Introducing SMURF: A software system for monitoring urban functionalities

Repetti, Alexandre; Soutter, Marc; Musy, A.

doi:10.1016/j.compenvurbsys.2005.06.001

Cited by 10 publications

(8 citation statements)

References 21 publications

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“…One of the first studies in this field was conducted by Sheetz et al [24], which proposed that mental maps can be evaluated by Group Support System (GSS) for more rapid and accurate analysis. Furthermore, in recent years, considering the many capabilities of GIS in environmental and urban studies [67][68][69] measures have been taken to analyse people's perception towards urban environments using the tools within this program [70][71][72]. In the context of analysing mental maps in a computational manner, in research conducted by Trowbridge et al [73], the Georeferencing ArcGIS tool was used to evaluate the accuracy of the mental maps based on the metric distances of the main map, which actually evaluated the accuracy of landmark locations by overlapping the mental map with the city's main map.…”

Section: Methods Of Mental Map Analysismentioning

confidence: 99%

Design and Validation of a Computational Program for Analysing Mental Maps: Aram Mental Map Analyzer

et al. 2019

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Considering citizens’ perceptions of their living environment is very helpful in making the right decisions for city planners who intend to build a sustainable society. Mental map analyses are widely used in understanding the level of perception of individuals regarding the surrounding environment. The present study introduces Aram Mental Map Analyzer (AMMA), an open-source program, which allows researchers to use special features and new analytical methods to receive outputs in numerical data and analytical maps with greater accuracy and speed. AMMA performance is contingent upon two principles of accuracy and complexity, the accuracy of the program is measured by Accuracy Placed Landmarks (APL) and General Orientation (GO), which respectively analyses the landmark placement accuracy and the main route mapping accuracy. Also, the complexity section is examined through two analyses Cell Percentage (CP) and General Structure (GS), which calculates the complexity of citizens’ perception of space based on the criteria derived from previous studies. AMMA examines all the dimensions and features of the graphic maps and its outputs have a wide range of valid and differentiated information, which is tailored to the research and information subject matter that is required.

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Section: Methods Of Mental Map Analysismentioning

confidence: 99%

Design and Validation of a Computational Program for Analysing Mental Maps: Aram Mental Map Analyzer

et al. 2019

View full text Add to dashboard Cite

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“…One of the first studies in this field was conducted by Sheetz et al (1994), which proposed that mental maps can be evaluated by Group Support System (GSS) for more rapid and accurate analysis. Furthermore, in recent years, considering the many capabilities of GIS in environmental and urban studies ( Repetti, Soutter, and Musy, 2006;Steiniger and Hunter, 2013;Jung, 2009) measures have been taken to analyze people's perception towards urban environments using the tools within this program (Tu Huynh and Doherty, 2007;Curtis et al, 2014;Huerta, Schade, and Granell, 2014). In the context of analyzing mental maps in a computational manner, in research conducted by Trowbridge et al (2015), the Georeferencing ArcGIS tool was used to evaluate the accuracy of the mental maps based on the metric distances of the main map, which actually evaluated the accuracy of landmark locations by overlapping the mental map with the city's main map.…”

Section: Methods Of Mental Map Analysismentioning

confidence: 99%

Smart Cities Planning and Sustainable Urban Development through Development and Analyzing Mental Maps of Citizen Perceptions

Aram¹,

Solgi²,

García³

et al. 2019

Preprint

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Considering citizens' perceptions of their living environment is very helpful in making the right decisions for city planners who intend to build a sustainable society. Mental map analyses are widely used in understanding the level of perception of individuals regarding the surrounding environment. The present study introduces Aram Mental Map Analyzer (AMMA), an open-source program, which allows researchers to use special features and new analytical methods to receive outputs in numerical data and analytical maps with greater accuracy and speed. AMMA performance is contingent upon two principles of accuracy and complexity, the accuracy of the program is measured by Accuracy Placed Landmarks (APL) and General Orientation (GO), which respectively analyses the landmark placement accuracy and the main route mapping accuracy. Also, the complexity section is examined through two analyses Cell Percentage (CP) and General Structure (GS), which calculates the complexity of citizens’ perception of space based on the criteria derived from previous studies. AMMA examines all the dimensions and features of the graphic maps, and its outputs have a wide range of valid and differentiated information, which is tailored to the research and information subject matter that is required.

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“…By contrast, many cities in developed countries such as the United States have systems in place through which planners can easily access information such as property boundaries, ownership, tax, and type (land use) superimposed on orthophotos soil types, topography, and vegetation-related data (National Academy of Sciences 2003). In most developing countries, municipal records are often unable to keep pace with the high rate of urbanization and informal urban development (Repetti, Soutter, and Musy 2005). EO not only provides a quick synoptic view of urban areas but also allows planners to cross-check or complement other data sources such as censuses or field surveys, thereby improving the validity and reliability of research results (Baud et al 2010).…”

Section: Why Apply Eo?mentioning

confidence: 99%

Earth Observation for Sustainable Urban Planning in Developing Countries

Musakwa

Niekerk

2014

Journal of Planning Literature

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Cities are constantly changing and authorities face immense challenges in obtaining accurate and timely data to effectively manage urban areas. This is particularly problematic in the developing world where municipal records are often unavailable or not updated. Spaceborne earth observation (EO) has great potential for providing up-to-date spatial information about urban areas. This article reviews the application of EO for supporting urban planning. In particular, the article overviews case studies where EO was used to derive products and indicators required by urban planners. The review concludes that EO has sufficiently matured in recent years but that a shift from the current focus on purely science-driven EO applications to the provision of useful information for day-to-day decision-making and urban sustainability monitoring is clearly needed.

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Introducing SMURF: A software system for monitoring urban functionalities

Cited by 10 publications

References 21 publications

Design and Validation of a Computational Program for Analysing Mental Maps: Aram Mental Map Analyzer

Design and Validation of a Computational Program for Analysing Mental Maps: Aram Mental Map Analyzer

Smart Cities Planning and Sustainable Urban Development through Development and Analyzing Mental Maps of Citizen Perceptions

Earth Observation for Sustainable Urban Planning in Developing Countries

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