Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital
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METODE DETEKSI TERUMBU KARANG DENGAN MENGGUNAKAN DATA SATELIT SPOT DAN PENGUKURAN SPEKTROFOTOMETER STUDI KASUS: PERAIRAN PANTAI RINGGUNG, KABUPATEN PESAWARAN
Full text linkCoral reefs are one of the spectacular ecosystems. These ecosystem provides good sand services, including protection from tropical storms, reef fisheries, opportunities for tourism and development of new pharmaceuticals. Coral reefs are marine resource that are to environmental changes (changes in water quality). it is very important to identify its status and monitor the changes of coralreef areas very often. Therefore, it is necessary to identify and monitor status changes as often as possible. This information is critical for conservation and sustainable development. This study focused on the identification of coral reefs by combining spectral information obtained from direct measurements in the field with the information band spectral remote sensing satellite SPOT. Based on the experiments, the correlation function which has the biggest correlation coefficient is a function obtained between the summation of the band (band1+band3) with the sum of spectral (spectral1 + spectral3). Based on the analsis, the methode/algorithm has been developed can identify/detect the shallow coral reefs/coral reefs-1 (depth of less than 1 meter) and not superficial coral reef/coral reefs-2 (depth of greater than 1 meters). Processing results show that Coral reefs-2 are found along the beach of Ringgung, while based on the calculation, around of the Tegal island there are 49 ha coral reefs-1, and 116 ha of Coral reefs-2, and around sandbar/sand arising surface water (area is 320 m²), the area coral reefs-1 are 12.38 ha and coral reef-2 in the area of approximately 42 ha
PEMANFAATAN CITA Pi-SAR2 UNTUK IDENTIFIKASI SEBARAN ENDAPAN PIROKLASTIK HASIL ERUPSI GUNUNGAPI GAMALAMA KOTA TERNATE
No full textThis research aims to identify the distribution of pyroclastic deposits from the eruption volcano by using Pi-SAR2 imagery. The object of research is Gamalama Volcano, located in the city of Ternate in North Maluku Province. Research methods include radiometric calibration Pi-SAR2 to get the value of backscatter intensity sigma naught, calculation of statistical values (mean, standard of deviation and coefficient of correlation between bands) backscatter intensity of sigma naught among pyroclastic deposits and other surface objects, as well as the separation distribution of pyroclastic deposits using thresholding methods. This research concludes that the Pi-SAR2 imagery can be used to identify the distribution of volcanic pyroclastic deposits from the eruption. Concurrent use of polarization HH, VV and HV will give better results than using a single polarization HH and VV. This research suggests further research to be done by applying the method of verification is supported by the use of field data (ground check)
PEMANFAATAN KANAL POLARISASI DAN KANAL TEKSTUR DATA PISAR-L2 UNTUK KLASIFIKASI PENUTUP LAHAN KAWASAN HUTAN DENGAN METODE KLASIFIKASI TERBIMBING
Full text linkPolarimetric and Interferometric Airborne SAR in L band (PiSAR-L2) is an upgraded PiSAR program, which has a purpose for experimental activities of PALSAR-2 sensor equiped by ALOS-2 in 2013. Japan Aerospace Exploration Agency (JAXA) and Ministry of Reseach and Technology Indonesia have collaborated to explore the utilization PiSAR-L2 data for some applications in Indonesia. The purpose of this research is to utilize full polarimetric band of PiSAR-L2 data to classify land cover of forest area in Riau province. Field data conducted by JAXA team was used as reference data to collect input and verification training samples. SAR data pre-processing was conducted by doing backscatter conversion (digital number to Sigma naught) and filtering process using Lee filter. Classification was carried out by Maximum Likelihood classifier using Maximum Likelihood Enhanced Neighbour method. The research used three treatments for input data, using three SAR polarization bands (HH, VV and HV), and using six bands (three SAR polarization bands and three texture bands (deviation HH, VV and HV), and using six bands (three polarization dan 3 texture bands) with training samples improvement based on confusion matrix result. Verification of classification results were done using confusion matrix for each treatment. The result shows that texture band can enhance the degree of separation between object classes of vegetation, especially between forest and acacia plantation. Classification using six bands (three polarization dan 3 texture bands) with training sample improvement increased the overall accuracy and kappa statistic of the classification result to be 80% and 0.612 respectively
supabase Please extract the text as it is Here is the extracted text from the image: DENOSING OF HIGH RESOLUTION REMOTE SENSING DATA USING STATIONARY WAVELET TRANSFORM Danang Surya Candra Peneliti Bidang Jianta, Pusdata, LAPAN e-mail: thedananx@yahoo.
