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- Investigation of the Development of Tropical Storm Nicholas based on
Global and Regional Climate Data
Authors: Intan Nuni Wahyuni, Ayu Shabrina, Fadhil Lobma, Arnida L. Latifah
First page: 98
Abstract: This paper studies the simulation of Cyclone Nicholas that occurred close to the coastal area of Western Australia and fell on the mainland of Southwestern Australia. The simulation was conducted via a dynamical downscaling model, Weather Research and Forecasting (WRF), to obtain a higher resolution with reference to the regional climate data. The model simulation is generated using a global reanalysis of climate data for the initial and lateral boundary conditions. We investigated the response of the tropical storm to the model regarding the track and intensity using a modified Kyklop method that appears more appropriate for a landfall cyclone. Our study suggests that the regional climate data computed by the model deviates from the storm track of the global climate data forcing field. In this study, the track of the simulated storm is parallel to the satellite data, but it is shifted slightly to the east, closer to the mainland. Nevertheless, the model simulation can implement the intensity of the storm as strongly as the observation, while the forcing data delivers substantial underestimation.
PubDate: 2023-12-29
DOI: 10.23917/forgeo.v37i2.21728
Issue No: Vol. 37, No. 2 (2023)
- The Atmospheric Dynamics Related to Extreme Rainfall and Flood Events
during September-October-November in South Sulawesi
Authors: Amhar Ulfiana, Muhammad Arsyad, Pariabti Palloan
First page: 107
Abstract: This study was conducted to analyse the occurrence of extreme rainfall and the dynamics of the atmosphere prior to the occurrence of extreme rainfall and flood events in South Sulawesi during September-October-November (South Sulawesi’s dry season). The data used is daily data for the period 2001-2020. Using 50 mm/day and the 90th percentile rainfall threshold of 119 rain stations distributed over 24 regencies, extreme rainfall events in each region were identified. Furthermore, after screening for extreme rainfall events followed by flood events, a composite analysis was carried out to obtain patterns of atmospheric conditions before the extreme rainfall events. The results of the study confirm that spatially, the highest extreme rainfall indices values dominate in the western and northern regions of South Sulawesi, both frequency and intensity indicators. Flood events in South Sulawesi during September-October-November 2001-2020 were recorded as 23 days, of which 19 days were the flood events after extreme rainfall events. The dynamics of the atmosphere before the extreme rainfall event followed by the flood event showed anomalies in precipitable water, 850 mb winds, and 200 mb winds. An increase in the amount of precipitable water and a wind speed of 850 mb, as well as a decrease in wind speed of 250 mb compared to normal in the South Sulawesi region and its surroundings, has resulted in an increase in the formation of rain clouds that have the potential to increase the chance of extreme rainfall.
PubDate: 2023-12-29
DOI: 10.23917/forgeo.v37i2.22339
Issue No: Vol. 37, No. 2 (2023)
- Vulnerability Analysis of School Buildings to Tsunami in the Cilacap
Coastal Area
Authors: Hercules Pungky Naga Dewa, Anang Widhi Nirwansyah, Ratna Sari Dewi, Ismail Demirtag
First page: 117
Abstract: Cilacap is one of several areas that experienced significant damage due to the Pangandaran tsunami in 2007. Currently, tsunamis are one of the most serious threats to coastal areas as they can cause devastation to the function of coastal areas. The physical environment can extensively affect the probability of damage caused by tsunamis. In addition, it is critical to maintain building stability as a substantial component in the integrated management efforts of coastal areas. The aim of this research is to assess the physical susceptibility and the vulnerability of school buildings to tsunami, particularly senior high school buildings (known as SMA/MA) located in the coastal area of the Cilacap region. This research is essential for the continuity of learning and teaching activities in the coastal area. Therefore, mapping the physical environment and school buildings in the coastal area of the Cilacap region is necessary. In this study, the physical approach method and Papathoma Vulnerability Tsunami Assessment (PVTA) model were optimally applied to assess coastal vulnerabilities to tsunami. Ultimately, the results were further evaluated by using cross-tabulation. The results confirm that specific coastal areas were categorised as having “moderate to high” susceptibility. Simultaneously, owing to the field survey, we determined that school buildings at this location were made of simple reinforced concrete materials. Notwithstanding that the vulnerability of the school buildings were low, the conditions were deemed to be reasonably harmful given that the schools were located in a “moderate to high” susceptibility. The results of this study have implications for the level of potential physical susceptibility of the coastal areas and the vulnerability of school buildings to tsunamis in the Cilacap region.
