Pub Date : 2020-01-01DOI: 10.1553/giscience2020_02_s107
Julian Bruns, Florian Micklich, Johannes Kutterer, A. Abecker, Philipp Zehnder
The types of data available have changed in the last decade. While, historically, data were gathered in batches and distributed as such, e.g. as a database or shapefile, today we are dealing increasingly with real-time data. This data is produced and consumed continuously in real time. The phenomenon is most commonly known as streaming data. Traditionally, software for spatial analysis, such as a Geographical Information System (GIS) or spatial database, was created and optimized for the batch processing of data. However, the inherent characteristics of streaming data provide new challenges for data-stream processing systems, which have not yet been solved. In this paper, we propose enhancing systems for the handling and analysis of streaming data through the use of spatial operators. We identify Complex Event Processing (CEP) as a promising underlying concept for such a system and use the (open source) self-service IoT toolbox ‘StreamPipes’ as a representative for this. On the basis of a review of the literature, we selected 6 core types of spatial operator and implemented 33 basic spatial operators in 11 groups. These can be combined with the existing non-spatial operators for in-depth analysis of streaming data that involves spatial
{"title":"Spatial Operators for Complex Event Processing","authors":"Julian Bruns, Florian Micklich, Johannes Kutterer, A. Abecker, Philipp Zehnder","doi":"10.1553/giscience2020_02_s107","DOIUrl":"https://doi.org/10.1553/giscience2020_02_s107","url":null,"abstract":"The types of data available have changed in the last decade. While, historically, data were gathered in batches and distributed as such, e.g. as a database or shapefile, today we are dealing increasingly with real-time data. This data is produced and consumed continuously in real time. The phenomenon is most commonly known as streaming data. Traditionally, software for spatial analysis, such as a Geographical Information System (GIS) or spatial database, was created and optimized for the batch processing of data. However, the inherent characteristics of streaming data provide new challenges for data-stream processing systems, which have not yet been solved. In this paper, we propose enhancing systems for the handling and analysis of streaming data through the use of spatial operators. We identify Complex Event Processing (CEP) as a promising underlying concept for such a system and use the (open source) self-service IoT toolbox ‘StreamPipes’ as a representative for this. On the basis of a review of the literature, we selected 6 core types of spatial operator and implemented 33 basic spatial operators in 11 groups. These can be combined with the existing non-spatial operators for in-depth analysis of streaming data that involves spatial","PeriodicalId":29645,"journal":{"name":"GI_Forum","volume":"89 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80361780","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 : 2020-01-01DOI: 10.1553/giscience2020_01_s89
Saskia Wolff, T. Lakes
An increasing demand for agricultural products within the past years has led to increasing agricultural intensification. Various agricultural compositions and landscape configurations can have different impacts on the provision of ecosystem services. The EU follows the aim of supporting and developing sustainable food production systems. We use the plot-based data provided by the Integrated Administration and Control System (IACS) to identify different types of agricultural landscapes and their spatial distribution in Brandenburg, Germany. By calculating a set of landscape metrics to characterise agricultural land use, we were able to identify six types of agricultural landscapes by a Two-Step cluster analysis for a hexagonal grid. Thereby, the majority of Brandenburg is covered by agriculture characterised by high share of cropland but different degrees of fragmentation. By providing a framework using landscape metrics derived from IACS data, the approach of clustering to identify typologies is highly transferable to other regions within the EU and may provide an important asset for offering new units of analysis for a better tailored environmental and agricultural planning depending on the local to regional characteristics.
