DAMAGE DETECTION OF HUMAN ACTIVITY BASED ON NTL, LST AND NO2 FOR 2018 CENTRAL SULAWESI EARTHQUAKE, TSUNAMI AND LIQUEFACTION DAMAGE

• Main Author: Najjar, Boolein
• Format: Theses
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/56230
• Institution: Institut Teknologi Bandung

Damage detection methods, concepts and datasets combination are diverse. According to purpose which can detect any changes that happened after any action whether human based or natural based. Hence, change detection will help for disaster assessment studies as well. This research proposed new dataset combination and concept which based on human activities for damage detection after natural hazard. Datasets are night-time light by NPP-VIIRS DNB, nitrogen dioxide (NO2) by Sentinel-5P and land surface temperature by MODIS. This will represent changes that happened to these datasets after damage happened. These new datasets combination will be applied to Eastern Indonesia province, Central Sulawesi province. After 7.5 Mw earthquake, tsunami with 4m waves heights and four sub-districts have liquefaction that happened on September 28, 2018. Main regencies will be applied this new combination on is Donggala Regency, Parigi Moutong Regency, Sigi Regency and Palu city which is capital city of Central Sulawesi province. These are most areas that have been affected after destructive disasters happened there. This three datasets combination will produce damage probability index map for each regency and city. These damage probability index maps will compare it to damage data that got. Finally, main limitations that face this research is type of areas that have been studied which is the majority is rural areas, population density in those areas, buildings type, scattering and density in each area which affect the values.