Pub Date : 2019-08-01DOI: 10.23917/FORGEO.V33I1.7592
Sudaryatno Sudaryatno, P. Widayani, T. W. Wibowo, Bagus Wiratmoko, Wahyu Nurbandi
Purworejo District, which is located in Central Java, Indonesia, is prone to landslides. These are a natural hazard that often occur in mountainous areas, so landslide hazard analysis is needed to develop mitigation strategies. This paper elaborates on the use of an evidence-based statistical approach using the Information Value Model (IVM) to conduct landslide hazard mapping. The parameters of slope, aspect, elevation, rainfall, NDVI, distance from rivers, distance from the road network, and distance from faults were employed for the analysis, which was conducted based on a raster data environment, since the pixel is the most appropriate means to represent continuous data. Landslide evidence data were collected by combining secondary data and interpreting satellite imagery to identify old landslides. The IVM was successfully calculated by combining factors related to disposition to landslides and data on 19 landslide occurrences. The results helped produce a landslide susceptibility map for the northern and eastern parts of Purworejo District.
位于印度尼西亚中爪哇的Purworejo地区容易发生山体滑坡。这是一种经常发生在山区的自然灾害，因此需要进行滑坡危害分析以制定减灾战略。本文详细阐述了利用信息价值模型(Information Value Model, IVM)进行滑坡灾害制图的循证统计方法。分析采用坡度、坡向、高程、降雨量、NDVI、河流距离、路网距离、断层距离等参数，基于栅格数据环境进行分析，因为像素是表示连续数据最合适的手段。利用二次数据和卫星图像解译相结合的方法收集滑坡证据数据，识别老滑坡。结合滑坡处置相关因素和19次滑坡发生的数据，成功地计算出了IVM。这些结果帮助绘制了普尔沃雷霍区北部和东部的滑坡易感性图。
{"title":"Evidence Based Landslide Hazard Mapping in Purworejo using Information Value Model Approach","authors":"Sudaryatno Sudaryatno, P. Widayani, T. W. Wibowo, Bagus Wiratmoko, Wahyu Nurbandi","doi":"10.23917/FORGEO.V33I1.7592","DOIUrl":"https://doi.org/10.23917/FORGEO.V33I1.7592","url":null,"abstract":"Purworejo District, which is located in Central Java, Indonesia, is prone to landslides. These are a natural hazard that often occur in mountainous areas, so landslide hazard analysis is needed to develop mitigation strategies. This paper elaborates on the use of an evidence-based statistical approach using the Information Value Model (IVM) to conduct landslide hazard mapping. The parameters of slope, aspect, elevation, rainfall, NDVI, distance from rivers, distance from the road network, and distance from faults were employed for the analysis, which was conducted based on a raster data environment, since the pixel is the most appropriate means to represent continuous data. Landslide evidence data were collected by combining secondary data and interpreting satellite imagery to identify old landslides. The IVM was successfully calculated by combining factors related to disposition to landslides and data on 19 landslide occurrences. The results helped produce a landslide susceptibility map for the northern and eastern parts of Purworejo District.","PeriodicalId":31244,"journal":{"name":"Forum Geografi","volume":"65 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83956591","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}
Pub Date : 2019-08-01DOI: 10.23917/FORGEO.V33I1.7795
Dodi Widiyanto
This paper attempts to unveil the hidden potential of the local food through local food mapping, drawing local food potential based on the “triple burden” theory from Professor Moerdijati Gardjito. An index, called “index of food relocalisation” is adopted and then modified into different name called local food index due to data availability, which is expected to provide a geographical location of the local food potential by proposing a research questions: where do the local food potentials distribute in Yogyakarta Special Province, and why the local food potentials located in that particular area(s)? The findings show that Gunungkidul and Kulonprogo are two potential regencies with their local food crops availabilities This finding is accompanied by an explanation from the analysis from the agroecological subzone and spatial income distribution of paddy and second crops, production activities.
