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SPECTRAL CHARACTERISTICS OF FLASH FLOOD AREAS FROM MEDIUM SPATIAL OPTICAL IMAGERY Priyatna, Muhammad; Khomarudin, Muhammad Rokhis; Chulafak, Galdita Aruba; Wijaya, Sastra Kusuma
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 18, No 2 (2021)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.ijreses.2021.v18.a3666

This study aims to investigate surface reflectance changes over flash flood areas in Nusa Tenggara Timur, Indonesia. Fifteen sample points from Sentinel-2 satellite imagery were used to analyse the differences in reflectance of areas before and after flash flood events. The method used involved analysis of the significant differences in the dreflectance values of each Sentinel-2 channel. The analysis results show that channels 6, 7, and 8A displayed significant differences compared to the others with regard to reflectance before and after flooding, for both settlements and shrubs. The results could be used for further research in building a reflectance index for the rapid detection of affected areas, with a focus on these channels.

DETECTING THE SURFACE WATER AREA IN CIRATA DAM UPSTREAM CITARUM USING A WATER INDEX FROM SENTINEL-2 Suwarsono, Suwarsono; Yulianto, Fajar; Fitriana, Hana Listi; Nugroho, Udhi Catur; Sukowati, Kusumaning Ayu Dyah; Khomarudin, Muhammad Rokhis
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 17, No 1 (2020)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.ijreses.2020.v17.a3286

This paper describes the detection of the surface water area in Cirata dam, Â upstream Citarum, using a water index derived from Sentinel-2. MSI Level 1C (MSIL1C) data from 16 November 2018 were extracted into a water index such as the NDWI (Normalized Difference Water Index) model of Gao (1996), McFeeters (1996), Roger and Kearney (2004), and Xu (2006). Water index were analyzed based on the presence of several objects (water, vegetation, soil, and built-up). The research resulted in the ability of each water index to separate water and non-water objects. The results conclude that the NDWI of McFeeters (1996) derived from Sentinel-2 MSI showed the best results in detecting the surface water area of the reservoir.

SPATIO-TEMPORAL ANOMALIES IN SURFACE BRIGHTNESS TEMPERATURE PRECEDING VOLCANO ERUPTIONS DETECTED BY THE LANDSAT-8 THERMAL INFRARED SENSOR (CASE STUDY: KARANGETANG VOLCANO) Suwarsono, Suwarsono; Triyono, Djoko; Khomarudin, Muhammad Rokhis; Rokhmatuloh, Rokhmatuloh
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 18, No 1 (2021)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.ijreses.2021.v18.a3465

Indonesia's geological as part of the â€œring of fireâ€ includes the consequence that community life could be affected by volcanic activity. The catastrophic incidence of volcanic eruptions in the last ten years has had a disastrous impact on human life. To overcome this problem, it is necessary to conduct research on the strengthening of the early warning system for volcanic eruptions utilising remote sensing technology.Â This study analyses spatial and temporal anomalies of surface brightness temperature in the peak area of Karangetang volcano during the 2018-2019 eruption. Karangetang volcano is an active volcano located in North Sulawesi, with a magmatic eruption type that releases lava flow. We analyse the anomalies in the brightness temperature from channel-10 of the Landsat-8 TIRS (Thermal Infrared Scanner) time series during the period in question. The results of the research demonstrate that in the case of Karangetang Volcano the eruptions of 2018-2019 indicate increases in the surface brightness temperature of the crater region. As this volcano has many craters, the method is also very useful to establish in which crater the center of the eruption occurred.

Geospatial Data Integration for the Flood Vulnerable Area Classification in Jratunseluna Watershed Assaidi, Humaid; Khomarudin, Muhammad Rokhis; Badron, Khairayu; Ismail, Ahmad Fadzil; Ramza, Harry
Journal of Computer Networks, Architecture and High Performance Computing Vol. 6 No. 3 (2024): Articles Research Volume 6 Issue 3, July 2024
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v6i3.4233

Flood is a threat that has significant impacts on communities and the environment. To improve the management of disaster risk, this research takes an integrated approach by utilizing geospatial data from various sources. The main objective of this research is to provide an integrated approach to determining flood-vulnerable area classes. This research focuses on the processing of various geospatial data such as DEM (Digital Elevation Model) imagery, Landsat 8 satellite imagery, Hydrological data based on SHuttle Elevation Derivatives at multiple Scales (HydroSHEDS) water flow accumulation imagery, and Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) rainfall imagery which are used as data sources to model the flood vulnerable area classification of The Jratunseluna watershed. Landsat 8 satellite imagery is used as a source for landuse land cover (LULC) classification, it is done to score each land category to the level of ability to absorb and drain excess water, the remaining data is used to score the earth elevation, accumulated water flow, and rainfall from the area. The weights and scores are used as the basis values to create a flood-vulnerable area classification model. The result of this research is a flood-vulnerable area classification map generated from a pre-made model.

