PROCJENA PODLOŽNOSTI NA KLIZIŠTA INICIRANA POTRESOM: POTRES OD 7,5 MW U 2018. GODINI U PALUU, SULAWESI, INDONEZIJA

A catastrophic Palu earthquake on September 28th, 2018 with Mw 7.5 triggered countless slope failures, generating numerous landslides. This paper presents a practical method for susceptibility assessment of earthquake-induced landslides in the Palu region and the surrounding area. The statistical weight of evidence (WoE) model was used to assess the relationship between landslides induced by seismic motion and its causative factors to determine the susceptibility level and derive an earthquake-induced landslide susceptibility map of this study area. The 1273 landslides were classified into two data series, training data for modelling (70%) and test data for validation (30%). The six selected thematic maps as landslide causative factors are lithology, land use, peak ground acceleration (PGA), and slope (gradient, aspect, elevation). The selection of causative factors considerably influences the frequency of landslides in the area. The result is satisfactory because the AUC value of the chosen model excelled the minimum limit, which is 0.6 (60%). The estimated success rate of the model is 85.7%, which shows that the relevancy of the model is good with the occurrence of landslides. The prediction rate of 84.6% indicates that the applied model is very good at predicting new landslides.Katastrofalni potres koji se dogodio u Paluu 28. rujna 2018. godine, magnitude 7,5 Mw, izazvao je brojne nestabilnosti na padinama, uključujući nastanak velikoga broja klizišta. Ovaj rad predstavlja praktičnu metodu za definiranje procjene podložnosti na klizišta izazvana potresom u regiji Palu i okolnom području. Metoda Weight of Evidence (WoE) korištena je za procjenu odnosa između klizišta izazvanih seizmičkim kretanjem i preduvjeta kako bi se odredila razina podložnosti i izradila karta podložnosti na klizišta izazvana potresom u istraživanom području. 1273 klizišta podijeljena su u dvije serije podataka: podatci za treniranje modela (70 %) i podatci za validaciju modela (30 %). Korišteno je šest odabranih tematskih karata kao faktora koji utječu na pojavu klizišta: litologija, korištenje zemljišta, vršno ubrzanje tla (PGA), nagib padine, orijentacija padine i nadmorska visina. Odabir uzročnih faktora znatno utječe na učestalost klizišta na tom području. Rezultat modela zadovoljavajući je jer je vrijednost AUC odabranoga modela premašila minimalnu granicu koja iznosi 0,6 (60 %). Procijenjena uspješnost modela iznosi 85,7 %, što pokazuje relevantnost modela kod pojave klizišta. Stopa predviđanja od 84,6 % upućuje na to da je primijenjeni model vrlo dobar u predviđanju novih klizišta

The Aplication of Landslide Inventory Data Base of Indonesia (LIDIA) For Supporting Landslide Susceptibility Mapping in Cianjur Regency, West Java, Indonesia

Susceptibility analysis for predicting landslides most frequently has been done using deterministic methods and statistical methods. Some landslide events caused loss of life, infrastructure and properties. In order to minimize the risk, the mitigation has been done. These damages can be mitigated if the cause and effect relationships of the events are knowing. One of the mitigation method is using landslide susceptibility map. In this study, we used Weight of Evidence methods to produce landslide susceptibility map. The study had been carried out, using Landslide Inventory Database of Indonesia (LIDIA), remote sensing data, field surveys and geographic information system (GIS) tools. This method can be used without requiring geotechnical, groundwater or failure depth data. However, the other factors to influence landslide occurrence, such as elevation, slope aspect, slope angle, distance from drainage, lithology, distance from lineament, soil texture, precipitation, land use/land cover (LULC) and NDVI were considered. Then analytical result verified by using test data of landslide, and the AUC success rate is 0.85 and AUC prediction rate is 0.79 with difference 0.06. This conditions the allowed tolerance of 15%. This has shown good model of landslide susceptibility. The obtained landslide susceptibility map and landslide inventory data base of Indonesia can be used for landslide hazard prevention and mitigation, and proper planning for land use in the future

Triple Helix in Disaster Management: Case Study of Strategic Environmental Assessment (SEA) for Government Office Relocation Planning of Padang City, Indonesia

AbstractDisaster management is the dynamic form of series of integrated and sustainable activities that is carried out before, during and post disaster in order to realize the optimum protection to the community, social assets, economy and environment (Rachmat, 2004). National and local governments play a key role in it, especially in the disaster risk reduction by establishing the policies, plans and programs. Universities and research institutions supports the effort by providing expertise in the tools and methodology as well as providing education and training for the government's personals. Businesses, in form of private consultancies, get involved in the project level by processing and analyzing the data using the appropriate methods.Strategic and environmental assessment is the keywords in Strategic Environmental Assessment (SEA). Strategic means that it happens in an early enough stage in the decision making process that it can have a significant influence on key decisions. Environmental is considered in the broadest sense which means that besides natural or bio-physical impacts, it may also include related social and economic aspects (Looien, 2009).This paper would like to present how SEA is utilized in the spatial planning decision for relocating Padang City Government office to a free hazard area while considering the socio-economic environment. The methodology used in this work is a case study of site selection for relocation of Padang City Government office and look at the interaction of government, academics and business in the process. It is followed by the discussion on the triple helix model that applies, including the cooperation and mutual relationship with international bodies in terms of exchange of hardware and software equipment with relevant data. The paper will result in the conceptual triple helix model that applies in disaster management. As a case study, the result of the work has its limitation but provide insight about the innovation in building infrastructure in hazard prone areas

SUSCEPTIBILITY ASSESSMENT OF EARTHQUAKE-INDUCED LANDSLIDES: THE 2018 PALU, SULAWESI MW 7.5 EARTHQUAKE, INDONESIA

A catastrophic Palu earthquake on September 28th, 2018 with Mw 7.5 triggered countless slope failures, generating numerous landslides. This paper presents a practical method for susceptibility assessment of earthquake-induced landslides in the Palu region and the surrounding area. The statistical weight of evidence (WoE) model was used to assess the relationship between landslides induced by seismic motion and its causative factors to determine the susceptibility level and derive an earthquake-induced landslide susceptibility map of this study area. The 1273 landslides were classified into two data series, training data for modelling (70%) and test data for validation (30%). The six selected thematic maps as landslide causative factors are lithology, land use, peak ground acceleration (PGA), and slope (gradient, aspect, elevation). The selection of causative factors considerably influences the frequency of landslides in the area. The result is satisfactory because the AUC value of the chosen model excelled the minimum limit, which is 0.6 (60%). The estimated success rate of the model is 85.7%, which shows that the relevancy of the model is good with the occurrence of landslides. The prediction rate of 84.6% indicates that the applied model is very good at predicting new landslides