{"title":"Characterising Agricultural Landscapes using Landscape Metrics and Cluster Analysis in Brandenburg, Germany","authors":"Saskia Wolff, T. Lakes","doi":"10.1553/giscience2020_01_s89","DOIUrl":"https://doi.org/10.1553/giscience2020_01_s89","url":null,"abstract":"An increasing demand for agricultural products within the past years has led to increasing agricultural intensification. Various agricultural compositions and landscape configurations can have different impacts on the provision of ecosystem services. The EU follows the aim of supporting and developing sustainable food production systems. We use the plot-based data provided by the Integrated Administration and Control System (IACS) to identify different types of agricultural landscapes and their spatial distribution in Brandenburg, Germany. By calculating a set of landscape metrics to characterise agricultural land use, we were able to identify six types of agricultural landscapes by a Two-Step cluster analysis for a hexagonal grid. Thereby, the majority of Brandenburg is covered by agriculture characterised by high share of cropland but different degrees of fragmentation. By providing a framework using landscape metrics derived from IACS data, the approach of clustering to identify typologies is highly transferable to other regions within the EU and may provide an important asset for offering new units of analysis for a better tailored environmental and agricultural planning depending on the local to regional characteristics.","PeriodicalId":29645,"journal":{"name":"GI_Forum","volume":"43 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75561820","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 : 2020-01-01DOI: 10.1553/giscience2020_01_s63
I. Ismayilova, E. Uuemaa, A. Helm, Christian Röger, S. Timpf
Calcareous alvar grasslands are one of the most species-rich habitats in Estonia. Land-use change and cessation of traditional agricultural practices have led to a decrease of the area of these valuable grasslands during the past century. Therefore, their conservation and restoration are becoming increasingly important. Efforts to restore these habitats have already been made in recent years. Land suitability analysis for potential restoration sites, using the machine learning technique Random Forest (RF), was performed for the first time in this study, which aimed to assess the use of RF for a suitability analysis of alvar grassland. RF predicted 610.91 km2 of areas suitable for restoring alvar grasslands or for creating alvarlike habitats in Estonia. These areas include all existing alvar areas as well an additional 140.91 km2 suitable for establishing new habitat similar to calcareous alvar grasslands. We discuss suitability analysis to help with restoration planning and find it to be a reasonable and efficient tool that has potential to provide relevant information. The quality of the prediction could be improved by including additional data relevant for alvar grasslands, such as soil depth, but such data was unfortunately unavailable.
{"title":"Land Suitability Analysis of Alvar Grassland Vegetation in Estonia Using Random Forest","authors":"I. Ismayilova, E. Uuemaa, A. Helm, Christian Röger, S. Timpf","doi":"10.1553/giscience2020_01_s63","DOIUrl":"https://doi.org/10.1553/giscience2020_01_s63","url":null,"abstract":"Calcareous alvar grasslands are one of the most species-rich habitats in Estonia. Land-use change and cessation of traditional agricultural practices have led to a decrease of the area of these valuable grasslands during the past century. Therefore, their conservation and restoration are becoming increasingly important. Efforts to restore these habitats have already been made in recent years. Land suitability analysis for potential restoration sites, using the machine learning technique Random Forest (RF), was performed for the first time in this study, which aimed to assess the use of RF for a suitability analysis of alvar grassland. RF predicted 610.91 km2 of areas suitable for restoring alvar grasslands or for creating alvarlike habitats in Estonia. These areas include all existing alvar areas as well an additional 140.91 km2 suitable for establishing new habitat similar to calcareous alvar grasslands. We discuss suitability analysis to help with restoration planning and find it to be a reasonable and efficient tool that has potential to provide relevant information. The quality of the prediction could be improved by including additional data relevant for alvar grasslands, such as soil depth, but such data was unfortunately unavailable.","PeriodicalId":29645,"journal":{"name":"GI_Forum","volume":"11 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84201528","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 : 2020-01-01DOI: 10.1553/giscience2020_02_s147
T. Strasser, D. Tiede
In this study, we present a concept for the assessment of impervious surfaces integrating VHR satellite data and a-priori information from additional datasets. Spatial concepts like neighbourhood and region, distance, spatial dependence or spatial variability are adapted in a knowledge-based approach using an object-based image analysis model to accumulate evidence from different sources. We look at constraints for timely and comprehensive VHR optical data acquisition that covers larger areas with adequate image characteristics (sensor family, seasonality, sensor viewing angles and sun inclination). For a study area covering the municipality of Hallein (Austria), we discuss preliminary results with a focus on real-world object characterization (including surface material, spectral reflectivity, object size and shape) and on building a knowledge-base for the classification of real-world objects. We also assess image characteristics and effects on image analysis. The knowledge about real-world object characteristics and image object statistics will be used to develop an integrated approach that aims for transferability to larger areas. future developments and data.
