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Department of Geography Education , University of Jember, FKIP Building Jl. Kalimantan 37, Jember, East Java, 68121, Indonesia.
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Geosfera Indonesia
Published by Universitas Jember
ISSN : 25989723     EISSN : 26148528     DOI : https://doi.org/10.19184/geosi
Core Subject : Science, Education, Social,
Earth & Planetary Sciences Education Environmental Science
Geosfera Indonesia is a journal publishes original research, review, and short communication (written by researchers, academicians, professional, and practitioners from all over the world) which utilizes geographic and environment approaches (human, physical landscape, nature-society and GIS) to resolve human-environment interaction problems that have a spatial dimension.
Arjuna Subject : Ilmu Sosial - Geografi, Perencanaan dan Pengembangan
Articles 7 Documents
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Search results for , issue "Vol. 7 No. 3 (2022): GEOSFERA INDONESIA" : 7 Documents clear
Performance of UAV Image for Flood Mapping with 2 Dimensional Model in Kaliputih River, Panti District Icha Derka; Entin Hidayah; Gusfan Halik
Geosfera Indonesia Vol. 7 No. 3 (2022): GEOSFERA INDONESIA
Publisher : Department of Geography Education, University of Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/geosi.v7i3.30169

Abstract

In January 2006, the flash flood in Panti Sub-district was a national disaster, causing damage to building infrastructure and fatalities. From this incident, it is necessary to have flood mitigation by providing a map of the distribution of flood inundation using a 2D hydraulic model to provide information regarding the extent of flood inundation in the study area. Due to the limited DEM data for 2D modeling, it is necessary to use UAV images to provide a DSM with good and higher resolution. This study aims to assess the performance of 2D flood modeling results using HEC-RAS equipped with RAS Mapper through UAV processing as input. There are 21 GCP in the study area as an increase in accuracy, the RMSE value in the horizontal direction is 0.3853m, and the vertical direction is 0.1836m. From the CE90 accuracy test results for a horizontal accuracy of 0.58m and LE90 for a vertical accuracy of 0.30m, it can be concluded that the map accuracy test meets the 1:2500 scale. Terrain maps are input to HEC-RAS; selected meshes are 5x5m and 2x2m. The modeling results can show the inundation depth in each GCP from the min-max depth. The model calibration shows an RMSE value of 0.183, while the flood depth validation shows an RMSE value of 0.13. In other words, modeling can represent the distribution of flood inundation in the study area and provide benefits for the community to be more alert in the event of a flood in the coming year. Keywords : UAV; GCP; DSM; HEC-RA; Flood mapping Copyright (c) 2022 Geosfera Indonesia and Department of Geography Education, University of Jember This work is licensed under a Creative Commons Attribution-Share A like 4.0 International License
The Implementation of Disaster Curriculum Toward Disaster Preparedness Campus at Syiah Kuala University Ahmad Nubli Gadeng; Enok Maryani; Epon Ningrum; Iwan Setiawan
Geosfera Indonesia Vol. 7 No. 3 (2022): GEOSFERA INDONESIA
Publisher : Department of Geography Education, University of Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/geosi.v7i3.30246

Abstract

The earthquake and tsunami disasters in Aceh Province, Indonesia led to several injuries, deaths, unfound bodies, and high property losses on 26 December 2004. This hazardous period has reportedly become a valuable case for Syiah Kuala University, where various solutions are being considered for eradicating subsequent occurrences. Therefore, this study aims to determine the implementation patterns of the disaster curriculum developed and applied at Syiah Kuala University, to achieve a DPC (Disaster Preparedness Campus) reputation and enhance DP (Disaster Preparedness) among community members, especially students. A qualitative verification method outlined as a description was used, due to being an inductive approach to the entire experimental process. Data collection was also carried out through observation and literature review, as well as several interviews with the following, (1) The head of the technical implementation unit general course of Syiah Kuala University, (2) The coordinator and lecturer of disaster and environmental knowledge course, and (3) The students of Syiah Kuala University studying the course. After this process, a Delphi method was used to analyze the data obtained, with the outcomes confirmed by a competent expert. Based on the results, three important steps were found to improve disaster preparedness among the people of Aceh and Syiah Kuala University students, namely (1) The establishment of the Tsunami Disaster Mitigation Research Center in 2006, (2) The establishment of the Master Program Study of Disaster Science in the university's Postgraduate Program in 2010, and (3) Development of the general course of disaster knowledge and environment in 2016, which was a compulsory requirement for all students from various faculties, departments, and programs. This indicated that Syiah Kuala University was the first campus to mandate a disaster science course in Indonesia. These results are expected to improve disaster preparedness for students, with Syiah Kuala University becoming a DPC (Disaster Preparedness Campus) in Indonesia. Keywords : Implementation; Disaster Curriculum; Disaster Preparedness Campus Copyright (c) 2022 Geosfera Indonesia and Department of Geography Education, University of Jember This work is licensed under a Creative Commons Attribution-Share A like 4.0 International License
Utilization of Sentinel-2 Imagery in Mapping the Distribution and Estimation of Mangroves' Carbon Stocks in Bengkulu City Ayub Sugara; Agung H. Lukman; Aninda W. Rudiastuti; Ari Anggoro; Muhammad F. Hidayat; Feri Nugroho; Ali M. Muslih; An Nisa N. Suci; Rifi Zulhendri; Marissa Rahmania
Geosfera Indonesia Vol. 7 No. 3 (2022): GEOSFERA INDONESIA
Publisher : Department of Geography Education, University of Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/geosi.v7i3.30294

