Scientific- Research Quarterly of Geographical Data (SEPEHR)

Scientific- Research Quarterly of Geographical Data (SEPEHR)

Spatial description of indoor space in Volunteered Geographic Information environments

Document Type : Research Paper

Authors
Sara Haghbayan 1
Mohammad Reza Malek 2
1 MSc in GIS, Department of GIS, Faculty of geodesy and geomatics eng.,K. N. Toosi University of Technology
2 Associate professor, Department of GIS, Faculty of geodesy and geomatics eng.,K. N. Toosi University of Technology
10.22131/sepehr.2020.38610
Abstract
Extended Abstract
Introduction
Recently, different volunteered Geographic Information (VGI)databases and websites have been launched for a variety of purposes and different groups of users. Various groups and portals collect and share these data. Thus, there is a huge potential for the participation of millions of people who can act like remote sensors and share their data with other members of the group without any cost.Therefore,diffrent users with different skill levelscan provide spatial data through personalized measurements. Various research perspectives have shown that sometimes Volunteered Geographic Information can compete with business data.The present research seeks to solve the problems in searching and finding properties, and describe indoor space using visual components in web-basedplatforms. The impact of spatial information on satisfaction of residentsortheir problems has made this research especially important.Most of related studiessought to provide models for estimationof prices, and the impact of environmental factors on the price of real estates. They also have endeavored tocreate websites for residential real estatesearch with an emphasis on descriptive information.The present research seeks to describe indoor space of residential real estate using spatial tools.In this regard, criteria like height, dimensions, topological relationships, shape, color, geographic location, and directional relationships are considered.Description of residential properties’ indoor space requires information in both spatial and descriptive dimensions. Due to the especial potential of Geospatial Information System in the simultaneous visualization of spatial and descriptive information, spatial analysis was used in the present study.
Clearly, any research is performed based on a set of presuppositions. Particularly when we seek to theoretically investigate a process like modeling or design an information system, the work scope will be very wide and serious challenges will occur without proper assumptions. The present study assumes equal spatial perception, verbal expression and visualizationabilityin all people. It is also assumed that all estate visitors havecell phones equipped with cameras and Global Positioning System and their response to qualitative relationships is better than that of quantitative relationships. Moreover,real estateis used as a synonym for apartmentin this research.
 Materials & Methods
Considering the critical role of the ordinary users and the fact that survey processes are usually expensive and time consuming, volunteered spatial information environments are the most appropriate way of gathering people’s spatial perception. Not only these environments are rather easy to use, but also they simultaneously receive up-to-date information from the participant and provide them with appropriate services according to their status.
After modeling and designing, the proposed systemwas implemented in Visual Studio 2012 platform using ASP.NET framework andC#language. Server Structured Query Language (SQL) Database 2012 was usedto save spatial information. Tehran District 14 (longitude: 51.46207, latitude: 35.66905) was chosen as the study area and data collected from several residential properties was recorded in our database.
 Results & Discussion
Results indicate more than 65 percent conformity between the mental image generated using the proposed method and the reality. Users’ satisfaction with the proposed model was compared with their satisfaction with three popular Iranian sites, and a foreign site regarding. The impact of tools applied in these websites was also investigated. Results indicate 78.78% satisfaction with the proposed system, which is the highest level of satisfaction as compared to other studied websites.Moreover, compared to other toolsinvestigated in the present study,virtual tours and thenmaps are more in visualization.Sincespatial perceptions depends on various parameters such aspersonal interests, spatial dimensions, gender, age, education, culture, and fields of study, different groups were investigated in the present study.
 Conclusion
Using information collected inVolunteered Geographic Informationenvironments, ordinary people can share information and use each other’s experiences and opinions. This improves their knowledge level and results in a better understanding of the advantages and disadvantages of different real estates. Due to increased knowledge level, people will not select undesirable properties. This will create a competitive market and increase designers and engineers’attention to indoor space, which will consequently increase ordinary users’welfare.
Keywords
Volunteered Geographic Information (VGI)
Indoor Space
spatial tools
Real estate
1-Afifi, M., Parke, B., & Al-Hussein, M. (2014). Integrated approach for older adult friendly home staircase architectural design. Automation in Construction, 39, 117-125.
2-Allen, M. T., Cadena, A., Rutherford, J., & Rutherford, R. C. (2015). Effects of Real Estate Brokers’ Marketing Strategies: Public Open Houses, Broker Open Houses, MLS Virtual Tours, and MLS Photographs. Journal of Real Estate Research, 37(3), 343-369.
3-Becker, T., Nagel, C., & Kolbe, T. H. (2009). A multilayered space-event model for navigation in indoor spaces 3D geo-information sciences (pp. 61-77): Springer.