No full textLand cover change, from bare land, water and to vegetation, or vice versa can be used as the basis for paddy fields mapping using the theory of probability, that is probability a land cover can be regarded as an paddy fields if a sequence of land cover changes of water, vegetation and bare land or vice versa on multitemporal images have been detected. The data being used were Landsat multitemporal imagery, while the methods being used in this analysis is the transformation of vegetation index and converted to land covers (bare land, water and vegetation). Detection of three types of land covers (bare land-water_vegetasi or viceversa) at sample area is assumed to have a probability 1 as paddy fields, if only two of the land cover types were detected (water and bare land , or water and vegetation , or vegetation or bare land ) the land cover of that pixel is assumed to have the probability as paddy fields 0.67, whereas if only one land cover types were detected for example only of water, or bare land or vegetation only, then the probability as paddy fields is assumed to be just 0.33. The results of the study showed that multitemporal Landsat of the study area is adequate for paddy fields mapping with accuracy of 91.2%
PEMETAAN MUATAN PADATAN TERSUSPENSI MENGGUNAKAN DATA SATELIT LANDSAT (STUDI KASUS: TELUK SEMANGKA)
Full text linkTotal Suspended Matters (TSM) defined all solids or particles with a larger size 1 µm that are suspended in water resulting in decreased quality of water until the water can not be used as intended. There are various methods that have been made in mapping the TSM based on remote sensing satellite data both low and high resolution. This paper describes TSM mapping which TSM algorithm was directly applied to the digital number value of Landsat image. The mapping process was preceded by a thresholding method to separate the water with other objects (clouds, cloud shadows and the mainland), then the TSM concentration was calculated through the algebraic sum of band 1, 2, 3, and 4 and ended with density slice range process. Based on the TSM analysis, the TSM concentration in the Semangka Gulf was caused by human waste and also the material carried by streams of water from ponds and sewage waste soil erosion. TSM concentration areas was spread out in water of the Wonosobo District until 640 meters of spreading length and Kota Agung Timur districts until 3240 meters of spreading length
EVALUASI PRODUK MODIS GROSS PRIMARY PRODUCTION PADA HUTAN RAWA GAMBUT TROPIS INDONESIA
Full text linkGross Primary Production (GPP) estimation method was developed as one approach for calculating the amount of carbon stored in vegetation. One of the GPP products which can be operationally downloaded free of charge from Terra/Aqua MODIS (NASA satellite) is MODIS GPP product (MOD17). The examination of this product needs to be performed in several ecosystem types due to its global properties. Recently, a new version of the product has been launched, however its examination on tropical forests particularly over Indonesia has not been implemented yet. In this study, new version of MODIS GPP (MOD17A2-51) was evaluated in tropical peat swamp forest, in Central Kalimantan Province using time series and statistical analysis of field data (GPP EC). The study results show that the time series of 8-daily MODIS GPP provide a similar pattern although it has low correlation. In general, MODIS GPP tend to be underestimate either on rainy or dry season. However, an overestimate result was found during the ENSO-caused long dry season in 2002. Nevertheless, the accumulated value of GPP with seasonal consideration (dry and rainy) shows good relationship (r=0.94, RMS= 17.47, and Efficiency score= 0.68). The 2nd dry season period (August-October) shows better distribution than other periods. This study concludes that the MODIS GPP product version 51 can be used for biomass seasonal monitoring of tropical peat swamp forests in Indonesia
KLASIFIKASI SPASIAL PENUTUP LAHAN DENGAN DATA SAR DUAL-POLARISASI MENGGUNAKAN NORMALIZED DIFFERENCE POLARIZATION INDEX DAN FITUR KERUANGAN DARI MATRIK KOOKURENSI
