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DIFFERENCES OF COASTALLINE CHANGES IN THE AREA AFFECTED BY LAND COVER CHANGES AND COASTAL GEOMORPHOLOGICAL SOUTH BALI 1995 - 2021
No full textThe South Bali coast is prone to abrasion due to its geographical position facing the Indian Ocean. High sea waves and currents in the south of Bali will erode beaches whose lithology and morphology are prone to abrasion. Land cover conditions that do not support coastal protection will also affect the high abrasion of the southern coast of Bali. This study aims to analyze the shoreline changes in South Bali from 1995-2021. The analytical method used is the Digital shoreline analysis system (DSAS), with data from Landsat 5 TM, Landsat 7 ETM+, Landsat 8 OLI/TIRS, and Sentinel 2A. The analysis results show that the area directly facing the waves is relatively high, with volcanic rock formations, and there is no mangrove as coastal protection. The lack of good coastal management shows the area with the highest abrasion. It was found in the western part of Tabanan Regency, eastern Gianyar, and southern Badung. Meanwhile, the average coastal accretion was relatively high in the neck of South Bali, in areas where the land cover was mangrove and adjacent to river mouths, which experienced much sedimentation
TEA PLANT HEALTH RESEARCH USING SPECTROMETER
No full textTea leaves are the most important part for consumption. Leaves that are healthy have a distinct color, while leaves that are not healthy have a color that is very different from the original. Chlorophyll in leaves effects the reflection of infrared light, allowing healthy plants to reflect more infrared light than unhealthy plants. Leaf color and chlorophyll have an important role in showing the growth and health of tea plants. Remote sensing consists of collecting information about objects and features without contacting the equipment. The Normalized Difference Vegetation Index (NDVI), one of the first remote sensing analysis products used to simplify the complexity of multispectral imaging, is now the most commonly used index for botanical assessment. inconsistencies in NDVI depending on sensor-specific spatial and spectral resolutions. Different parts of the leaf have discolored spots due to health conditions or nutritional stress, so there are different spectral values on different parts of the leaf. Unhealthy tea leaves have low NIR values due to disease, insects, and sunburn, which damage the chloroplast structure of the leaves, weaken the absorption of the appropriate band, and increase reflectance. There is a difference between the measurement results of the NDVI spectrometer and the sentinel image. This is due to the fact that the Sentinel-2 image can only retrieve image pixels with a resolution and not diseased leaf parts, as with the use of a spectrometer, which directly extracts the value of the infected area from the normal part of the plan
TSUNAMI DISASTER MODELING FOR NON-MILITARY DEFENSE IN PANGANDARAN REGENCY USING GEOGRAPHIC INFORMATION SYSTEMS
No full textThe tsunami disaster is one of the non-military threats to the State of Indonesia. Pangandaran Regency has a coastline of 91 km which is directly opposite the Megathrust of West-Central Java. The coastal area of Pangandaran Regency is an important center of tourism and economic activity and a high risk area for tsunamis due to earthquakes. This study was conducted to model the tsunami and analyze the magnitude of the inundation generated in settlements and tourist attractions in Pangandaran Regency as a form of defensive effort in disaster mitigation. The method used is tsunami modeling based on earthquake parameters using winITDB software. After modeling, it will be continued with H-Loss calculations based on tsunami run-up height data parameters, Digital Elevation Model (DEM) data, land use or cover data, and shoreline data using Geographic Information Systems. The results of the tsunami modeling are that the estimation waves height and estimation time arrival from three tide gauges are 15,34 m and 31,13 minutes. The total inundation area is 31.081 ha. The area of inundation according to the classification of land use is the most crucial and includes life, namely settlements and places of activity covering an area of 2.339,2 ha
RADAR-BASED STOCHASTIC PRECIPITATION NOWCASTING USING THE SHORT-TERM ENSEMBLE PREDICTION SYSTEM (STEPS) (CASE STUDY: PANGKALAN BUN WEATHER RADAR)
