (2003). "Is Prediction of Future Landslides Possible with a GIS?". Natural Hazards 30 (3): 487. doi:10.1023/B:NHAZ.0000007282.62071.75.
- Lee, S; Talib, Jasmi Abdul (2005). "Probabilistic landslide susceptibility and factor effect analysis". Environmental Geology 47 (7): 982. doi:10.1007/s00254-005-1228-z.
- Ohlmacher, G (2003). "Using multiple logistic regression and GIS technology to predict landslide hazard in northeast Kansas, USA". Engineering Geology 69 (3-4): 331. doi:10.1016/S0013-7952(03)00069-3