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The International Journal of Remote Sensing and Earth Sciences (IJReSES)
Published by Badan Riset dan Inovasi Nasional
ISSN : 02166739     EISSN : 2549516X     DOI : https://doi.org/10.55981/ijreses
Core Subject : Science,
Earth & Planetary Sciences
The International Journal of Remote Sensing and Earth Sciences (IJReSES), published by Badan Riset dan Inovasi Nasional (BRIN) in collaboration with the Ikatan Geografi Indonesia (IGI) and managed by the Department of Geography Universitas Indonesia, is a pivotal platform in the global dissemination of research in earth sciences and remote sensing. It aims to enrich the literature in these fields and serves as a key resource, particularly in Indonesia and Asian countries, while extending its reach worldwide. The journal is instrumental in complementing the body of knowledge in Remote Sensing and Earth Sciences and is committed to fostering the participation of young scientists, especially from Indonesia and Asian countries. Scope and Focus: IJReSES encompasses a wide spectrum of topics related to remote sensing and earth sciences, including but not limited to: - Remote sensing technologies and methodologies - Geospatial data acquisition, processing, and analysis - Earth observation and satellite imagery - Geographic Information Systems (GIS) - Environmental monitoring and management - Climate change and its impacts - Natural resource management - Land use and land cover change - Urban and rural development - Disaster risk reduction and response - Geology and geomorphology - Soil and water sciences - Biodiversity and ecosystem studies
Arjuna Subject : Ilmu Bumi dan Planet (semua kategori) - Ilmu Bumi dan Planet (Lain-Lain)
Articles 327 Documents
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ENHANCING COASTAL DISASTER MITIGATION MEASURES: VEGETATION BASED FEASIBILITY STUDY FOR SOUTHERN JAVA, INDONESIA Adiguna Rahmat Nugraha; Jason R. Parent
International Journal of Remote Sensing and Earth Sciences Vol. 19 No. 2 (2022)
Publisher : BRIN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.ijreses.2022.v19.a3767

Abstract

Indonesia is a country that is prone to disaster especially earthquake and volcanic eruption because its located in the ring of fire. The type of disasters can produce another type of disaster which is: tsunami. Â The nature of tsunamis that were hard to predict and arrive with little warning, Indonesians can minimize the effect of tsunami by creating coastal protection. In this study we look for the location to create the coastal forest as an enhancement of the mitigation effort. We conducted our study in the Pangandaran district as were a severe tsunami in the 2006 that caused more than 400 deaths. We conducted a suitability analysis to identify tsunami prone area based on the following criteria: should be had elevation <10m, slope gradient <2%, within proximity of 500m from coastline, and <100m from river and should be settlement or urban area. The creation of vulnerability map was using map algebra to calculate the weighted parameter from each class. Based our analysis using GIS analysis, the most vulnerable area in the Pangandaran district is the bay area, where we founded 1,419 acres of coastal area for which coastal forests could be planted to enhance protection against tsunamis.Â
PREDICTIVE MAPPING OF CRITICAL LAND IN BENGAWAN SOLO WATERSHED: AN INTEGRATED APPROACH USING LANDSAT IMAGERY AND TERRAIN ANALYSIS Nirmawana Simarmata; Dewi Nawang Sari; Annisha Bunga Fathya; M Sri Harta
International Journal of Remote Sensing and Earth Sciences Vol. 21 No. 1 (2024)
Publisher : BRIN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.ijreses.2024.v21.a3907

Abstract

Inappropriate land use can have negative impacts, increasing the risk of land becoming critical. Managing critical land and growing human needs is essential to balance land and water resources. This research aims to map necessary land in the Bengawan Solo watershed. The research method integrates remote sensing and geographic information system (GIS) methods. Critical land analysis was conducted based on the Regulation of the Director General of Watershed and Protected Forest Control Number P.3/PDASHL/SET/KUM.1/7/2018, which is used as a reference in determining whether land is categorized as critical land. The regulation uses 4 (four) variables in its processing: land cover variables, slope, erosion hazard level, and forest area. The study results show land criticality in the Bengawan Solo watershed in 2023. Most areas have low slopes (0-8%), considered non-critical, covering 30.50% of the total area. In contrast, the Potentially Critical category (8-15%) dominates with 45.94% of the area, indicating potential risks in moderately steep areas. Areas with steeper slopes fall into the Critical (10.29%) and Very Critical (2.68%) categories.
MAPPING THE AIR MOISTURE CHANGE IN UNDER CANOPY TREES USING A HEMISPHERICAL AND AERIAL PHOTOGRAPH BASED ON MACHINE LEARNING APPROACHES Mochamad Firman Ghazali
International Journal of Remote Sensing and Earth Sciences Vol. 19 No. 2 (2022)
Publisher : BRIN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.ijreses.2022.v19.a3816