{"title":"Local Food Potentials and Agroecology in Yogyakarta Special Province, Indonesia","authors":"Dodi Widiyanto","doi":"10.23917/FORGEO.V33I1.7795","DOIUrl":"https://doi.org/10.23917/FORGEO.V33I1.7795","url":null,"abstract":"This paper attempts to unveil the hidden potential of the local food through local food mapping, drawing local food potential based on the “triple burden” theory from Professor Moerdijati Gardjito. An index, called “index of food relocalisation” is adopted and then modified into different name called local food index due to data availability, which is expected to provide a geographical location of the local food potential by proposing a research questions: where do the local food potentials distribute in Yogyakarta Special Province, and why the local food potentials located in that particular area(s)? The findings show that Gunungkidul and Kulonprogo are two potential regencies with their local food crops availabilities This finding is accompanied by an explanation from the analysis from the agroecological subzone and spatial income distribution of paddy and second crops, production activities.","PeriodicalId":31244,"journal":{"name":"Forum Geografi","volume":"39 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85796343","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}
Pub Date : 2019-08-01DOI: 10.23917/FORGEO.V33I1.8021
T. W. Wibowo, A. Bustomi, A. Sukamdi
The development of tourist attractions is now highly influenced by social media. The speed at which information can be disseminated via the Internet has become an essential factor in enabling distinct tourist attractions to potentially gain high popularity in a relatively short time. This condition was not as prevalent several years ago when tourism promotion remained limited to a certain kind of media. As a consequence, rapid change in the relative popularity of tourist attractions is inevitable. Against this, knowledge of tourist attraction hotspots is essential in tourism management. This means there is a need to study how to both quickly determine the popularity level of tourist attractions and encompass a relatively large area. This article utilised tweet data from microblogging website Twitter as the basis from which to determine the popularity level of a tourist attraction. Data mining was conducted using Python and the Tweepy module. The tweet data were collected at the end of April and early May 2017, at times when there are several long holiday weekends. A Tweet Proximity Index (TPI) was used to calculate both the density and frequency of tweets based on a defined search radius. A Density Index (DI) was also used as a technique for determining the popularity. The results from both approaches were then compared to a random survey about people’s perceptions of tourist attractions in the study area. The result shows that geotagged tweet data can be used to determine the popularity of a tourist attraction, although it still only achieved a medium level of accuracy. The TPI approach used in this study produced an accuracy of 76.47%, while the DI achieved only 58.82%. This medium accuracy does indicate that the two approaches are not yet strong enough to be used for decision-making but should be more than adequate as an initial description. Further, it is necessary to improve the method of indexing and the exploration of other aspects of Twitter data.
{"title":"Tourist Attraction Popularity Mapping based on Geotagged Tweets","authors":"T. W. Wibowo, A. Bustomi, A. Sukamdi","doi":"10.23917/FORGEO.V33I1.8021","DOIUrl":"https://doi.org/10.23917/FORGEO.V33I1.8021","url":null,"abstract":"The development of tourist attractions is now highly influenced by social media. The speed at which information can be disseminated via the Internet has become an essential factor in enabling distinct tourist attractions to potentially gain high popularity in a relatively short time. This condition was not as prevalent several years ago when tourism promotion remained limited to a certain kind of media. As a consequence, rapid change in the relative popularity of tourist attractions is inevitable. Against this, knowledge of tourist attraction hotspots is essential in tourism management. This means there is a need to study how to both quickly determine the popularity level of tourist attractions and encompass a relatively large area. This article utilised tweet data from microblogging website Twitter as the basis from which to determine the popularity level of a tourist attraction. Data mining was conducted using Python and the Tweepy module. The tweet data were collected at the end of April and early May 2017, at times when there are several long holiday weekends. A Tweet Proximity Index (TPI) was used to calculate both the density and frequency of tweets based on a defined search radius. A Density Index (DI) was also used as a technique for determining the popularity. The results from both approaches were then compared to a random survey about people’s perceptions of tourist attractions in the study area. The result shows that geotagged tweet data can be used to determine the popularity of a tourist attraction, although it still only achieved a medium level of accuracy. The TPI approach used in this study produced an accuracy of 76.47%, while the DI achieved only 58.82%. This medium accuracy does indicate that the two approaches are not yet strong enough to be used for decision-making but should be more than adequate as an initial description. Further, it is necessary to improve the method of indexing and the exploration of other aspects of Twitter data.","PeriodicalId":31244,"journal":{"name":"Forum Geografi","volume":"29 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87087161","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}
Pub Date : 2019-08-01DOI: 10.23917/FORGEO.V33I1.7499
D. Auliyani, T. M. Basuki, W. W. Wijaya
One of the drawbacks of developing plants for the rehabilitation of degraded land in Indonesia is the relative lack of information about species that are suited to the local conditions. Therefore, spatial information on land degradation and the plants suitable for rehabilitation is crucial. The objectives of this study were to map the susceptibility of land to degradation and to identify some alternative species for its rehabilitation. The research was conducted in Jang Watershed, Bintan Island, Kepulauan Riau Province, Indonesia. A quick assessment of land degradation was carried out to classify the degree of land susceptibility. The land suitability evaluation was conducted manually by matching the existing biophysical condition and plant growth requirements using a geographic information system. This analysis was applied for annual plants, such as Acacia mangium, Durio zibethinus, Artocarpus champeden, Theobroma cacao and Hevea brassiliensis. Furthermore, the maps of land susceptibility to degradation and species suitability were overlaid and the result was used to provide recommendations for rehabilitating the degraded land. This study showed that 22% of the Jang Watershed area can be categorised as highly susceptible to degradation. The suitability analysis illustrated that 59% of the degraded areas were suitable for Acacia mangium. The planting of fast-growing species such as Acacia mangium is expected to improve the physical, chemical and biological properties of the soil.