Abstract

The mangroves' aboveground biomass significantly contributes to the global carbon cycle or economic and ecological values. This makes knowledge about the spatial extent of the mangroves indispensable for policymakers. The sequence of mangroves’ condition range also requires remote sensing data to update the geographical information and synthesize carbon stock in Bengkulu. Therefore, this study aims to create a spatial distrribution of mangroves and evaluate their carbon stock in Bengkulu City using Sentinel-2 imagery. The semi-empirical method uses Sentinel-2 imagery through NDVI to appraise and picture the mangroves' aboveground carbon stock. An allometric equation was used to compute the mangroves' aboveground carbon stock from field measurements. Non-linear regression was used to establish a connection between the NDVI calculated from the Sentinel-2 imagery and the mangroves' aboveground biomass measured in the field, which was subsequently used for aboveground carbon estimation. The results showed that mangroves mapping could derive overall accuracy of 89.09%, where the high-density class existed in 135.12 Ha of total area. It was also discovered that Sentinel-2 imagery could estimate mangroves carbon stock up to 61%. The carbon stock estimation based on the imagery has a value of 16.3992 – 115.134 t C/ha, while that of field survey data ranges from 19.69 to 326.06 t C/ha. These results showed that Sentinel-2B spectral data is functional and has a good chance of being able to predict carbon stock. Keywords : Carbon; mangroves; NDVI; remote sensing; sentinel-2B Copyright (c) 2022 Geosfera Indonesia and Department of Geography Education, University of Jember This work is licensed under a Creative Commons Attribution-Share A like 4.0 International License
The Application of Multi Temporal Satellite Data For Land Cover Mapping of Bawean Island, East Java Zainul Hidayah; Haryo Dwito Armono; Maulinna Kusumo Wardhani; Dwi Budi Wiyanto
Geosfera Indonesia Vol. 7 No. 3 (2022): GEOSFERA INDONESIA
Publisher : Department of Geography Education, University of Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/geosi.v7i3.30797

Abstract

Land cover dynamics in a small island can be determined using Geographic Information System (GIS) approach based on multitemporal image analysis. This study aimed to classify major land cover types and to map land cover changes of Bawean Island. Two sets of 10 meter resolution satellite data ALOS AVNIR (2010) and Sentinel-2A (2020) were used in this study. Satellite image analysis was carried out through several stages namely image pre-processing including radiometric and geometric correction, supervised image classification and accuracy test. Image classification results from 2010 to 2020 showed a significant change in land cover on Bawean Island. The forest vegetation land cover declined significantly from 13,470.5 Ha in 2010 to 8,543.4 Ha in 2020. Most of the area have been converted into paddy fields and built-up areas. The accuracy test and validation were determined by comparing the 2020 Sentinel image classification results with field observation conducted in 2021. The analysis showed good results with 82.52% overall accuracy and 79.66 Kappa coefficient. Further investigation found that changes in land cover on Bawean Island occured due to the agriculture and infrastucture development. Keywords : Geographic Information System (GIS); land cover; satellite images; small island Copyright (c) 2022 Geosfera Indonesia and Department of Geography Education, University of Jember This work is licensed under a Creative Commons Attribution-Share A like 4.0 International License
Simulation of Rainfall Using Two Statistical Data Driven Models: A Study on Santhal Pargana Division of Jharkhand State, India Shrinwantu Raha; Shasanka Kumar Gayen
Geosfera Indonesia Vol. 7 No. 3 (2022): GEOSFERA INDONESIA
Publisher : Department of Geography Education, University of Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/geosi.v7i3.34487

