Pub Date : 2021-06-29DOI: 10.1553/giscience2021_01_s169
A. Scandiffio
The current research aims to explore the potential of ESA Sentinel-2 time-series satellite imagery, for detecting the seasonal landscape changes of paddy-rice fields, in the north-west of Italy, by using GIS mapping tools. On a regional scale context, paddy-rice mapping has several implications for agricultural monitoring, precision farming, food production, water management and climate change. However, it also concerns theirs high scenic value in the landscape perception, which can be a great resource for sustainable tourism. The defining characteristic of paddy-rice is that rice plants grow on flooded soils. In the field of slow tourism, such a temporary site-specific condition of the landscape can become an unconventional tourist destination. The research has been applied to territories in between cities: Turin and Milan, where the phenomenon of paddy-rice flooding, in the spring season, generates an outstanding scenic perception of the rural landscape. The research shows the effectiveness of the GIS workflow to compute the vegetation indices, which are sensitive for mapping flooded paddy-rice fields. The final outcome is a thematic map highlighting the scenic routes in the existing road network that allows experiencing such seasonal landscape conditions.
{"title":"Mapping Flooded Paddy-Rice Fields in the Landscape between Turin and Milan: A GIS-Based Method for Detecting Scenic Routes for Experiential Tourism","authors":"A. Scandiffio","doi":"10.1553/giscience2021_01_s169","DOIUrl":"https://doi.org/10.1553/giscience2021_01_s169","url":null,"abstract":"The current research aims to explore the potential of ESA Sentinel-2 time-series satellite imagery, for detecting the seasonal landscape changes of paddy-rice fields, in the north-west of Italy, by using GIS mapping tools. On a regional scale context, paddy-rice mapping has several implications for agricultural monitoring, precision farming, food production, water management and climate change. However, it also concerns theirs high scenic value in the landscape perception, which can be a great resource for sustainable tourism. The defining characteristic of paddy-rice is that rice plants grow on flooded soils. In the field of slow tourism, such a temporary site-specific condition of the landscape can become an unconventional tourist destination. The research has been applied to territories in between cities: Turin and Milan, where the phenomenon of paddy-rice flooding, in the spring season, generates an outstanding scenic perception of the rural landscape. The research shows the effectiveness of the GIS workflow to compute the vegetation indices, which are sensitive for mapping flooded paddy-rice fields. The final outcome is a thematic map highlighting the scenic routes in the existing road network that allows experiencing such seasonal landscape conditions.","PeriodicalId":29645,"journal":{"name":"GI_Forum","volume":"56 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73804198","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 : 2021-06-29DOI: 10.1553/giscience2021_01_s120
M. Hirschmugl, Carina Sobe, L. Traverso, David Cifuentes, A. Calera, C. Khawaja, M. Colangeli
Sustainable Development Goal (SDG) target 7.2 requests a substantial increase in the share of renewable energy in the global energy mix by 2030. Renewable energy production in all sectors has to be evaluated for its contribution to reach this target. Biomass for energy production has gained a bad reputation over the past years due to the “food versus fuel” debate or reported unsustainable practices. The BIOPLAT-EU project is employing geoinformation technologies combined with sustainability and economic expertise to more accurately evaluate the sustainability of bioenergy value chains. The project has three main parts: first, the generation of a pan-European map of marginal, underutilized, and contaminated (MUC) lands potentially usable for bioenergy production. This is realized by employing remote sensing time series, existing Copernicus, and other spatial data sets. Second, the generation of a web-based geographical information system (GIS) connecting the MUC lands with other important information sources necessary to assess sustainability. Thisrd, the sustainability assessment includes not only typical social and environmental sustainability indicators like soil, water, or greenhouse gas emissions, but also economic sustainability indicators like employment. Current financial barriers are addressed by integrating innovative financing solutions considering SDG target 12.A.
