Bambang Trisakti
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PEMANFAATAN DATA SATELIT UNTUK ANALISIS POTENSI GENANGAN DAN DAMPAK KERUSAKAN AKIBAT KENAIKAN MUKA AIR LAUT (APPLICATION OF SATTELITE DATA TO ANALYZE INUNDATION POTENTIAL AND THE IMPACT OF SEA LEVEL RISE) Anggraini, Nanin; Trisakti, Bambang; Soesilo, Tri Edhi Budhi
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 9 No. 2 Desember 2012
Publisher : Indonesian National Institute of Aeronautics and Space (LAPAN)

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Abstract

Meningkatnya volume air laut menyebabkan kenaikan muka air laut yang mengancam keberadaan pulau-pulau kecil dan wilayah pesisir seperti pesisir Jakarta Utara. Selain karena kenaikan muka air laut, Jakarta Utara juga terancam oleh fenomena penurunan permukaan tanah. Penelitian ini bertujuan untuk memprediksi kenaikan muka air laut pada tahun 2030 dan dampaknya terhadap wilayah pesisir. Prediksi total tinggi muka air laut diperoleh berdasarkan data pasang surut (pasut), penurunan permukaan tanah, dan kenaikan muka air laut skenario B2 dari IPCC. Wilayah pesisir yang berpotensi tergenang karena kenaikan muka air laut diprediksi dengan data DEM SRTM X-C resolusi spasial 30 m. Analisis dampak kerusakan dilakukan dengan cara overlay antara potensi genangan dengan penggunaan lahan dari data QuickBird. Hasil memperlihatkan bahwa, prediksi total tinggi muka air laut tahun 2030 akibat pasut adalah 2,88 m, penurunan permukaan tanah 2,28 m, dan skenario IPCC 1,29 m, sehingga tinggi muka air laut rencana adalah 6,45 m. Jenis penggunaan lahan yang berpotensi rusak akibat tergenang didominasi oleh permukiman sebesar 1045 ha dan industri 563 ha. Permukiman yang berpotensi tergenang paling luas berada di Kecamatan Penjaringan dengan luas 523 ha dan wilayah industri berada di Kecamatan Cilincing dengan luas 171 ha. Kata kunci: DEM SRTM X-C band, Kenaikan muka air laut, Penurunan permukaan tanah, skenario B2 SRES IPCC, QuickBird
Methane Emission from Digestion of Palm Oil Mill Effluent (POME) in a Thermophilic Anaerobic Reactor Irvan, I; Trisakti, Bambang; Wongistani, Vivian; Tomiuchi, Yoshimasa
International Journal of Science and Engineering (IJSE) Vol 3, No 1 (2012)
Publisher : Chemical Engineering Diponegoro University

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Abstract

As the issue of global warming draws increasing concern, many studies to reduce CO2 and CH4 gases (greenhouse gases, GHG) have been implemented in several countries, including in Indonesia. Considering that Indonesia has a huge numbers of palm oil mills, no doubt if their waste water treatment as one of the major sources in GHG.  This paper presents the results from a research project between Metawater Co., Ltd.-Japan and University of Sumatera Utara-Indonesia. The objective of the research is to study the methane emission of thermophilic fermentation in the treatment of palm oil mill effluent (POME) on a laboratory scale. Anaerobic digestion was performed in two-litre water jacketed biodigester type continuous stirred tank reactor (CSTR) and operated at a thermophilic temperature (55 oC). As raw material, a real liquid waste (POME) from palm oil mill was used. Fresh POME was obtained from seeding pond of PTPN II waste water treatment facility which has concentration of 39.7 g of VS/L and COD value of 59,000 mg/L. To gain precise results, complete recording and reliable equipment of reactor was employed. As the experimental results, for hydraulic retention time (HRT) 8 days, VS decomposition rate of 63.5% and gas generation of 6.05-9.82 L/day were obtained, while for HRT 6 and 4 days, VS decomposition rate of 61.2, 53.3% and gas generation of  6.93-8.94  and  13.95-16.14 L/day were obtained respectively. Keywords—methane (CH4), palm oil mill effluent (POME), anaerobic digestion, thermophilic, green house gases (GHG)
PERBANDINGAN KLASIFIKASI BERBASIS OBYEK DAN KLASIFIKASIBERBASIS PIKSEL PADA DATA CITRA SATELIT SYNTHETICAPERTURE RADAR UNTUK PEMETAAN LAHAN(COMPARISON OF OBJECT BASED AND PIXEL BASEDCLASSIFICATION ON SYNTHETIC APERTURE RADAR SATELLITEIMAGE DATA FOR LAND MAPPING) Sutanto, Ahmad; Trisakti, Bambang; Arimurthy, Aniati Murni
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 11 No. 1 Juni 2014
Publisher : Indonesian National Institute of Aeronautics and Space (LAPAN)

