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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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THE RELATIONSHIP BETWEEN LAND USE AND LAND COVER TO RUN-OFF COEFFICIENT VALUE IN BRANTAS WATERSHED AREA, TULUNGAGUNG - EAST JAVA, INDONESIA Bowo Eko Cahyono; Asih Sumarlin; Nurul Priyantari; Katsunoshin Nishi
International Journal of Remote Sensing and Earth Sciences Vol. 20 No. 2 (2023)
Publisher : BRIN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.ijreses.2023.v20.a3851

Abstract

The Ngrowo-Ngasinan sub-watershed is a part of Brantas Watershed which has an important role for the aquatic ecosystems in the Brantas watershed. Land cover changes in this sub-watershed can be identified by utilizing remote sensing technology. The use of remote sensing technology by applying Landsat 8 image data can be done by classifying several classes of land cover in the study area. Land cover affected the flow rate of a watershed because of its association with several problems due to the conversion of land. Land cover which influences the watershed ecosystems is forest. In addition to land cover, regional rainfall also affects the flow rate (runoff) in the area
COMPARISON OF THE RADIOMETRIC CORRECTION LANDSAT-8 IMAGE BASED ON OBJECT SPECTRAL RESPONSE AND VEGETATION INDEX Fadila Muchsin; Supriatna; Adhi Harmoko; Indah Prasasti; Mulia Inda Rahayu; Liana Fibriawati; Kuncoro Adi Pradhono
International Journal of Remote Sensing and Earth Sciences Vol. 18 No. 2 (2021)
Publisher : BRIN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.ijreses.2021.v18.a3632

Abstract

Landsat-8 standard level (level 1T) data received by users still in digital form can be used directly for land cover/land use mapping. These data have low radiometric accuracy when used to produce information such as vegetation indices, biomass, and land cover/land use classification. In this study, radiometric/atmospheric correction was conducted using FLAASH, 6S, DOS, TOA+BRDF and TOA method to eliminate atmospheric disturbances and compare the results with field measurements based on object spectral response and NDVI values. The results of the spectral measurements of objects in paddy fields at harvest time in the Cirebon Regency, West Java, Indonesia show that the FLAASH and 6S method have spectral responses that are close to those of objects in the field compared to the DOS, TOA and TOA+BRDF methods. For the NDVI value, the 6S method has the same tendency as the object's NDVI value in the field.
ENVIRONMENT QUALITY IDENTIFICATION USING LANDSAT-8 IN THE PERIOD OF COVID-19 LOCKDOWN IN JAKARTA Khalifah Insan Nur Rahmi; Mangapul Parlindungan Tambunan; Rudy P. Tambunan
International Journal of Remote Sensing and Earth Sciences Vol. 20 No. 2 (2023)
Publisher : BRIN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.ijreses.2023.v20.a3850

Abstract

The quality of the urban environment during the Covid-19 lockdown became a concern because it was reported that it had improved but the spatial studies were still limited. Spatial information at regional scale can be extracted from Landsat-8 imagery. This study aims to spatially and temporally analyze environmental quality variables from Landsat-8 Imagery and compare environmental quality indices before, during and after the Covid-19 lockdown in Jakarta. Environmental quality variables extracted from Landsat-8 imagery are PM10, LST, NDVI, NDWI, NDMI. Radiometric correction and masking were applied to obtain Landsat-8 reflectance and radian values. PM10 concentrations were estimated using linear regression between station data and visible-near infrared (VNIR) reflectance band values. The variable land surface temperature (LST) is obtained from the brightness temperature band 10 extraction. NDVI, NDWI, and NDMI are extracted from the transformation of the reflectance band index. The environmental quality index is extracted from a weighted linear combination method where each variable has a weighted value of 50% PM10, 31% LST, 11% NDVI, 5% NDWI, and 3% NDMI. The results of the distribution of the environmental quality index before, during and after the Covid-19 lockdown show changes. Before the lockdown, some areas in Jakarta had a poor environmental quality index, while during the lockdown, only a few areas were still of poor quality, including the reclamation island and the Cilincing industrial area, North Jakarta. After the lockdown, the environmental quality index decreased again i.e. good, medium and bad categories but the distribution was not as wide as before the lockdown.
Back Pages IJReSES Vol. 20, No. 2 (2023) Journal Manager
International Journal of Remote Sensing and Earth Sciences Vol. 20 No. 2 (2023)
Publisher : BRIN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.ijreses.2023.v20.a3903

Abstract

Back Pages IJReSES Vol. 20, No. 2 (2023)
Backpages Vol.18 No.1 (2021) Journal Editor
International Journal of Remote Sensing and Earth Sciences Vol. 18 No. 1 (2021)
Publisher : BRIN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.ijreses.2021.v18.a3669

Abstract

Backpages Vol.18 No.1 (2021)
Front Pages IJReSES Vol. 19, No. 1 (2022) Journal Manager
International Journal of Remote Sensing and Earth Sciences Vol. 19 No. 1 (2022)
Publisher : BRIN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.ijreses.2022.v19.a3859

