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Fahmi Arif Kurnianto
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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 220 Documents
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Back Matter (Reviewer Acknowledgement, Back Cover) Fahmi Arif Kurnianto
Geosfera Indonesia Vol. 5 No. 2 (2020): GEOSFERA INDONESIA
Publisher : Department of Geography Education, University of Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/geosi.v5i2.19457

Abstract

Geospatial Approach for the Analysis of Forest Cover Change Detection using Machine Learning R. Sanjeeva Reddy; G. Anjan Babu; A. Rama Mohan Reddy
Geosfera Indonesia Vol. 5 No. 3 (2020): GEOSFERA INDONESIA
Publisher : Department of Geography Education, University of Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/geosi.v5i3.20157

Abstract

Spatial data classification is famous over recent years in order to extract knowledge and insights into the data. It occurs because vast experimentation was used with various classifiers, and significant improvement was examined in accuracy and performance. This study aimed to analyze forest cover change detection using machine learning. Supervised and unsupervised learning methods were used to analyze spatial data. A Vector machine was used to support the supervised learning, and a neural network method was used to support unsupervised learning. The Normalized Difference Vegetation Index (NDVI) was used to identify the bands and extract pixel information relevant to the vegetation. The supervised method shows better results because of its robust performance and better analysis of spatial data classification using vegetation index. The proposed system experimentation was implemented by analyzing the results obtained from Support Vector Machine (SVM) and NN (Neural Network) methods. It is demonstrated in the results that the use of NDVI mainly enhances the performance and increases the classifier's accuracy to a greater extent. Keywords: Spatial data; Normalized Difference Vegetation Index; NDVI;Vegetation index, Support Vector Machine; Neural Network; Forest Cover Change Copyright (c) 2020 Geosfera Indonesia Journal and Department of Geography Education, University of Jember This work is licensed under a Creative Commons Attribution-Share A like 4.0 International License
Assessing The Impacts of Climate Variability on Rural Households in Agricultural Land Through The Application of Livelihood Vulnerability Index Ginjo Gitima; Abiyot Legesse; Dereje Biru
Geosfera Indonesia Vol. 6 No. 1 (2021): GEOSFERA INDONESIA
Publisher : Department of Geography Education, University of Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/geosi.v6i1.20718

Abstract

Climate variability adversely affects rural households in Ethiopia as they depend on rain-fed agriculture, which is highly vulnerable to climate fluctuations and severe events such as drought and pests. In view of this, we have assessed the impacts of climate variability on rural household’s livelihoods in agricultural land in Tarchazuria district of Dawuro Zone. A total of 270 samples of household heads were selected using a multistage sampling technique with sample size allocation procedures of the simple random sampling method. Simple linear regression, the standard precipitation index, the coefficient of variance, and descriptive statistics were used to analyze climatic data such as rainfall and temperature. Two livelihood vulnerability analysis approaches, such as composite index and Livelihood Vulnerability Index-Intergovernmental Panel on Climate Change (LVI-IPCC) approaches, were used to analyze indices for socioeconomic and biophysical indicators. The study revealed that the variability patterns of rainfall and increasing temperatures had been detrimental effects on rural households' livelihoods. The result showed households of overall standardized, average scores of Wara Gesa (0.60) had high livelihood vulnerability with dominant major components of natural, physical, social capital, and livelihood strategies to climate-induced natural hazards than Mela Gelda (0.56). The LVI-IPCC analysis results also revealed that the rural households in Mela Gelda were more exposed to climate variability than Wara Gesa and slightly sensitive to climate variability, considering the health and knowledge and skills, natural capitals, and financial capitals of the households. Therefore, interventions including road infrastructure construction, integrated with watershed management, early warning information system, providing training, livelihood diversification, and SWC measures' practices should be a better response to climate variability-induced natural hazards. Keywords: Households; Livelihood Vulnerability Index; climate variability; Tarchazuria District Copyright (c) 2021 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
Emerging Geospatial Technologies in Environmental Research, Education, and Outreach Sergio Bernardes; Margueritte Madden; Ashurst Walker; Andrew Knight; Nicholas Neel; Akshay Mendki; Dhaval Bhanderi; Andrew Guest; Shannon Healy; Thomas Jordan
Geosfera Indonesia Vol. 5 No. 3 (2020): GEOSFERA INDONESIA
Publisher : Department of Geography Education, University of Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/geosi.v5i3.20719