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Abstract

Pemanfaatan data penginderaan jauh untuk pemetaan lahan sudah lama berkembang. Di Indonesia yang beriklim tropis, awan menjadi masalah klasik dalam pemindaian permukaan bumi dengan menggunakan satelit penginderaan jauh sensor optik. Satelit dengan sensor Synthetic Aperture Radar (SAR) mempunyai kemampuan untuk menembus awan sehingga menjadi solusi permasalahan tutupan awan. Pada penelitian ini digunakan data ALOS PALSAR untuk mengkaji teknik klasifikasi berbasis obyek dan berbasis piksel. Data ALOS PALSAR dipilih karena mempunyai kemampuan pengenalan suatu obyek berdasarkan karakteristik hamburan baliknya (backscatter). Klasifikasi berbasis obyek menggunakan metode Statistical Region Merging (SRM) untuk proses segmentasi obyek, dan metode Support Vector Machine (SVM) untuk proses klasifikasi, sedangkan klasifikasi berbasis piksel menggunakan metode SVM. Pada tahap klasifikasi telah diujicobakan beberapa fitur Dekomposisi Target dan Dekomposisi Citra dari data ALOS PALSAR. Pengujian akurasi klasifikasi dilakukan dengan metode confusion matrix menggunakan data Region of Interest (ROI) dari data QuickBird. Implementasi klasifikasi berbasis obyek memberikan hasil lebih baik dari klasifikasi berbasis piksel dengan jumlah fitur optimal yakni 7 fitur, terdiri dari 3 fitur dekomposisi Freeman (Red, Green, Blue), Entropy, Alpha Angle, Anisotrophy dan Normalized Difference Polarization Index (NDPI). Akurasi keseluruhan mencapai 73,64% untuk hasil klasifikasi berbasis obyek dan 62,6% untuk klasifikasi berbasis piksel.Kata kunci : Klasifikasi berbasis obyek, SRM, SVM, Sensor SAR1
PEMANFAATAN CITRA Pi-SAR2 UNTUK IDENTIFIKASI SEBARAN ENDAPAN PIROKLASTIK HASIL ERUPSI GUNUNGAPI GAMALAMA KOTA TERNATE (UTILIZATION OF Pi-SAR2 IMAGES FOR IDENTIFICATION THE PYROCLASTIC DEPOSITS FROM GAMALAMA VOLCANO ERUPTION TERNATE CITY) Suwarsono, -; Yudhatama, Dipo; Trisakti, Bambang; Sambodo, Katmoko Ari
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 10 No. 1 Juni 2013
Publisher : Indonesian National Institute of Aeronautics and Space (LAPAN)

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Abstract

Penelitian ini bertujuan untuk mengidentifikasi sebaran material endapan piroklastik hasil erupsi gunungapi dengan memanfaatkan citra radar Pi-SAR2. Obyek gunungapi yang dijadikan lokasi penelitian adalah Gunungapi Gamalama yang berada di wilayah Kota Ternate Provinsi Maluku Utara. Metode penelitian mencakup kalibrasi radiometrik data Pi-SAR2 untuk mendapatkan nilai intensitas hamburan balik (backscatter) sigma naught, perhitungan nilai-nilai statistik (rerata, standar deviasi dan koefisien korelasi antar band) sigma naught endapan piroklastik dan obyek-obyek permukaan lainnya, serta pemisahan sebaran endapan piroklastik menggunakan metode pengambangan (thresholding). Penelitian ini menyimpulkan bahwa citra Pi-SAR2 dapat dipergunakan untuk mengidentifikasi sebaran endapan piroklastik hasil erupsi gunungapi. Penggunaan secara bersamaan polarisasi HH, VV dan HV akan memberikan hasil lebih baik dibandingkan dengan menggunakan single polarisasi HH maupun VV. Penelitian ini menyarankan untuk dilakukan penelitian lebih lanjut dengan menerapkan metode verifikasi yang didukung dengan penggunaan data-data lapangan (ground check). Kata kunci: Pi-SAR2, Identifikasi, Endapan piroklastik, Gunungapi Gamalama
EKSTRAKSI OTOMATIS INFORMASI DEM DARI CITRA STEREO PRISM-ALOS Trisakti, Bambang
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol 4, No.1 Juni (2007)
Publisher : Indonesian National Institute of Aeronautics and Space (LAPAN)

