Monanisa Monanisa, K. Aryaningrum, A. Kurniawan, A. Pitoyo, S. Sukmaniar, W. Saputra
Increasingly thriving businesses that utilize existing startups are a form of disruptive innovation. Today, these startup users can multiply the number of their customers online to include a broader population in downtown areas. This research aimed to analyze the locations of startup users in Palembang City, Indonesia, spatially using the Accuracy Values of Spatial Data Modeling. Frequency, a descriptive quantitative approach, and spatial data modeling analysis were the two methods applied to 364 sampling points distributed in Palembang City. The results indicated that single women with an average of high school or equivalent education dominated the demographics of the startup users. Also, on average, the startup users were 20–29 years of age. The spatial analysis revealed that their business locations formed a dispersed pattern, with an even density in the downtown area. Based on the sensitivity and specificity values on the ROC curve (receiver operating characteristic) and the accuracy level obtained from AUC (area under the ROC curve), the Spatial Data Modeling (SDM) of the density distribution showed very high-accuracy results, 98.8%.
{"title":"Spatial Analysis of Startup User Locations and Its Accuracy Values Using Spatial Data Modeling, Palembang City, Indonesia","authors":"Monanisa Monanisa, K. Aryaningrum, A. Kurniawan, A. Pitoyo, S. Sukmaniar, W. Saputra","doi":"10.22146/ijg.70537","DOIUrl":"https://doi.org/10.22146/ijg.70537","url":null,"abstract":"Increasingly thriving businesses that utilize existing startups are a form of disruptive innovation. Today, these startup users can multiply the number of their customers online to include a broader population in downtown areas. This research aimed to analyze the locations of startup users in Palembang City, Indonesia, spatially using the Accuracy Values of Spatial Data Modeling. Frequency, a descriptive quantitative approach, and spatial data modeling analysis were the two methods applied to 364 sampling points distributed in Palembang City. The results indicated that single women with an average of high school or equivalent education dominated the demographics of the startup users. Also, on average, the startup users were 20–29 years of age. The spatial analysis revealed that their business locations formed a dispersed pattern, with an even density in the downtown area. Based on the sensitivity and specificity values on the ROC curve (receiver operating characteristic) and the accuracy level obtained from AUC (area under the ROC curve), the Spatial Data Modeling (SDM) of the density distribution showed very high-accuracy results, 98.8%.","PeriodicalId":52460,"journal":{"name":"Indonesian Journal of Geography","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45106149","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The population is increasing rapidly globally, and urban expansion of the cities has become an extensive trend in developing nations. Urban expansion patterns, such as transportation structure and road networks, affect transportation planning. This research was conducted on a mega project in Lahore city of Pakistan, i.e., the Lahore Ring Road (LRR) project. Limited research focused on the beneficiary assessment of the road project, and this research was carried out to fill this research gap. This research aims to evaluate the beneficiary assessment of DHA Phase 8 and Halloki Settlement along the Lahore Ring Road. The simple Random Sampling technique was used to conduct the household survey in the study area. This study concluded that most of the residents did not modify their houses nor increase the built-up area and height after the introduction of the project. This study inferred that the rental potential was high at some locations and low at old existing settlements. This research further concluded that community participation was ignored, and public facilities were not improved in the study area. But a project of LRR was very much beneficial and alive for the residents of Lahore city. Community participation should be enhanced in such types of megaprojects, and allied facilities in the nearby community should be upgraded. This research will be helpful for policymakers, urban planners, transportation planners, development authorities, and other stakeholders in planning future road projects in the country.
