Researchers use optical images to identify landslide hazards

A study published in remote sensing used optical multi-temporal remote sensing imagery to study the deformation characteristics of landslides and their evolution pattern. The analysis and identification of landslide risks contributes to their prevention and provides a basis for the early detection and investigation of similar incidents.

Study: Comprehensive remote sensing technology for landslide hazard and disaster chain monitoring in Beijing’s Xishan mining area. Image Credit: Alex Traveler /

Landslides: a geological hazard

Landslides are one of the most common and dangerous geological disasters on Earth. Human engineering activities and extreme climatic conditions have led to an increase in the frequency of landslides.

Landslides threaten the safety and property of residents due to their abrupt nature, rapid movements and strong concealment.

Landslide identification is essential to assess and manage landslide risk. Early detection of landslides can significantly reduce the number of potential victims. With the development of remote sensing technology, they can be identified by visually interpreting topographic surfaces and remote sensing images.

Remote sensing technology for landslide hazard identification

In recent years, remote sensing imagery has become more widespread and related technologies such as multi-temporal high resolution optical image analysis technology and interformetric synthetic aperture radar (InSAR) have seen substantial applications in the identification of geological risks.

Multi-temporal remote sensing technology

High-resolution multi-temporal optical images are ideal for identifying geohazards with visible deformation due to their wide geographic coverage and abundant storage.

InSAR Technology

In regions with high surface coherence and modest deformation rates, InSAR technology excels in identifying geological catastrophes. It is also suitable for detecting large-scale geological disasters.

Study area: Xishan mining area

The Xishan Coal Mines in Beijing, China operated for nearly 1,000 years until 2008 when all coal mines were closed. However, the stability of the mountain was already affected by underground mining, especially due to the operations of some small coal companies which included shallow mining depths, high mining intensities and high disturbances, resulting in landslides and other geological hazards.

Landslides and their induced hazard chains are highly catastrophic in the mountainous region, but they are difficult to detect due to high concealment.

Beijing is the cultural and political center of China, and the Xishan mining district is densely populated. However, few researchers have studied landslides in this region; therefore, it is crucial to identify geological and other potential hazards.

Use of optical and InSAR imagery for identification of landslide and hazard evolution patterns

In the study area, 19 landslides and 32 cave-ins were investigated. Researchers collected multi-temporal remote sensing observations in the Xishan mining area and identified landslides by extracting deformation data from InSAR time series and optical images.

They extracted the location of collapses and tension cracks induced by the swelling of the lower slope and estimated the changes in geomorphology, vegetation and slope. SAR data and remote sensing imagery were compared to differentiate texture and tone between landslides and their surrounding areas.

Finally, the researchers categorized the pattern of landslide evolution and examined risk chain triggers and disaster patterns.

Important Study Findings

The four stages of landslide development observed in the Xishan mining area include initial deformation, rear part failure and joining, slope face swelling and collapse, and landslide creep. The complete evolution process takes more than ten years. During these steps, surface deformation was evident.

Landslides are classified into three categories based on their strata of development, sliding properties and stage of deformation.

The first type is triggered by the collapse of a high level rock mass. It forms in the upper layers of the coal stratum. This landslide continues to deform after its collapse. The rupture of the goaves causes the second and third types of landslides.

The second type occurs mainly in the underlying layers of coal strata. The majority of these landslides are in the early deformation stage. The third type develops in coal strata. These landslides are in the creeping stage and deform much faster than the second type.

The rainfall and topography of the Dongjianggou and Anzigou ditches are conducive to debris flow. Therefore, most landslides in this region are vulnerable to a chain of goaf-landslide-debris flow hazard in the event of heavy rainfall.

Surface and subsurface disturbances in a goaf can be severe, and their underground systems are complicated. In these places, landslides and chain disasters can occur in addition to subsidence and cracks in the ground.

Identifying geohazard areas using multi-platform remote sensing technologies is crucial to reducing and preventing damage from landslides and other geohazards in these areas. Additionally, remote sensing can be accompanied by a comprehensive monitoring system that collects and verifies data using space, air and ground observations.


Jiao, R., Wang, S., Yang, H., Guo, X., Han, J., Pei, X. & Yan, C. (2022). Comprehensive remote sensing technology for landslide hazard and disaster chain monitoring in Beijing’s Xishan mining area. remote sensing.

Disclaimer: The views expressed here are those of the author expressed privately and do not necessarily represent the views of Limited T/A AZoNetwork, the owner and operator of this website. This disclaimer forms part of the terms of use of this website.

Previous Survey: YouTube, blogs and Reddit are where Americans turn for cryptocurrency investing advice
Next Call for photographers and digital artists for images reflecting NH's diverse communities