Landslide Monitoring with Citizen Science

/Landslide Monitoring with Citizen Science
Landslide Monitoring with Citizen Science2018-10-30T12:37:49+00:00


The extreme weather events have increased considerably with the rise of human population and climate change. Therefore natural hazards such as flooding, wildfire, droughts, landslides etc. have also increased.


Landslide is perhaps the most dangerous natural hazard because it occurs frequently throughout the World and cause serious economic losses and also life threatening situations.


CitSci (citizen science) is participation of non-professionals to scientific processes voluntarily for different tasks (e.g. data collection, interpretation, analysis, quality control, hypothesis generation and testing, etc.).


The project which use CitSci in landslide researches are increasing, also because conventionally researchers rely heavily on the observations of local communities for collection of landslide data. Sometimes they are even the only available data for performing the analyses and identifying the processes.


The LaMA (Landslide Monitoring App) developed at Hacettepe University aims at collecting regional landslide data by citizen scientists, so that crucial information on landslides such as the time of occurrence, type and location can be collected. These types of information are extremely important for the characterization of landslides, understanding their mechanisms and thus predict the future.


The landslide characterization, i.e. landslide susceptibility mapping, hazard and risk assessment, is of great importance for the risk and disaster management as well. The density (frequency) and the quality of spatial and temporal data required for the regional landslide characterization should be high to reduce the uncertainties and develop accurate models by researchers. With the development of mobile and geospatial technologies and the rise of citizen science, the data needed for regional landslide assessment and risk management can be collected more frequently and accurately. Collecting data with conventional methods is expensive and sometimes open to some errors sourced from operational difficulties. In addition, to apply a cross-check process on the data collected with conventional methods is almost impossible. Use of CitSci has serious advantageous to eliminate these problems because it is possible to collect much more data and observations from the same event and/or location.