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Pengembangan Modul Pengelolaan Data Citra Inderaja dalam Sistem Bank Data Penginderaan Jauh Nasional (BDPJN) = Development of Remote Sensing Data Management Module in National Remote Sensing Data Bank (BDPJN) System
No full textPUSTEKDATA melaksanakan salah satu fungsinya untuk pengelolaan data citra inderaja melalui sistem Bank Data Penginderaan Jauh Nasional (BDPJN) dan telah mengelola beberaja jenis data citra inderaja dari resolusi rendah, menengah dan tinggi. Pengelolaan yang dimaksud adalah pengelolaan penyimpanan (subsistem storage) danpengelolaan diseminasi data citra inderaja (subsistem katalog). Permasalahan yang dihadapi adalah kebutuhanakan kapasitas penyimpanan data citra yang meningkat seiring dengan penambahan data hasil proses akuisisi dan pengadaan data citra inderaja. Dikembangkannya subsistem archive menggunakan media tape library untuk memindahkan datacitra dari media penyimpanan (storage) ke media tape (LTO) dengan pengaturan tertentu diharapkan dapat menjadi solusi dalam pengelolaan penyimpanan. Namun, adanya subsistem archive menimbulkan permasalahan baru di subsistem katalog karena lokasi data citra telah berubah dari media penyimpanan (storage) ke media tape (LTO) yangmengakibatkan data tidak bisa diakses oleh subsistem katalog. Tulisan ini mencoba melakukan kajian terhadap subsistem BDPJN yang ada dan mengembangkan modul prototyping antarmuka (interface) antara subsistem archivedan subsistem katalog dengan tujuan agar data tetap dapat diakses oleh subsistem katalog walaupun lokasi data telah berubah. Hasil percobaan menunjukkan bahwa secara umum dengan dikembangkannya modul antarmuka dapat mengatasi permasalahan perubahan lokasi data sehingga dapat diakses oleh subsistem katalog. Namun demikian masihterdapat hal-hal yang perlu diperhatikan dan dapat ditingkatkan untuk semakin meningkatkan performansi proses pengelolaan sistem BDPJN.PUSTEKDATA fulfill one of its functions for the management of remote sensing image data through the system of the National Remote Sensing Data Bank (BDPJN) and has been managing several types of remote sensing image data of low, medium and high resolution. The data management consists of the management of storage (storagesubsystem) and the management of remote sensing image data dissemination (subsystem catalog). The problem faced is the capacity need for image data storage increased along with the addition of data from the acquisition and procurement of remote sensing image data. The development of subsystems archive using the tape media library to transfer image data from storage media (storage) media to tape (LTO) with a particular arrangement is expected to be a solution in the storage management. However, the archive subsystem poses new problems in the subsystem catalog because the data location has been changed from the data storage to tape (LTO) which cause the data cannot be accessed by the catalog subsystem. This paper attempts to review the existing BDPJN subsystems and develop prototypes module interface (interface) between subsystems archive and catalog subsystem with the aim that the data can still be accessed by the subsystem catalog even though the location of the data has been changed. The results showed that in general the development of the interface module can overcome the problems of the change of location of data that is accessible by the subsystem catalog. However, there are still several things that need to be considered and can be upgraded to further improve process performance management of BDPJN system.hlm. 443-45
The dynamics of land use/land cover change modeling and their implication for the flood damage assessment in the Tondano watershed, North Sulawesi, Indonesia
No full texthlm.1-2
Hail Detection By A Low Cost Local Weather Radar Operated For Disaster Early Warning System
No full textHlm.33-3
Analysis of Urban Heat Temperature and Day/Night Temperature Variation in Jakarta City Using Remotely Sensed Data