No full textNowcasting, or the short-term forecasting of precipitation, is urgently needed to support the mitigation circle in hydrometeorological disasters. Pangkalan Bun weather radar is single-polarization radar with a 200 km maximum range and which runs 10 elevation angles in 10 minutes with a 250 meters spatial resolution. There is no terrain blocking around the covered area. The Short-Term Ensemble Prediction System (STEPS) is one of many algorithms that is used to generate precipitation nowcasting, and is already in operational use. STEPS has the advantage of producing ensemble nowcasts, by which nowcast uncertainties can be statistically quantified. This research aims to apply STEPS to generate stochastic nowcasting in Pangkalan Bun weather radar and to analyze its advantages and weaknesses. Accuracy is measured by counting the possibility of detection and false alarms under the 5 dBZ threshold and plotting them in a relative operating characteristic (ROC) curve. The observed frequency and forecast probability is represented by a reliability diagram to evaluate nowcast reliability and sharpness. Qualitative analysis of the results showed that the STEPS ensemble produces smoothed reflectivity fields that cannot capture extreme values in an observed quasi-linear convective system (QLCS), but that the algorithm achieves good accuracy under the threshold used, up to 40 minutes lead time. The ROC shows a curved upper left-hand corner, and the reliability diagram is an almost perfect nowcast diagonal line
DETECTING SURFACE WATER AREAS AS ALTERNATIVE WATER RESOURCE LOCATIONS DURING THE DRY SEASON USING SENTINEL-2 IMAGERY (CASE STUDY: LOWLAND REGION OF BEKASI-KARAWANG, WEST JAVA PROVINCE)
No full textIn Indonesia, drought is a type of disaster that often occurs, especially during the dry season. What is most needed at such times is the availability of sufficient water sources to meet shortages. Therefore, water source locations are vital during the dry season in order to meet needs. To meet this information need, remote sensing data offer a precise solution. This research proposes a rapid method of detecting surface water areas based on remote sensing image data. It focuses on the use of remote sensing satellite imagery to detect objects and the location of surface water sources. The purpose of the study is to rapidly identify objects and locate surface water sources using Sentinel-2 MSI (MultiSpectral Instrument), one of the latest types of remote sensing satellite data. Several water index (WI) methods were applied before deciding which was most suitable for detecting surface water objects. The lowland region of Bekasi-Karawang, a drought prone area, was designated as the research location. The results of the research show that by using Sentinel-2 MSI imagery, MNDWI (Modified Normalized Water Index) is the appropriate parameter to detect surface water areas in the lowland region of Bekasi-Karawang, West Java Province, Indonesia, during times of drought. The method can be employed as an alternative approach based on remote sensing data for the rapid detection of surface water areas as alternative sources of water during the dry season. The existence of natural water sources (swamps, marshes, ponds) that remain during this time can be used as alternative water resources. Further research is still needed which focuses on different geographical conditions and other regions in Indonesia
ASSESSING THE POSSIBILITY OF LAND SUBSIDENCE DUE TO GEOTHERMAL PRODUCTION IN SARULLA GEOTHERMAL FIELD USING SENTINEL-1
No full textSarulla geothermal field is one of the largest geothermal fields in the world which has a 330 MW installed capacity. The field consists of three areas, namely Namora Langit (NIL)-1, NIL-2, and Silangkitang (SIL) which operated from 2017 and 2018. It is situated precisely at the Sarulla graben which is an active tectonic area composed of Quaternary Toba tuff and intermediate lava and extrusive felsic pyroclastic Toru. This study aims to see whether land subsidence may emerge in the Sarulla geothermal field and its environs in addition to determining whether the geothermal activity or anthropogenic is responsible for the deformation. We used the persistent scatterer (PS) interferometry synthetic aperture radar (InSAR) method to calculate the rate of subsidence in the area. 30 ascending images from Sentinel-1 were gathered from 5 January to 18 December 2020 with a separation of 12 days to run the analysis. The results demonstrate that Sarulla is undergoing subsidence occurring at NIL and SIL with a velocity of 0 to -32.9 mm/year. Although negative deformation occurs in the geothermal area, there is no solid evidence indicating geothermal fluid extraction is the cause of subsidence
PRELIMINARY STUDY OF A RADIO FREQUENCY INTERFERENCE FILTER FOR NON-POLARIMETRIC C-BAND WEATHER RADAR IN INDONESIA (CASE STUDY: TANGERANG WEATHER RADAR)
