Pub Date : 2020-07-02DOI: 10.1080/17489725.2020.1817582
Fahad Al-homayani, M. Mahoor
ABSTRACT Outdoor positioning systems based on the Global Navigation Satellite System have several shortcomings that have deemed their use for indoor positioning impractical. Location fingerprinting, which utilizes machine learning, has emerged as a viable method and solution for indoor positioning due to its simple concept and accurate performance. In the past, shallow learning algorithms were traditionally used in location fingerprinting. Recently, the research community started utilizing deep learning methods for fingerprinting after witnessing the great success and superiority these methods have over traditional/shallow machine learning algorithms. This paper provides a comprehensive review of deep learning methods in indoor positioning. First, the advantages and disadvantages of various fingerprint types for indoor positioning are discussed. The solutions proposed in the literature are then analyzed, categorized, and compared against various performance evaluation metrics. Since data is key in fingerprinting, a detailed review of publicly available indoor positioning datasets is presented. While incorporating deep learning into fingerprinting has resulted in significant improvements, doing so, has also introduced new challenges. These challenges along with the common implementation pitfalls are discussed. Finally, the paper is concluded with some remarks as well as future research trends.
{"title":"Deep learning methods for fingerprint-based indoor positioning: a review","authors":"Fahad Al-homayani, M. Mahoor","doi":"10.1080/17489725.2020.1817582","DOIUrl":"https://doi.org/10.1080/17489725.2020.1817582","url":null,"abstract":"ABSTRACT Outdoor positioning systems based on the Global Navigation Satellite System have several shortcomings that have deemed their use for indoor positioning impractical. Location fingerprinting, which utilizes machine learning, has emerged as a viable method and solution for indoor positioning due to its simple concept and accurate performance. In the past, shallow learning algorithms were traditionally used in location fingerprinting. Recently, the research community started utilizing deep learning methods for fingerprinting after witnessing the great success and superiority these methods have over traditional/shallow machine learning algorithms. This paper provides a comprehensive review of deep learning methods in indoor positioning. First, the advantages and disadvantages of various fingerprint types for indoor positioning are discussed. The solutions proposed in the literature are then analyzed, categorized, and compared against various performance evaluation metrics. Since data is key in fingerprinting, a detailed review of publicly available indoor positioning datasets is presented. While incorporating deep learning into fingerprinting has resulted in significant improvements, doing so, has also introduced new challenges. These challenges along with the common implementation pitfalls are discussed. Finally, the paper is concluded with some remarks as well as future research trends.","PeriodicalId":44932,"journal":{"name":"Journal of Location Based Services","volume":"14 1","pages":"129 - 200"},"PeriodicalIF":2.3,"publicationDate":"2020-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/17489725.2020.1817582","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48688129","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 : 2020-07-02DOI: 10.1080/17489725.2020.1823497
I. Kveladze, N. Agerholm
ABSTRACT Arterial roads have operational significance and play a substantial role in the mobility of modern society. They make up the majority of road network in urban and rural areas and allow high-speed movement despite traffic-controlling elements. In densely populated areas where the presence of Vulnerable Road Users (VRUs) is high, high-speed movement is problematic, and speed calming measures are needed to improve traffic safety, since many VRUs do crossroads, regardless of the road network regulations. These aspects have been researched in the traffic domain in a small scale, and not much has been investigated from a visualisation perspective. To provide comprehensive insights on the movement characteristics of arterial roads, we propose a GeoVisual Analytics (GVA) approach. GVA techniques are suitable solutions to display and extract knowledge from large amounts of Floating Car Data (FCD) collected through on-board devices of vehicles. By cross-sector collaboration between cartographic and traffic experts, five arterial road segments in Aalborg City were selected to answer where and when in particular VRUs do cross streets by ignoring traffic rules. Based on clusters of large unexplainable deviations from driving speed in FCD, the results uncovered meaningful patterns from complex traffic movements. They also allowed for the provision of some recommendations that are critical for traffic safety in urban areas.