No full textThermal satellite sensor images are widely used for identifying the environment temperature mainly in urbanized areas. The Thermal Infra Red Sensor (TIRS) onboard Landsat-8 contains two thermal bands, which measure land surface temperature (LST) at 30-meter resolution. Thermal band data provide important information about water irrigation, heat, as well as heat island in urban area. By using MODIS satellite also we can assess the day/night LST hence we can comprehend the diurnal temperature variation. In this study the LST that retrieved from satellite data will be used to identify urban heat island (UHI) effect in Jakarta city using Split Windows Algorithm method. As a result we obtain that the UHI area located on area with higher human and industrial activities, especially in central to eastern part of Jakarta. There is a tendency that the border area of Jakarta (east, west and southern part) can transform to be new UHI in the future. From field measurement also we calculate the lowest and the highest temperature is 23.2oC (for vegetation class) and 51oC (for road asphalt) respectively.Hlm.87-9
Development Of Labviewbasedportable Telemetrysystemfor The Daytime Measurement Of Solarultraviolet Intensity
No full textUV light is only a small part of the solar radiation spectrum, but these rays are most harmful to the skin, even the hazard can increase proportionally with intensity increasing on the skin exposed. The intensity of UV reaching the earth's surface is also one of the factors that are influenced by the ozone concentration in the atmosphere of an area. Considering that UV intensity could damage to human health and could be influenced by atmospheric conditions, it has been designed a Labview based portable telemetry system that detects the exposure intensity of UV rays. This system can measure the solar UV light intensity wirelessly using the 433MHz radio communication frequency and is equipped with a GPS module which serves to in form the coordinate position of the system. Using the graphical user interface (GUI) of Labview, the UV exposure-index measurement and local coordinate information will be displayed. The system has a good measurement performance and has the RF telemetry range as far as15 meters indoor and 90 meters out door.Hlm.173-18
Metode Estimasi Konsentrasi Gas Rumah Kaca Waktu Lampau (Paleoklimatologi)
No full textIt has been estimated greenhouse gas (GHG) concentrations of CO2 and CH4 in 1900 in Indonesia. Estimation GHG concentrations is done because of the difficulty of knowing a large concentration of GHG in the past. Knowledge of the concentration of GHG in 1900 are part of the climate change and to analyze the history of climate change. The methodused is a statistical analysis using software Powersim Constructor 2.5. The results of the estimation of concentration of GHG in Indonesia in 1900 was 219.79 ppm for CO2 and CH4 amounted to 971.42 ppb. If these results are compared with CO2 concentration measurement of paleoclimatology (ice cores) in Maona Loa (Hawaii) correlation coefficientof 0.95, while the concentration of CH4 has a correlation coefficient of 0.98 with the results of measurements of the location and the same method as the concentration of CO2. If the results of the model compared to the global CO2 concentration from NOAA satellites and a 0.99 correlation coefficient for the concentration of CH4 was r = 0.97. Based on correlationtest between output model with satellite data and correlation test between output model with observation data (in situ) to produce positive correlation coefficient (r) of which greater than 0.5, then the model with use Powersim can be recommended to estimate past CO2 and CH4 concentration.Hal. 131-13
Pengembangan Nilai Kualitas Radiometrik untuk Citra Landsat-8 (Fase I: Identifikasi Kabut)
No full textKualitas radiometrik citra menunjukkan seberapa baik citra tersebut bebas dari pengaruh kesalahanradiometrik, setidaknya ada 2 parameter yang dapat diperoleh dari data Landsat-8 dan digunakan untuk menilai kualitasradiometrik, yaitu adanya kabut (haze) dan adanya awan atau jarak dari awan. Sebagai langkah awal daripengembangan kualitas radiometrik citra, penelitian ini mengembangkan teknik untuk mengidentifikasi haze dari dataLandsat-8. Data yang digunakan adalah data Landsat-8 yang sudah terkoreksi geometrik ortho kemudian dilakukankoreksi radiometrik TOA (Top Of Atmosferic) dan BRDF (Biderectional Reflectance Distribution Function). Analisayang digunakan adalah membandingkan teknik tasseled cap haze transformation, simplified tasseled cap hazetransformation, haze optimized transform, dan algoritma pengembangan dengan teknik supervised haze transformation.Algoritma yang dikembangkan menggunakan histogram 2 dimensi (scaterplot 2D) dari kanal kanal biru dan merah,analisa dilakukan berdasarkan data contoh (sample) reflektansi vegetasi dan lahan terbuka dari tiga kelas haze (tanpahaze, sedikit haze, dan banyak haze). Dengan menggunakan analisa visual, dipilih algoritma terbaik dalam mendeteksihaze yaitu supervised haze transformation.Hlm. 124-13