Yudo Prasetyo

Pattern Analysis of El Nino and La Nina Phenomenon Based on Sea Surface Temperature (SST) and Rainfall Intensity using Oceanic Nino Index (ONI) in West Java Area

Climate change occurs in 1998-2016 brings significant alteration in the earth surface. It is affects an extremely anomaly temperature such as El Nino and La Nina or mostly known as ENSO (El Nino Southern Oscillation). West Java is one of the regions in Indonesia that encounters the impact of this phenomenon. Climate change due to ENSO also affects food production and other commodities. In this research, processing data method is conducted using programming language to process SST data and rainfall data from 1998 to 2016. The data are sea surface temperature from NOAA satellite, SST Reynolds (Sea Surface Temperature) and daily rainfall temperature from TRMM satellite. Data examination is done using analysis of rainfall spatial pattern and sea surface temperature (SST) where is affected by El Nino and La Nina phenomenon. This research results distribution map of SST and rainfall for each season to find out the impacts of El Nino and La Nina around West Java. El Nino and La Nina in Java Sea are occurring every August to February. During El Nino, sea surface temperature is between 27°C - 28°C with average temperature on 27.71°C. Rainfall intensity is 1.0 mm/day – 2.0 mm/day and the average are 1.63 mm/day. During La Nina, sea surface temperature is between 29°C - 30°C with average temperature on 29.06°C. Rainfall intensity is 9.0 mm/day - 10 mm/day, and the average is 9.74 mm/day. The correlation between rainfall and SST is 0,413 which is expresses a fairly strong correlation between parameters. The conclusion is, during La Nina SST and rainfall increase. While during El Nino SST and rainfall decrease. Hopefully this research could be a guideline to plan disaster mitigation in West Java region that is related extreme climate change.

Determination of The Water Catchment Area in Semarang City Using a Combination of Object Based Image Analysis (OBIA) Classification, InSAR and Geographic Information System (GIS) Methods Based On a High-Resolution SPOT 6 Image and Radar Imagery

Semarang is the biggest city in central Java-Indonesia which has a rapid and massive infrastructure development nowadays. In order to control water resources and flood, the local goverment has been built east and west flood canal in Kaligarang and West Semarang River. One of main problem in Semarang city is the lack of fresh water in dry season because ground water is not rechargeable well. Rechargeable groundwater ability depends on underground water recharge rate and catchment area condition. The objective of the study is to determine condition and classification of water catchment area in Semarang city. The catchment area conditions will be determine by five parameters as follows soil type, land use, slope, ground water potential and rainfall intensity. In this study, we use three methods approach to solve the problem which is segmentation classification to acquire land use classification from high resolution imagery using nearest neighborhood algorithm, Interferometric Synthetic Aperture Radar (SAR) to derive DTM from SAR Imagery and multi criteria weighting and spatial analysis using GIS method. There are three types optical image (ALOS PRISM, SPOT-6 and ALOS PALSAR) to calculate water catchment area condition in Semarang city. For final result, this research will divide the water catchment into six criteria as follows good, naturally normal, early critical, a little bit critical, critical and very critical condition. The result shows that water catchment area condition is in an early critical condition around 2607,523 Ha (33,17 %), naturally normal condition around 1507,674 Ha (19,18 %), a little bit critical condition around 1452,931 Ha (18,48 %), good with 1157,04 Ha (14,72 %), critical with 1058,639 Ha (13,47 %) and very critical with 75,0387 Ha (0,95 %). The distribution of water catchment area conditions in West and East Flood Canal have an irreguler pattern. In northern area of watershed consists of begin to critical, naturally normal and good condition. Meanwhile in southern area of watershed consists of a little bit critical, critical and very critical condition.