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2021 | OriginalPaper | Buchkapitel

Landslides Hazard Mapping Using High-Resolution Satellite Data

verfasst von : Saloni Jain, Rakesh Khosa, A. K. Gosain

Erschienen in: Geohazards

Verlag: Springer Singapore

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Abstract

Landslides are one of the severe natural hazards induced by heavy rainfall, deforestation, slope failure and urban expansion. It can lead to significant loss of life and property in hilly and gully regions. Field studies that identify and map landslides are expensive and time-consuming as it includes the cost of the survey, travelling, workforce, and instrument. Although progression in technology and availability of high-resolution remote sensing data has now made it possible to identify landslides (satellite images and aerial photographs), accessibility to high-resolution satellite data is still an expensive and tedious procedure. Several studies have conducted in a GIS environment to map landslide zones, but the resolution of the open-source data is commonly coarse (30 m), which adds to the uncertainty of the outcome. In this study, application of the appropriate rule set with object-based image analysis (OBIA) technique has been used to identify landslides zones, through a combination of spectral, textural and geometrical properties of imagery and topographic data. It overcomes the shortcomings induced by pixel-based classification. For the current study, High spatial resolution data such as Google Earth imagery and CartoDEM (30 m) has been used. This approach shows an excellent prospect for quick and near-to-actual assessment of landslides zones which are generally induced by extreme rainfall events in the hilly regions of India. The methodology used has the potential to facilitate more reliable disaster management strategies. This study shows the potential of open-source data and emerging technology in the field of landslide assessment.

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Metadaten
Titel
Landslides Hazard Mapping Using High-Resolution Satellite Data
verfasst von
Saloni Jain
Rakesh Khosa
A. K. Gosain
Copyright-Jahr
2021
Verlag
Springer Singapore
DOI
https://doi.org/10.1007/978-981-15-6233-4_7