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TECHNIQUE FOR IDENTIFYING BURNED VEGETATION AREA USING LANDSAT 8 DATA Bambang Trisakti; Udhi Catur Nugroho; Ani Zubaidah
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 13, No 2 (2016)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

During the last two decades, forest and land fire is a catastrophic event that happens almost every year in Indonesia. Therefore, it is necessary to develop a technic to monitor forest fires using satellite data to obtain the latest information of burned area in a large scale area. The objective of this research is to develop a method for burned area mapping that happened between two Landsat 8 data recording on August 13rd and September 14th 2015. Burned area was defined as a burned area of vegetation. The hotspot distribution during the period August - September 2015 was used to help visual identification of burned area on the Landsat image and to verify the burned area resulted from this research. Samples were taken at several land covers to determine the spectral pattern differences among burned area, bare area and other land covers, and then the analysis was performed to determine the suitable spectral bands or indices and threshold values that will be used in the model. Landsat recorded on August 13rd before the fire was extracted for soil, while Landsat recorded on September 14th after the fire was extracted for burned area. Multi-temporal analysis was done to get the burned area occurring during the certain period. The results showed that the clouds could be separated using combination of ocean blue and cirrus bands, the burned area was extracted using a combination of NIR and SWIR band, while soil was extracted using ratio SWIR / NIR. Burned area obtained in this study had high correlation with the hotspot density of MODIS with the accuracy was around 82,4 %.

PRELIMINARY DETECTION OF GEOTHERMAL MANIFESTATION POTENTIAL USING MICROWAVE SATELLITE REMOTE SENSING Atriyon Julzarika; Udhi Catur Nugroho
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 15, No 2 (2018)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

The satellite technology has developed significantly. The sensors of remote sensing satellites are in the form of optical, Microwave, and LIDAR. These sensors can be used for energy and mineral resources applications. The example of those applications are height model and the potential of geothermal manifestation detection. This study aims to detect the potential of geothermal manifestation using remote sensing. The study area is the Northern of the Inverse Arc of Sulawesi. The method used is remote sensing approach for its preliminary detection with 4 steps as follow (a) mining land identification, (b) geological parameter extraction, (c) preparation of standardized spatial data, and (d) geothermal manifestation. Mining lands identification is using Vegetation Index Differencing method. Geological parameters include structural geology, height model, and gravity model. The integration method is used for height model. The height model integration use ALOS PALSAR data, Icesat/GLAS, SRTM, and X SAR. Structural geology use dip and strike method. Gravity model use physical geodesy approach. Preparation of standardized spatial data with re-classed and analyzed using Geographic Information System between each geological parameter, whereas physical geodesy methods are used for geothermal manifestation detection. Geothermal manifestation using physical geodesy approach in Barthelmes method. Grace and GOCE data are used for gravity model. The geothermal manifestation detected from any parameter is analyzed by using geographic information system method. The result of this study is 10 area of geothermal manifestation potential. The accuracy test of this research is 87.5 % in 1.96 σ. This research can be done efficiently and cost-effectively in the process. The results can be used for various geological and mining applications.

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

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.

PRELIMINARY DETECTION OF GEOTHERMAL MANIFESTATION POTENTIAL USING MICROWAVE SATELLITE REMOTE SENSING Atriyon Julzarika; Udhi Catur Nugroho
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.a2772

The satellite technology has developed significantly. The sensors of remote sensing satellites are in the form of optical, Microwave, and LIDAR. These sensors can be used for energy and mineral resources applications. The example of those applications are height model and the potential of geothermal manifestation detection. This study aims to detect the potential of geothermal manifestation using remote sensing. The study area is the Northern of the Inverse Arc of Sulawesi. The method used is remote sensing approach for its preliminary detection with 4 steps as follow (a) mining land identification, (b) geological parameter extraction, (c) preparation of standardized spatial data, and (d) geothermal manifestation. Mining lands identification is using Vegetation Index Differencing method. Geological parameters include structural geology, height model, and gravity model. The integration method is used for height model. The height model integration use ALOS PALSAR data, Icesat/GLAS, SRTM, and X SAR. Structural geology use dip and strike method. Gravity model use physical geodesy approach. Preparation of standardized spatial data with re-classed and analyzed using Geographic Information System between each geological parameter, whereas physical geodesy methods are used for geothermal manifestation detection. Geothermal manifestation using physical geodesy approach in Barthelmes method. Grace and GOCE data are used for gravity model. The geothermal manifestation detected from any parameter is analyzed by using geographic information system method. The result of this study is 10 area of geothermal manifestation potential. The accuracy test of this research is 87.5 % in 1.96 Ïƒ. This research can be done efficiently and cost-effectively in the process. The results can be used for various geological and mining applications.

TECHNIQUE FOR IDENTIFYING BURNED VEGETATION AREA USING LANDSAT 8 DATA Bambang Trisakti; Udhi Catur Nugroho; Any Zubaidah
International Journal of Remote Sensing and Earth Sciences Vol. 13 No. 2 (2016)
Publisher : BRIN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.ijreses.2016.v13.a2447

During the last two decades, forest and land fire is a catastrophic event that happens almost every year in Indonesia.Â Therefore, it is necessary to develop a technic to monitor forest fires using satellite data to obtain the latest information of burned area in a large scale area. The objective of this research is to develop a method for burned area mapping that happened between two Landsat 8 data recording on August 13rd and September 14th 2015. Burned area was defined as a burned area of vegetation. The hotspot distribution during the period August - September 2015 was used to help visual identification of burned area on the Landsat image and to verify the burned area resulted from this research. Samples were taken at several land covers to determine the spectral pattern differences among burned area, bare area and other land covers, and then the analysis was performed to determine the suitable spectral bands or indices and threshold values that will be used in the model. Landsat recorded on August 13rd before the fire was extracted for soil, while Landsat recorded on September 14th after the fire was extracted for burned area. Multi-temporal analysis was done to get the burned area occurring during the certain period. The results showed that the clouds could be separated using combination of ocean blue and cirrus bands, the burned area was extracted using a combination of NIR and SWIR band, while soil was extracted using ratio SWIR / NIR. Burned area obtained in this study had high correlation with the hotspot density of MODIS with the accuracy was around 82,4 %.

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