A multi-hazard map-based flooding, gully erosion, forest fires, and earthquakes in Iran

Pouyan, Soheila; Pourghasemi, Hamid Reza; Bordbar, Mojgan; Rahmanian, Soroor; Clague, John J.

doi:10.1038/s41598-021-94266-6

Cited by 37 publications

(15 citation statements)

References 120 publications

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“…The first step of the exploratory analysis is data standardization. As usual [15,16], the metric of standard deviation was adopted to test the machine learning model's accuracy and to measure confidence in the obtained statistical conclusions. This allows us to compare variable data with different units of measure, scaling all the variables such that each scaled variable will have mean value equal to 0 and standard deviation equal to 1, referred to the data distribution for each variable.…”

Section: Standardizationmentioning

confidence: 99%

“…In particular, Schmidt et al proposed a multi-hazard risk assessment methodology in New Zealand, devising an adaptable computational tool allowing its users to input the natural phenomena of interest [11]. Still, relatively scarce are the studies exploiting machine learning techniques to assess multi-hazard risks [14][15][16], albeit machine learning is especially useful when dealing with the huge amount of data encountered in risk analysis, particularly at the regional scale.…”

Section: Introductionmentioning

confidence: 99%

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A Machine Learning Framework for Multi-Hazard Risk Assessment at the Regional Scale in Earthquake and Flood-Prone Areas

et al. 2022

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Communities are confronted with the rapidly growing impact of disasters, due to many factors that cause an increase in the vulnerability of society combined with an increase in hazardous events such as earthquakes and floods. The possible impacts of such events are large, also in developed countries, and governments and stakeholders must adopt risk reduction strategies at different levels of management stages of the communities. This study is aimed at proposing a sound qualitative multi-hazard risk analysis methodology for the assessment of combined seismic and hydraulic risk at the regional scale, which can assist governments and stakeholders in decision making and prioritization of interventions. The method is based on the use of machine learning techniques to aggregate large datasets made of many variables different in nature each of which carries information related to specific risk components and clusterize observations. The framework is applied to the case study of the Emilia Romagna region, for which the different municipalities are grouped into four homogeneous clusters ranked in terms of relative levels of combined risk. The proposed approach proves to be robust and delivers a very useful tool for hazard management and disaster mitigation, particularly for multi-hazard modeling at the regional scale.

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Section: Standardizationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Machine Learning Framework for Multi-Hazard Risk Assessment at the Regional Scale in Earthquake and Flood-Prone Areas

et al. 2022

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“…The forest fire disrupts the interrelation of the ecosystem. It also distract the various environmental cycles, modify the air composition by instigating change of climate (CC) and mean sea level rise (MSLR) etc [6][7][8][9].…”

Section: Review Of Literaturementioning

confidence: 99%

Distressed Lives and Livelihood in Biosphere Reserves during Anthropocene; Similipal Forest Blaze -2021

Mishra

Kumar

et al. 2022

CJAST

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Inland Biosphere reserves are mainly focusing on conservation of forests for a sustainable biodiversity that has. alerted the ecologists, and forest managers. The reserving forests were under jurisdiction .of the state forest department. The aboriginal tribes were the forest savers, so the damages by the wild fire were less in past. Present investigation includes the wild forest blazes in India during 2021 with special attention to the Similipal forest fire 2021 in Mayurbhanj district, Odisha. The socio-biological impacts of the forest fire on the aboriginal communities are searched. The soft-wares used in the present study were ArcGIS, QGIS, GPS Visualizer, USGS Earth Explorer, Google Earth Pro-Paint, Bhuvan, Accu-Weather, and ERDAS IMAGINE 11 for analyzing, image processing, and presentation. The assessment of the anthropogenic burnt area has been about 1000 Km2. The involvement of the ethnic communities is found to be the protectors of the fire in past are now oustees. The wild blaze management in forests can be done by public private partnership mode. The mass consciousness can be adopted involving the particularly vulnerable tribal group like, the Vana Suraksha Samiti, under the Forest Rights Act of the state government.

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“…Suatu bentang alam yang merupakan kawasan lindung memiliki tingkat kerentanan bencana yang lebih tinggi dibandingkan kawasan lain (Yuliono et al, 2020). Bencana yang sering terjadi dikawasan hutan di antaranya seperti longsoran tanah, batuan maupun salju (Bebi et al, 2021;Unterberger dan Olschewski, 2021;Perzl et al, 2021) hingga kebakaran hutan (Navalho et al, 2017;Pouyan et al, 2021).…”

Section: Bahaya Lanskap DI Kawasan Hutanunclassified

Integrasi Analisis Preferensi Visual dan Bahaya Lanskap dalam Perencanaan Wisata di Taman Hutan Raya Ir. H. Djuanda, Bandung

Rahmafitria

Hindayani

2022

Jurnal Lanskap Indonesia

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Ir. H. Djuanda Forest Park, is a natural tourism destination located in Bandung, West Java and in low land parts of Gunung Pulosari, passed by Cikapundung river stream. This research aimed to recommend the appropriate tourism planning to be implemented in the Ir. H. Djuanda Forest Park. Through landscape hazard analysis within slope gradient and soil element contained, we developed landscape sensitivity map. The result shows that 65,508% from the total area is a high sensitivity land. Beside that, only 4,335% from the total area is a low sensitivity lands and can be explored for active tourism attraction. The visual preference analysis was held to identify the potential attractiveness of many tourisms object in this area. The high potential object is dominanated with natural landscape objects and man-made object is the less potential. Almost all of the potential objects are located in high sensitivity land. Unfortunately, the uninterested object with unclear function is located in low sensitivity land which it is suitable for intensive recreation activities. The planner of this area should consider the role of limited activities and facilities development in low caring capacity land. For conservation purpose, planting endemic vegetation in sensitive landslide land should be carried out in order to maintain forest sustainability.

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A multi-hazard map-based flooding, gully erosion, forest fires, and earthquakes in Iran

Cited by 37 publications

References 120 publications

A Machine Learning Framework for Multi-Hazard Risk Assessment at the Regional Scale in Earthquake and Flood-Prone Areas

A Machine Learning Framework for Multi-Hazard Risk Assessment at the Regional Scale in Earthquake and Flood-Prone Areas

Distressed Lives and Livelihood in Biosphere Reserves during Anthropocene; Similipal Forest Blaze -2021

Integrasi Analisis Preferensi Visual dan Bahaya Lanskap dalam Perencanaan Wisata di Taman Hutan Raya Ir. H. Djuanda, Bandung

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