THE USE OF HIGH RESOLUTION IMAGES TO EVALUATE THE EVENT OF FLOODS AND TO ANALYSIS THE RISK REDUCTION CASE STUDY: KAMPUNG PULO, JAKARTA

The flood hit Kampung Pulo region in almost every year. This disaster has caused the evacuation of some residents in weeks. Given the frequency of occurrence is quite high in the region it is necessary to do a study to support disaster risk reduction. This study aimed to evaluate the incidence of flooding that occurred in Kampung Pulo in terms of topography, river conditions, characteristics of the building, and socioeconomic conditions. Methods of study include geomorphology analysis, identification of areas of stagnant, the estimated number of people exposed, the estimation of socio-economic conditions of the population, as well as determining the location of an evacuation. The data used is high-resolution remote sensing imagery is QuickBird and SPOT-6. It also used the results of aerial photography using Unmanned Aerial Vehicle (UAV). Aerial photography was conducted on January 18, 2013, which is when the serious flooding that inundated almost the entire region of Kampung Pulo. Information risk level of buildings and population resulting from this study were obtained by using GIS. The results obtained from this study can be used to develop recommendations and strategies for flood mitigation in Kampung Pulo, Jakarta. One of them is the determination of the location for vertical evacuation plan in the affected areas

Land Cover Classification of Alos Avnir Data using Ikonos as Reference

Abstract. Advanced Land Observation Satellite (ALOS) is a Japanese satellite equipped with 3 sensors i.e., PRISM, AVNIR, and PALSAR. The Advanced Visible and Near Infrared Radiometer (AVNIR) provides multi spectral sensors ranging from Visible to Near Infrared to observe land and coastal zones. It has 10 meter spatial resolution, which can be used to map land cover with a scale of 1:25000. The purpose of this research was to determineclassification for land cover mapping using ALOS AVNIR data. Training samples were collected for 11 land cover classes from Bromo volcano by visually referring to very high resolution data of IKONOS panchromatic data. The training samples were divided into samples for classification input and samples for accuracy evaluation. Principal component analysis (PCA) was conducted for AVNIR data, and the generated PCA bands were classified using Maximum Likehood Enhanced Neighbor method. The classification result was filtered and re-classed into 8 classes. Misclassifications were evaluated and corrected in the post processing stage. The accuracy of classifications results, before and after post processing, were evaluated using confusion matrix method. The result showed that Maximum Likelihood Enhanced Neighbor classifier with post processing can produce land cover classification result of AVNIR data with good accuracy (total accuracy 94% and kappa statistic 0.92). ALOS AVNIR has been proven as a potential satellite data to map land cover in the study area with good accuracy.p.13-20 : ilus. ; 30 c

MODEL SIMULASI BANJIR MENGGUNAKAN DATA PENGINDERAAN JAUH, STUDI KASUS KABUPATEN SAMPANG DENGAN MENGGUNAKAN METODE GRIDDED SURFACE SUBSURFACE HYDROLOGIC ANALYSIS (FOOD SIMULATION MODEL USING REMOTE SENSING DATA, CASE STUDY OF SAMPANG REGION USING GRIDDED SURFACE HYDROLOGIC ANALYSIS METHOD)

Permasalahan banjir yang terjadi setiap tahun di Kabupaten Sampang disebabkan jumlah aliran yang masuk ke Kota Sampang sangat besar, terjadinya sedimentasi yang sangat tinggi di sungai yang melintasi kota, serta kurang baiknya sistem drainase terutama di daerah permukiman perkotaan. Beberapa permasalahan tersebut akhirnya dapat memicu terjadinya banjir di Kota Sampang. Metode yang digunakan untuk model simulasi banjir adalah metode Gridded Surface Subsurface Hydrologic Analysis (GSSHA), dimana metode tersebut mampu untuk menghasilkan komponen hidrologi dengan baik. Data yang digunakan dalam penelitian ini, antara lain: data Qmorph, Digital Elevation Model–Shuttle Radar Topography Mission (DEM-SRTM), SPOT-5 tahun 2010, peta tanah, data penampang sungai serta data lapangan. Penelitian model simulasi banjir ini menghasilkan volume banjir, debit puncak dan waktu yang digunakan untuk mencapai debit puncak banjir, yang digambarkan dalam hidrograf serta hasil perhitungan kedalaman banjir. Debit puncak yang dihasilkan oleh beberapa DAS, a.l.: DAS Klampis sebesar 5,40 m³/detik, DAS Jelgung sebesar 364788,90 m³/detik, DAS Kamoning sebesar 37,80 m³/detik, Sub DAS Kamoning sebesar 32,40 m³/detik, dan 3 DAS yang merupakan gabungan dari DAS tersebut sebesar 174059.10 m³/detik. Kata Kunci: Model simulasi banjir, GSSHA, Penginderaan jauh

The Use of High Resolution Images to Evaluate the Event of Floods And to Analysis The Risk Reduction Case Study: Kampung Pulo, Jakarta

The flood hit Kampung Pulo region in almost every year. This disaster has caused the evacuation of some residents in weeks. Given the frequency of occurrence is quite high in the region it is necessary to do a study to support disaster risk reduction. This study aimed to evaluate the incidence of flooding that occurred in Kampung Pulo in terms of topography, river conditions, characteristics of the building, and socioeconomic conditions. Methods of study include geomorphology analysis, identification of areas of stagnant, the estimated number of people exposed, the estimation of socio-economic conditions of the population, as well as determining the location of an evacuation. The data used is high-resolution remote sensing imagery is QuickBird and SPOT-6. It also used the results of aerial photography using Unmanned Aerial Vehicle (UAV). Aerial photography was conducted on January 18, 2013, which is when the serious flooding that inundated almost the entire region of Kampung Pulo. Information risk level of buildings and population resulting from this study were obtained by using GIS. The results obtained from this study can be used to develop recommendations and strategies for flood mitigation in Kampung Pulo, Jakarta. One of them is the determination of the location for vertical evacuation plan in the affected areas.p. 127-136 : ilus. ; 28 c

Model Simulasi Banjir Menggunakan Data Penginderaan Jauh, Studi Kasus Kabupaten Sampang Dengan Menggunakan Metode Gridded Surface Subsurface Hydrologic Analysis

Hal.90-101 : ilus. ; 30 c

Pemantauan fase pertumbuhan tanaman padi sawah menggunakan data Modis wilayah Provinsi Banten dan Jawa Barat

Hal.19-18 : ilus. ; 28 c