Several studies have been done on landslides in many countries; remote sensing is a vital key in investigating and monitoring landslides. Remote sensing images are increasingly used in mapping and monitoring methods. Landslides prediction using ground monitoring techniques proves to be hard and tedious. More reliable landslide inventory maps have been developed based on stereo images from SAR. The various application of remote sensing on landslides include:
1. Landslide mapping
Landslide maps can be as simple as those maps that use the location of old landslides to indicate potential instability or as complex as maps applying probabilities based on variables such as rainfall, slope angle, soil type, and levels of earthquake shaking. Several types of maps are used to describe and predict landslide hazards. They include:
- Landslide inventory maps such as the US landslide inventory map
- Landslide susceptibility maps such as Susceptibility to Deep-seated landslides in California
- Potential landslide maps such as NASA Global view of Landslide susceptibility
2. Landslide detecting
Various factors can trigger landslides. They include intense or prolonged rainfall, rapid snowmelt, earthquakes, volcanic eruptions, mining, and cutting slopes for road development. Because it is time-consuming and expensive to develop landslide inventories using in-situ measurement, remote sensing data and tools can efficiently develop landslide inventory maps. Advanced remote sensing, spatial analysis techniques, and high-resolution satellite images help develop more reliable landslide detection maps.
3. Landslide analysis
Landslide disasters require a systematic and objective assessment of the multi-landslide hazards, which entails different characteristics and casual factors of hazard and their spatial, temporal, and size probabilities. Remotely sensed data gives several important factors used in developing landslide hazard zones. In general, landslide hazard analysis is done using aerial photography and remotely sensed images. High-resolution spatial data for factors associated with landslide hazards is important for effective disaster analysis.
4. Landslide monitoring
The best method to reduce the impact of landslide hazards and improve risk management is through landslide monitoring and planning. Landslide monitoring includes developing landslide inventory, landslide susceptibility maps, and conducting a landslide hazard analysis. In addition, landslide monitoring entails comparing the speed of debris movement, rate of slope movement, surface topography concerning landslide conditions from different landslide occurrences to assess the activity of a landslide. Therefore, remote sensing data and techniques are used for in-depth hazard mapping and monitoring due to their extensive observation coverage and frequency, especially for high mountainous regions.
5. SAR
SAR data have been used widely in landslide research due to the broad coverage and high spatial resolution and the ability to continue operating under all weather conditions. The satellite SAR data used include archived ERS and Envisat ASAR, PALSAR.
6. Optical remote sensing
Optical remote sensing images were mainly used to generate landslide inventory with long time series of Landsat TM, ASTER, and Rapid Eye in consideration from 1986 to 2016
7. Light detecting and ranging (LiDAR)
Multi-temporal LiDAR images and Orthophotos can be analyzed to establish landscape changes caused by an active landslide.