Abstract

The essential roles of trees in controlling the local climatic variation, such as air moisture, are still interesting to observe. Therefore, this study must deliver knowledge of the benefits of growing trees and enhance people's awareness of climate change adaptation. Here, the analysis requires several data fields such as hemispherical photography, an aerial photograph of a UAV, and air temperature collected using a wet and dry bulb thermometer, which has converted to air moisture. All these are considered to understand the air moisture change under the trees' canopy during a day observation. The hemispherical photography and aerial photograph of a UAV are processed to measure the tree's canopy size and then used together with interpolated air moisture to map the variation in air moisture distribution in under-canopy trees using random forest (RF) and Artificial Neural Network (ANN). The result shows that hemispherical photography describes the ability to control the air moisture change. As its size increases, the air moisture level tends to be higher. It was maintained at more than 70% compared to the area with lower canopy cover. This characteristic is similar to the pattern shown by the RF and ANN. However, the SVM has better results as it can separate air humidity in vegetated and non-vegetated areas.
AUTOMATION OF DAILY LANDSLIDE POTENTIAL INFORMATION BASED ON REMOTE SENSING SATELLITE IMAGERY USING OPEN-SOURCE SOFTWARE TECHNOLOGY Ahmad Sutanto; Anwar Annas; Mohammad Ardha; Taufik Hidayat; Muhammad Rokhis Khomarudin
International Journal of Remote Sensing and Earth Sciences Vol. 20 No. 1 (2023)
Publisher : BRIN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.ijreses.2023.v20.a3836

Abstract

This automation system automatically generated landslide potential information based on daily precipitation data. This system is essential to replace the previous manual processing system with an automated and integrated system. The results of the developed system are the distribution of areas with landslide potential based on daily precipitation data. The system was built using geographic information systems and web service techniques. This allows the automation process to be performed quickly and accurately. The landslide susceptibility map used is from the National Disaster Management Agency, so the information is more reliable. Himawari-8 is used to determine the potential for extreme precipitation in 10 minutes because this satellite has a very high temporal resolution. The system is already in use and has proven to replace manual processing and is faster. Further development will be more challenging if the system can be connected to the sensors installed on site so that the sensors on site can issue a landslide warning in case of extreme precipitation so that the surrounding communities can respond immediately. Opportunities for future development of the system may also be incorporated into landslide potential prediction based on the precipitation forecast model
SPATIO-TEMPORAL ANALYSIS OF CHANGES IN CORAL REEF AREA USING LANDSAT 8 SATELLITE IMAGERY ON PARI ISLAND, KEPULAUAN SERIBU, DKI JAKARTA Faisal Akmal; Bambang Semedi; Azura Ulfa
International Journal of Remote Sensing and Earth Sciences Vol. 21 No. 1 (2024)
Publisher : BRIN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.ijreses.2024.v21.a3894

Abstract

Coral reefs are ecosystems that are sensitive to change. High pressure can cause damage to coral reefs. Monitoring the condition of coral reefs needs to be done to know the current condition. One way that can be used to monitor coral reefs is by utilizing remote sensing. The research was conducted to know the changes in the coral reef area and the factors that influence the changes in the coral reef area in Pari Island, Kepulauan Seribu, DKI Jakarta in the period 2013 to 2022. The research was conducted using Landsat 8 image data from 2013 to 2022. Image data processing was done with an object-based classification method. Coral cover measurements were conducted using the Line Intercept Transect (LIT) method. The results showed a change in coral reef area of 7.02 ha with the condition of live coral cover ranging from 27-43% which is included in the fair category. The results of field measurements show that the condition of water parameters falls into the unsuitable category. The increase in area that occurred was thought to be due to management activities carried out by the Pari Island community and activities carried out by LIPI in 2016, namely conducting coral reef restoration. The decrease in area is partly due to coastal reclamation activities, destructive tourist activities, and parameter conditions.
ASSESSMENT OF FLASH FLOOD HAZARD POTENTIAL IN A SMALL MOUNTAINOUS CIKUNDUL WATERSHED IN CIANJUR, WEST JAVA, INDONESIA Eko Kusratmoko; Armila Rista Septina; Muhammad Attorik Falensky
International Journal of Remote Sensing and Earth Sciences Vol. 21 No. 1 (2024)
Publisher : BRIN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.ijreses.2024.v21.a3918