{"title":"Energy from Biomass: Assessing Sustainability by Geoinformation Technology","authors":"M. Hirschmugl, Carina Sobe, L. Traverso, David Cifuentes, A. Calera, C. Khawaja, M. Colangeli","doi":"10.1553/giscience2021_01_s120","DOIUrl":"https://doi.org/10.1553/giscience2021_01_s120","url":null,"abstract":"Sustainable Development Goal (SDG) target 7.2 requests a substantial increase in the share of renewable energy in the global energy mix by 2030. Renewable energy production in all sectors has to be evaluated for its contribution to reach this target. Biomass for energy production has gained a bad reputation over the past years due to the “food versus fuel” debate or reported unsustainable practices. The BIOPLAT-EU project is employing geoinformation technologies combined with sustainability and economic expertise to more accurately evaluate the sustainability of bioenergy value chains. The project has three main parts: first, the generation of a pan-European map of marginal, underutilized, and contaminated (MUC) lands potentially usable for bioenergy production. This is realized by employing remote sensing time series, existing Copernicus, and other spatial data sets. Second, the generation of a web-based geographical information system (GIS) connecting the MUC lands with other important information sources necessary to assess sustainability. Thisrd, the sustainability assessment includes not only typical social and environmental sustainability indicators like soil, water, or greenhouse gas emissions, but also economic sustainability indicators like employment. Current financial barriers are addressed by integrating innovative financing solutions considering SDG target 12.A.","PeriodicalId":29645,"journal":{"name":"GI_Forum","volume":"34 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85844820","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 : 2021-01-01DOI: 10.1553/giscience2021_02_s34
Torben Foehrder, J. Mund, P. Spathelf
{"title":"Advantages of 360° Virtual Forest Tours to Supplement Academic Forestry Education","authors":"Torben Foehrder, J. Mund, P. Spathelf","doi":"10.1553/giscience2021_02_s34","DOIUrl":"https://doi.org/10.1553/giscience2021_02_s34","url":null,"abstract":"","PeriodicalId":29645,"journal":{"name":"GI_Forum","volume":"71 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72746691","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 : 2021-01-01DOI: 10.1553/giscience2021_02_s193
David Li, Matthias Budde, Julian Bruns
Isochrone Mapping has been used since the late 19th century as a planning and visualization tool in various domains, such as transport planning and hydrology. In the past, isochrone calculation was based mainly on static properties and therefore also yielded static maps. This resulted in a potentially significant — and at the same time unquantifiable — degree of uncertainty. Today however, advances both in information technology and in the availability of input data allow much more nuanced views on the subject. This paper gives an overview of work on dynamic factors that contribute to uncertainty in isochrone calculation and mapping. Various application scenarios and their constraints are discussed, and open research challenges and possibilities identified. Finally, we present preliminary results from a practical approach to quantifying uncertainties in isochrone calculation for motorized individual transport based on Monte Carlo simulations and data from open routing APIs.
{"title":"Towards Dynamic Isochrone Mapping Accounting for Uncertainty","authors":"David Li, Matthias Budde, Julian Bruns","doi":"10.1553/giscience2021_02_s193","DOIUrl":"https://doi.org/10.1553/giscience2021_02_s193","url":null,"abstract":"Isochrone Mapping has been used since the late 19th century as a planning and visualization tool in various domains, such as transport planning and hydrology. In the past, isochrone calculation was based mainly on static properties and therefore also yielded static maps. This resulted in a potentially significant — and at the same time unquantifiable — degree of uncertainty. Today however, advances both in information technology and in the availability of input data allow much more nuanced views on the subject. This paper gives an overview of work on dynamic factors that contribute to uncertainty in isochrone calculation and mapping. Various application scenarios and their constraints are discussed, and open research challenges and possibilities identified. Finally, we present preliminary results from a practical approach to quantifying uncertainties in isochrone calculation for motorized individual transport based on Monte Carlo simulations and data from open routing APIs.","PeriodicalId":29645,"journal":{"name":"GI_Forum","volume":"46 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80917544","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 : 2021-01-01DOI: 10.1553/giscience2021_02_s167
H. N. Serere, Bernd Resch, C. Havas, Andreas Petutschnig
Geo-social media have become an established data source for spatial analysis of geographic and social processes in various fields. However, only a small share of geo-social media data are explicitly georeferenced, which often compromises the reliability of the analysis results by excluding large volumes of data from the analysis. To increase the number of georeferenced tweets, inferred locations can be extracted from the texts of social media posts. We propose a customized workflow for location extraction from tweets and subsequent geocoding. We compare the results of two methods: DBpedia Spotlight (using linked Wikipedia entities), and spaCy combined with the geocoding methods of OpenStreetMap Nominatim. The results suggest that the workflow using spaCy and Nominatim identifies more locations than DBpedia Spotlight. For 50,616 tweets posted within California, USA, the granularity of the extracted locations is reasonable. However, several directions for future research were identified, including improved semantic analysis, the creation of a cascading workflow, and the need to integrate different data sources in order to increase reliability and spatial accuracy.