No full textC-Band weather radar that operates at a frequency of 5 GHz is very vulnerable to radio frequency interference (RFI) because it is located on a free used frequency. RFI can cause image misinterpretation and precipitation echo distortion. The new allocation for free spectrum recommended by the World Radio Conference 2003 and weather radar frequency protection in Indonesia controlled by the Balai Monitoring Spektrum Frekuensi (BALMON) have not provided permanent protection against weather radar RFI. Several RFI filter methods have been developed for polarimetric radars, but there have been no studies related to RFI filters on non-polarimetric radars in Indonesia. This research aims to conduct an initial study of RFI filters on such radars. Four methods were applied in the initial study. The Himawari 8 cloud mask was used to eliminate interference echo based on VS, IR, and I2 channels, while the nature of false echo interference that does not have a radial velocity value was used as the basis for the application of the Doppler velocity filter. Another characteristic in the form of consistent echo interference up to the maximum range was used as the basis for applying a beam filling analysis filter with reflectivity thresholds of 5 dBZ and 10 dBZ, with beam filling of more than 75%. Finally, supervised learning Random Forest (RF) was also used to identify interference echo based on the characteristics of the sampling results on reflectivity, radial velocity, and spectral width data. The results show that the beam filling analysis method with a threshold of 5 dBZ provides the best RFI filter without eliminating echo precipitation
LAND USE/COVER CHANGE ON POTENTIAL LOSS OF SUMATRAN TIGERS IN KERINCI SEBLAT NATIONAL PARK BASED ON REMOTE SENSING DATA
No full textThe Sumatran tiger is an animal whose life is threatened due to land use changes and human activities. This study described the correlations between land cover/use change and the potential loss of Sumatran tigers in Kerinci Seblat National Park (KSNP) based on remote sensing data. Remote sensing technology was used due to the good historical data, and it can be used for land cover change analysis. The results of the land change analysis can be used to the analysis of the changes in the suitability level of the Sumatran tiger habitat. The analysis of land change in 2000 and 2020 with the random forest classification method and changes in the level of suitability of the Sumatran Tiger habitat has been carried out. The results of the analysis of land cover/use changes showed a very significant reduction in the area of primary forest, namely 282.58 km2, while the increase in the area of plantations and secondary forests was 186.52 km2 and 101.68 km2. This change affects the suitability level of the Sumatran tiger habitat from a very suitable level decreased from 164.42 km2 to suitable and not suitable. The declining suitability level class indicated the potential loss of Sumatran tigers in the Kerinci Seblat National Park. The increasing of plantation and settlement areas will increase the activity of humans. The conflict of human activity with Sumatran tigers’ life will impact the loss of Sumatran Tigers in KSN
CLOUD IDENTIFICATION FROM MULTITEMPORAL LANDSAT-8 USING K-MEANS CLUSTERING
No full textIn the processing and analysis of remote-sensing data, cloud that interferes with earth-surface data is still a challenge. Many methods have already been developed to identify cloud, and these can be classified into two categories: single-date and multi-date identification. Most of these methods also utilize the thresholding method which itself can be divided into two categories: local thresholding and global thresholding. Local thresholding works locally and is different for each pixel, while global thresholding works similarly for every pixel. To determine the global threshold, two approaches are commonly used: fixed value as threshold and adapted threshold. In this paper, we propose a cloud-identification method with an adapted threshold using K-means clustering. Each related multitemporal pixel is processed using K-means clustering to find the threshold. The threshold is then used to distinguish clouds from non-clouds. By using the L8 Biome cloud-cover assessment as a reference, the proposed method results in Kappa coefficient of above 0.9. Furthermore, the proposed method has lower levels of false negatives and omission errors than the FMask method
BATHYMETRY DATA EXTRACTION ANALYSIS USING LANDSAT 8 DATA
No full textThe remote sensing technique can be used to produce bathymetric map. Bathymetric mapping is important for the coastal zone and watershed management. In the previous study conducted in Menjangan Island of Bali, bathymetric extractin information from the top of the atmosphere (TOA) reflectance image of Landsat ETM+ data has R2 = 0.620. Not optimal  correlation value produced is highly influenced by the reflectance image of Landsat ETM+ data, were used, hence the lack of the research which became the basis of the present study. The study was on the Karang Lebar water of Thousand Islands, Jakarta. And the aim was to determine whether there was an increased correlation coefficient value of bathymetry extraction information generated from Surface reflectance and TOA reflectance imager of Landsat 8 data acquired on August 12, 2014. The method of extraction was done using algorithms Van Hengel and Spitzer (1991). Extraction   absolute depth information obtained from the model logarithm of Landsat 8 surface reflectance images and pictures TOA produce a correlation value of R2 = 0.663 and R2 = 0.712