{"title":"Spatial Analysis of Land Degradation Susceptibility and Alternative Plants for Its Rehabilitation","authors":"D. Auliyani, T. M. Basuki, W. W. Wijaya","doi":"10.23917/FORGEO.V33I1.7499","DOIUrl":"https://doi.org/10.23917/FORGEO.V33I1.7499","url":null,"abstract":"One of the drawbacks of developing plants for the rehabilitation of degraded land in Indonesia is the relative lack of information about species that are suited to the local conditions. Therefore, spatial information on land degradation and the plants suitable for rehabilitation is crucial. The objectives of this study were to map the susceptibility of land to degradation and to identify some alternative species for its rehabilitation. The research was conducted in Jang Watershed, Bintan Island, Kepulauan Riau Province, Indonesia. A quick assessment of land degradation was carried out to classify the degree of land susceptibility. The land suitability evaluation was conducted manually by matching the existing biophysical condition and plant growth requirements using a geographic information system. This analysis was applied for annual plants, such as Acacia mangium, Durio zibethinus, Artocarpus champeden, Theobroma cacao and Hevea brassiliensis. Furthermore, the maps of land susceptibility to degradation and species suitability were overlaid and the result was used to provide recommendations for rehabilitating the degraded land. This study showed that 22% of the Jang Watershed area can be categorised as highly susceptible to degradation. The suitability analysis illustrated that 59% of the degraded areas were suitable for Acacia mangium. The planting of fast-growing species such as Acacia mangium is expected to improve the physical, chemical and biological properties of the soil.","PeriodicalId":31244,"journal":{"name":"Forum Geografi","volume":"15 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78310349","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}
Pub Date : 2019-08-01DOI: 10.23917/FORGEO.V33I1.7551
Christopher A. Gomez, D. Hart, P. Wassmer, Imai Kenta, H. Matsui, Mariko Shimizu
The question of whether or not we agree with the term Anthropocene becomes inconsequential when examining coastal environments. With few exceptions, anthropogenic encroachment on, and reshaping of, the global coastal zone is evident from space via multiple spectral views. Humans have become one of the dominant agents of coastal system change during the latest part of their relatively short existence, and nowhere is the humanization of coastal landscapes more evident than on islands. Using three island nations characterized by different stages and styles of coastal development – New Zealand, Japan, and Indonesia - we investigate the role of anthropogenic activity in coastal evolution, geomorphology and sediment records. Using field investigations, Geographical Information System (GIS) analyses, and mathematical and conceptual models, we reveals how anthropogenic activity influences processes at multiple time and space scales, with enduring effects. Our first anthropogenic impact investigation focusses on the potential effects of sea level rise (SLR) due to anthropogenic climate change. Using the earthquake-induced land-subsidence experienced in Christchurch, New Zealand, as a relative SLR example (‘Laboratory Christchurch’), evidence shows that coastal settlements are likely to be impacted not only at the shore but further inland via coast- connected waterways, where drainage is impeded due to an increase in the base level of that is the sea. Relative SLR makes it more difficult to evacuate water from subaerial and subsurface hydrosystems, and simulations show that future SLR is also likely to temporarily reduce some rivermouth sediment discharges, creating the potential for accelerated erosion in river-coast interface environments. In addition to flow-on effects from waterways, coastlines themselves have been highly affected by human activity over recent decades to centuries. In Tokyo, the shoreline has undergone artificial progradation, in places by more than 2 km, where concrete has supplanted mudflats, often at elevations above the hinterland of reclaimed areas. In addition to changes in Tokyo’s unconsolidated shores, consolidated coastal cliffs have been modified with the removal of natural talus buffers, again increasing the potential for erosion acceleration. Finally, in our third example, studies of the 2004 Indian Ocean tsunami and the 2011 Tohoku tsunami show that anthropogenic activities and structures play an important role in controlling the erosion and depostion of sediments during extreme events. A chronology of tsunami deposits from the Tohoku coast shows that sedimentary records from tsunami events have become thinner in recent centuries, independent of the incident tsunami wave hydrodynamics, and in relation to increasing levels of coastal plain, shoreline and nearshore development. In light of these multi-scale and multi-process effects, we argue that the Anthropocene is clearly distinguishable from the Holocene in coastal envir
