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All Journal Journal of Degraded and Mining Lands Management International Journal of Remote Sensing and Earth Sciences (IJReSES) Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital
Chulafak, Galdita Aruba
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Aerospace Engineering Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Computer Science & IT Control & Systems Engineering Earth & Planetary Sciences Electrical & Electronics Engineering

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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) Nugroho, Jalu Tejo; Suwarsono, Suwarsono; Chulafak, Galdita Aruba; Julzarika, Atriyon; Manalu, Johannes; Harini, Sri; Suhadha, Argo; Sulma, Sayidah
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.a3626

Abstract

In 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.
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

Abstract

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.
Developing algorithms for estimating total suspended solids (TSS) using unmanned aerial vehicle: A case study in the Upper Citarum River, Indonesia Setiawan, Fajar; Basuki, Tyas Mutiara; Santosa, Budi Heru; Pramono, Irfan Budi; Chulafak, Galdita Aruba; Rahmadya, Aldiano; Nada, Firda Maftukhakh Hilmya
Journal of Degraded and Mining Lands Management Vol. 12 No. 2 (2025)
Publisher : Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15243/jdmlm.2025.122.7379

Abstract

Monitoring total suspended solids (TSS) is essential as suspended sediments impact the environment and human health in various ways. However, TSS data are limited in many regions because the methods currently applied through in situ measurements are time-consuming and labor-intensive. The study aimed to develop algorithms to estimate TSS using data derived from UAVs and field measurements. Remote sensing technology, such as unmanaged aerial vehicle (UAV), was applied to obtain imagery data to estimate TSS content. These results were then compared with laboratory analysis of in-situ water samples, determined by gravimetric methods following standard protocols. The results showed that the algorithm developed using three-band ratios, the blue/green + red/green + NIR (near infra red)/green, produces a high R2 (0.70), indicating that this combination is reliable for use in estimating TSS content in a river section. The high accuracy of the red band for suspended sediment prediction is attributed to its spectral signature in turbid water, which shows higher reflectance compared to clean water. The results of this study have the potential to help river managers obtain TSS data quickly at a relatively low cost.
OPTIMASI PARAMETER DALAM KLASIFIKASI SPASIAL PENUTUP PENGGUNAAN LAHAN MENGGUNAKAN DATA SENTINEL SAR Chulafak, Galdita Aruba; Kushardono, Dony; Zylshal, Zylshal
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 14 No. 2 (2017)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.pjpdcd.1017.v14.a2746

Abstract

In this study, application of Sentinel-1 Synthetic Aperture Radar (SAR) data for the land use cover classification was investigated. The classification was implemented with supervised Neural Network classifier for Dual polarization (VH and VV) Sentinel-1 data using texture information of gray level co-occurance matrix (GLCM). The purpose of this study was to obtain the optimum parameters in the extraction of texture information of pixel window size, the orientation of neighboring relationships on the texture feature extraction, and the type of texture information feature used for the classification. The classification results showed that in the study area, the best accuracy obtained is 5 × 5 pixel window size, 00 orientation angle, and the use of entropy texture information as classification input. It was also found that more features texture information used as classification input can improve the accuracy, and with careful selection of appropriate texture information as classification input will give the best accuracy.
Co-Authors Atriyon Julzarika Budi Heru Santosa Dony Kushardono FAJAR SETIAWAN Irfan Budi Pramono Jalu Tejo Nugroho, Jalu Tejo Johannes Manalu, Johannes Khomarudin, Muhammad Rokhis Muhammad Priyatna, Muhammad Nada, Firda Maftukhakh Hilmya Rahmadya, Aldiano Sastra Kusuma Wijaya Sayidah Sulma, Sayidah Sri Harini Suhadha, Argo Suwarsono Suwarsono Tyas Mutiara Basuki Zylshal, Zylshal