Abstract

Drawing on the historical importance of visual interpretation for image understanding and knowledge discovery, emerging technologies in geovisualization are incorporated into research, education and outreach at the Center for Geospatial Research (CGR) in the Department of Geography at the University of Georgia (UGA), USA. This study aimed to develop the 3D Immersion and Geovisualization (3DIG) system consisting of uncrewed aerial systems (UAS) for data acquisition, augmented and virtual reality headsets and mobile devices, an augmented reality digital sandbox, and a video wall. We were working together integrated data products from the UAS imagery, including digital image mosaics and 3D models, and readily available gaming engine software to create augmented and virtual reality immersive visualizations. The use of 3DIG in research is demonstrated in a case study documenting the seasonal growth of vegetables in small gardens with a time series of 3D crop models generated from UAS imagery and Structure from Motion photogrammetry. Demonstrations of 3DIG in geography and geology courses, as well as public events, also indicate the benefits of emerging geospatial technologies for creating active learning environments and fostering participatory community engagement. Keywords: Environmental Education; Geovisualization; Augmented Reality; Virtual Reality; UAS, Photogrammetry Copyright (c) 2020 Geosfera Indonesia Journal and Department of Geography Education, University of Jember This work is licensed under a Creative Commons Attribution-Share A like 4.0 International License
Development of Web-Based GIS Alert System for Informing Environmental Risk of Dengue Infections in Major Cities of Pakistan Naureen Zainab; Aqil Tariq; Saima Siddiqui
Geosfera Indonesia Vol. 6 No. 1 (2021): GEOSFERA INDONESIA
Publisher : Department of Geography Education, University of Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/geosi.v6i1.20792

Abstract

Dengue is one of the emerging major public health problems, and its incidence varies with climate conditions. It affects millions of people's lives owing to unusual socioeconomic conditions and epidemiological factors. This study was designed to build a web-based GIS alert system for dengue data management and analysis which would centralize information and make it accessible to all relevant stakeholders before, during, and after crises. Three geographical regions were selected in this study. The user interface of the dengue alert system was developed based upon MapGuide. Results indicate that risk level was mainly associated with Breteau Index. Karachi and Lahore were at their highest risk, i.e., level 4. Islamabad and Chakwal were also at the highest risk, i.e., level 4. Attock had high risk, i.e., level 3 followed by Haripur with minimal level 1. The high Breteau Index showed a direct relationship to high potential transmission of dengue outbreaks, a more significant peak of dengue was the result of monsoons, while smaller peaks were observed due to domestic water storage. Hence, it was concluded that monsoon is the best suitable season for the development of dengue. Web-Based GIS Alert System for dengue data management and analysis was developed, centralizing information and making it accessible to all relevant stakeholders before, during & after a crisis. This program creation will provide a more analytical forum for advising multiple levels of risk and an experimental method for measuring the effect of different factors on risk level distribution by adjusting the component's weighting. Keywords : Dengue; GIS analysis; GUI; Alert system; Breteau index; Weighted overlay Copyright (c) 2021 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
Rethinking Urbanization: A Transit-Information-Communication –Technology-Oriented Development Path for the Developing Countries and Post-Industrial Towns Schuman Lam; Heng Li; Ann T.W. Yu
Geosfera Indonesia Vol. 6 No. 1 (2021): GEOSFERA INDONESIA
Publisher : Department of Geography Education, University of Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/geosi.v6i1.20810