{"title":"Using Spatial Concepts to Integrate Data and Information from Various Sources for a Knowledge-based Assessment of Impervious Surfaces","authors":"T. Strasser, D. Tiede","doi":"10.1553/giscience2020_02_s147","DOIUrl":"https://doi.org/10.1553/giscience2020_02_s147","url":null,"abstract":"In this study, we present a concept for the assessment of impervious surfaces integrating VHR satellite data and a-priori information from additional datasets. Spatial concepts like neighbourhood and region, distance, spatial dependence or spatial variability are adapted in a knowledge-based approach using an object-based image analysis model to accumulate evidence from different sources. We look at constraints for timely and comprehensive VHR optical data acquisition that covers larger areas with adequate image characteristics (sensor family, seasonality, sensor viewing angles and sun inclination). For a study area covering the municipality of Hallein (Austria), we discuss preliminary results with a focus on real-world object characterization (including surface material, spectral reflectivity, object size and shape) and on building a knowledge-base for the classification of real-world objects. We also assess image characteristics and effects on image analysis. The knowledge about real-world object characteristics and image object statistics will be used to develop an integrated approach that aims for transferability to larger areas. future developments and data.","PeriodicalId":29645,"journal":{"name":"GI_Forum","volume":"33 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81303044","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 : 2019-12-12DOI: 10.1553/giscience2019_02_s24
S. Hennig
Web-based participation has received growing interest over recent years. Such participation includes both profit- and non-profit-oriented sharing-economy initiatives. Not-for-profit sharing-economy initiatives focus less on economic aspects and more on awareness-raising in society regarding sustainability objectives (e.g. sustainable production and consumption of goods). In the current discussions around climate change and sustainable lifestyles, awareness-raising is important and new ways of reaching the public are attracting more interest. The question now is not simply to what extent non-profit sharing-initiatives achieve their goals, but how to assess any achievement as, due to the nature of these projects, little information on the participants’ background, perspectives and behaviour is available. These questions are discussed with reference to the Mundraub project, which allows people to share information on plants (e.g. fruit and nut trees, berry bushes and herbs) in public urban spaces (primarily German cities) so that others can harvest the plants for free. To learn about how sustainability objectives are achieved, data for the sites where the plants that have been mapped to Mundraub are located were analysed statistically. The results indicate that the people who are reached by the Mundraub project are mostly those who are already interested and aware of sustainability-related topics. The assessment approach used is a first attempt towards a better understanding of the extent to which the sustainability objectives of non-profit sharing-economy activities have been reached and towards identifying how the achievement of objectives might be improved on.
{"title":"Sustainability Objectives of Non-Profit Sharing-Economy Activities: Assessing Achievement. A Case Study of the Mundraub Food-Sharing Poject","authors":"S. Hennig","doi":"10.1553/giscience2019_02_s24","DOIUrl":"https://doi.org/10.1553/giscience2019_02_s24","url":null,"abstract":"Web-based participation has received growing interest over recent years. Such participation includes both profit- and non-profit-oriented sharing-economy initiatives. Not-for-profit sharing-economy initiatives focus less on economic aspects and more on awareness-raising in society regarding sustainability objectives (e.g. sustainable production and consumption of goods). In the current discussions around climate change and sustainable lifestyles, awareness-raising is important and new ways of reaching the public are attracting more interest. The question now is not simply to what extent non-profit sharing-initiatives achieve their goals, but how to assess any achievement as, due to the nature of these projects, little information on the participants’ background, perspectives and behaviour is available. These questions are discussed with reference to the Mundraub project, which allows people to share information on plants (e.g. fruit and nut trees, berry bushes and herbs) in public urban spaces (primarily German cities) so that others can harvest the plants for free. To learn about how sustainability objectives are achieved, data for the sites where the plants that have been mapped to Mundraub are located were analysed statistically. The results indicate that the people who are reached by the Mundraub project are mostly those who are already interested and aware of sustainability-related topics. The assessment approach used is a first attempt towards a better understanding of the extent to which the sustainability objectives of non-profit sharing-economy activities have been reached and towards identifying how the achievement of objectives might be improved on.","PeriodicalId":29645,"journal":{"name":"GI_Forum","volume":"50 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82683438","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 : 2019-12-11DOI: 10.1553/giscience2019_02_s10
Pablo Cabrera-Barona, Myriam Paredes, D. Cole
This paper identifies spatial patterns of body mass index (BMI) and obesity in the Metropolitan District of Quito, Ecuador, by applying spatial autocorrelation. We identified BMI hotspots in western rural parishes, and hotspots of obesity in northern urban parishes. We then explored associations between distances to food outlets, physical activity and smoking (independent variables), and BMI and obesity (BMI > 30) (dependent variables) by applying global regressions (GR) and geographical weighted regressions (GWR). Smoking was found to be significantly negatively associated with BMI and obesity. Distance to supermarkets was found to be negatively associated with obesity.