PubDate: 2023-12-29
DOI: 10.23917/forgeo.v37i2.23269
Issue No: Vol. 37, No. 2 (2023)
- Machine Learning-Based Rice Field Mapping in Kulon Progo using a Fusion of
Multispectral and SAR Imageries
Authors: Yusri Khoirurrizqi, Rohmad Sasongko, Nur Laila Eka Utami, Amanda Irbah, Sanjiwana Arjasakusuma
First page: 134
Abstract: The land-conversion of rice fields can reduce rice production and negatively impact food security. Consequently, monitoring is essential to prevent the loss of productive agricultural land. This study uses a combination of Sentinel-2 MSI, Sentinel-1 SAR, along with SRTM (elevation and slope data) to monitor rice fields land-conversion. NDVI, NDBI and NDWI indices are transformed from the annual median composite Sentinel-2 MSI images used to identify different rice fields with another object. A monthly median composite of SAR images from Sentinel-1 data are used to identify cropping patterns of rice fields in the inundation phase. The classification is performed by using the Random Forest machine learning algorithm in the Google Earth Engine (GEE) platform. Random Forest classification is run using 1000 trees, with a 70:30 ratio of training and testing data from sample features extracted by visual interpretation of high resolution Google Earth imagery. In this study, Random Forest classification is effective in computing a high amount of multi-temporal and multi-sensory data to map rice-field land conversion with an accuracy rate of 96.16% (2021) and 95.95% (2017) for mapping paddy fields. From the multitemporal rice field maps in 2017—2021, a conversion of 826.66 hectares of rice-fields to non-rice fields was identified. Based on the spatial distribution, the conversion from rice-field to non-rice field is higher at the area near the roads, built area and Yogyakarta International Airport. Therefore, it is important to assess and ensure that National Strategic Projects are managed with due regard to environmental impacts and food security.
PubDate: 2023-12-29
DOI: 10.23917/forgeo.v37i2.20304
Issue No: Vol. 37, No. 2 (2023)
- Land Use Change Modelling Using Logistic Regression, Random Forest and
Additive Logistic Regression in Kubu Raya District, West Kalimantan
Authors: Alfa Nugraha Pradana, Anik Djuraidah, Agus Mohamad Soleh
First page: 149
Abstract: Kubu Raya District is a district in the province of West Kalimantan which has a wetland ecosystem including a high-density swamp or peatland ecosystem along with an extensive area of mangroves. The function of wetland ecosystems is essential for fauna, as a source of livelihood for the surrounding community and as storage reservoir for carbon stocks. Most of the land in Kubu Raya District is peatland. As a consequence, peat has long been used for agriculture and as a source of livelihood for the community. Along with the vast area of peat, the district also has a potential high risk of peat fires. This study aims to predict land use changes in Kubu Raya District using three statistical machine learning models, specifically Logistic Regression (LR), Random Forest (RF) and Additive Logistic Regression (ALR). Land cover map data were acquired from the Ministry of Environment and Forestry and subsequently reclassified into six types of land cover at a resolution of 100 m. The land cover data were employed to classify land use or land cover class for the Kubu Raya district, for the years 2009, 2015 and 2020. Based on model performance, RF provides greater accuracy and F1 score as opposed to LR and ALR. The outcome of this study is expected to provide knowledge and recommendations that may aid in developing future sustainable development planning and management for Kubu Raya District.