Abstract

This study explores a new path of urbanization to enhance the conventional economy-led urban development practice by conducting an urban quality of life (Uqol) survey. It analyzes the Uqol evaluation gap caused by demographic attributes between developing countries, developed countries, and post-industrial town. We adopted a mixed-methods research design, including a literature review and an Uqol survey, to suggest the transit-oriented-development (TOD) and information-communication-technology (ICT) based urban-rural development concept. The finding indicates a disparity of Uqol mean score rankings among the developing countries, developed countries, and the marginalized post-industrial town. It highlights the health, transportation, socio-economic, and technological development in the developing countries strongly desired. Furthermore, Kruskal-Wallis H-test and Mann-Whitney U-test results show significant differences in economy, technology-ICT, smart living, and lifestyle within education, profession, age, and country groups. It clarifies that the well-being gap is shaped by demography and exhibited geographically, which implies TOD-ICT advancement can break down geographical barriers for achieving sustainable growth in remote areas. Supported by the planetary urbanization theory, the human-technology-driven urban development process would facilitate the maturity and implementation of the proposed TOD-ICT-based urban-ruralism (UxR) concept for enhancing the future global urbanization process. Keywords : Human and Social Geography; Information-Communication-Technology; Urban Policymaking; Transit-Oriented-Development; Urban Quality of Life Copyright (c) 2021 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
Seasonal Variability of Waterlogging in Rangpur City Corporation Using GIS and Remote Sensing Techniques Md. Naimur Rahman; Sajjad Hossain Shozib
Geosfera Indonesia Vol. 6 No. 2 (2021): GEOSFERA INDONESIA
Publisher : Department of Geography Education, University of Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/geosi.v6i2.21006

Abstract

Waterlogging hazard is a significant environmental issue closely linked to land use for sustainable urbanization. NDWI is widely and effectively used in identifying and visualizing surface water distribution based on satellite imagery. Landsat 7 ETM+ and Landsat 8 OLI TIRS images of pre and post-monsoon (2002, 2019) have been used. The main objective of this study is to detect the seasonal variation of waterlogging in Rangpur City Corporation (RPCC) in 2002 and 2019. In the present study, we used an integrated procedure by using ArcGIS raster analysis. For pre and post-monsoon, almost 93% accuracy was obtained from image analysis. Results show that in 2002 during the pre and post-monsoon period, waterlogged areas were about 159.58 km2 and 32.32 km2, respectively, wherein in 2019, the changes in waterlogged areas are reversed than 2002. In 2019, during pre-monsoon, waterlogged area areas were 122.79 km2, and during post-monsoon, it increased to 127.05 km2. The research also depicts that the trend of the waterlogging situation largely depends on seasonal rainfall and a flawed drainage system. Keywords : Seasonal variation; Waterlogging; Remote sensing; GIS; Rangpur City Corporation Copyright (c) 2021 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
Quantifying The Significance of Distance to Temporal Dynamics of Covid-19 Cases in Nigeria Using a Geographic Information System Ifeyinwa Sarah Obuekwe; Umar Saleh Anka; Sodiq Opeyemi Ibrahim; Usman Ahmad Adam
Geosfera Indonesia Vol. 6 No. 1 (2021): GEOSFERA INDONESIA
Publisher : Department of Geography Education, University of Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/geosi.v6i1.21405

Abstract

The coronavirus disease 2019 (COVID-19) is caused by a new strain of coronavirus that spreads primarily by close contact. Although Nigeria adopted lockdown measures, no defined strategies were used in setting the distance threshold for these lockdowns. Hence, understanding the drivers of COVID-19 is pivotal to an informed decision for containment measures in the absence of vaccines. Spatial and temporal analyses are crucial drivers to apprehending the pattern of diseases over space and time. Thus, this study aimed to quantify the significance of distance to the temporal dynamics of COVID-19 cases in Nigeria using the Geographic Information System. Incremental spatial autocorrelation was used to analyze datasets of each month in ArcGIS. March, April, May, and June exhibited patterns with no significant peaks, while July and August exhibited patterns with two statistically significant peaks. The first and second peaks of July were 301,338.39 and 365,947.83 meters, respectively, while August was 301,338.39 and 336,128.09 meters, respectively. Therefore, a significant difference in the clustering of COVID-19 over distances between July and August was established. This indicated that progression in the spread of the virus increased the virus's spatial coverage while the distance of risk of exposure decreased. This study's findings could be utilized to establish maximum movement restriction areas to contain the spread of COVID-19. Keywords: Distance; Incremental spatial autocorrelation; Covid-19; Disease; Nigeria Copyright (c) 2021 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
Analysis on Factors Influencing Geography Teachers’ Ability in Constructing High-Order Thinking Skills (HOTS) Assessment Instrument Suhendro Suhendro; Dede Sugandi; Mamat Ruhimat
Geosfera Indonesia Vol. 6 No. 2 (2021): GEOSFERA INDONESIA
Publisher : Department of Geography Education, University of Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/geosi.v6i2.21428