{"title":"Extracting and Geocoding Locations in Social Media Posts: A Comparative Analysis","authors":"H. N. Serere, Bernd Resch, C. Havas, Andreas Petutschnig","doi":"10.1553/giscience2021_02_s167","DOIUrl":"https://doi.org/10.1553/giscience2021_02_s167","url":null,"abstract":"Geo-social media have become an established data source for spatial analysis of geographic and social processes in various fields. However, only a small share of geo-social media data are explicitly georeferenced, which often compromises the reliability of the analysis results by excluding large volumes of data from the analysis. To increase the number of georeferenced tweets, inferred locations can be extracted from the texts of social media posts. We propose a customized workflow for location extraction from tweets and subsequent geocoding. We compare the results of two methods: DBpedia Spotlight (using linked Wikipedia entities), and spaCy combined with the geocoding methods of OpenStreetMap Nominatim. The results suggest that the workflow using spaCy and Nominatim identifies more locations than DBpedia Spotlight. For 50,616 tweets posted within California, USA, the granularity of the extracted locations is reasonable. However, several directions for future research were identified, including improved semantic analysis, the creation of a cascading workflow, and the need to integrate different data sources in order to increase reliability and spatial accuracy.","PeriodicalId":29645,"journal":{"name":"GI_Forum","volume":"31 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87443059","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 : 2021-01-01DOI: 10.1553/giscience2021_02_s18
J. Pokraka, Torsten Kralemann–Poppell, Inga Gryl, Paula Schmidt
This article presents empirical findings from a learning environment based on education for Spatial Citizenship (Gryl & Jekel, 2012; Schulze et al., 2015) conducted with primary school children (6 to 10 years of age) in the city of Essen, Germany. In workshops comprising three stages, participants used an easy-to-use mapping application to trace significant places and objects in their school surroundings in relation to the workshops’ overall topic of envisioning designs and features of a ‘city for children’. This paper focuses on the analysis of collaborative maps created from children’s perspectives on urban space in their own life-
本文展示了基于空间公民教育的学习环境的实证研究结果(Gryl & Jekel, 2012;Schulze et al.， 2015)在德国埃森市对小学生(6至10岁)进行的研究。在三个阶段的工作坊中，参与者使用一个易于使用的地图应用程序来追踪学校环境中的重要地点和物体，这与工作坊的总体主题有关，即设想设计和“儿童城市”的特征。本文重点分析了儿童在自己的生活中对城市空间的视角所创作的协作地图
{"title":"‘This is a Great Place for Children. Here, They Can Play, Do What They Want, Have Fun and Other Things.’ Mapping Primary School Children’s Everyday Spaces","authors":"J. Pokraka, Torsten Kralemann–Poppell, Inga Gryl, Paula Schmidt","doi":"10.1553/giscience2021_02_s18","DOIUrl":"https://doi.org/10.1553/giscience2021_02_s18","url":null,"abstract":"This article presents empirical findings from a learning environment based on education for Spatial Citizenship (Gryl & Jekel, 2012; Schulze et al., 2015) conducted with primary school children (6 to 10 years of age) in the city of Essen, Germany. In workshops comprising three stages, participants used an easy-to-use mapping application to trace significant places and objects in their school surroundings in relation to the workshops’ overall topic of envisioning designs and features of a ‘city for children’. This paper focuses on the analysis of collaborative maps created from children’s perspectives on urban space in their own life-","PeriodicalId":29645,"journal":{"name":"GI_Forum","volume":"51 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73089476","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 : 2021-01-01DOI: 10.1553/giscience2021_02_s82
S. Hennig
{"title":"Orchard Meadow Trees: Tree Detection Using Deep Learning in ArcGIS Pro","authors":"S. Hennig","doi":"10.1553/giscience2021_02_s82","DOIUrl":"https://doi.org/10.1553/giscience2021_02_s82","url":null,"abstract":"","PeriodicalId":29645,"journal":{"name":"GI_Forum","volume":"42 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81382701","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 : 2021-01-01DOI: 10.1553/giscience2021_01_s112
Shenmin Zhang, Yong Xue, Xiran Zhou
The development of big remote sensing data related technologies and applications poses a big challenge that massive computing capability is needed to support big data processing. In order to solve this challenge, this paper proposes an architecture of heterogeneous platform of high performance computing, which employs the computer hardware resources to improve the efficiency of big remote sensing data processing by optimizing scheduling strategies and designing high-performance algorithms. Furthermore, the proposed platform can dynamically incorporated with a workflow engine regarding big remote sensing data processing. These algorithms are modular to meet the flexible combination of different processes.