Abstract

Flash flood is a geomorphic hazard that can cause huge losses in a short period of time. Cianjur regency, especially Cikundul Watershed is a flash flood frequent area. Therefore, flash flood potential mapping is needed to reduce the threat that can be caused by flash flood. In the flash flood potential mapping, Flash Flood Potential Index (FFPI) method is still rarely applied in Indonesia. This study aims to see the comparison of flash flood potential areas based on models developed in the FFPI method which is Smith, Brewster, Krudzlo, and Ceru models. The four models used slope, land use, soil texture, and vegetation cover as variables. Spatial analysis and statistical test was implemented to validate the flash flood potential areas with flash flood affected locations. The result reveals that Cikundul Watershed was dominated by moderate potential areas based on Brewster, Krudzlo, and Ceru model but low by Smith model. The result also reveals that 65% of 68 Sub-Sub Watershed have different potential and 35% have same potential. High potential areas in all four models was distributed in the Upper Cikundul Watershed. The Crosstab Fit Test result shows that Smith model is the closest model to the actual event.
DIFFERENCES OF COASTALLINE CHANGES IN THE AREA AFFECTED BY LAND COVER CHANGES AND COASTAL GEOMORPHOLOGICAL SOUTH BALI 1995 - 2021 Muhammad Dimyati; Muhamad Rafli; Astrid Damayanti
International Journal of Remote Sensing and Earth Sciences Vol. 19 No. 2 (2022)
Publisher : BRIN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.ijreses.2022.v19.a3781

Abstract

The 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 Dwi Hastuti; Masita Dwi Mandini Manessa; Mangapul Parlindungan
International Journal of Remote Sensing and Earth Sciences Vol. 19 No. 2 (2022)
Publisher : BRIN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.ijreses.2022.v19.a3831

Abstract

Tea 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 plant
TSUNAMI HAZARD MODELING IN THE COASTAL AREA OF KULON PROGO REGENCY Dwiana Putri Setyaningsih; Hubertus Ery Cantas Pratama Sutiono; Amelia Rizki Gita Paramanandi; Ernani Uswatun Khasanah; Tri Wahyuni; Bernadeta Aurora Edwina Kumala Jati; Muhammad Falakh Al Akbar; Wirastuti Widyatmanti; Totok Wahyu Wibowo
International Journal of Remote Sensing and Earth Sciences Vol. 19 No. 2 (2022)
Publisher : BRIN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.ijreses.2022.v19.a3822

Abstract

Kulon Progo Regency is located in the southern part of Java Island, one of Indonesia's areas that is prone to tsunami disasters. Kulon Progo Regency is prone to tsunamis because it faces a subduction zone in the Indian Ocean. Therefore, it is necessary to model tsunami inundation and map the tsunami hazard zone in the Kulon Progo coastal area. This study aims to model tsunami inundation and produce a tsunami hazard map with a tsunami height scenario of 5 meters and 10 meters. The method used in modeling tsunami inundation is using a mathematical calculation developed by Berryman-2006 using the parameters of the coefficient of surface roughness, slope, and the height of the tsunami at the coastline. The estimated tsunami inundation area is classified into a tsunami hazard index using the fuzzy logic method resulting in an index of 0 – 1, which is then divided into three hazard classes. The results of the tsunami hazard mapping with the 5 meters scenario are 15 villages in 4 sub-districts included in the hazard zone with a total area of 20672,34 Ha affected. The results of the tsunami hazard mapping with a 10 meters scenario are 26 villages in 4 sub-districts with a total area of 53042,66 Ha affected. The results of this research can be used as basic information for disaster mitigation.
TSUNAMI DISASTER MODELING FOR NON-MILITARY DEFENSE IN PANGANDARAN REGENCY USING GEOGRAPHIC INFORMATION SYSTEMS Mauliza Fatwa Yusdian; Riyan Eko Prasetiyo; Asep Adang Supriyadi; Yosef Prihanto
International Journal of Remote Sensing and Earth Sciences Vol. 20 No. 1 (2023)
Publisher : BRIN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.ijreses.2023.v20.a3842

Abstract

The 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.

Page 3 of 33 | Total Record : 327

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