{"title":"GeoVisual analytics for understanding the distribution of speeding patterns on arterial roads: assessing the traffic safety of vulnerable road users","authors":"I. Kveladze, N. Agerholm","doi":"10.1080/17489725.2020.1823497","DOIUrl":"https://doi.org/10.1080/17489725.2020.1823497","url":null,"abstract":"ABSTRACT Arterial roads have operational significance and play a substantial role in the mobility of modern society. They make up the majority of road network in urban and rural areas and allow high-speed movement despite traffic-controlling elements. In densely populated areas where the presence of Vulnerable Road Users (VRUs) is high, high-speed movement is problematic, and speed calming measures are needed to improve traffic safety, since many VRUs do crossroads, regardless of the road network regulations. These aspects have been researched in the traffic domain in a small scale, and not much has been investigated from a visualisation perspective. To provide comprehensive insights on the movement characteristics of arterial roads, we propose a GeoVisual Analytics (GVA) approach. GVA techniques are suitable solutions to display and extract knowledge from large amounts of Floating Car Data (FCD) collected through on-board devices of vehicles. By cross-sector collaboration between cartographic and traffic experts, five arterial road segments in Aalborg City were selected to answer where and when in particular VRUs do cross streets by ignoring traffic rules. Based on clusters of large unexplainable deviations from driving speed in FCD, the results uncovered meaningful patterns from complex traffic movements. They also allowed for the provision of some recommendations that are critical for traffic safety in urban areas.","PeriodicalId":44932,"journal":{"name":"Journal of Location Based Services","volume":"14 1","pages":"201 - 230"},"PeriodicalIF":2.3,"publicationDate":"2020-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/17489725.2020.1823497","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46268714","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 : 2020-04-02DOI: 10.1080/17489725.2020.1805521
K. Nguyen, Zhiyuan Luo, C. Watkins
ABSTRACT Contact tracing is widely considered as an effective procedure in the fight against epidemic diseases. However, one of the challenges for technology based contact tracing is the high number of false positives, questioning its trust-worthiness and efficiency amongst the wider population for mass adoption. To this end, this paper proposes a novel, yet practical smartphone-based contact tracing approach, employing WiFi and acoustic sound for relative distance estimate, in addition to the air pressure and the magnetic field for ambient environment matching. We present a model combining six smartphone sensors, prioritising some of them when certain conditions are met. We empirically verified our approach in various realistic environments to demonstrate an achievement of up to 95% fewer false positives, and 62% more accurate than Bluetooth-only system. To the best of our knowledge, this paper was one of the first work to propose a combination of smartphone sensors for contact tracing.
{"title":"Epidemic contact tracing with smartphone sensors","authors":"K. Nguyen, Zhiyuan Luo, C. Watkins","doi":"10.1080/17489725.2020.1805521","DOIUrl":"https://doi.org/10.1080/17489725.2020.1805521","url":null,"abstract":"ABSTRACT Contact tracing is widely considered as an effective procedure in the fight against epidemic diseases. However, one of the challenges for technology based contact tracing is the high number of false positives, questioning its trust-worthiness and efficiency amongst the wider population for mass adoption. To this end, this paper proposes a novel, yet practical smartphone-based contact tracing approach, employing WiFi and acoustic sound for relative distance estimate, in addition to the air pressure and the magnetic field for ambient environment matching. We present a model combining six smartphone sensors, prioritising some of them when certain conditions are met. We empirically verified our approach in various realistic environments to demonstrate an achievement of up to 95% fewer false positives, and 62% more accurate than Bluetooth-only system. To the best of our knowledge, this paper was one of the first work to propose a combination of smartphone sensors for contact tracing.","PeriodicalId":44932,"journal":{"name":"Journal of Location Based Services","volume":"14 1","pages":"128 - 92"},"PeriodicalIF":2.3,"publicationDate":"2020-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/17489725.2020.1805521","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47999475","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 : 2020-04-02DOI: 10.1080/17489725.2020.1811409
Stéphane Roche
ABSTRACT In response to the current Coronavirus SARS-CoV-2 pandemic, many countries are developing digital strategies for the identification of individuals who have been in contact with infected persons. Those strategies are mainly based on Contact Tracing applications. While the effectiveness of these technologies has not yet been demonstrated, and that their deployment conditions remain socially complex, they raise serious ethical questions. This paper presents an overview of the development of Contact Tracing and, suggests a reflection and possible solutions for their ethical and sustainable deployment through a more active and transparent citizen engagement.