{"title":"Dynamic Workflow Engine of Atmospheric Big Remote Sensing Data Processing Powered by Heterogenous Platform for High Performance Computing","authors":"Shenmin Zhang, Yong Xue, Xiran Zhou","doi":"10.1553/giscience2021_01_s112","DOIUrl":"https://doi.org/10.1553/giscience2021_01_s112","url":null,"abstract":"The development of big remote sensing data related technologies and applications poses a big challenge that massive computing capability is needed to support big data processing. In order to solve this challenge, this paper proposes an architecture of heterogeneous platform of high performance computing, which employs the computer hardware resources to improve the efficiency of big remote sensing data processing by optimizing scheduling strategies and designing high-performance algorithms. Furthermore, the proposed platform can dynamically incorporated with a workflow engine regarding big remote sensing data processing. These algorithms are modular to meet the flexible combination of different processes.","PeriodicalId":29645,"journal":{"name":"GI_Forum","volume":"24 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82172780","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 : 2021-01-01DOI: 10.1553/giscience2021_02_s215
Yi-liang Deng, Wolfgang Spitzer, Sabine Gadocha, Thomas Prinz
With the growing residential development of urban areas and their hinterlands in the Alpine region, urban sprawl is a major concern. It is therefore essential for decision-making authorities and urban planners to monitor the demand for, and consumption of, the limited reserve of land zoned for residential buildings and the development of future settlements. Data such as demographic statistics, population forecasts, and geospatial data of the land reserve are required for this purpose. However, due to the variety of these data, tools for exploring them in an integrated and intuitive manner are rarely available. This paper introduces a web application designed to facilitate this task, a map-based strategical dashboard that was developed within the Alpine Building Centre project (Zentrum Alpines Bauen, www.alpinesbauen.at). The paper describes the application’s design goals, data preparation, architecture and user interface. With a use case in Oberndorf bei Salzburg, we demonstrate how the application visualizes the predicted future settlement situation based on existing housing patterns and population development forecasts. The use case also shows how the application allows simulation and evaluation of various scenarios for housing demand and zoned residential land use, thus assisting decision makers to devise spatial development concepts for balancing housing sufficiency and reducing urban sprawl. This paper aims to present the application as an approach of using an interactive map-based dashboard to present and utilize multidimensional data in the field of residential land use for the purposes of urban planning.
{"title":"A Web Application for Simulating Future Settlement Development","authors":"Yi-liang Deng, Wolfgang Spitzer, Sabine Gadocha, Thomas Prinz","doi":"10.1553/giscience2021_02_s215","DOIUrl":"https://doi.org/10.1553/giscience2021_02_s215","url":null,"abstract":"With the growing residential development of urban areas and their hinterlands in the Alpine region, urban sprawl is a major concern. It is therefore essential for decision-making authorities and urban planners to monitor the demand for, and consumption of, the limited reserve of land zoned for residential buildings and the development of future settlements. Data such as demographic statistics, population forecasts, and geospatial data of the land reserve are required for this purpose. However, due to the variety of these data, tools for exploring them in an integrated and intuitive manner are rarely available. This paper introduces a web application designed to facilitate this task, a map-based strategical dashboard that was developed within the Alpine Building Centre project (Zentrum Alpines Bauen, www.alpinesbauen.at). The paper describes the application’s design goals, data preparation, architecture and user interface. With a use case in Oberndorf bei Salzburg, we demonstrate how the application visualizes the predicted future settlement situation based on existing housing patterns and population development forecasts. The use case also shows how the application allows simulation and evaluation of various scenarios for housing demand and zoned residential land use, thus assisting decision makers to devise spatial development concepts for balancing housing sufficiency and reducing urban sprawl. This paper aims to present the application as an approach of using an interactive map-based dashboard to present and utilize multidimensional data in the field of residential land use for the purposes of urban planning.","PeriodicalId":29645,"journal":{"name":"GI_Forum","volume":"6 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78411440","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 : 2021-01-01DOI: 10.1553/giscience2021_02_s45
Daniel Raithofer, C. Hintermann
Major crises such as the Covid-19 pandemic put societies to the test. The conjuncture of globalization, with all its challenging transformation processes, social inequality, and the epidemic spread of a new (viral) pathogen has fuelled feelings of uncertainty and insecurity in virtually every part of society, on a global scale. Focusing on learners, this paper proposes ‘intellectual resilience’ as a new educational concept aiming to empower learners to more fully comprehend and navigate global crises. An intellectually resilient person is defined as someone who can use multiple scientific approaches and concepts in a participative, democratically informed way. The aim is to explore the potential of school geography education to support young learners in handling crisis situations
{"title":"Intellectual Resilience – Draft of a New Educational Approach for the Geography Classroom","authors":"Daniel Raithofer, C. Hintermann","doi":"10.1553/giscience2021_02_s45","DOIUrl":"https://doi.org/10.1553/giscience2021_02_s45","url":null,"abstract":"Major crises such as the Covid-19 pandemic put societies to the test. The conjuncture of globalization, with all its challenging transformation processes, social inequality, and the epidemic spread of a new (viral) pathogen has fuelled feelings of uncertainty and insecurity in virtually every part of society, on a global scale. Focusing on learners, this paper proposes ‘intellectual resilience’ as a new educational concept aiming to empower learners to more fully comprehend and navigate global crises. An intellectually resilient person is defined as someone who can use multiple scientific approaches and concepts in a participative, democratically informed way. The aim is to explore the potential of school geography education to support young learners in handling crisis situations","PeriodicalId":29645,"journal":{"name":"GI_Forum","volume":"86 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74801411","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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