APLIKASI PENGINDERAAN JAUH DAN SISTEM INFORMASI GEOGRAFIS UNTUK PEMETAAN KERENTANAN BANJIR (Kasus DAS Nunkurus Kabupaten Kupang Nusa Tenggara Timur)

• Main Authors: , DEFRITUS ALDRIN PUNUF, , Dr. R Suharyadi, M.Sc
• Format: Theses and Dissertations NonPeerReviewed
• Published: [Yogyakarta] : Universitas Gadjah Mada 2012
• Subjects: ETD
• Online Access: https://repository.ugm.ac.id/99136/; http://etd.ugm.ac.id/index.php?mod=penelitian_detail&sub=PenelitianDetail&act=view&typ=html&buku_id=55682
• Institution: Universitas Gadjah Mada

This research is aimed to identify the flood�susceptibility parameters and to acknowledge the spatial distribution of the flood prone areas through applying the satellite imagery and Geographic Information System at Nunkurus watershed in the Regency of Kupang, the Province of East Nusa Tenggara. This research carried out upon the methodologies of the satellite imagery interpretation and the spatial analysis through the Geographic Information System. Data used were Aster VNIR acquired on March 2011, topographic map (Rupa Bumi Indonesia) 1:25000 as well as related thematic maps. The interpretation is intended to identify the parameters of the flood vulnerability e.g. the overland flow and the inundated areas. The interpretation is conducted both by applying the manual and the digital interpretation through the image transformation. The analysis of the overland flow is brought by applying the Cook Method, while to determine the flood�s prone areas is referred to the Hydrology division of the Public Worker (DPU Pengairan) through spatial modeling by applying the arithmetic sequence method. The research�s results showed that the Aster VNIR image has a high compatibility in identifying the physical parameters of flood�s susceptibility. For the accuracy test of the interpretation resulted 95,56% for the land form parameters and 77,7% for the soil infiltration. Furthermore, the result for vegetation cover analysis through NDVI showed that there is a high correlation (85%) between the vegetation density in the field with the NDVI value. Moreover, results for the spatial modeling of the flood�s prone areas are differentiated into three sequences: first is areas with a high susceptibility which approximately 46 km2 or 23,6% of the total of Watershed area which then covers three villages namely as Naibonat, Pukdale, and Camplong I. The second class is approximately 77 km2 or 39,50% of the total watershed area, which covers part of Oesao Village, Raknamo Village, Naunu Village and Camplong II Village. The third category is the slight one which approximately occupies 72 km2 or 36,90% of the total area. Some villages covered are Naunu, Oebola, Silu, Oenuntono, Kairane, Fatuknutu, Kuanheum and Fatuteta. However, the accuracy test of the flood�s probe areas mapping is for 76,19%.