{"title":"Smile, you’re being traced! Some thoughts about the ethical issues of digital contact tracing applications","authors":"Stéphane Roche","doi":"10.1080/17489725.2020.1811409","DOIUrl":"https://doi.org/10.1080/17489725.2020.1811409","url":null,"abstract":"ABSTRACT In response to the current Coronavirus SARS-CoV-2 pandemic, many countries are developing digital strategies for the identification of individuals who have been in contact with infected persons. Those strategies are mainly based on Contact Tracing applications. While the effectiveness of these technologies has not yet been demonstrated, and that their deployment conditions remain socially complex, they raise serious ethical questions. This paper presents an overview of the development of Contact Tracing and, suggests a reflection and possible solutions for their ethical and sustainable deployment through a more active and transparent citizen engagement.","PeriodicalId":44932,"journal":{"name":"Journal of Location Based Services","volume":"14 1","pages":"71 - 91"},"PeriodicalIF":2.3,"publicationDate":"2020-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/17489725.2020.1811409","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43851233","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 : 2020-04-02DOI: 10.1080/17489725.2020.1788184
S. Akdag, Ahu Ergen
ABSTRACT In the age of globalisation and high competition among destinations, cities are empowered with new marketing tools to attract new residents and visitors while keeping their existing communities satisfied. Therefore, the main objective of the paper is to understand the role of location-based mobile applications among university students, who as members of the wired generation tend to use technology more than older generations. The secondary objective is to explore the most preferred location-based apps with their benefits and how they are used by the students to link themselves to the city and its services. Two focus groups are conducted with university students in Besiktas, which is claimed to be one of the most student-friendly environments in Istanbul. The findings reveal students’ preferences and reasoning for the use of location-based mobile apps. Apart from their satisfaction with the diversity of shopping, wayfinding, and geosocial networking apps, their concerns for digital privacy and personal data protection have become apparent. Further research is recommended for understanding the satisfaction and expectations of different user segments in the city since their evaluations might contribute to further develop and improve location-based services, and promote the city in the local and global markets.
{"title":"Role of location-based mobile apps in city marketing: Beşiktaş as a student-friendly district","authors":"S. Akdag, Ahu Ergen","doi":"10.1080/17489725.2020.1788184","DOIUrl":"https://doi.org/10.1080/17489725.2020.1788184","url":null,"abstract":"ABSTRACT In the age of globalisation and high competition among destinations, cities are empowered with new marketing tools to attract new residents and visitors while keeping their existing communities satisfied. Therefore, the main objective of the paper is to understand the role of location-based mobile applications among university students, who as members of the wired generation tend to use technology more than older generations. The secondary objective is to explore the most preferred location-based apps with their benefits and how they are used by the students to link themselves to the city and its services. Two focus groups are conducted with university students in Besiktas, which is claimed to be one of the most student-friendly environments in Istanbul. The findings reveal students’ preferences and reasoning for the use of location-based mobile apps. Apart from their satisfaction with the diversity of shopping, wayfinding, and geosocial networking apps, their concerns for digital privacy and personal data protection have become apparent. Further research is recommended for understanding the satisfaction and expectations of different user segments in the city since their evaluations might contribute to further develop and improve location-based services, and promote the city in the local and global markets.","PeriodicalId":44932,"journal":{"name":"Journal of Location Based Services","volume":"14 1","pages":"49 - 70"},"PeriodicalIF":2.3,"publicationDate":"2020-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/17489725.2020.1788184","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43244342","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 : 2020-01-02DOI: 10.1080/17489725.2019.1682202
O. Vedernikov, L. Kulik, K. Ramamohanarao
ABSTRACT Hitchhiking is a travel mode characterised by unpredictable travel times involving several possible combinations of lifts on roads. In this paper, we formulate a hitchhiker’s problem and develop a time-dependent stochastic route planning algorithm for hitchhikers. Namely, we introduce a concept of the stochastic time-dependent hitchhiking graph to find hitchhiking strategies with the least expected travel time or maximised reliability. We introduce various heuristics to prune the original hitchhiking graph to improve computational efficiency. We provide a complexity analysis of the problem and evaluate the proposed solution on real-world networks of several countries.
