Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital
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Pengembangan Tiling database untuk Penyimpanan Data Penginderaan Jauh pada Pembangunan LAPAN Engine
Full text linkRemote sensing image data is included in the unstructured data category which is characterized by large volumes of data and is regularly updated. Special techniques are needed in large capacity data storage and supported by high-capacity data processing machines. This study aims to find a design representation of remote sensing image data that is more efficient in storage and processing than conventional methods. The design proposed is with the concept of tiling databases, namely the method of breaking down image data into small size pieces with certain identities and then entering them into a database. The test results compared to the conventional method found that the storage volume can be reduced by up to 25%, the speed of reading the data also increases by about 21%. This system can support the development of LAPAN Engine because it offers a storage strategy that is more effective in terms of volume, and efficient in terms of the speed of reading data even though the tiling process into the database takes pretty long time.
 
ANALISIS METODE KOMPRESI BERDOMAIN WAVELET PADA CITRA SATELIT RESOLUSI SANGAT TINGGI
Full text linkA problem that often arises in remote sensing images, especially very high-resolution images, is the large storage and bandwidth needed to transmit those images. On satellite images processing, a compression needs to be done on those satellites images to make it easier in terms of transmission and storage. This paper compare several wavelet-domain methods namely wavelet method, bandelet method, and CCSDS to find the best method to compress the very high-resolution satellites imageries Pleiades. Experiment results show that the method wavelet and bandelet is better in preserving the images quality with around 50 dB PSNR, while CCSDS is better in reducting the image size to the eighth of original image
ANALISIS PENINGKATAN KUALITAS GEOMETRI DENGAN MENGGUNAKAN TITIK IKAT BUNDLE ADJUSTMENT (STUDI KASUS DATA PLEIADES WILAYAH KABUPATEN MADIUN DAN KABUPATEN MAGETAN)
Full text linkRecently, the utilization of very high spatial resolution data such as Pleaides has reached at a high demand. Particularly to support disaster mitigation, where automation and fast image processing are necessary and unavoidable. Pleiades imagery has been acquired at LAPAN ground station starting in 2018. This study examines the improvement of the Pleiades images geometry accuracy processed using the bundle adjustment (BA) method in order to support image mosaicking where case study is located in the Madiun regency and the Magetan regency. This method uses parameters to relate the geometry between scenes by using tie points. These points are located in the intersection area between scenes. Geometry quality assessment of the imagery produced using BA correction are measured by comparing between the coordinate of the imagery and the coordinates obtained from the field measurement. The assessment shows that BA geometry correction has improved the geometry quality of the images which nearly similar to the field measurement and achieved a better geometry accuracy compare to the images processed without BA method
PENGARUH DISTRIBUSI SPASIAL SAMPEL PEMODELAN TERHADAP AKURASI ESTIMASI LEAF AREA INDEX (LAI) MANGROVE
Full text linkLeaf Area Index (LAI) has an important role in defining the health of mangrove forest. Remote sensing images able to estimate mangrove LAI, especially through semi-empirical approach. This approach needs appropriate selection of sample location and value distribution for both modelling and accuracy assessment purposes. However, both aspects are often neglected when selecting the sample for modelling. This research aims to explor and analyze the LAI field sample collected to answer (1) if the spatial and (2) value distribution of modelling samples affect the accuracy of mangrove LAI estimation. The method used was by developing regression models between Soil-Adjusted Vegetation Index (SAVI) pixel values derived from ALOS AVNIR-2 image (10m) and field LAI measurement using LICOR LAI-2200. The modelling samples were selected randomly and purposively through three simulations based on spatial distribution and value range of the samples. The accuracy of the estimation was assessed using 1:1 relationship plots and Standard Error of Estimate (SEE). The research results show that the accuracy of LAI estimation is dependent to the spatial distribution and the range value of the modelling samples. High estimation accuracy achieved when the sample location for modelling is evenly distributed and covers the range of the field sample values
PENGARUH TINGGI MUKA AIR GAMBUT SEBAGAI INDIKATOR PERINGATAN DINI BAHAYA KEBAKARAN DI SUNGAI JANGKANG - SUNGAI LIONG
Full text linkDisasters of forest and land fires are increasingly concerned. The nature of peat soil which is easy to lose water and high organic matter content causes peat soils to be very sensitive to fire. Therefore it is necessary to know indicators for early warning of fires on peatlands. The purpose of this study is to determine the critical groundwater level (GWL) as an indicator of peatland fires on the Jangkang River - Sungai Liong. Determination of the critical point of peatland fires as a fire early warning is done by calculating the difference from the value of the undefined TMA with a range of possible errors. The TMA value is obtained from the estimation of several methods, namely data on the physical properties of the soil, the drought index, and a combination of both. The TMA estimation of the physical properties of the soil has a range of fires at depths of 74.3 - 107 cm. In estimating TMA using a drought index, potential fires occur in TMA ranging from 27 - 101 cm. While the combined estimates of the physical properties of the soil and the drought index ranged from 66.8 - 98.8 cm the occurrence of fires on peatland. The results of this study show that the estimated TMA from a combination of field data and drought index provides fairly good accuracy. Thus TMA can be an early warning indicator of the danger of peatland fires. This TMA estimation can give faster results and pretty good accuracy. But this estimation model for TMA does not necessarily apply directly to other research locations. The critical point of peat soil water depth ranges from 27 to 74 cm. The depth of the peatland surface should be maintained less than the critical point, if not then the potential for peatland fires will increase.
