TY - JOUR
T1 - Flood evacuation routes mapping based on derived-flood impact analysis from landsat 8 imagery using network analyst method
AU - Watik, N.
AU - Jaelani, L. M.
N1 - Publisher Copyright:
© 2019 International Society for Photogrammetry and Remote Sensing.
PY - 2019/8/20
Y1 - 2019/8/20
N2 - Reported by National Disaster Response Agency of Indonesia (BPBD) as many as 94 dies, 149 injured, and more than 88 thousands homeless caused by floods in 2018. Besides bringing casualties to people and environment, the floods also affect the damages to transportation infrastructures in which vital to disaster emergency response operation e.g. evacuation process. Due to the complex impact of current disaster, the demands of providing a short-term response increases accordingly. Therefore, this research proposes a prototype of flood evacuation route utilizing network analyst method. The network analyst method particularly focus on finding alternative route based on time and distance. This research uses a flood simulation model derived from Landsat 8 imagery and terrain data. Subsequently, the simulation model divides the flood severity based on the depth which consist of < 0.3 m (slight), 0.3-0.5 m (moderate), and > 0.5 m (serious) in order to generate an impact analysis regarding the estimation of damages and casualties. In order to resemble the real situation of flood, barriers (e.g. flood area) are applied into the finding evacuation route procedure. Thereby, the estimated evacuation route can be executed considering the safest and fastest way. Moreover, some comparisons between before and after flood are conducted in order to know the effectiveness of evacuation routes. By such comparison proves that network analyst enables to support disaster management operation with respect to handling the evacuation procedure.
AB - Reported by National Disaster Response Agency of Indonesia (BPBD) as many as 94 dies, 149 injured, and more than 88 thousands homeless caused by floods in 2018. Besides bringing casualties to people and environment, the floods also affect the damages to transportation infrastructures in which vital to disaster emergency response operation e.g. evacuation process. Due to the complex impact of current disaster, the demands of providing a short-term response increases accordingly. Therefore, this research proposes a prototype of flood evacuation route utilizing network analyst method. The network analyst method particularly focus on finding alternative route based on time and distance. This research uses a flood simulation model derived from Landsat 8 imagery and terrain data. Subsequently, the simulation model divides the flood severity based on the depth which consist of < 0.3 m (slight), 0.3-0.5 m (moderate), and > 0.5 m (serious) in order to generate an impact analysis regarding the estimation of damages and casualties. In order to resemble the real situation of flood, barriers (e.g. flood area) are applied into the finding evacuation route procedure. Thereby, the estimated evacuation route can be executed considering the safest and fastest way. Moreover, some comparisons between before and after flood are conducted in order to know the effectiveness of evacuation routes. By such comparison proves that network analyst enables to support disaster management operation with respect to handling the evacuation procedure.
KW - Flood
KW - Flood simulation model
KW - Landsat 8 imagery
KW - Network analyst
KW - Route analysis
UR - http://www.scopus.com/inward/record.url?scp=85074285866&partnerID=8YFLogxK
U2 - 10.5194/isprs-archives-XLII-3-W8-455-2019
DO - 10.5194/isprs-archives-XLII-3-W8-455-2019
M3 - Conference article
AN - SCOPUS:85074285866
SN - 1682-1750
VL - 42
SP - 455
EP - 460
JO - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives
JF - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives
IS - 3/W8
T2 - 2019 GeoInformation for Disaster Management, Gi4DM 2019
Y2 - 3 September 2019 through 6 September 2019
ER -