{"title":"Optimal route planning for stochastic time-dependent hitchhiker’s problem","authors":"O. Vedernikov, L. Kulik, K. Ramamohanarao","doi":"10.1080/17489725.2019.1682202","DOIUrl":"https://doi.org/10.1080/17489725.2019.1682202","url":null,"abstract":"ABSTRACT Hitchhiking is a travel mode characterised by unpredictable travel times involving several possible combinations of lifts on roads. In this paper, we formulate a hitchhiker’s problem and develop a time-dependent stochastic route planning algorithm for hitchhikers. Namely, we introduce a concept of the stochastic time-dependent hitchhiking graph to find hitchhiking strategies with the least expected travel time or maximised reliability. We introduce various heuristics to prune the original hitchhiking graph to improve computational efficiency. We provide a complexity analysis of the problem and evaluate the proposed solution on real-world networks of several countries.","PeriodicalId":44932,"journal":{"name":"Journal of Location Based Services","volume":"14 1","pages":"1 - 27"},"PeriodicalIF":2.3,"publicationDate":"2020-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/17489725.2019.1682202","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42448157","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 : 2020-01-02DOI: 10.1080/17489725.2020.1738577
I. Dobraja, M. J. Kraak
ABSTRACT Nowadays large amounts of movement data is available. This makes it important not only to be aware of how to collect and store this data, but also how to visually represent the information to get insights and “read” the story behind data. When visualising origin-destination data, the traditional flow map is the solution most often selected. A single flow map, however, does not necessarily show all the available attribute variables and also tends too clutter quickly.A more appropriate solution is a dashboard. It provides users with summaries of the represented information. Despite the dashboard suitability to support getting insights, current dashboards have some limitations regarding the flexibility of the layout. To overcome these limitations, we introduce adaptability in dashboards. In our case adaptability ensures that users get insights into the component of interest (space, time, or attribute) on 3 levels of detail. Adaptability is initiated by user tasks to resulting in changes in the visualizations of represented information and dashboard interfaces. We illustrate the concept of an adaptable dashboard with two case studies.