{"title":"Assessing Gains of stakeholders for Mega Project implementation: Learning from Beneficiary Assessment of Lahore Ring Road Project, Pakistan","authors":"M. Asim, A. Rehman, M. Nadeem","doi":"10.22146/ijg.65778","DOIUrl":"https://doi.org/10.22146/ijg.65778","url":null,"abstract":"The population is increasing rapidly globally, and urban expansion of the cities has become an extensive trend in developing nations. Urban expansion patterns, such as transportation structure and road networks, affect transportation planning. This research was conducted on a mega project in Lahore city of Pakistan, i.e., the Lahore Ring Road (LRR) project. Limited research focused on the beneficiary assessment of the road project, and this research was carried out to fill this research gap. This research aims to evaluate the beneficiary assessment of DHA Phase 8 and Halloki Settlement along the Lahore Ring Road. The simple Random Sampling technique was used to conduct the household survey in the study area. This study concluded that most of the residents did not modify their houses nor increase the built-up area and height after the introduction of the project. This study inferred that the rental potential was high at some locations and low at old existing settlements. This research further concluded that community participation was ignored, and public facilities were not improved in the study area. But a project of LRR was very much beneficial and alive for the residents of Lahore city. Community participation should be enhanced in such types of megaprojects, and allied facilities in the nearby community should be upgraded. This research will be helpful for policymakers, urban planners, transportation planners, development authorities, and other stakeholders in planning future road projects in the country.","PeriodicalId":52460,"journal":{"name":"Indonesian Journal of Geography","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47220854","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
S. Supriatna, M. Mukhtar, K. Wardani, Fathia Hashilah, M. D. Manessa
Land cover change is a prevalent thing in Indonesia. This phenomenon often causes deforestation rates to continue to increase every year, which can cause various natural disasters. This study will look at changes in land cover, make land cover prediction models, and see the relationship between land cover changes and the flood disaster that occurred in Banjarmasin City and its surroundings. Remote sensing is used to see changes in land cover from year to year with GlobeLand30 satellite imagery. Satellite imagery processing is carried out using the Cellular Automata – Markov Chain method to see the land cover prediction. The results show that the most significant land cover change from 2000 to 2020 is experienced by built-up land and forests, while in 2030, forests are predicted to experience deforestation of 356 km2 from 2020. The deforestation will cause catastrophic flooding in 2021, where flooding extends to areas that are not estimated to be high flood hazards, with 111 flood points located in the plantation area.
{"title":"CA-Markov Chain Model-based Predictions of Land Cover: A Case Study of Banjarmasin City","authors":"S. Supriatna, M. Mukhtar, K. Wardani, Fathia Hashilah, M. D. Manessa","doi":"10.22146/ijg.71721","DOIUrl":"https://doi.org/10.22146/ijg.71721","url":null,"abstract":"Land cover change is a prevalent thing in Indonesia. This phenomenon often causes deforestation rates to continue to increase every year, which can cause various natural disasters. This study will look at changes in land cover, make land cover prediction models, and see the relationship between land cover changes and the flood disaster that occurred in Banjarmasin City and its surroundings. Remote sensing is used to see changes in land cover from year to year with GlobeLand30 satellite imagery. Satellite imagery processing is carried out using the Cellular Automata – Markov Chain method to see the land cover prediction. The results show that the most significant land cover change from 2000 to 2020 is experienced by built-up land and forests, while in 2030, forests are predicted to experience deforestation of 356 km2 from 2020. The deforestation will cause catastrophic flooding in 2021, where flooding extends to areas that are not estimated to be high flood hazards, with 111 flood points located in the plantation area.","PeriodicalId":52460,"journal":{"name":"Indonesian Journal of Geography","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49002180","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This research aims to make a historical mapping of the development of road infrastructure and the impact on land use changes. A historical analysis was conducted based on the documents and reports of transportation development, road construction, and urban planning in Semarang City, the capital city of Central Java, Indonesia. From a historical perspective, the transportation development and the land use change of Semarang City were determined by economic activities from the early period of colonialism, especially when this city was devoted as a port city in Java with massive coastal inhabitants. Along with this economic activity, ports and roads were built, accelerating the city’s development until the mid of 20th century. Road construction generated urban problems such as rapid urbanization, and environmental problems. Meanwhile, the road construction also accelerated the city agglomeration, connecting Semarang City with other cities on the Java North Coast. However, in the 1990s the symptom of the use of private transportation occurred in Semarang which became the most critical issue in the later periods.
