Integration of Bayesian Networks with GIS for Dynamic Avalanche Hazard Assessment: NSDI Perspective

Abstract

Natural hazard assessments are core to risk definition and early warning systems and play a fundamental role in the prevention of major damages. Traditional hazard identification methods are static. For this reason, new information and conditions cannot be easily included in the pre-defined hazard assessments. The Bayesian Networks can be used effectively for dynamic hazard identification. In this study, a methodology based on the Bayesian Networks model is presented for dynamic avalanche hazard assessment, in which changed and renewed data can be included in the system. In the proposed methodology, the integration of the Bayesian Networks and Geographical Information Systems (GIS) is modeled in the National Spatial Data Infrastructure (NSDI) perspective. In this structure, it is possible to combine and analyze the data obtained from different sources and factors for avalanche hazard can be dynamically updated with real-time updated data and temporal hazard mapping can be produced. The proposed methodology provides a generic structure and has an attribute making it applicable for dynamic mapping studies for other disasters.

Keywords

• Dynamic Hazard Assessment,Avalanche,Bayesian Networks,GIS,NSDI

Dinamik Çığ Tehlike Değerlendirmesi İçin Bayes Ağlarının CBS'ye Entegrasyonu: UKVA Perspektifi

Abstract

Doğal afetlerle ilgili çalışmalarda tehlike değerlendirmesi, risk tanımlama ve erken uyarı sistemlerinin temelidir ve büyük kayıpların engellenmesinde önemli bir rol oynamaktadır. Klasik tehlike tanımlama yöntemleri statiktir. Bu nedenle, yeni bilgi ve koşullar önceden tanımlanmış tehlike değerlendirmelerine kolayca dahil edilemez. Bayes Ağları, dinamik tehlike tanımlaması için etkin bir şekilde kullanılabilir. Bu çalışmada, değişen ve yenilenen verilerin sisteme dahil edilebildiği dinamik çığ tehlike değerlendirmesi için Bayes Ağlarına dayanan bir yaklaşım sunulmuştur. Önerilen metodolojide, Bayes Ağlarının ve Coğrafi Bilgi Sistemlerinin (CBS) entegrasyonu, Ulusal Konumsal Veri Altyapısı (UKVA) perspektifinde modellenmiştir. Bu yapıda, farklı kaynaklardan elde edilen verilerin birleştirilmesi ve analiz edilmesi mümkün olup, çığ tehlikesi için etken faktörler gerçek zamanlı güncel verilerle dinamik olarak güncellenerek zamansal tehlike haritaları üretilebilir. Önerilen metodoloji genel bir yapı sunmaktadır ve diğer afetlere yönelik dinamik harita üretimi çalışmaları için uyarlanabilir niteliktedir.

Keywords

• Dinamik Tehlike Değerlendirmesi,Çığ,Bayes Ağları,CBS,UKVA

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