{"title":"Principles of dashboard adaptability to get insights into origin-destination data","authors":"I. Dobraja, M. J. Kraak","doi":"10.1080/17489725.2020.1738577","DOIUrl":"https://doi.org/10.1080/17489725.2020.1738577","url":null,"abstract":"ABSTRACT Nowadays large amounts of movement data is available. This makes it important not only to be aware of how to collect and store this data, but also how to visually represent the information to get insights and “read” the story behind data. When visualising origin-destination data, the traditional flow map is the solution most often selected. A single flow map, however, does not necessarily show all the available attribute variables and also tends too clutter quickly.A more appropriate solution is a dashboard. It provides users with summaries of the represented information. Despite the dashboard suitability to support getting insights, current dashboards have some limitations regarding the flexibility of the layout. To overcome these limitations, we introduce adaptability in dashboards. In our case adaptability ensures that users get insights into the component of interest (space, time, or attribute) on 3 levels of detail. Adaptability is initiated by user tasks to resulting in changes in the visualizations of represented information and dashboard interfaces. We illustrate the concept of an adaptable dashboard with two case studies.","PeriodicalId":44932,"journal":{"name":"Journal of Location Based Services","volume":"14 1","pages":"28 - 48"},"PeriodicalIF":2.3,"publicationDate":"2020-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/17489725.2020.1738577","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46199631","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 : 2019-09-16DOI: 10.1080/17489725.2019.1660423
R. Mariescu-Istodor, A. S. Sayem, P. Fränti
ABSTRACT The recommendation problem has been widely studied and researchers are constantly searching for better methods. Recommending events is an even more difficult problem because there is no information such as ratings from past events. In this paper, we introduce a method for recommending activity events: activities hosted by one or more individuals which involve movement: walking, running, cycling, cross-country skiing, and driving to users who have location history such as trajectories, meetings, POI visits, and geo-tagged photos. We tested the method in a real environment in Mopsi platform: http://cs.uef.fi/mopsi/events. Although there are many location-based event recommendation systems in literature, this is to our knowledge the first system that recommends activity events like bicycle and skiing trips. The experiments show that we can predict whether a user is attending the event or not with 80% accuracy, which is significantly better than random chance (50%).
{"title":"Activity event recommendation and attendance prediction","authors":"R. Mariescu-Istodor, A. S. Sayem, P. Fränti","doi":"10.1080/17489725.2019.1660423","DOIUrl":"https://doi.org/10.1080/17489725.2019.1660423","url":null,"abstract":"ABSTRACT The recommendation problem has been widely studied and researchers are constantly searching for better methods. Recommending events is an even more difficult problem because there is no information such as ratings from past events. In this paper, we introduce a method for recommending activity events: activities hosted by one or more individuals which involve movement: walking, running, cycling, cross-country skiing, and driving to users who have location history such as trajectories, meetings, POI visits, and geo-tagged photos. We tested the method in a real environment in Mopsi platform: http://cs.uef.fi/mopsi/events. Although there are many location-based event recommendation systems in literature, this is to our knowledge the first system that recommends activity events like bicycle and skiing trips. The experiments show that we can predict whether a user is attending the event or not with 80% accuracy, which is significantly better than random chance (50%).","PeriodicalId":44932,"journal":{"name":"Journal of Location Based Services","volume":"13 1","pages":"293 - 319"},"PeriodicalIF":2.3,"publicationDate":"2019-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/17489725.2019.1660423","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49531707","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 : 2019-07-01DOI: 10.1080/17489725.2019.1630680
Damla Çay, T. Nagel, A. Yantaç
ABSTRACT For citizens, being aware of what is happening in their urban surroundings becomes challenging as more information from diverse sources becomes available. In this paper, we describe our user-centered approach of designing an interactive tool making use of urban data visualisations to facilitate people’s decisions about social and cultural events. After gathering the needs of urban actors through formative user studies, we identified beneficial data types and collected a variety of data sets from publicly accessible online sources. For the aim of enabling casual exploration of events in the city, we designed a set of geovisualisation prototypes and designed a variety of evaluative user studies based on established geovisualisation techniques. The main aim here is to enable casual exploration of events in the city more than the intended search for specific events. We developed two prototypes that make use of two different geovisualisations to represent events: Prototype A uses common location markers, and prototype B uses a novel glyph design to visualize more types of data at a glance. We share the lessons learned from the results of our study, which will inform the design of geographical data visualisations for citizens.