{"title":"Road Transportation Development and Land Use Changes in Semarang City, Central Java, Indonesia","authors":"E. Hartatik, Wasino Wasino, E. Trihatmoko","doi":"10.22146/ijg.66195","DOIUrl":"https://doi.org/10.22146/ijg.66195","url":null,"abstract":"This research aims to make a historical mapping of the development of road infrastructure and the impact on land use changes. A historical analysis was conducted based on the documents and reports of transportation development, road construction, and urban planning in Semarang City, the capital city of Central Java, Indonesia. From a historical perspective, the transportation development and the land use change of Semarang City were determined by economic activities from the early period of colonialism, especially when this city was devoted as a port city in Java with massive coastal inhabitants. Along with this economic activity, ports and roads were built, accelerating the city’s development until the mid of 20th century. Road construction generated urban problems such as rapid urbanization, and environmental problems. Meanwhile, the road construction also accelerated the city agglomeration, connecting Semarang City with other cities on the Java North Coast. However, in the 1990s the symptom of the use of private transportation occurred in Semarang which became the most critical issue in the later periods.","PeriodicalId":52460,"journal":{"name":"Indonesian Journal of Geography","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42817367","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
M. Barchia, D. Budianta, B. Sulistyo, Dodi Hardiansyah, H. Suhartoyo, R. Novanda
Unpredictable conditions of rice cultivation on fragile peatlands in Indonesia due to land-use changes would be an obstacle to agricultural food production and food security. This study aimed to determine the changes in land usage in Bengkulu, from prospective rice fields to oil palm plantations. The study was conducted from June to October 2020 at Air Manjuto irrigation paddy fields in Mukomuko Regency, Bengkulu Province. The analysis used satellite imagery with appropriate resolutions and multitemporal time from the United States Geological Survey's Landsat 5 Thematic Mapper (TM), Landsat 7 Enhanced Thematic Mapper + (ETM+), and Landsat 8 Operational Land Imager (OLI) collected from the years of 2000, 2008, and 2019. (USGS). The landscapes covering the Air Manjuto area were mostly marginal swampy peaty soils with ordo of Inceptisols, Histosols, and Entisols, which favor intensive rice cultivation. Oil palm plantation covers about 80% of the area, and in the last ten years, the cultivation by small-scale farmers increased sharply, about 8,219 ha or 68% from the previous decade, and no bush and bare land. In contrast, rice fields were an extraordinary loss of 6,819 ha or about 74% in the last decade, from 9,187 ha in 2008 to 2,308 ha in 2019. The loss of a huge area for rice cultivation at the Air Manjuto irrigation area threatens production in Bengkulu. The loss should be reversed through supporting infrastructure facilities and incentives, agrochemical subsidies, and agricultural insurances, and no more rice fields should be converted.
{"title":"Land Use Change Threat to Paddy Cultivation Sustainability on the Irrigated Rice Fields in Bengkulu Province, Indonesia","authors":"M. Barchia, D. Budianta, B. Sulistyo, Dodi Hardiansyah, H. Suhartoyo, R. Novanda","doi":"10.22146/ijg.73304","DOIUrl":"https://doi.org/10.22146/ijg.73304","url":null,"abstract":"Unpredictable conditions of rice cultivation on fragile peatlands in Indonesia due to land-use changes would be an obstacle to agricultural food production and food security. This study aimed to determine the changes in land usage in Bengkulu, from prospective rice fields to oil palm plantations. The study was conducted from June to October 2020 at Air Manjuto irrigation paddy fields in Mukomuko Regency, Bengkulu Province. The analysis used satellite imagery with appropriate resolutions and multitemporal time from the United States Geological Survey's Landsat 5 Thematic Mapper (TM), Landsat 7 Enhanced Thematic Mapper + (ETM+), and Landsat 8 Operational Land Imager (OLI) collected from the years of 2000, 2008, and 2019. (USGS). The landscapes covering the Air Manjuto area were mostly marginal swampy peaty soils with ordo of Inceptisols, Histosols, and Entisols, which favor intensive rice cultivation. Oil palm plantation covers about 80% of the area, and in the last ten years, the cultivation by small-scale farmers increased sharply, about 8,219 ha or 68% from the previous decade, and no bush and bare land. In contrast, rice fields were an extraordinary loss of 6,819 ha or about 74% in the last decade, from 9,187 ha in 2008 to 2,308 ha in 2019. The loss of a huge area for rice cultivation at the Air Manjuto irrigation area threatens production in Bengkulu. The loss should be reversed through supporting infrastructure facilities and incentives, agrochemical subsidies, and agricultural insurances, and no more rice fields should be converted.","PeriodicalId":52460,"journal":{"name":"Indonesian Journal of Geography","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43388705","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Nowadays measuring national and regional development primarily relies on demographic and socio-economic indicators. An indicator in physical dimension e.g., areas of human settlements and their economic uses of lands is usually ignored due to unavailability of data in countries like Thailand. Remotely-sensed derived built-up area was used, for the first time, as a physical indicator for studying Thailand’s regional development. Remote sensing - using the decision tree classifier with the combination indices of band ratios, NDVI, MNDWI, and NDBI - and GIS techniques were utilized to estimate the regional proportion of built-up area. The relationships between the percentage of the derived built-up area and the three development indicators - urbanization rate, Gross Regional Product, and Human Achievement Index - were analyzed. Resultantly, the estimate of the 2019 derived built-up area in Thailand was 2.46% with the average accuracy of 84.5%. Regional variation in development levels existed and relationships between the percentage of built-up area and the three development indicators for the regions were strong. However, there was no relationship after excluding the region having the effect of Bangkok. Therefore, remotely-sensed derived built-up area gives new information and is suggested for use for the analysis of Thailand’s regional development.
