Yi-liang Deng, Wolfgang Spitzer, Sabine Gadocha, Thomas Prinz
{"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":null,"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":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"GI_Forum","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1553/giscience2021_02_s215","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Social Sciences","Score":null,"Total":0}
引用次数: 0
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.