 
MODIFIKASI DIGITAL ELEVATION MODEL (DEM) CITRA RESOLUSI TINGGI MENGGUNAKAN FUSI INTERFEROMETRI SAR DAN STEREOSAR BERBASIS FAKTOR PEMBOBOTAN
Full text linkSAR satellite sensors are capable to measure elevation of the earth surface using interferometry (InSAR) or radargrammetry (StereoSAR) methods. The InSAR method utilizes phase value from SAR images, while the StereoSAR uses amplitude value to produce elevation of the earth surface. Both methods have advantages and disadvantages on each own. Problems with low accuracy on DEM generated using InSAR occur on shadow and layover area, while in the second method (StereoSAR) the problem arise when cross correlation between the two images have low value. This paper proposes a technique to combine InSAR and StereoSAR methods to generate DEM using high resolution SAR images. A pair of TerraSAR-X or TanDEM-X images with a 21 degree incidence angle are used in this study and processed using the InSAR method and another pair of images at an angle of 21 degrees and 41 degrees using the StereoSAR method in Bandung and surrounding areas. The experimental results show that the fusion DEM of the two methods have better accuracy and decrease the absolute error both from InSAR and StereoSAR technique methods that separately around 3.48 m and 1.80 m
ESTIMASI BATIMETRI DARI DATA SPOT 7 STUDI KASUS PERAIRAN GILI MATRA NUSA TENGGARA BARAT
Full text linkIndonesia is an archipelagic state consists of five large islands and thousands of small islands surrounded by shallow marine waters. For this reason, complete and accurate bathymetric information is needed. Large scale bathymetry data in Indonesian waters is still limited, including in the shallow sea waters of Gili Matra, NTB Province. To overcome these problems, remote sensing technology is used. The aim of the study was to analyze the effect of shallow marine habitat base objects on estimating bathymetry from SPOT 7 satellite images. Many methods can be used to produce estimated bathymetry with this technology. The analysis used in this study is multiple linear regression (MLR). The data used is SPOT 7 satellite imagery in the shallow sea waters of Gili Matra, West Nusa Tenggara Province. The estimation of bathymetry was carried out using insitu depth data with two modifications. The first modification did not pay attention to the basic habitat object types and the second modification paid attention to the coral habitat, seagrass, macroalgae and substrate objects. The results of this study provide the value of determination R2 which increased from 72.1% to 78.6% and decreased the RMSE value from 3.3 meters to 2.9 meters
MODEL ESTIMASI TINGGI MUKA AIR TANAH LAHAN GAMBUT MENGGUNAKAN INDEKS KEKERINGAN
Full text linkThe Ground Water Level plays an important role in determining the greenhouse gas emission and, in turn, in regulating global climate system. Information on existing water levels is still using field measurements. The purpose of this study was to evaluate the best approximation model for estimating water level using drought index. This study utilizes Landsat 8 data to calculate Normalized Difference Water Index and Visible and Shortwave infrared Drought Index for 3 months (March, April and June 2016). The best estimation model is selected by the Akaike Information Criteria correction method and validated using K-Fold cross-validation. The results of this study indicate that the estimation of water level is affected by both drought indices with the TMA (mm) equation = -439,47 – 1639,7 * NDWI_Maret – 640,23 * NDWI_April + 477 * VSDI_Maret. Estimated water level began to detect hotspots ranging from 64,35 ± 36,9 6 cm (27 - 101 cm). The critical point for KHG Sei Jangkang - Sei Liong is 27 cm, thus the water level depth should be maintained less than that to avoid fire in peatlands
ALGORITMA HAZE DETECTION DENGAN MENGGUNAKAN HAZE INDEX PADA CITRA SPOT 6/7
Full text linkMultispectral satellite imagery often contaminated by haze and cirrus. It will reduce the accuracy of data interpretation. There are some haze detection methods that have been developed by the experts. However, haze detection is still one of the important challenges for the correction of multispectral optical data. The method is used on hazy SPOT 6/7 imagery. This method is developed based on the reflectance slope of blue and red visible bands. It is used based on the comparison that has been done in the STCHT, HOT, and SHT method. Adding the formula with different coefficients to get the optimum haze index value. Furthermore, the regression analysis has been done on the haze and cloud’s threshold value that is given by the applications of optimum haze index