{"title":"What is happening in the city? A case study for user-centred geovisualisation design","authors":"Damla Çay, T. Nagel, A. Yantaç","doi":"10.1080/17489725.2019.1630680","DOIUrl":"https://doi.org/10.1080/17489725.2019.1630680","url":null,"abstract":"ABSTRACT For citizens, being aware of what is happening in their urban surroundings becomes challenging as more information from diverse sources becomes available. In this paper, we describe our user-centered approach of designing an interactive tool making use of urban data visualisations to facilitate people’s decisions about social and cultural events. After gathering the needs of urban actors through formative user studies, we identified beneficial data types and collected a variety of data sets from publicly accessible online sources. For the aim of enabling casual exploration of events in the city, we designed a set of geovisualisation prototypes and designed a variety of evaluative user studies based on established geovisualisation techniques. The main aim here is to enable casual exploration of events in the city more than the intended search for specific events. We developed two prototypes that make use of two different geovisualisations to represent events: Prototype A uses common location markers, and prototype B uses a novel glyph design to visualize more types of data at a glance. We share the lessons learned from the results of our study, which will inform the design of geographical data visualisations for citizens.","PeriodicalId":44932,"journal":{"name":"Journal of Location Based Services","volume":"13 1","pages":"270 - 292"},"PeriodicalIF":2.3,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/17489725.2019.1630680","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47127434","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 : 2019-06-21DOI: 10.1080/17489725.2019.1619851
T. Aditya, Dany Laksono, Nur Izzahuddin
ABSTRACT Haze over Sumatera and Kalimantan has been a prolonged trans-boundary issue in South East Asia mainly due to setting fire to drained peatland. At present, fire sources (i.e. hotspots) are located based on satellite data. Sensors such as MODIS and AVHRR detect extremes in average temperatures of an area. The hotspots have low spatial resolution and large spatial footprints, thus making it harder to detect fires. This research proposed a ground-based spatial validation of satellite data based on crowdsourcing in order to obtain more accurate estimates of the location and severity of the fire. We developed an Android application for reporting and validating fires in peatlands. Crowd data collected were integrated with satellite hotspot data by the dashboard system as a monitoring platform for government agencies. The 110,888 hectares of Padang Island, in Riau Province, were chosen as the study area given its vulnerability to peatland fire and imminent danger of subsidence as the collateral effect of draining peatlands. Residents of Padang Island tested the use-case scenario of the app to assess its applicability. The study showed the potential use of mobile apps for local communities to help the government validate hotspots for haze mitigation.
{"title":"Crowdsourced hotspot validation and data visualisation for location-based haze mitigation","authors":"T. Aditya, Dany Laksono, Nur Izzahuddin","doi":"10.1080/17489725.2019.1619851","DOIUrl":"https://doi.org/10.1080/17489725.2019.1619851","url":null,"abstract":"ABSTRACT Haze over Sumatera and Kalimantan has been a prolonged trans-boundary issue in South East Asia mainly due to setting fire to drained peatland. At present, fire sources (i.e. hotspots) are located based on satellite data. Sensors such as MODIS and AVHRR detect extremes in average temperatures of an area. The hotspots have low spatial resolution and large spatial footprints, thus making it harder to detect fires. This research proposed a ground-based spatial validation of satellite data based on crowdsourcing in order to obtain more accurate estimates of the location and severity of the fire. We developed an Android application for reporting and validating fires in peatlands. Crowd data collected were integrated with satellite hotspot data by the dashboard system as a monitoring platform for government agencies. The 110,888 hectares of Padang Island, in Riau Province, were chosen as the study area given its vulnerability to peatland fire and imminent danger of subsidence as the collateral effect of draining peatlands. Residents of Padang Island tested the use-case scenario of the app to assess its applicability. The study showed the potential use of mobile apps for local communities to help the government validate hotspots for haze mitigation.","PeriodicalId":44932,"journal":{"name":"Journal of Location Based Services","volume":"13 1","pages":"239 - 269"},"PeriodicalIF":2.3,"publicationDate":"2019-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/17489725.2019.1619851","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48797243","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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