Abstract

Although the variability and prediction of rainfall is an essential issue of the Santhal Pargana Division of the Jharkhand State but the issue is still far from its’ conclusive statement till date. Therefore, this study aimed to simulate the monthly rainfall from 1901 to 2020 using an eight-step procedure. After downloading the monthly rainfall for the Santhal Pargana Division from 1901 to 2020, the TBATS and Naive models were used to simulate the rainfall. The accuracy assessment of each model was done by using the MASE, MAE, RMSE, ME, and R. For the Naïve model, the Godda station was noticed with a comparatively high combined error. The lowest combined error was found for the Pakur station in case of Naïve models. Similar result was also obtained for the TBATS model. The TBATS was found with comparatively higher accuracy, as the combined error was less for the TBATS. The spatial assessment for the standardized rainfall varied from 84.419 mm. to 149.225 mm. For the Naïve predicted model, the rainfall was marked in between 8.133 mm. to 67.059 mm. For the TBATS fitted model, the rainfall fluctuated from the 37.127 mm. to 62.993 mm. Dumka station was noticed with comparatively low rainfall (i.e.,37.127 mm.). Deoghar and Jamtara stations were marked with a moderate rainfall. Remaining stations were marked with higher amount of rainfall for the TBATS fitted model. The Wilcoxon test proved that each model was significant at 95% confidence interval. The result produced in this research is fruitful enough to be utilized for agricultural planning in the Santhal Pargana Division of the Jharkhand state, India. Keywords : TBATS model; Naive model; simulation; accuracy Copyright (c) 2022 Geosfera Indonesia and Department of Geography Education, University of Jember This work is licensed under a Creative Commons Attribution-Share A like 4.0 International License
The Compatibility of Area Functions Map with Actual Site Conditions in Konawe Selatan District La Ode Nursalam; Agus Sugiarto; Putri Tipa Anasi; Ahmad Tarmizi Abd Karim; Fahrudi Ahwan Ikhsan; Andri Estining Sejati
Geosfera Indonesia Vol. 7 No. 3 (2022): GEOSFERA INDONESIA
Publisher : Department of Geography Education, University of Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/geosi.v7i3.34637

Abstract

The Konawe Selatan District region is characterized by Karst hills, various soil types, and steep slopes. Functional classification considers the physical and non-physical characteristics of the location to determine its many uses. The map developed by the Regulation of the Agriculture Minister of Indonesia should be checked with the actual condition for the validation process before presenting to the society and Local government. Therefore, this research aimed to determine the compatibility of the area function map result with the actual conditions in Konawe Selatan District, Southeast Sulawesi, Indonesia. The research is a regional survey, collecting data from interviews and observations, and the data were analyzed descriptively and quantitatively with percentages. The results show that the compatibility of the Konawe Selatan District area function map is 89.61%, functioning as a guideline in the land use plan. Furthermore, the map could guide potential land-use planning functions such as protected forests, limited production forests, rice fields, and settlements. In conclusion, the map is appropriate for disseminating information and material for land use policies in Konawe Selatan District to stakeholders. Keywords : actual condition; area function; compatibility; map Copyright (c) 2022 Geosfera Indonesia and Department of Geography Education, University of Jember This work is licensed under a Creative Commons Attribution-Share A like 4.0 International License
Exploration of Knowledge and Community Preparedness in Flood Disaster Mitigation Erman Syarif; M. Maddatuang; H. Hasriyanti; Alief Saputro
Geosfera Indonesia Vol. 7 No. 3 (2022): GEOSFERA INDONESIA
Publisher : Department of Geography Education, University of Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/geosi.v7i3.35066

Abstract

Floods are natural disasters that should be highly considered due to their threats to human lives and the economy. It is also the third largest natural disaster in the world, which has claimed many lives and properties. Therefore, this study aims to identify community knowledge about floods and determine the efforts to increase preparedness strategies. A qualitative study was conducted in the village of Sapanan, Binamu District, Jeneponto Regency, Indonesia. Subsequently, data collection was carried out by observation, interviews, and documentation with various selected informants. Based on the results, the following were obtained, 1) The level of knowledge and actions performed by the Sapanan people was quite good regarding flooding. This was due to the experience of the community with the disaster, which they had decided to use as a learning platform, 2) The impacts often caused after flooding were the outbreaks of many diseases, which hindered the community from performing their usual activities. This was because they were busy cleaning their homes, with children consequently unable to attend school regarding the muddy state of the chairs and environment, and 3) The community's efforts to increase preparedness for the disasters included land use monitoring and prone location planning in safe areas. In this case, the level of knowledge and actions performed by the people of Sapanan village was quite good concerning flooding. This was because of their numerous experience with the disaster, which they had decided to use as a learning platform. Keywords : knowledge; preparedness; the community; flood Copyright (c) 2022 Geosfera Indonesia and Department of Geography Education, University of Jember This work is licensed under a Creative Commons Attribution-Share A like 4.0 International License

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