4-Bermejo, C., & Hui, P. (2017). Steal Your Life Using 5 Cents: Hacking Android Smartphones with NFC Tags. arXiv preprint arXiv:1705.02081.
5-Boumová, I., & Zdráhalová, J. (2016). The Apartment with the Best Floor Plan Layout: Architects versus Non-architects. Critical Housing Analysis, 3(1), 30-41.
6-Egenhofer, M. J., & Al-Taha, K. K. (1992). Reasoning about gradual changes of topological relationships Theories and methods of spatio-temporal reasoning in geographic space (pp. 196-219): Springer.
7-Falomir, Z., Museros, L., Castelló, V., & Gonzalez-Abril, L. (2013). Qualitative distances and qualitative image descriptions for representing indoor scenes in robotics. Pattern Recognition Letters, 34(7), 731-743.
8-Felfernig, A., Friedrich, G., & Schmidt-Thieme, L. (2007). Guest editors’ introduction: Recommender systems. IEEE Intelligent Systems, 22(3), 18-21.
9-Frontczak, M., & Wargocki, P. (2011). Literature survey on how different factors influence human comfort in indoor environments. Building and Environment, 46(4), 922-937.
10-Goetz, M., & Zipf, A. (2013). The evolution of geo-crowdsourcing: bringing volunteered geographic information to the third dimension Crowdsourcing geographic knowledge (pp. 139-159): Springer.
11-Gustafson, J., Bell, L., Beskow, J., Boye, J., Carlson, R., Edlund, J., . . . Wirén, M. (2000). AdApt—a multimodal conversational dialogue system in an apartment domain. Paper presented at the The Sixth International Conference on Spoken Language Processing (ICSLP), Beijing, China.
12-Han, J., Zhu, J., Li, Y., Yu, X., Wang, S., Wu, G., . . . Momma, K. (2012). Experimental visualization of lithium conduction pathways in garnet-type Li 7 La 3 Zr 2 O 12. Chemical Communications, 48(79), 9840-9842.
13-Ho, H.-P., Chang, C.-T., & Ku, C.-Y. (2015). House selection via the internet by considering homebuyers’ risk attitudes with S-shaped utility functions. European Journal of Operational Research, 241(1), 188-201.
14-Jamali, A., Abdul Rahman, A., & Boguslawski, P. (2016). 3D topologial indoor building modeling integrated with open street map.
15-Jovanović, A., Pejić, P., Djorić-Veljković, S., Karamarković, J., & Djelić, M. (2014). Importance of building orientation in determining daylighting quality in student dorm rooms: Physical and simulated daylighting parameters’ values compared to subjective survey results. Energy and Buildings, 77, 158-170.
16-Kaklauskas, A., Zavadskas, E. K., Banaitis, A., & Šatkauskas, G. (2007). Defining the utility and market value of a real estate: a multiple criteria approach. International Journal of Strategic Property Management, 11(2), 107-120.
17-Kurraz, H. A., & Ziara, M. M. (2015). Towards lowering the cost of houses in Palestine: New perspective. IUG Journal of Natural Studies, 15(2).
18-Lee, S., & Ha, M. (2013). Customer interactive building information modeling for apartment unit design. Automation in Construction, 35, 424-430.
19-Lin, Z., Anderson, G. D., & Anderson, T. (2003). Enabling Real Estate Businesses on the Web: From E-Business Model to The Application Services.
20-Medjdoub, B., & Yannou, B. (2000). Separating topology and geometry in space planning. Computer-aided design, 32(1), 39-61.
21-Meyers-Levy, J., & Zhu, R. (2007). The influence of ceiling height: The effect of priming on the type of processing that people use. Journal of Consumer Research, 34(2), 174-186.
22-Muhanna, W., & Wolf, J. (2002). The impact of e-commerce on the real estate industry: Baen and Guttery revisited. Journal of Real Estate Portfolio Management, 8(2), 141-152.
Oberfeld, D., Hecht, H., & Gamer, M. (2010). Surface lightness influences perceived room height. The Quarterly Journal of Experimental Psychology, 63(10), 1999-2011.
23-Olefson, S. B. (1996). Method and apparatus for selection and viewing real estate properties: Google Patents.
Pekkonen, M., Du, L., Skön, J.-P., Raatikainen, M., & Haverinen-Shaughnessy, U. (2015). The influence of tenure status on housing satisfaction and indoor environmental quality in Finnish apartment buildings. Building and Environment, 89, 134-140.
24-Salajegheh, J., Hakimpour, F., & Esmaeily, A. (2014). Developing a web-based system by integrating VGI and SDI for real estate management and marketing. The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 40(2), 231.
25-Salleh, S. A., Salleh, W. M. N. W., Nawawi, A. H., & Sadek, E. S. S. M. (2008). The Integration of 3D GIS and Virtual Technology in the Design and Development of Residential Property Marketing Information System (GRPMIS). Computer and Information Science, 1(4), 37.
26-Shukur, F., Othman, N., & Nawawi, A. H. (2016). The values of parks to the house residents. Asian Journal of Environment-Behaviour Studies, 1(1), 113-122.
27-Soleimani, S. (2015). Landscape Description in Volunteered Geographic Information (VGI) Using Spatial and Temporal Relationships. Unpublished M. Sc. Thesis, KNT University, Tehran, Iran (In Persian).
Sonawane, M. B., & Mhaske, S. Y. (2016). Daylighting estimation and analysis in residential apartment building: GIS based approach. Paper presented at the IOP Conference Series: Earth and Environmental Science.
28-Uttal, D. H., Fisher, J. A., & Taylor, H. A. (2006). Words and maps: developmental changes in mental models of spatial information acquired from descriptions and depictions. Developmental Science, 9(2), 221-235.
29-Vartanian, O., Navarrete, G., Chatterjee, A., Fich, L. B., Gonzalez-Mora, J. L., Leder, H., . . . Skov, M. (2015). Architectural design and the brain: effects of ceiling height and perceived enclosure on beauty judgments and approach-avoidance decisions. Journal of environmental psychology, 41, 10-18.
30-Veitch, J., Christoffersen, J., & Galasiu, A. (2012). Daylight and View through Residential Windows: Effects on Well-being. LD+ A Magazine (October 1, 2012).