Contextualizing community-based landslide risk reduction: an evolutionary perspective

Raška, Pavel

doi:10.1007/s10346-018-1099-5

Cited by 12 publications

(4 citation statements)

References 56 publications

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“…In a developed country perspective, for example in Italy, it was found that the landslide-exposed communities were less aware of the disaster risk (Calvello et al, 2016), did not consider landslides as a threat and were less unwilling to participate in prevention activities (Gravina et al, 2017). In all these case studies in an urban hill context, the common recommendations to address landslide disasters were focused on developing landslide early warning systems, initiating communitybased DRR activities (Raška, 2019), integrating land use planning, understanding social vulnerability and increasing communications between communities at risk and government agencies (Klimeš et al, 2019;Antronico et al, 2020). This proves that the findings from the urbanised hill communities in Bangladesh are comparable with other developing and developed nations globally.…”

Section: Landslide Vulnerability Of the Rohingya Refugeesmentioning

confidence: 99%

The root causes of landslide vulnerability in Bangladesh

Ahmed

2021

Landslides

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Communities living in the Chittagong Hill Districts (CHD) of Bangladesh recurrently observe landslide disasters during the monsoon season (June–September). CHD is primarily dominated by three distinct groups of hill communities, namely, urbanised hill (Bengali), indigenous tribal and stateless Rohingya refugees. Landslide vulnerability amongst them is complex and varies between physical, social, economic, environmental, institutional and cultural dimensions. This study aims to understand driving forces of landslide disasters in the region by emphasising human factors. Data from the three contrasting communities were collected through participatory workshops, in-depth interviews and fieldwork observation. The participants were local people and landslide experts who were purposefully selected from five case study communities in the CHD. They ranked different socio-economic problems, identified causes of landslides and proposed landslide mitigation action plans. Results suggest that the urbanised Bengali and Rohingya refugee communities are highly vulnerable to landslides. The urbanised hill communities largely deal with poverty, social injustice, lack of planning regulations and illegal hill cutting issues, whereas the Rohingya refugees’ predominant constraints are linked to the ongoing genocide and state-sponsored violence in Myanmar hindering their sustainable repatriation, and their protracted living conditions in Bangladesh. The indigenous tribal communities are comparatively resilient to landslides due to their unique history, traditional knowledge, cultural heritage and lifestyle. Landslides in the CHD should be characterised as socio-natural hazards since the components of landslide disasters are profoundly intertwined with the culture–conflict–corruption nexus.

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Section: Landslide Vulnerability Of the Rohingya Refugeesmentioning

confidence: 99%

The root causes of landslide vulnerability in Bangladesh

Ahmed

2021

Landslides

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“…They pose a serious threat to people, properties and the environment in many areas. Many researchers are committed to wide area landslide detection, providing essential data support for landslide hazard mitigation and prevention [3][4][5].…”

Section: Introductionmentioning

confidence: 99%

Wide Area Detection and Distribution Characteristics of Landslides along Sichuan Expressways

Chen

Zhang

et al. 2022

Remote Sensing

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Wide area landslide detection is a major international research hotspot in the field of geological hazards, and the integration of multi-temporal optical satellite images and spaceborne interferometric synthetic aperture radar (InSAR) appears to be an effective way to realize this. In this paper, a technical framework is presented for wide area landslide detection: (i) multi-temporal satellite optical images are used to detect landslides with distinguishable geomorphological features; (ii) Generic Atmospheric Correction Online Service (GACOS) assisted InSAR stacking is employed to generate annual surface displacement rate maps in radar line of sight using satellite SAR images from both ascending and descending tracks, which are in turn utilized to automatically detect active landslides from ground motion using hotspot analysis, and (iii) the distribution characteristics of the detected landslides are investigated by examining their relationships with topographic and hydrological factors. Three expressways in Sichuan Province, China—namely the Yakang (Ya’an-Kangding), Yaxi (Ya’an-Xichang), and Lushi (Luding-Shimian) expressways—and their surrounding regions (a total area of approximately 20,000 square kilometers) were chosen as the study area. A total of 413 landslides were detected, among which 320 were detected using multi-temporal satellite optical images, and 109 were detected using GACOS-assisted InSAR stacking. It should be noted that only 16 landslides were detected by both approaches; these landslides all exhibited not only obvious geomorphological features but also ground motion. A statistical analysis of the topographic and hydrological factors shows that of the detected landslides: 81% are distributed at elevations of 1000–2500 m, over 60% lie within the elevation range of 100~400 m, and 90% present with medium and steep slopes (20°~45°), and 80% are located within areas seeing an annual rainfall of 950~1050 mm. Nine landslides were found to pose potential safety hazards to the expressways. The research findings in this paper have directly benefitted the Sichuan expressways; equally important, it is believed that the technical framework presented in this paper will provide guidance for hazard mitigation and the prevention of transportation hazards in the future.

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“…In both these respects, the historical databases complement current landslide inventories that can be used to trace the spatial patterns in landslide occurrence and their causative factors (Van Den Eeckhaut and Hervás, 2012;Herrera et al, 2018;Marc et al, 2018). Within the landslide hazard and risk assessments, the historical landslide databases provide evidence as it is generally assumed that past landslide occurrence frequencies may be used to describe the probabilities of landslide occurrence in the near future (Remondo et al, 2008;Van Den Eeckhaut et al, 2009;Wu and Yeh, 2020).…”

Section: Introductionmentioning

confidence: 99%

CHILDA – Czech Historical Landslide Database

Bíl

Raška

Dolák

et al. 2021

Nat. Hazards Earth Syst. Sci.

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Abstract. National and regional historical landslide databases are increasingly viewed as providing empirical evidence for the geomorphic effects of ongoing environmental change and for supporting adaptive territorial planning. In this work, we present the design and current content of the Czech Historical Landslide Database (CHILDA), the first of its kind for the territory of Czechia (the Czech Republic). We outline the CHILDA system, its functionality, and technical solution. The database was established by merging and extending the fragmented regional datasets for highly landslide-prone areas in Czechia. Currently, the database includes 699 records (619 landslides, 75 rockfalls, and 5 other movement types) encompassing the period from the oldest determined records (1132) up to 1989, which represents an important cultural, political, and socioeconomic divide.

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Contextualizing community-based landslide risk reduction: an evolutionary perspective

Cited by 12 publications

References 56 publications

The root causes of landslide vulnerability in Bangladesh

The root causes of landslide vulnerability in Bangladesh

Wide Area Detection and Distribution Characteristics of Landslides along Sichuan Expressways

CHILDA – Czech Historical Landslide Database

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