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Abstract

ALOS satellite was launched on January 24th 2006 and is equipped by PRISM sensor which has a mission to produce stereoscopic image. PRISM is a panchromatic radiometer with 2.5 spatial resolution, and it has 3 telescopes for recording the image from nadir, forward and backward view is known as stereoscopic image which is usefull to generate earth surface height or DEM (Digital Elevation Model). Automatic DEM extraction was done by area based matching technique using PRISM DEM software. This technique correlates area/pixel in master image with same are/pixel in target image based based on grey value similarity of pixel. Relief displacement (parallax) of each area/pixel was extracted from the correlation process, and then it was used to generate earth surface height or DEM. The generated DEM was compared with reference data (SRTM X and C band) to analyze the level of DEM accuracy. The result shows that DEM from automatic extraction needs geoids correction (Eart surface relief correction). After doing the correction, the DEM has similar distribution height but smoother DEM pattern than referenced DEM. Finally, RMSE of PRISMDEM are around 16 m relative to the referenced DEM.
KAJIAN DAMPAK PERUBAHAN IKLIM TERHADAP KEBAKARAN HUTAN DAN DEFORESTASI DI PROVINSI KALIMANTAN BARAT Anggraini, Nanin; Trisakti, Bambang
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol 8 (2011)
Publisher : Indonesian National Institute of Aeronautics and Space (LAPAN)

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Abstract

Increasing or decreasing of rainfall intensity, due to the climate change, affects the enviroment condition in many Indonesia areas. For instance: low rainfall intensity causes high number of forest fire occurrence in Kalimantan Island. The impact of climate change is studied by analyizing the correlation among rainfall intensity, number of forest fire occurrence and forest area change in West Kalimantan Province. The rainfall is extracted using Tropical Rainfall Measurement Mission (TRMM) data for 2001- 2008. The number of forest fire occurrence is identified by the number of hotspot extracted from thermal sensor of satellite data MODIS for 2001 - 2008. The forest area is calculated from MODIS data for 2003, 2005, 2007 and 2009. Pixel which has Normalized Difference Vegetation Index (NDVI) value more than 0,7 along a year round is assumed as forest pixel. The NDVI value is obtained by doing training sample in forest area. The result shows that the rainfall has slightly upward trend in  limantan. The rainfall has negatif correlation with the number of hotspot. When the rainfall was the lowest and the number of hotspot was the highest in 2004, the forest area between 2003 and 2005 decreased (deforestation) significantly. On the other hand, then the rainfall was high and the hotspot was low in 2008, no decreasing in forest area otherwise we found the increasing of forest area. It is probably due to reforestation and expansion of plantation area (such as oil palm).Keywords: Rainfall, Climate change, Forest area, Hotspot, NDVI
KAJIAN KOREKSI TERRAIN PADA CITRA LANDSAT THEMATIC MAPPER (TM) Trisakti, Bambang; Kartasasmita, Mahdi; Kustiyo, -; Kartika, Tatik
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol 6, (2009)
Publisher : Indonesian National Institute of Aeronautics and Space (LAPAN)