Abstract

Front Pages IJReSES Vol. 19, No. 1 (2022)
PRELIMINARY STUDY OF A RADIO FREQUENCY INTERFERENCE FILTER FOR NON-POLARIMETRIC C-BAND WEATHER RADAR IN INDONESIA (CASE STUDY: TANGERANG WEATHER RADAR) Abdullah Ali; Iddam Hairuly Umam; Hidde Leijnse; Umi Sa’adah
International Journal of Remote Sensing and Earth Sciences Vol. 18 No. 2 (2021)
Publisher : BRIN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.ijreses.2021.v18.a3727

Abstract

C-Band weather radar that operates at a frequency of 5 GHz is very vulnerable to radio frequency interference (RFI) because it is located on a free used frequency. RFI can cause image misinterpretation and precipitation echo distortion. The new allocation for free spectrum recommended by the World Radio Conference 2003 and weather radar frequency protection in Indonesia controlled by the Balai Monitoring Spektrum Frekuensi (BALMON) have not provided permanent protection against weather radar RFI. Several RFI filter methods have been developed for polarimetric radars, but there have been no studies related to RFI filters on non-polarimetric radars in Indonesia. This research aims to conduct an initial study of RFI filters on such radars. Four methods were applied in the initial study. The Himawari 8 cloud mask was used to eliminate interference echo based on VS, IR, and I2 channels, while the nature of false echo interference that does not have a radial velocity value was used as the basis for the application of the Doppler velocity filter. Another characteristic in the form of consistent echo interference up to the maximum range was used as the basis for applying a beam filling analysis filter with reflectivity thresholds of 5 dBZ and 10 dBZ, with beam filling of more than 75%. Finally, supervised learning Random Forest (RF) was also used to identify interference echo based on the characteristics of the sampling results on reflectivity, radial velocity, and spectral width data. The results show that the beam filling analysis method with a threshold of 5 dBZ provides the best RFI filter without eliminating echo precipitation.
LAND USE/COVER CHANGE ON POTENTIAL LOSS OF SUMATRAN TIGERS IN KERINCI SEBLAT NATIONAL PARK BASED ON REMOTE SENSING DATA Muhammad Ardha; Muhammad Rokhis Khomarudin; Gatot Nugroho
International Journal of Remote Sensing and Earth Sciences Vol. 19 No. 1 (2022)
Publisher : BRIN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.ijreses.2022.v19.a3782

Abstract

The Sumatran tiger is an animal whose life is threatened due to land use changes and human activities. This study described the correlations between land cover/use change and the potential loss of Sumatran tigers in Kerinci Seblat National Park (KSNP) based on remote sensing data. Remote sensing technology was used due to the good historical data, and it can be used for land cover change analysis. The results of the land change analysis can be used to the analysis of the changes in the suitability level of the Sumatran tiger habitat. The analysis of land change in 2000 and 2020 with the random forest classification method and changes in the level of suitability of the Sumatran Tiger habitat has been carried out. The results of the analysis of land cover/use changes showed a very significant reduction in the area of primary forest, namely 282.58 km2, while the increase in the area of plantations and secondary forests was 186.52 km2 and 101.68 km2. This change affects the suitability level of the Sumatran tiger habitat from a very suitable level decreased from 164.42 km2 to suitable and not suitable. The declining suitability level class indicated the potential loss of Sumatran tigers in the Kerinci Seblat National Park. The increasing of plantation and settlement areas will increase the activity of humans. The conflict of human activity with Sumatran tigers’ life will impact the loss of Sumatran Tigers in KSNP
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

Abstract

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.
ANALYSIS OF CLASSIFICATION METHODS FOR MAPPING SHALLOW WATER HABITATS USING SPOT-7 SATELLITE IMAGERY IN NUSA LEMBONGAN ISLAND, BALI Kuncoro Teguh Setiawan; Gathot Winarso; Andi Ibrahim; Anang Dwi Purwanto; I Made Parsa
International Journal of Remote Sensing and Earth Sciences Vol. 19 No. 1 (2022)
Publisher : BRIN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.ijreses.2022.v19.a3748

Abstract

Shallow water habitat maps are crucial for the sustainable management purposes of marine resources. The use of a better digital classification method can provide shallow water habitat maps with the best accuracy rate that is able to indicate actual conditions. Experts use the object-based classification method as an alternative to the pixel-based method. However, the pixel-based classification method continues to be relied upon by experts in obtaining benthic habitat conditions in shallow water. This study aims to analyze the classification results and examine the accuracy rate of shallow-water habitats distribution using SPOT-7 satellite imagery in Nusa Lembongan Island, Bali. Water column correction by Lyzenga 2006 was opted, while object-based and pixel-based classification was used in this study. The benthic habitat classification scheme uses four classes: substrate, seagrass, macroalgae, and coral. The results show different accuracy is obtained between pixel-based classification with maximum likelihood models and object-based classification with decision tree models. Mapping benthic habitats in Nusa Lembongan, Bali, with object-based classification and decision tree models, has higher accuracy than the other with 68%.

Page 7 of 33 | Total Record : 327

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