{"title":"Coastal Evolution, Geomorphic Processes and Sedimentary Records in the Anthropocene","authors":"Christopher A. Gomez, D. Hart, P. Wassmer, Imai Kenta, H. Matsui, Mariko Shimizu","doi":"10.23917/FORGEO.V33I1.7551","DOIUrl":"https://doi.org/10.23917/FORGEO.V33I1.7551","url":null,"abstract":"The question of whether or not we agree with the term Anthropocene becomes inconsequential when examining coastal environments. With few exceptions, anthropogenic encroachment on, and reshaping of, the global coastal zone is evident from space via multiple spectral views. Humans have become one of the dominant agents of coastal system change during the latest part of their relatively short existence, and nowhere is the humanization of coastal landscapes more evident than on islands. Using three island nations characterized by different stages and styles of coastal development – New Zealand, Japan, and Indonesia - we investigate the role of anthropogenic activity in coastal evolution, geomorphology and sediment records. Using field investigations, Geographical Information System (GIS) analyses, and mathematical and conceptual models, we reveals how anthropogenic activity influences processes at multiple time and space scales, with enduring effects. Our first anthropogenic impact investigation focusses on the potential effects of sea level rise (SLR) due to anthropogenic climate change. Using the earthquake-induced land-subsidence experienced in Christchurch, New Zealand, as a relative SLR example (‘Laboratory Christchurch’), evidence shows that coastal settlements are likely to be impacted not only at the shore but further inland via coast- connected waterways, where drainage is impeded due to an increase in the base level of that is the sea. Relative SLR makes it more difficult to evacuate water from subaerial and subsurface hydrosystems, and simulations show that future SLR is also likely to temporarily reduce some rivermouth sediment discharges, creating the potential for accelerated erosion in river-coast interface environments. In addition to flow-on effects from waterways, coastlines themselves have been highly affected by human activity over recent decades to centuries. In Tokyo, the shoreline has undergone artificial progradation, in places by more than 2 km, where concrete has supplanted mudflats, often at elevations above the hinterland of reclaimed areas. In addition to changes in Tokyo’s unconsolidated shores, consolidated coastal cliffs have been modified with the removal of natural talus buffers, again increasing the potential for erosion acceleration. Finally, in our third example, studies of the 2004 Indian Ocean tsunami and the 2011 Tohoku tsunami show that anthropogenic activities and structures play an important role in controlling the erosion and depostion of sediments during extreme events. A chronology of tsunami deposits from the Tohoku coast shows that sedimentary records from tsunami events have become thinner in recent centuries, independent of the incident tsunami wave hydrodynamics, and in relation to increasing levels of coastal plain, shoreline and nearshore development. In light of these multi-scale and multi-process effects, we argue that the Anthropocene is clearly distinguishable from the Holocene in coastal envir","PeriodicalId":31244,"journal":{"name":"Forum Geografi","volume":"49 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88396751","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}
Pub Date : 2019-08-01DOI: 10.23917/FORGEO.V33I1.6803
S. F. Shalihati, Esti Sarjanti
The occurrence of animal accidents is one of the consequences of physical environmental interaction of animal in terms of their movement from one place to another and non physical environment in the form of transportation usage by human. Accidents happened to animals can affect the structure of the food chain. It would be a matter if it occurred continuously because some species of animals that were important to the ecosystem would not exist anymore. The records of the frequency of animal accident and habitat along Jalan Padamara-Karangcegak by geospatial could be used to analyze the correlation between the dominance of animal species getting the accidents and the potential width of the habitat owned along the road. Qualitative description was used as the method of the research. It was from the primary data analysis of the distribution of accident and secondary data of the land use from Google Earth of satellite image which was then processed by Geographic Information System. The results obtained during observations from April to July 2016 showed that there was a correlation between the animal habitat and the accidents happened. The animal with a wider habitat dominated the accidents occurred than animals with no extensive habitat.
