Integration of Bayesian Networks with GIS for Dynamic Avalanche Hazard Assessment: NSDI Perspective
Öz
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.
Anahtar Kelimeler
Kaynakça
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Ayrıntılar
Birincil Dil
İngilizce
Konular
Mühendislik
Bölüm
Araştırma Makalesi
Yazarlar
İpek Yılmaz
*
ONDOKUZ MAYIS ÜNİVERSİTESİ
Türkiye
Derya Öztürk
ONDOKUZ MAYIS ÜNİVERSİTESİ
Türkiye
Yayımlanma Tarihi
31 Ocak 2018
Gönderilme Tarihi
14 Aralık 2017
Kabul Tarihi
5 Şubat 2018
Yayımlandığı Sayı
Yıl 2018 Cilt: 4 Sayı: 1