{"title":"Remotely-Sensed Derived Built-up Area as an Alternative Indicator in the Study of Thailand’s Regional Development","authors":"Sirivilai Teerarojanarat","doi":"10.22146/ijg.72921","DOIUrl":"https://doi.org/10.22146/ijg.72921","url":null,"abstract":"Nowadays measuring national and regional development primarily relies on demographic and socio-economic indicators. An indicator in physical dimension e.g., areas of human settlements and their economic uses of lands is usually ignored due to unavailability of data in countries like Thailand. Remotely-sensed derived built-up area was used, for the first time, as a physical indicator for studying Thailand’s regional development. Remote sensing - using the decision tree classifier with the combination indices of band ratios, NDVI, MNDWI, and NDBI - and GIS techniques were utilized to estimate the regional proportion of built-up area. The relationships between the percentage of the derived built-up area and the three development indicators - urbanization rate, Gross Regional Product, and Human Achievement Index - were analyzed. Resultantly, the estimate of the 2019 derived built-up area in Thailand was 2.46% with the average accuracy of 84.5%. Regional variation in development levels existed and relationships between the percentage of built-up area and the three development indicators for the regions were strong. However, there was no relationship after excluding the region having the effect of Bangkok. Therefore, remotely-sensed derived built-up area gives new information and is suggested for use for the analysis of Thailand’s regional development.","PeriodicalId":52460,"journal":{"name":"Indonesian Journal of Geography","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48508729","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ruki Ardiyanto, S. Supriatna, T. L. Indra, Masita Dwi Mandini Manesa
Bekasi City has a high population density, as seen from its growth rate in 2020. Therefore, geospatial analysis is required to support and provide effective and efficient health services, evaluate the need for referral hospital capacity, and minimize the spread of COVID-19 cases in this city. The geospatial methods used in this study are Geometric Network Analyst and Geographic Weighted Regression (GWR), with Service Area (SA) used for analysis. The results based on the distance between the referral hospitals and settlements in Bekasi City showed that more than 2.201 million people, or 90%, have been well covered. Meanwhile, regarding travel time, 1.792 million people or 73% in eight sub-districts are in well-served areas. Conversely, referral hospitals do not cover four sub-districts, namely Bantar Gebang, Jati Sampurna, Medan Satria, and Jati Asih. The spatial modeling analysis results using GWR with spatial-temporal data recapitulation of data reports for eight months showed predictions for the spread of confirmed cases in six sub-districts, namely West Bekasi, North Bekasi, East Bekasi, Medan Satria, Mustika Jaya, and Rawalumbu. This implies that local governments need to suggest more referral hospitals serving people who live far from the existing referral hospitals.
