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All Journal Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan (Journal of Natural Resources and Environmental Management) International Journal of Remote Sensing and Earth Sciences (IJReSES) Jurnal Tanah dan Iklim The International Journal of Remote Sensing and Earth Sciences (IJReSES)
Indah Prasasti
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Agriculture, Biological Sciences & Forestry Earth & Planetary Sciences Environmental Science

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DETECTING DEFORMATION DUE TO THE 2018 MERAPI VOLCANO ERUPTION USING INTERFEROMETRIC SYNTHETIC APERTURE RADAR (INSAR) FROM SENTINEL-1 TOPS Suwarsono; Indah Prasasti; Jalu Tejo Nugroho; Jansen Sitorus; Rahmat Arief; Khalifah Insan Nur Rahmi; Djoko Triyono
International Journal of Remote Sensing and Earth Sciences Vol. 16 No. 1 (2019)
Publisher : BRIN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.ijreses.2019.v16.a3145

Abstract

This paper describes the application of Sentinel-1 TOPS (Terrain Observation with Progressive Scans), the latest generation of SAR satellite imagery, to detect displacement of the Merapi volcano due to the May–June 2018 eruption. Deformation was detected by measuring the vertical displacement of the surface topography around the eruption centre. The Interferometric Synthetic Aperture Radar (InSAR) technique was used to measure the vertical displacement. Furthermore, several Landsat-8 Thermal Infra Red Sensor (TIRS) imageries were used to confirm that the displacement was generated by the volcanic eruption. The increasing temperature of the crater was the main parameter derived using the Landsat-8 TIRS, in order to determine the increase in volcanic activity. To understand this phenomenon, we used Landsat-8 TIRS acquisition dates before, during and after the eruption. The results show that the eruption in the May–June 2018 period led to a small negative vertical displacement. This vertical displacement occurred in the peak of volcano range from -0.260 to -0.063 m. The crater, centre of eruption and upper slope of the volcano experienced negative vertical displacement. The results of the analysis from Landsat-8 TIRS in the form of an increase in temperature during the 2018 eruption confirmed that the displacement detected by Sentinel-1 TOPS SAR was due to the impact of volcanic activity. Based on the results of this analysis, it can be seen that the integration of SAR and thermal optical data can be very useful in understanding whether deformation is certain to have been caused by volcanic activity.
DETECTING THE LAVA FLOW DEPOSITS FROM 2018 ANAK KRAKATAU ERUPTION USING DATA FUSION LANDSAT-8 OPTIC AND SENTINEL-1 SAR Suwarsono; Indah Prasasti; Jalu Tejo Nugroho; Jansen Sitorus; Djoko Triyono
International Journal of Remote Sensing and Earth Sciences Vol. 15 No. 2 (2018)
Publisher : BRIN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.ijreses.2018.v15.a3078

Abstract

The increasing volcanic activity of Anak Krakatau volcano has raised concerns about a major disaster in the area around the Sunda Strait. The objective of the research is to fuse Landsat-8 OLI (Operational Land Imager) and Sentinel-1 TOPS (Terrain Observation with Progressive Scans), an integration of SAR and optic remote sensing data, in observing the lava flow deposits resulted from Anak Krakatau eruption during the middle 2018 eruption. RGBI and the Brovey transformation were conducted to merge (fuse) the optical and SAR data. Â The results showed that optical and SAR data fusion sharpened the appearance of volcano morphology and lava flow deposits. The regions are often constrained by cloud cover and volcanic ash, which occurs at the time of the volcanic eruption. Â The RGBI-VV and Brovey RGB-VV methods provide better display quality results in revealing the morphology of volcanic cone and lava deposits. The entire slopes of Anak Krakatau Volcano, with a radius of about 1 km from the crater is an area prone to incandescent lava and pyroclastic falls. The direction of the lava flow has the potential to spread in all directions. The fusion method of optical Landsat-8 and Sentinel-1 SAR data can be used continuously in monitoring the activity of Anak Krakatau volcano and other volcanoes in Indonesia both in cloudy and clear weather conditions.
THE EFFECT OF ENVIRONMENTAL CONDITION CHANGES ON DISTRIBUTION OF URBAN HEAT ISLAND IN JAKARTA BASED ON REMOTE SENSING DATA Indah Prasasti; Suwarsono; Nurwita Mustika Sari
International Journal of Remote Sensing and Earth Sciences Vol. 12 No. 1 (2015)
Publisher : BRIN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.ijreses.2015.v12.a2670

Abstract

Anthropogenic activities of urban growth and development in the area of Jakarta has caused increasingly uncomfortable climatic conditions and tended to be warmer and potentially cause the urban heat island (UHI). This phenomenon can be monitored by observing the air temperature measured by climatological station, but the scope is relatively limited. Therefore, the utilization of remote sensing data is very important in monitoring the UHI with wider coverage and effective. In addition, the remote sensing data can also be used to map the pattern of changes in environmental conditions (microclimate). This study aimed to analyze the effect of changes in environmental conditions (land use/cover, Normalized Difference Vegetation Index (NDVI) and Normalized Difference Build-up Index (NDBI)) toward the spread of the urban heat island (UHI). In this case, the UHI was identified from pattern changes of Land Surface Temperature (LST) in Jakarta based on data from remote sensing. The data used was Landsat 7 in 2007 and Landsat 8 in 2013 for parameter extraction environmental conditions, namely: land use cover, NDVI, NDBI, and LST. The analysis showed that during the period 2007 to 2013, there has been a change in the condition of the land use/cover, impairment NDVI, and expansion NDBI that trigger an increase in LST and the formation of heat islands in Jakarta, especially in the area of business centers, main street and surrounding area, as well as in residential areas.
APPLICATION OF CMORPH DATA FOR FOREST/LAND FIRE RISK PREDICTION MODEL IN CENTRAL KALIMANTAN Indah Prasasti; Rizaldi Boer; Lailan Syaufina
International Journal of Remote Sensing and Earth Sciences Vol. 11 No. 1 (2014)
Publisher : BRIN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.ijreses.2014.v11.a2600