{"title":"Analysis of Animal Accidents along the Road of Padamara-Karangcegak in Geospatial Perspective","authors":"S. F. Shalihati, Esti Sarjanti","doi":"10.23917/FORGEO.V33I1.6803","DOIUrl":"https://doi.org/10.23917/FORGEO.V33I1.6803","url":null,"abstract":"The occurrence of animal accidents is one of the consequences of physical environmental interaction of animal in terms of their movement from one place to another and non physical environment in the form of transportation usage by human. Accidents happened to animals can affect the structure of the food chain. It would be a matter if it occurred continuously because some species of animals that were important to the ecosystem would not exist anymore. The records of the frequency of animal accident and habitat along Jalan Padamara-Karangcegak by geospatial could be used to analyze the correlation between the dominance of animal species getting the accidents and the potential width of the habitat owned along the road. Qualitative description was used as the method of the research. It was from the primary data analysis of the distribution of accident and secondary data of the land use from Google Earth of satellite image which was then processed by Geographic Information System. The results obtained during observations from April to July 2016 showed that there was a correlation between the animal habitat and the accidents happened. The animal with a wider habitat dominated the accidents occurred than animals with no extensive habitat.","PeriodicalId":31244,"journal":{"name":"Forum Geografi","volume":"49 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76406925","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}
Pub Date : 2018-12-20DOI: 10.23917/FORGEO.V32I2.6958
D. Danardono, Eko Bayu Dharma Putra, E. Haryono, E. Nurjani, M. I. T. Sunariya
Increased of the number of visitor at Gelatik Cave is a challenge in terms of cave management. In natural conditions, Caves are vulnerable with environmental changes especially microclimates condition. The change of microclimate inside the cave can destruct cave ornaments.Therefore, it is necessary to calculate the cave carrying capacity with microclimates as the main parameter. This research aims to (1) explore the daily variation of speleoclimate in Gelatik Cave Tourism and (2) analyze the cave tourism capacity in Gelatik Cave. Microclimate parameter that was measured in this research was temperature, relative humidity, and carbon dioxide inside the cave. Measurement of microlimate parameter was carried out automatically for 24 hours during peak season in December 2017 and low season in May 2018. Cave tourism capacity was measured using Lobo method (Lobo, 2015). The results showed that temperature, relative humidity, and carbon dioxide in the Gelatik Cave varry due to tourism activities. The most sensitive parameter is the carbon dioxide concentration inside the cave. The maximum of tourists allowed to visit Gelatik Cave is 76 visitors/ day during holidays and working days. Meanwhile, the maximum time of stay accepted for a particular area inside Gelatik Cave is 17 minutes 10 seconds during weekdays and 12 minutes 53 seconds during the holiday season.
{"title":"Speleoclimate Monitoring to Assess Cave Tourism Capacity in Gelatik Cave, Gunungsewu Geopark, Indonesia","authors":"D. Danardono, Eko Bayu Dharma Putra, E. Haryono, E. Nurjani, M. I. T. Sunariya","doi":"10.23917/FORGEO.V32I2.6958","DOIUrl":"https://doi.org/10.23917/FORGEO.V32I2.6958","url":null,"abstract":"Increased of the number of visitor at Gelatik Cave is a challenge in terms of cave management. In natural conditions, Caves are vulnerable with environmental changes especially microclimates condition. The change of microclimate inside the cave can destruct cave ornaments.Therefore, it is necessary to calculate the cave carrying capacity with microclimates as the main parameter. This research aims to (1) explore the daily variation of speleoclimate in Gelatik Cave Tourism and (2) analyze the cave tourism capacity in Gelatik Cave. Microclimate parameter that was measured in this research was temperature, relative humidity, and carbon dioxide inside the cave. Measurement of microlimate parameter was carried out automatically for 24 hours during peak season in December 2017 and low season in May 2018. Cave tourism capacity was measured using Lobo method (Lobo, 2015). The results showed that temperature, relative humidity, and carbon dioxide in the Gelatik Cave varry due to tourism activities. The most sensitive parameter is the carbon dioxide concentration inside the cave. The maximum of tourists allowed to visit Gelatik Cave is 76 visitors/ day during holidays and working days. Meanwhile, the maximum time of stay accepted for a particular area inside Gelatik Cave is 17 minutes 10 seconds during weekdays and 12 minutes 53 seconds during the holiday season.","PeriodicalId":31244,"journal":{"name":"Forum Geografi","volume":"55 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84223952","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}
Pub Date : 2018-11-26DOI: 10.23917/FORGEO.V32I2.6288
Fatkhuroyan Fatkhuroyan, T. Wati, Alfan Sukmana, Roni Kurniawan
Rainfall is the most important factor in the Earth’s water and energy cycles. The aim of this research is to evaluate the accuracy of Global Satellite Mapping of Rainfall (GSMaP) data by referencing daily rain-gauged rainfall measurements across the Indonesian Maritime Continent. We compare the daily rainfall data from GSMaP Moving Kalman Filter (MVK) to readings from 152 rain-gauge observation stations across Indonesia from March 2014 to December 2017. The results show that the correlation coefficient (CC) provides better validation in the rainy season while root mean square error (RMSE) is more accurate in the dry season. The highest proportion correct (PC) value is obtained for Bali-NTT, while the highest probability of detection (POD) and false alarm ratio (FAR) values are obtained for Kalimantan. GSMaP-MVK data is over-estimated compared to observations in Indonesia, with the mean accuracy for daily rainfall estimation being 85.47% in 2014, 85.74% in 2015, 82.73 in 2016, and 82.59% in 2017.
