Predicting occurrence of landslides using remote sensing techniques:
Landslides are one of the most damaging natural hazards in mountainous terrain.
Rocks are disintegrated and decomposed by the process of weathering. Weathered material soaked with rain water slides down due to gravity. This sudden downward slip movement of rock material is called landslide.
Landslides can occur due to:
-condition of soil
-moisture and
-angle of slope
Occurrence of landslides is particularly common in geodynamic sensitive belts.
The main factors triggering landslides are:
-heavy and prolonged rainfall
-cutting and deep excavation on slope for construction of buildings, roads, canals or mining activity without proper disposal of debries and
-earthquake shocks and tremors
Widespread deforestation for development activities and increasing population pressure has forced people to conduct agriculture on steeper slopes thereby aggravating occurrence of landslides in terrain of varying relief.
Prediction of the occurrence of a landslide in an area is essential to minimize the intensity of a landslide hazard.
Remote sensing images provide useful land use information that can be used in conjunction with GIS software along with other spatial factors to predict the occurrence of a landslide.
Remote sensing is mainly used to map the distribution of existing landslide location and factors that affect the occurrence of a landslide.
Satellite images can be used to recognise and interpret detailed geomorphic characteristics of large and small landslides and determine the likelihood of a landslide.
Current high resolution stereo SAR (Synthetic Aperture Radar) and optical images produce multiscale landslide inventory maps to improve mitigation.
Remote sensing techniques have been widely used to study characteristics of land surface due to advantage of repetitive data acquisition of a large area in a short time.
Spatial analysis using data derived from remote sensing techniques and other thematic map data helps in prediction and estimation of landslide hazard areas.
Satellite data can be used to derive land surface temperature and land use information.
Elevation and terrain slope can be determined from Digital Elevation Model (DEM) generated from aerial photographs using stereo correlation techniques.
Underground water level information can be estimated from the combination of the above data. From these data, simple algorithms are used to classify area into different risk zones.
All the risk maps are combined using spatial analysis and a final risk map is produced taking into account all the factors.
Thus, remote sensing techniques when integrated with GIS are an extremely useful tool to study potential landslide areas.
Landslides are one of the most damaging natural hazards in mountainous terrain.
Rocks are disintegrated and decomposed by the process of weathering. Weathered material soaked with rain water slides down due to gravity. This sudden downward slip movement of rock material is called landslide.
Landslides can occur due to:
-condition of soil
-moisture and
-angle of slope
Occurrence of landslides is particularly common in geodynamic sensitive belts.
The main factors triggering landslides are:
-heavy and prolonged rainfall
-cutting and deep excavation on slope for construction of buildings, roads, canals or mining activity without proper disposal of debries and
-earthquake shocks and tremors
Widespread deforestation for development activities and increasing population pressure has forced people to conduct agriculture on steeper slopes thereby aggravating occurrence of landslides in terrain of varying relief.
Prediction of the occurrence of a landslide in an area is essential to minimize the intensity of a landslide hazard.
Remote sensing images provide useful land use information that can be used in conjunction with GIS software along with other spatial factors to predict the occurrence of a landslide.
Remote sensing is mainly used to map the distribution of existing landslide location and factors that affect the occurrence of a landslide.
Satellite images can be used to recognise and interpret detailed geomorphic characteristics of large and small landslides and determine the likelihood of a landslide.
Current high resolution stereo SAR (Synthetic Aperture Radar) and optical images produce multiscale landslide inventory maps to improve mitigation.
Remote sensing techniques have been widely used to study characteristics of land surface due to advantage of repetitive data acquisition of a large area in a short time.
Spatial analysis using data derived from remote sensing techniques and other thematic map data helps in prediction and estimation of landslide hazard areas.
Satellite data can be used to derive land surface temperature and land use information.
Elevation and terrain slope can be determined from Digital Elevation Model (DEM) generated from aerial photographs using stereo correlation techniques.
Underground water level information can be estimated from the combination of the above data. From these data, simple algorithms are used to classify area into different risk zones.
All the risk maps are combined using spatial analysis and a final risk map is produced taking into account all the factors.
Thus, remote sensing techniques when integrated with GIS are an extremely useful tool to study potential landslide areas.
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