Geospatial Data Integration for the Flood Vulnerable Area Classification in Jratunseluna Watershed Assaidi, Humaid; Khomarudin, Muhammad Rokhis; Badron, Khairayu; Ismail, Ahmad Fadzil; Ramza, Harry
Journal of Computer Networks, Architecture and High Performance Computing Vol. 6 No. 3 (2024): Articles Research Volume 6 Issue 3, July 2024
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v6i3.4233

Flood is a threat that has significant impacts on communities and the environment. To improve the management of disaster risk, this research takes an integrated approach by utilizing geospatial data from various sources. The main objective of this research is to provide an integrated approach to determining flood-vulnerable area classes. This research focuses on the processing of various geospatial data such as DEM (Digital Elevation Model) imagery, Landsat 8 satellite imagery, Hydrological data based on SHuttle Elevation Derivatives at multiple Scales (HydroSHEDS) water flow accumulation imagery, and Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) rainfall imagery which are used as data sources to model the flood vulnerable area classification of The Jratunseluna watershed. Landsat 8 satellite imagery is used as a source for landuse land cover (LULC) classification, it is done to score each land category to the level of ability to absorb and drain excess water, the remaining data is used to score the earth elevation, accumulated water flow, and rainfall from the area. The weights and scores are used as the basis values to create a flood-vulnerable area classification model. The result of this research is a flood-vulnerable area classification map generated from a pre-made model.

The dynamics of shoreline change analysis based on the integration of remote sensing and geographic information system (GIS) techniques in Pekalongan coastal area, Central Java, Indonesia Yulianto, Fajar; Suwarsono, S; Maulana, Taufik; Khomarudin, Muhammad Rokhis
Journal of Degraded and Mining Lands Management Vol. 6 No. 3 (2019)
Publisher : Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15243/jdmlm.2019.063.1789

Coastal areas are found in the dynamic zone at the interface between the three major natural systems of the Earth's surface. The phenomenon of shoreline change is one of the most frequent problems encountered in the coastal environment and is caused by natural processes that result in dynamic changes in the coastal area. Coastal area change can affect the vulnerability of the coastal environment and its properties, such as shoreline stabilization, flood control, sediment retention, natural protection and others. The method of integrating remote sensing data with geographic information system (GIS) techniques has been widely used to monitor and analyze the dynamics of shoreline change in coastal areas. The purpose of this study is to map and analyze the dynamics of shoreline change from 1978 to 2017 in the study area. An approach combining spectral value index and visual interpretation of Landsat images was used and proposed to indicate the separation of land and water bodies, for shoreline extraction. The normalized difference water index (NDWI) can be used as a spectral value index approach for differentiating land and water bodies. Furthermore, the analysis of shoreline changes was performed using the digital shoreline analysis system (DSAS). Based on calculations made using DSAS, it can be seen that the pattern of coastline change tends to be dominated by offshore erosion. The results of this study may also be important as input data for coastal hazard assessment as part of the effort to overcome the problem of flood tides.

Spatial and temporal distribution of estimated surface runoff caused by land use/land cover changes in the upstream Citarum watershed, West Java, Indonesia Yulianto, Fajar; Khomarudin, Muhammad Rokhis; Hermawan, Eddy; Nugroho, Nunung Puji; Chulafak, Galdita Aruba; Nugroho, Gatot; Nugroho, Udhi Catur; Suwarsono, Suwarsono; Fitriana, Hana Listi; Priyanto, Eko
Journal of Degraded and Mining Lands Management Vol. 9 No. 2 (2022)
Publisher : Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15243/jdmlm.2022.092.3293

In Indonesia, flooding is one of the natural hazards that often occurs during the rainy season. Surface runoff coefficient values are an essential indicator of the supply of regional water resources. The smaller the surface runoff value, the greater the water storage in the ground, and the smaller surface was running water. This study analyses the spatial and temporal distribution of the estimated surface runoff caused by land use/land cover changes in the upstream Citarum watershed. The study area is located in the upstream Citarum watershed, West Java, Indonesia. The site has a long history of flooding and various complex environmental problems. The geographic Information System method was used as a tool in analyzing the spatially and temporally. The research result shows that there has been a change in land cover in several periods of the year in the Citarum upstream watershed. The occurrence of the LULC phenomenon positively affects the surface runoff coefficient. The increasing area of Built land and plantation in the Citarum upstream watershed will further increase the surface runoff coefficient and, in the end, will potentially increase the surface runoff and contribute to flooding in the Bandung basin. This study results can be used to provide input in determining the direction and policies for watershed management, taking into account the varying characteristics of each subwatershed.

The use of multi-sensor satellite imagery to analyze flood events and land cover changes using change detection and machine learning techniques in the Barito watershed Priyatna, Muhammad; Wijaya, Sastra Kusuma; Khomarudin, Muhammad Rokhis; Yulianto, Fajar; Nugroho, Gatot; Afgatiani, Pingkan Mayestika; Rarasati, Anisa; Hussein, Muhammad Arfin
Journal of Degraded and Mining Lands Management Vol. 10 No. 2 (2023)
Publisher : Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15243/jdmlm.2023.102.4073

Indonesia is one of the countries in the world that is frequently affected by floods. Flood disasters can have various negative impacts and therefore need to be analyzed to determine prevention and mitigation measures. This study examined land cover change, flood detection, and flood distribution using multitemporal Sentinel-1 and Landsat-8 satellite imagery in the Barito watershed. A combination of change detection and the application of the Otsu algorithm was used to detect floodplains from Sentinel-1 imagery. Land use/land cover (LULC) changes are detected using a combination of change detection and machine learning in the form of a random forest algorithm. The overlay technique was used to analyze the distribution of floodplains. In this study, the floodplain in the study area was mapped to 109,623 ha. The change detection method detects a decrease in the areas of primary forest, secondary forest, fields, rice fields, shrubs and ponds, respectively, by 13,020 ha, 116,235 ha, 259 ha, 146,696 ha, 47,308 ha, and 9,601 ha. Settlements, bare land, plantations and water bodies increase by 14,879 ha, 64,830 ha, 218,916 ha, and 34,768 ha, respectively. Flooding was mainly found in the classes of rice fields, water bodies and primary forests.

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