{"title":"Geospatial approach to accessibility of referral hospitals using geometric network analysts and spatial distribution models of covid-19 spread cases based on gis in bekasi city, west java","authors":"Ruki Ardiyanto, S. Supriatna, T. L. Indra, Masita Dwi Mandini Manesa","doi":"10.22146/ijg.66099","DOIUrl":"https://doi.org/10.22146/ijg.66099","url":null,"abstract":"Bekasi City has a high population density, as seen from its growth rate in 2020. Therefore, geospatial analysis is required to support and provide effective and efficient health services, evaluate the need for referral hospital capacity, and minimize the spread of COVID-19 cases in this city. The geospatial methods used in this study are Geometric Network Analyst and Geographic Weighted Regression (GWR), with Service Area (SA) used for analysis. The results based on the distance between the referral hospitals and settlements in Bekasi City showed that more than 2.201 million people, or 90%, have been well covered. Meanwhile, regarding travel time, 1.792 million people or 73% in eight sub-districts are in well-served areas. Conversely, referral hospitals do not cover four sub-districts, namely Bantar Gebang, Jati Sampurna, Medan Satria, and Jati Asih. The spatial modeling analysis results using GWR with spatial-temporal data recapitulation of data reports for eight months showed predictions for the spread of confirmed cases in six sub-districts, namely West Bekasi, North Bekasi, East Bekasi, Medan Satria, Mustika Jaya, and Rawalumbu. This implies that local governments need to suggest more referral hospitals serving people who live far from the existing referral hospitals.","PeriodicalId":52460,"journal":{"name":"Indonesian Journal of Geography","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49117859","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Gladys O. Chukwurah, Chioma Onwuneme John-nsa, F. Okeke, Eze Charles Chukwudi, Isimah Matthew Ogorchukwu
Accelerated spatial growth of urban areas is a key driver to land use/land cover change with its concomitant effect on environmental sustainability. The dearth of data on the rate of urban expansion, especially in many developing countries, including Nigeria has continued to hinder effective land use planning and sustainable development. The study aims to identify and analyze the settlement patterns and trends in urban growth at ten years intervals and their planning implications in Abuja, Nigeria. It relied on data generated via remote sensing and Geographic Information Systems to create the map and examine the land cover change in the study area. Classification of land cover using LANDSAT data and land cover transitions for 29 years (1990 to 2019) were mapped and the net land cover change was computed. The results showed the settlement pattern and an increase in the urban built-up area ranging from 1.8% in 1990 to 19.3% in 2019. The dispersion pattern revealed a large concentration of the built-up spaces to be in the eastern region and that the expansion continued from east to south and south-west. The bare land cover types were found to have increased while vegetation land cover decreased rapidly by 30.4% from 1990-2019. The study recommends the need for city planners to decentralize urban planning and development control with adequate provision of affordable urban facilities at the peripheries of cities in Nigeria. Furthermore, massive integration of green infrastructure in built-up areas is required to mitigate the effects of vegetation loss in cities.
{"title":"Rapid spatial growth of cities and its planning implications for developing countries: a case study of Abuja, Nigeria.","authors":"Gladys O. Chukwurah, Chioma Onwuneme John-nsa, F. Okeke, Eze Charles Chukwudi, Isimah Matthew Ogorchukwu","doi":"10.22146/ijg.70316","DOIUrl":"https://doi.org/10.22146/ijg.70316","url":null,"abstract":"Accelerated spatial growth of urban areas is a key driver to land use/land cover change with its concomitant effect on environmental sustainability. The dearth of data on the rate of urban expansion, especially in many developing countries, including Nigeria has continued to hinder effective land use planning and sustainable development. The study aims to identify and analyze the settlement patterns and trends in urban growth at ten years intervals and their planning implications in Abuja, Nigeria. It relied on data generated via remote sensing and Geographic Information Systems to create the map and examine the land cover change in the study area. Classification of land cover using LANDSAT data and land cover transitions for 29 years (1990 to 2019) were mapped and the net land cover change was computed. The results showed the settlement pattern and an increase in the urban built-up area ranging from 1.8% in 1990 to 19.3% in 2019. The dispersion pattern revealed a large concentration of the built-up spaces to be in the eastern region and that the expansion continued from east to south and south-west. The bare land cover types were found to have increased while vegetation land cover decreased rapidly by 30.4% from 1990-2019. The study recommends the need for city planners to decentralize urban planning and development control with adequate provision of affordable urban facilities at the peripheries of cities in Nigeria. Furthermore, massive integration of green infrastructure in built-up areas is required to mitigate the effects of vegetation loss in cities.","PeriodicalId":52460,"journal":{"name":"Indonesian Journal of Geography","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43480984","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
P. A. Aryaguna, G. R. Gaffara, D. A. Sari, Ade Arianto
Green open space is one of the most important land uses, especially in densely populated urban areas. Public Green Open Land in each area regulated in Law No. 1 of 2007 is at least 20%. Based on data from the Department of Creative Works, Land and Spatial Planning as well as the Environment Agency of DKI Jakarta, West Jakarta's Green open space asset area is 277.45 Ha of the total area of West Jakarta, which is 12543 Ha. There is a need for a study to determine the potential land for green open space in West Jakarta to catch up on the fulfillment of public green open space based on spatial and regional analysis. One of the GIS-based methods that can be used to determine potential green open space is the decision tree method. This method uses AHP analysis in its formulation based on experts in the relevant agencies. In total there are 8 parameters that influence in determining potential green open space in West Jakarta, namely flood risk, air quality, population, distance to roads, distance to water sources, building density and distance to green open space assets. The modeling results are divided into five classes ranging from very priority to not priority. The total area of land that is much prioritized to be used as green open space is 95.57 hectares spread out. The modeling results show that there are still potential lands to be used as green open spaces in West Jakarta.