{"title":"Associations of Body Mass Index with Food Environments, Physical Activity and Smoking","authors":"Pablo Cabrera-Barona, Myriam Paredes, D. Cole","doi":"10.1553/giscience2019_02_s10","DOIUrl":"https://doi.org/10.1553/giscience2019_02_s10","url":null,"abstract":"This paper identifies spatial patterns of body mass index (BMI) and obesity in the Metropolitan District of Quito, Ecuador, by applying spatial autocorrelation. We identified BMI hotspots in western rural parishes, and hotspots of obesity in northern urban parishes. We then explored associations between distances to food outlets, physical activity and smoking (independent variables), and BMI and obesity (BMI > 30) (dependent variables) by applying global regressions (GR) and geographical weighted regressions (GWR). Smoking was found to be significantly negatively associated with BMI and obesity. Distance to supermarkets was found to be negatively associated with obesity.","PeriodicalId":29645,"journal":{"name":"GI_Forum","volume":"118 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78118766","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 : 2019-12-11DOI: 10.1553/giscience2019_02_s180
C. Scharf, Inga Gryl
The approach of an education for innovativeness aims to enable pupils to participate in shaping societies in a mature manner, which includes the appropriation and designing of spaces. This approach is useful for educational and practical concepts such as Spatial Citizenship, which promotes the use of digital geomedia for individual and collective appropriation and re-shaping of spaces. However, encouraging innovativeness may also seem to foster participation in questionable inventing processes with trivial –or even harmful –intentions. Including an ethical meta level in the model design for innovativeness would generate reflection on the purpose of the novelty. In this paper, we look first at theories that address the term ‘problem’, social innovations andapplied ethics, in order then to develop a first attempt at creating an ethical meta level in the model design for innovativenes.
{"title":"Fostering Valuable Participation in Shaping Spaces and Societies: Towards Creating an Ethical Meta Level in the Model Design for Innovativeness","authors":"C. Scharf, Inga Gryl","doi":"10.1553/giscience2019_02_s180","DOIUrl":"https://doi.org/10.1553/giscience2019_02_s180","url":null,"abstract":"The approach of an education for innovativeness aims to enable pupils to participate in shaping societies in a mature manner, which includes the appropriation and designing of spaces. This approach is useful for educational and practical concepts such as Spatial Citizenship, which promotes the use of digital geomedia for individual and collective appropriation and re-shaping of spaces. However, encouraging innovativeness may also seem to foster participation in questionable inventing processes with trivial –or even harmful –intentions. Including an ethical meta level in the model design for innovativeness would generate reflection on the purpose of the novelty. In this paper, we look first at theories that address the term ‘problem’, social innovations andapplied ethics, in order then to develop a first attempt at creating an ethical meta level in the model design for innovativenes.","PeriodicalId":29645,"journal":{"name":"GI_Forum","volume":"168 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86734055","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 : 2019-12-11DOI: 10.1553/giscience2019_02_s60
Stuart Krause
Remote sensing methods for forest monitoring are evolving rapidly thanks to recent advances in Unmanned Aerial Vehicle technology and digital photogrammetry. Photogrammetric point clouds allow the non-destructive derivation of individual tree parameters at a low cost. The fusion of aerial and terrestrial photogrammetry for creating full-tree point clouds is of utility for forest research, as tree volume could be assessed more economically and efficiently than by traditional methods. However, this is challenging to implement due to difficulties with co-registration and issues of occlusion. This study explores the possibility of using spherical targets typically used for Terrestrial Laser Scanning to accomplish the co-registration of UAV-based and terrestrial photogrammetric datasets. Results show a full-tree point cloud derived from UAV oblique imagery in combination with terrestrial imagery. Despite issues of noise produced from the sky in terrestrial imagery, the methodology is promising for aerial and terrestrial point cloud fusion.
{"title":"Aerial and Terrestrial Photogrammetric Point Cloud Fusion for Intensive Forest Monitoring","authors":"Stuart Krause","doi":"10.1553/giscience2019_02_s60","DOIUrl":"https://doi.org/10.1553/giscience2019_02_s60","url":null,"abstract":"Remote sensing methods for forest monitoring are evolving rapidly thanks to recent advances in Unmanned Aerial Vehicle technology and digital photogrammetry. Photogrammetric point clouds allow the non-destructive derivation of individual tree parameters at a low cost. The fusion of aerial and terrestrial photogrammetry for creating full-tree point clouds is of utility for forest research, as tree volume could be assessed more economically and efficiently than by traditional methods. However, this is challenging to implement due to difficulties with co-registration and issues of occlusion. This study explores the possibility of using spherical targets typically used for Terrestrial Laser Scanning to accomplish the co-registration of UAV-based and terrestrial photogrammetric datasets. Results show a full-tree point cloud derived from UAV oblique imagery in combination with terrestrial imagery. Despite issues of noise produced from the sky in terrestrial imagery, the methodology is promising for aerial and terrestrial point cloud fusion.","PeriodicalId":29645,"journal":{"name":"GI_Forum","volume":"13 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87041550","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 : 2019-12-11DOI: 10.1553/giscience2019_02_s98
M. Mete, T. Yomralioglu
Estimating the value of real estate has applications in fields as diverse as taxation, buying and renting properties, expropriation and urban regeneration. Determining the most objective, accurate and acceptable value for real estate by considering spatial criteria is therefore important. One stochastic method used to determine real estate values is ‘nominal valuation’. In this approach, criteria that may affect land value are subjected to various spatial analyses, and pixel-based value maps can be produced using GIS. Land value maps are in raster data format and need to be compared with the actual market values. Pixel-resolution analyses are required that depend on the selected grid dimensions. First of all, nominal value maps were produced using a nominal valuation model, using criteria for proximity, visibility and terrain. These were weighted in order to produce a nominal asset value-based map according to the ‘Best Worst Method’. Changes in the unit land values were examined for maps at various resolutions; a resolution of 10 metres emerged as the ideal pixel size for valuation maps.