Abstract

Central Kalimantan Province is a region with high level of forest/land fire, especially during dry season. Forest/land fire is a dangerous ecosystem destroyer factor, so it needs to be anticipated and prevented as early as possible. CMORPH rainfall data have good potential to overcome the limitations of rainfall data observation. This research is aimed to obtain relationship model between burned acreage and several variables of rainfall condition, as well as to develop risk prediction model of fire occurrence and burned acreage by using rainfall data. This research utilizes information on burned acreage (Ha) and CMORPH rainfall data. The method applied in this research is statistical analysis (finding correlation and regression of two phases), while risk prediction model is generated from the resulting empirical model from relationship of rainfall variables using Monte Carlo simulation based on stochastic spreadsheet. The result of this study shows that precipitation accumulation for two months prior to fire occurrence (CH2Bl) has correlation with burned acreage, and can be estimated by using following formula (if rainfall ≤ 93 mm): Burnt Acreage (Ha) = 5.13 – 21.7 (CH2bl – 93) (R2 = 67.2%). Forest fire forecasts can be determined by using a precipitation accumulation for two months prior to fire occurrence and Monte Carlo simulation. Efforts to anticipate and address fire risk should be carried out as early as possible, i.e. two months in advance if the probability of fire risk had exceeded the value of 40%.
DETECTING THE AREA DAMAGE DUE TO COAL MINING ACTIVITIES USING LANDSAT MULTITEMPORAL (Case Study: Kutai Kartanegara, East Kalimantan) Suwarsono; Nanik Suryo Haryani; Indah Prasasti; Hana Listi Fitriana; M. Priyatna; M. Rokhis Khomarudin
International Journal of Remote Sensing and Earth Sciences Vol. 14 No. 2 (2017)
Publisher : BRIN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.ijreses.2017.v14.a2851

Abstract

Coal is one of the most mining commodities to date, especially to supply both national and international energy needs. Coal mining activities that are not well managed will have an impact on the occurrence of environmental damage. This research tried to utilize the multitemporal Landsat data to analyze the land damage caused by coal mining activities. The research took place at several coal mine sites in East Kalimantan Province. The method developed in this research is the method of change detection. The study tried to know the land damage caused by mining activities using NDVI (Normalized Difference Vegetation Index), NDSI (Normalized Difference Soil Index), NDWI (Normalized Difference Water Index) and GEMI (Global Environment Monitoring Index) parameter based change detection method. The results showed that coal mine area along with the damage that occurred in it can be detected from multitemporal Landsat data using NDSI value-based change detection method. The area damage due to coal mining activities can be classified into high, moderate, and low classes based on the mean and standard deviation of NDSI changes (ΔNDSI). The results of this study are expected to be used to support government efforts and mining managers in post-mining land reclamation activities.
DROUGHT AND FINE FUEL MOISTURE CODE EVALUATION: AN EARLY WARNING SYSTEM FOR FOREST/LAND FIRE USING REMOTE SENSING APPROACH Yenni Vetrita; Indah Prasasti; Nanik Suryo. Haryani; M. Priyatna; M. Rokhis Khomarudin
International Journal of Remote Sensing and Earth Sciences Vol. 9 No. 2 (2012)
Publisher : BRIN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.ijreses.2012.v9.a1841

Abstract

This study evaluated two parameters of fire danger rating system (FDRS) using remote sensing data i.e. drought code (DC) and fine fuel moisture code (FFMC) as an early warning program for forest/land fire in Indonesia. Using the reference DC and FFMC from observation data, we calculated the accuracy, bias, and error. The results showed that FFMC from satellite data had a fairly good correlation with FFMC observations (r=0.68, bias=7.6, and RMSE=15.7), while DC from satellite data had a better correlation with FFMC observations (r=0.88, bias=49.91, and RMSE=80.22). Both FFMC and DC from satellite and observation were comparable. Nevertheless, FFMC and DC satellite data showed an overestimation values than that observation data, particularly during dry season. This study also indicated that DC and FFMC could describe fire occurrence within a period of 3 months before fire occur, particularly for DC. These results demonstrated that remote sensing data can be used for monitoring and early warning fire in Indonesia.
Co-Authors . Suwarsono Adhi Harmoko Andi Ibrahim Any Zubaidah Dandy Aditya Novresiandi Dianovita Djoko Triyono Fadila Muchsin Hana Listi Fitriana Jalu Tejo Nugroho Jansen Sitorus Khalifah Insan Nur Rahmi Kiki Winda Veronica Kuncoro Adi Pradhono Kuncoro Adi Pradono Kurnia Ulfa Lailan Syaufina Liana Fibriawati M. Priyatna M. Rokhis Khomarudin Mirzha Hanifah Mulia Inda Rahayu Nanik Suryo Haryani Nanik Suryo. Haryani nFn suwarsono nFN suwarsono Nurwita Mustika Sari Rahmat Arief Rizaldi Boer Sayidah Sulma Suciantini Suciantini Supriatna Suwarsono Yenni Vetrita