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Abstract

Terrain correction is used to minimize the shadow effect due to variation of earth`s topography. So, the process is very useful to correct the distortion of the pixel value at the mountainous area in the satellite image. The aim of this paper is to study the terrain correction process and its implementation for Landsat TM. The algoritm of the terrain correction was built by determining the pixel normal angle which is defined as an angle between the sun and surface normal directions. The calculation of the terrain correction needs the information of sun zenith angle, sun elevation angle (obtained from header data), pixel slope, and pixel aspect derived from digital elevation model (DEM). The C coefficient from each band was determined by calculating the gradient and the intercept of the correlation between the Cos pixel normal angle and the pixel reflectance in each band. Then, the Landsat TM image was corrected by the algorithm using the pixel normal angle and C coefficient. C Coefficients used in this research were obtained from our calculation and from Indonesia National Carbon Accounting System (INCAS). The result shows that without the C coefficient, pixels value increases very high when the pixel normal angle approximates 900. The C coefficient prevents that condition, so the implementation of the C coefficient obtained from INCAS in the algorithm can produce the image which has the same topography appearance. Further, each band of the corrected image has a good correlation with the corrected band from the INCAS result. The implementation of the C coefficient from our calculation still needs some evaluation, especially for the method to determine the training sample for calculating the C coefficient. Keywords: Terrain correction, Pixel normal angle, C coefficient, Landsat TM
UTILIZATION OF IKONOS IMAGE AND SRTM AS ALTERNATIVE CONTROL POINT REFERENCE FOR ALOS DEM GENERATION Trisakti, Bambang; Winarso, Gathot; Julzarika, Atriyon
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 7, No 1 (2010): Vol 7,(2010)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

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Abstract

Abstract. Digital Elevation Model (DEM) was generated from Advanced LandObservation Satellite - The Panchromatic Remote-Sensing Instrument for Stereo Mapping(ALOS PRISM) stereo data using image matching and collinear correlation based on LeicaPhotogrametry Suite (LPS) software. The process needs three dimension of Ground ControlPoint (GCP) or Control Point (CP) XYZ as input data for collinear correlation to determineexterior orientation coefficient. The main problem of the DEM generation is the difficultyto obtain the accurate field measurement GCP in many areas. Therefore, another alternativeCP sources are needed. The aim of this research was to study the possibility of (IKONOS)image and Shuttle Radar Topography Mission (SRTM) X-C band to be used as CPreference for ALOS PRISM DEM generation. The study area was Sragen and Bandungregion. The DEM of each study area was generated using 2 methods: generated using fieldmeasurement GCPs taken by differential GPS and generated using CPs from IKONOSimage (XY coordinat) and SRTM for (Z elevation). The generated DEMs were compared.The accuracy of both DEMs were evaluated using another field measurement GCPs. Theresult showed that the generated DEM using CPs from IKONOS and SRTM X-C hadrelatively same height pattern and height distribution along transect line with the DEMusing GCPs. The absolute accuracy of the DEM using CPs was about 60% - 80% lessaccuracy comparing to the DEM using GCPs. This research showed that IKONOS imageand SRTM X-C band can be considered as good alternative CP source to generate highaccuracy DEM from ALOS PRISM stereo data.
LAND COVER CLASSIFICATION ALOS AVNIR DATA USING IKONOS AS REFERENCE Trisakti, Bambang; Ambarwati, Dini Oktaviana
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 9, No 1 (2012)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

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Abstract

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.
SIMULASI JALUR EVAKUASI UNTUK BENCANA TSUNAMI BERBASIS DATA PENGINDERAAN JAUH (STUDI KASUS; KOTA PADANG, PROPINSI SUMATERA BARAT) Trisakti, Bambang; Carolita, Ita; Nur, Mawardi
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol 4, No.1 Juni (2007)
Publisher : Indonesian National Institute of Aeronautics and Space (LAPAN)

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Abstract

Tsunami disaster caused great damages and very large victims especially when occurs in urban area along. Therefore information of evacuation in a map is very important for disaster preparedness in order to minimize the number of victims in affected area. Here, information generated from remote sensing satellite data (Landsat, SPOT-5 nad DEM) and secondary data (administration boundary and field survey data) are used ti simulate evacuation route and to produce a map for Padang City. Vulnerability and evacuation areas are determined based on information of maximum tsunami height in shoreline and topography condition. Landuse/landcover and infrastructure (road, bridge and building) are extracted from SPOT data. All the data obtained from remote sensing and secondary data are integrated using geospatial modeling to simulate tsunami evacuation routes. The simulation of evacuation route in Padang City for tsunami preparedness is provided by considering river line, shelters and save zone, available infrastructur (road), the shortest distance (to shelters and save zone) and local community experiences.