Abstract

The teacher's ability to construct assessment instruments is a focus that needs to be considered. Furthermore, the demand of the 21st century directs teachers to set questions that are oriented to train students' abilities in higher-order thinking. However, several factors affect the ability to construct HOTS-oriented assessment instruments. This study aims to investigate what factors influence geography teachers’ ability to develop higher-order thinking skills (HOTS) instruments to measure learning outcomes. This study used a survey method with a quantitative approach. The data collection technique was field observation, and multiple linear regression was used for analysis. The results showed the linearity of teacher education regarding the length of teaching geography was 0.904, the tertiary institution was 0.009, and the background of education was 0.019. Also, teachers' certification was 0.007, their training was 0.032, and their experience in making HOTS questions was 0.047. The coefficient value of determination R, namely 0.635 means the relationship between teaching length, the linearity of their education in tertiary institutions, background, certification, training, and experience regarding the ability to develop HOTS-oriented assessment instruments is 63.5%. This means the relationship is strong, and 36.5% is another factor. This study concludes that the factors that significantly affect the ability of geography teachers in developing HOTS-oriented assessment instruments are the linearity factor of teacher education in universities, education background, certification, teacher training and experience in making HOTS questions. Keywords: Teacher ability factors; Assessment, Higher-order thinking skills Copyright (c) 2021 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
Assessment of Flood Hazard Mapping Based on Analytical Hierarchy Process (AHP) and GIS: Application in Kencong District, Jember Regency, Indonesia Muhammad Asyroful Mujib; Bejo Apriyanto; Fahmi Arif Kurnianto; Fahrudi Ahwan Ikhsan; Elan Artono Nurdin; Era Iswara Pangastuti; Sri Astutik
Geosfera Indonesia Vol. 6 No. 3 (2021): GEOSFERA INDONESIA
Publisher : Department of Geography Education, University of Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/geosi.v6i3.21668

Abstract

Flood is one of the most frequent hydrometeorological disasters which leads in economic losses. The first step in flood disaster mitigation efforts is mapping vulnerable areas. Kencong District frequently affected by the annual flooding event. This study aims to assess flood hazard mapping by integrating the AHP method and Geographic Information System. This study used a descriptive quantitative approach through the correlation matrix of the AHP model for each physical environmental factor. These factors include slope, altitude, distance from the river, soil type, Topographic Wetness Index (TWI), and Curvature. Furthermore, with the Geographic Information System (GIS), the weighted overlay stage was carried out to obtain the results of flood-prone areas. Based on the AHP analysis, the most significant factors in determining flood-prone areas were the distance from rivers, slopes, and TWI. The results of flood-prone areas mapping were divided into five classes: from deficient 0.02%, low 4.26%, medium 37.11%, high 51.89%, and very high 6.72%. Validation of GIS mapping results with data in the field has an AUC value of 84%, which indicates that the prediction of the AHP-GIS model is perfect in flood-prone areas mapping in the Kencong District. The integration of AHP method and Geographic Information System in flood hazard assessment were able to produce a model to evaluate the spatial distribution of flood-prone areas. Keywords : Flood Hazard Mapping; Multi-criteria decision analysis; AHP Model; GIS; Jember Copyright (c) 2021 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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