{"title":"Green Open Space Priority Modelling Using GIS Analysis in West Jakarta","authors":"P. A. Aryaguna, G. R. Gaffara, D. A. Sari, Ade Arianto","doi":"10.22146/ijg.68184","DOIUrl":"https://doi.org/10.22146/ijg.68184","url":null,"abstract":"Green open space is one of the most important land uses, especially in densely populated urban areas. Public Green Open Land in each area regulated in Law No. 1 of 2007 is at least 20%. Based on data from the Department of Creative Works, Land and Spatial Planning as well as the Environment Agency of DKI Jakarta, West Jakarta's Green open space asset area is 277.45 Ha of the total area of West Jakarta, which is 12543 Ha. There is a need for a study to determine the potential land for green open space in West Jakarta to catch up on the fulfillment of public green open space based on spatial and regional analysis. One of the GIS-based methods that can be used to determine potential green open space is the decision tree method. This method uses AHP analysis in its formulation based on experts in the relevant agencies. In total there are 8 parameters that influence in determining potential green open space in West Jakarta, namely flood risk, air quality, population, distance to roads, distance to water sources, building density and distance to green open space assets. The modeling results are divided into five classes ranging from very priority to not priority. The total area of land that is much prioritized to be used as green open space is 95.57 hectares spread out. The modeling results show that there are still potential lands to be used as green open spaces in West Jakarta.","PeriodicalId":52460,"journal":{"name":"Indonesian Journal of Geography","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48615114","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A. Wibowo, Tia Pramudyasari, S. Adi, R. Saraswati, I. P. A. Shidiq
Natural and anthropogenic factors, such as volcanic eruptions and land use, are indirect causes of changes in the micro-scale climate. Over the past 30 years, climate change has been detected with increased air surface temperature (AST) above 30.00C, a phenomenon of Urban Heat Island. Therefore, this study aimed to create a spatial model to see changes in AST in Bandar Lampung City from1990 to 2020. The spatial and temporal analysis uses Landsat data to produce land surface temperature (LST) and AST models. The results showed a temperature rise in the LST area, which tends to be the northern part of Bandar Lampung City, by 25.0oC and above for 30 years. Compare LST and AST from two stations between 30 years is 5.00C. In 1990, the LST concentrated on the spatial distribution of the AST model with a temperature above 30.00C, while in 2020, it diffused to the northern part of Bandar Lampung City. The results concluded that the air temperature in the city has warmed up to 0.46OC (+10C), which is in line with the findings of IPPC and various world cities. It is also in occurrence with the UHI phenomenon since 2014 that climate change is part of mitigation.
{"title":"30-Year Spatial-Temporal Analysis of Air Surface Temperature as Climate Change Mitigation","authors":"A. Wibowo, Tia Pramudyasari, S. Adi, R. Saraswati, I. P. A. Shidiq","doi":"10.22146/ijg.73460","DOIUrl":"https://doi.org/10.22146/ijg.73460","url":null,"abstract":"Natural and anthropogenic factors, such as volcanic eruptions and land use, are indirect causes of changes in the micro-scale climate. Over the past 30 years, climate change has been detected with increased air surface temperature (AST) above 30.00C, a phenomenon of Urban Heat Island. Therefore, this study aimed to create a spatial model to see changes in AST in Bandar Lampung City from1990 to 2020. The spatial and temporal analysis uses Landsat data to produce land surface temperature (LST) and AST models. The results showed a temperature rise in the LST area, which tends to be the northern part of Bandar Lampung City, by 25.0oC and above for 30 years. Compare LST and AST from two stations between 30 years is 5.00C. In 1990, the LST concentrated on the spatial distribution of the AST model with a temperature above 30.00C, while in 2020, it diffused to the northern part of Bandar Lampung City. The results concluded that the air temperature in the city has warmed up to 0.46OC (+10C), which is in line with the findings of IPPC and various world cities. It is also in occurrence with the UHI phenomenon since 2014 that climate change is part of mitigation.","PeriodicalId":52460,"journal":{"name":"Indonesian Journal of Geography","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42894037","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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