{"title":"Creation of Nominal Asset Value-Based Maps using GIS: A Case Study of Istanbul Beyoglu and Gaziosmanpasa Districts","authors":"M. Mete, T. Yomralioglu","doi":"10.1553/giscience2019_02_s98","DOIUrl":"https://doi.org/10.1553/giscience2019_02_s98","url":null,"abstract":"Estimating the value of real estate has applications in fields as diverse as taxation, buying and renting properties, expropriation and urban regeneration. Determining the most objective, accurate and acceptable value for real estate by considering spatial criteria is therefore important. One stochastic method used to determine real estate values is ‘nominal valuation’. In this approach, criteria that may affect land value are subjected to various spatial analyses, and pixel-based value maps can be produced using GIS. Land value maps are in raster data format and need to be compared with the actual market values. Pixel-resolution analyses are required that depend on the selected grid dimensions. First of all, nominal value maps were produced using a nominal valuation model, using criteria for proximity, visibility and terrain. These were weighted in order to produce a nominal asset value-based map according to the ‘Best Worst Method’. Changes in the unit land values were examined for maps at various resolutions; a resolution of 10 metres emerged as the ideal pixel size for valuation maps.","PeriodicalId":29645,"journal":{"name":"GI_Forum","volume":"40 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82820884","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 : 2019-06-19DOI: 10.1553/GISCIENCE2019_01_S148
Monica Flores Castillo, Stephan Petryczka, Joyce Choi-Li, K. Ludwig
The South Bronx neighbourhood in New York City has historically been oppressed and left behind by urban planning policies that deliberately created social exclusion in the area. We Stay/Nos Quedamos, a community development organization located in the area, is actively seeking to establish a Community Land Trust, a mechanism designed to provide homeownership affordability to low-income households. This study seeks to identify potential sites suitable for acquisition and for establishing a Community Land Trust in the South Bronx area. Analysis is performed using Geographic Information Systems in combination with official New York City data. Moreover, by leveraging the local knowledge of Nos Quedamos, we propose a critical approach to GIS and official data. The results of this study will help Nos Quedamos and local stakeholders in decision-making, support political efforts and negotiations with local authorities in the establishment of a Community Land Trust, enhance housing affordability, and consolidate community-managed open spaces in the South Bronx. Furthermore, the methodology presented here could serve as a guide for other local organizations seeking to establish similar land trusts in their localities, especially in urban settings with a high demand for land acquisition.
{"title":"Mapping for Community-Driven Neighbourhood Planning: The Case of the South Bronx Land and Community Resource Trust","authors":"Monica Flores Castillo, Stephan Petryczka, Joyce Choi-Li, K. Ludwig","doi":"10.1553/GISCIENCE2019_01_S148","DOIUrl":"https://doi.org/10.1553/GISCIENCE2019_01_S148","url":null,"abstract":"The South Bronx neighbourhood in New York City has historically been oppressed and left behind by urban planning policies that deliberately created social exclusion in the area. We Stay/Nos Quedamos, a community development organization located in the area, is actively seeking to establish a Community Land Trust, a mechanism designed to provide homeownership affordability to low-income households. This study seeks to identify potential sites suitable for acquisition and for establishing a Community Land Trust in the South Bronx area. Analysis is performed using Geographic Information Systems in combination with official New York City data. Moreover, by leveraging the local knowledge of Nos Quedamos, we propose a critical approach to GIS and official data. The results of this study will help Nos Quedamos and local stakeholders in decision-making, support political efforts and negotiations with local authorities in the establishment of a Community Land Trust, enhance housing affordability, and consolidate community-managed open spaces in the South Bronx. Furthermore, the methodology presented here could serve as a guide for other local organizations seeking to establish similar land trusts in their localities, especially in urban settings with a high demand for land acquisition.","PeriodicalId":29645,"journal":{"name":"GI_Forum","volume":"13 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80013634","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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