Full text linkIn this study, the land cover classification method using the spatial information features of co-occurrence matrix and Normalized Difference Polarization Index (NDPI) data from dual polarization SAR Data was proposed. The spatial information features are used as input of supervised classification, and to get the performance of the proposed method, land cover classification was conducted with SAR C-band and L-band satellite data of Envisat ASAR and ALOS PALSAR. The results of the study are, the size of window on the SAR image to get the spatial information features of co-occurrence matrix and the use of additional NDPI data are giving effect to the accuracy of classification results. At the test area in Siak Riau Province which have 7 classes of land use, the optimum window size for co-occurrence matrix is 7 pixel x 7 pixel for ASAR data which has 75m spatial resolution, and more than 9 pixel x 9 pixel for PALSAR data which has 10m spatial resolution. The addition of the co-occurrence matrix information of NDPI data can improve the classification of accuracy up to 2%
STANDARISASI KOREKSI DATA SATELIT MULTIWAKTU DAN MULTISENSOR (LANDSAT TM/ETM+ DAN SPOT-4)
Full text linkRemote sensing satellite data has been widely used to support watershed and lake managements. However researches conducted in Indonesia are facing common problems related with standardization of data pre-processing, particularly that are related to orthorectification and radiometric correction. The objective of this research is to standardize the satellite data correction to monitor Total Suspended Material (TSM) in Limboto lake along 1990-2010 period using Landsat TM/ETM+ and SPOT-4. The data correction process was performed included orthorectification, sun correction, terrain correction and normalization of data with different time and different sensor. The result of each correction process was examined to evaluate the quality improvement before and after correction. The corrected data was then used to monitor the degree of turbidity of Limboto Lake during 1990-2010 periods. The study results show that data correction reduces position error and object spectral difference due to differences in acquisition time and sensor. The examined correction provides more accurate and consistent results. The quality of Limboto Lake was monitored decreases gradually, where the higher TSM concentration was found during the period of 1990-2010
APLIKASI MODEL PROBABILISTIK UNTUK SIMULASI ALIRAN MATERIAL ERUPSI STUDI KASUS: GUNUNG MERAPI, JAWA TENGAH
Full text linkSimulation of eruption material flow using probabilistic model based on the Monte Carlo algorithm was conducted in this research. The simulation result was used to support the creation of zoning map of volcanic hazards and the estimation of building number which has possibility to be impacted by the Merapi Volcano eruption. Input data for the simulation was Digital Elevation Model - Shuttle Radar Topographic Mission (DEM-SRTM) with a spatial resolution of 30 meters. In addition, GeoEye satelit imagery in 2009 was used to renew settlement information of the RBI map from BAKOSURTANAL. The simulation result of material flow eruption was overlaid with building area information to estimate the magnitude of eruption impact. The simulation results from this research has similar pattern and similar eruption material distribution with the reference map (volcanic hazard map of Merapi). The flow of Merapi eruption material generally leads to the south through the Gendol Rivers to Cangkringan, and to the southwest ward through the Puth Rivers to Srumbung. Material flow eruption is shown in height simulations 2 meters and 7 meters. The wider and widening of the simulation models material flow eruption generated, the greater impact on the settlements in the vicinity of Merapi Volcano
MODEL SIMULASI BANJIR MENGGUNAKAN DATA PENGINDERAAN JAUH, STUDI KASUS KABUPATEN SAMPANG DENGAN MENGGUNAKAN METODE GRIDDED SURFACE SUBSURFACE HYDROLOGIC ANALYSIS
Full text linkThe problem of flood that yearly occurred in Sampang district was due to the very large amount of runoff flow to the Sampang Cit, very high sedimentation in the river that crosses the city, as well as the lack of good drainage system especially in urban residential areas. Some of that problems eventually can lead to flooding in the City of Sampang. The method used for flood simulation model was GSSHA (Gridded Surface Subsurface Hydrologic Analysis), which is able to produce a good hydrological components. The data used data in this research among others are: Qmorph, DEM-SRTM (Digital Elevation Model-Shuttle Radar Topography Mission), SPOT-5 of 2010, land map, river cross sections and field data. This flood simulation model research resulting flood discharge, which is described in the hydrograph and flood depth calculations. The peak discharge resulted in several catchment areas (CA): Klampis CA is 5.40 m³/s, Jelgung CA is 364788.9 m³/s, Kamoning CA is 32.40 M³/s, and 3 CAs which are associated with the above CAs is 174059 m³/s