{"title":"Validation of Satellite Daily Rainfall Estimates Over Indonesia","authors":"Fatkhuroyan Fatkhuroyan, T. Wati, Alfan Sukmana, Roni Kurniawan","doi":"10.23917/FORGEO.V32I2.6288","DOIUrl":"https://doi.org/10.23917/FORGEO.V32I2.6288","url":null,"abstract":"Rainfall is the most important factor in the Earth’s water and energy cycles. The aim of this research is to evaluate the accuracy of Global Satellite Mapping of Rainfall (GSMaP) data by referencing daily rain-gauged rainfall measurements across the Indonesian Maritime Continent. We compare the daily rainfall data from GSMaP Moving Kalman Filter (MVK) to readings from 152 rain-gauge observation stations across Indonesia from March 2014 to December 2017. The results show that the correlation coefficient (CC) provides better validation in the rainy season while root mean square error (RMSE) is more accurate in the dry season. The highest proportion correct (PC) value is obtained for Bali-NTT, while the highest probability of detection (POD) and false alarm ratio (FAR) values are obtained for Kalimantan. GSMaP-MVK data is over-estimated compared to observations in Indonesia, with the mean accuracy for daily rainfall estimation being 85.47% in 2014, 85.74% in 2015, 82.73 in 2016, and 82.59% in 2017.","PeriodicalId":31244,"journal":{"name":"Forum Geografi","volume":"156 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85403111","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}
Pub Date : 2018-11-26DOI: 10.23917/FORGEO.V32I2.6226
Ida Pramuwardani, H. Hartono, S. Sunarto, A. Sopaheluwakan
In this study, geographical Madden–Julian oscillation (MJO) propagation in association with precipitation rate was obtained using lag correlation applied to empirical orthogonal function (EOF) analysis modes 1 and 2 of filtered MJO data. The precipitation rate over Indonesia was provided at day -10 through day +10 in five-day steps during the December, January, and February (DJF) Western North Pacific (WNP) and July, August and September (JAS) Australian (AU) monsoon phases. Connection with local atmospheric factors was then sought through comparison of local precipitation, represented by 3-hourly precipitation, and dynamical processes, represented by multilevel wind, at seven locations across Indonesia. The results show a global MJO contribution toward local-scale phenomena in Tangerang, Surabaya, and Makassar during the DJF-WNP monsoon phase and in Padang, Medan, Surabaya, Makassar, and Kupang during the JAS-AU monsoon phase. Meanwhile, a lack of MJO contribution toward local factors is presumably due to other local through wider atmospheric-scale phenomena which are suspected to have more influence, particularly in Medan, Padang, Manado, and Kupang during the DJF-WNP monsoon phase, and in Manado and Tangerang during the JAS-AU monsoon phase. This research uses a dataset of 15-year series of daily and three-hourly Tropical Rainfall Measuring Mission (TRMM) (3B42 V7 derived) measurements, 850 hPa zonal wind measurements from 30-year reanalysis data from the ERA-Interim reanalysis dataset, and a 15-year series of 12-hourly observational soundings data from seven stations of the Indonesian Meteorological Climatological and Geophysical Agency (BMKG).
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