PubDate: 2023-12-29
DOI: 10.23917/forgeo.v37i2.23270
Issue No: Vol. 37, No. 2 (2023)
- Leveraging Geospatial Technology for Enhanced Utility Management: A Case
Study in Electrical Distribution Power Systems
Authors: Gabriel Temidayo Adekunle, Olalekan Akeem Alausa, Oluwayemisi Shade Adaradoun, Kuswaji Dwi Priyono
First page: 164
Abstract: Over the years, electricity has developed into a crucial commodity for any nation. The need to evaluate the rate of electricity consumption in regard to utility management and the spatial distribution of major devices to facilitate appropriate planning within the estate is the motivation for this research. This study used geospatial technology to evaluate the electricity distribution to support planning and management in Omole Estate (Phase One) and environs within the city of Lagos, Nigeria. The focus was on determining the land use in study area, geolocations of the transformers, along with the cost of energy consumed per household. Spatial data for the research area was collected through a Hand-held GPS. Google Earth images were downloaded to supplement the data, and a comprehensive analysis of administered and recovered questionnaires was conducted to enrich the dataset. ArcGIS 10.6.1 software was employed to create the database and depict the area, whilst modifying all of the details required within. The result confirms that 72% of the respondents use electricity for domestic use, 18% for commercial use while 10% utilise it for domestic and commercial use. A significant portion of homes (33%) still use outdated postpaid meters and 35% of respondents do not know how much power they use at home each month or the cost per unit of that electricity. Regarding the respondents, 67% have a prepaid card/electrical meter installed (per kilowatt). Concerning cost, 10% of the respondents spends between N1000-N5000 for their monthly electricity consumption, 27% of the respondents between N5,000 and N10,000, 38% between N10,000 and N17,000, 24% between N17,000 and N25,000 and 2% above N25,000 per month on electricity. These findings will assist effective power distribution within the estate and provide guidance on charge rates for commercial power users which is approximately 28% overall.
PubDate: 2023-12-29
DOI: 10.23917/forgeo.v37i2.21982
Issue No: Vol. 37, No. 2 (2023)
- Analysis of Urbanisation’s Relationship with Clean Water Supply
Ecosystem Services in Sukoharjo Regency in 2022
Authors: Aditya Eka Saputra, Setya Nugraha, Rita Noviani
First page: 178
Abstract: The phenomenon of urban population growth is a global concern which will result in a decrease in the value of ecosystem services in an area. Sukoharjo Regency is an area affected by the development of Surakarta City; therefore, rapid growth is taking place. The objective of this study is to investigate the interplay between urbanization, ecosystem services, and the provision of clean water in Sukoharjo Regency in 2022. The methods used in the study were calculating the percentage of the urban population to determine the level of urbanisation, AHP and overlay to ascertain the ecosystem service score, together with cross-tabulation to establish the relationship between these two variables. The result of this study is that the level of urbanisation produces a pattern that districts in the north tend to comprise a higher level. The clean water supply ecosystem services in Sukoharjo Regency obtained results dominated by the low to medium level. The situation regarding the level of urbanisation and ecosystem services in Sukoharjo Regency reveals a relationship where an increase in the level of urbanisation will reduce the value of ecosystem services.
PubDate: 2023-12-29
DOI: 10.23917/forgeo.v37i2.21218
Issue No: Vol. 37, No. 2 (2023)
- Friends and Neighbours: Electoral Geography of 2020 Local Election in
Metro City, Lampung, Indonesia
Authors: Arizka Warganegara, Ari Darmastuti, Hertanto Hertanto, R Sigit Krisbintoro, Muhammad Febriansyah, Wahyu Tyas Pramono
Pages: 191 - 201
Abstract: This article discusses local political dynamics in Indonesia, notably in the city of Metro. There are several factors why a particular candidate is more politically electable than others, including ethno-religious factors and money. Moreover, a traditional factor that needs to be considered in the study of electoral geography is the influence of the spatial effect upon voting behaviour. In the election, demographics and geography are two important factors in voting behaviour. The local election resulted in a competitive and dynamic political contest among the local elite in Metro. The result of the 2020 local election was particularly interesting because the independent candidate won and defeated the party-based candidate. This is a mixed methods approach combining the data from interviews and a qualitative survey. This research aims to analyse the spatial factor in Metro’s local election, looking at why a certain candidate won in a particular area and how the geographical factor influenced voting behaviour. Secondly, the result of the qualitative survey supported the finding that voters still consider ethno-religious factor. The finding obtained by this research reveals two significant narratives, specifically the crucial factor of ethno-religious sentiment on voting preference and the spatial factor related to residency in securing a victory for the candidate in the local election. Essentially, research concludes that the spatial factor is of importance in the context of Metro’s local election and supports Woolstencroft's (1980) classical concept of electoral geography comprising “friends and neighbours”.
PubDate: 2023-12-31
DOI: 10.23917/forgeo.v37i2.23316
Issue No: Vol. 37, No. 2 (2023)
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