| Article of the Month - 
	  February 2018 | 
		The use of Volunteered Geographic 
		Information (VGI) in noise mapping  
		
			
				|  |  |  |  |  | 
			
				| Bakogiannis 
				Efthimios | Charalampos 
				Kyriakidis | Maria Siti | Nikolaos 
				Kougioumtzidis | Chryssy Potsiou | 
		
		This paper was presented 
		at the conference in Bucharest, Romania. The aim of this paper is to 
		present an overview of a research about the monitoring of the urban 
		acoustic environment affordably and reliably, and investigating the 
		potential use of Volunteered Geographic Information (VGI) for such 
		applications in typical medium-sized cities. 
		
		SUMMARY
		The quality of the soundscape in cities is a significant parameter 
		that influences the percentage of population affected by noise and is a 
		component of the “nuisance” indicator often used for the assessment of 
		the urban environmental sustainability in Europe. However, limited 
		attention has been given by planners to the acoustic environment of a 
		city so far. In Greece, research on this issue and its representation at 
		the city scale has been conducted only for a limited number of large 
		cities, whereas in most of the cities and towns there is no available 
		data. 
		The aim of this paper is to present an overview of a research about 
		the monitoring of the urban acoustic environment affordably and 
		reliably, and investigating the potential use of Volunteered Geographic 
		Information (VGI) for such applications in typical medium-sized cities. 
		This research is conducted as part of the ongoing Sustainable Urban 
		Mobility Plan projects (SUMP), aiming to improve the urban landscape, 
		increase quality of life and transform cities into more compact and 
		liveable urban cores. 
		Once the urban design characteristics are listed 
		by the experts, audio recordings are collected through crowdsourcing 
		(using apps in smart phones) in several city spots, according to a 
		grid-based sampling methodology. Then, a sound map is created using the 
		Ordinary Kriging technique in GIS, while finally the collected noise 
		data are imported in OpenStreetMap (OSM) by the volunteers. The 
		methodology was tested in two Greek medium-sized city centers (Kozani 
		and Drama). The soundscape data were then assessed by taking into 
		consideration the European and national legislation about the urban 
		acoustic environment as well as the various characteristics of each 
		study area. As expected, results show that residents are exposed to high 
		sound levels during the day. However, sound levels in car-free zones are 
		considerably lower except from specific streets where motorcycles enter 
		illegally (for delivery or freight purposes). 
		In overall, this research proved that there is a strong potential of 
		using crowdsourcing techniques to collect noise data and monitor the 
		soundscape reliably and affordably. It is crucial for the municipalities 
		to engage citizens in participating to urban renewal projects in main 
		streets as well as in vulnerable or sensitive city areas (i.e. 
		neighborhoods, school zones) in order to raise awareness about noise 
		pollution and create a better acoustic environment. Through these case 
		studies, this paper points out that crowd sourced noise mapping may be 
		utilized as a reliable tool for participatory planning. The paper 
		provides considerations on how the proposed methodology may be further 
		tested and improved.
		1. CONSIDERING NEW TECHNOLOGIES FOR RECORDING THE URBAN SONIC 
		ENVIRONMENT 
		Over 50 years have passed since Murray Schafer studied the influence 
		of the sonic environment on people. However, the term “soundscape”, 
		which was used to explain this relationship (Rodriguez-Manzo, et.al., 
		2015; Schulte-Fortkamp and Jordan, 2016), is still up-to-date. Another 
		contemporary issue has to do with the transformations of the soundscape. 
		In contrast with the natural and urban environment, where the 
		differentiations could be easily understandable through aerial 
		photography techniques of remote sensing and mapping tools, the 
		investigation of the changes that occur in the soundscape (Schaffer, 
		1993) is not easy due to the fact that, in many areas, mapping of the 
		soundscape is not carried out although it constitutes a useful tool for 
		the evaluation of buildings and urban areas (Schulte-Fortkamp and 
		Jordan, 2016).
		The view of Maffei et.al. (2012) and Margaritis et.al.(2015), that 
		the sonic environment does not consist of a significant parameter in the 
		urban planning practice is well-founded even in Greece, where the only 
		official mapping of the soundscape has been carried out between 
		2012-2016 only in specific cities, based on the 13586/724/2006 Joint 
		Ministerial Decision (FEK B’ 384) that followed and embodied the 
		European Directive 2002/49/ΕC (Vogiatzis and Remy, 2017),  aimed at 
		confronting high levels of noise in cities using common ways for all  
		EU country members (Stoter, et.al., 2008; Licitra and Memoli, 2008). 
		However, these mapping projects do not constitute a complete 
		representation of the sonic environment, but only the environmental 
		noise [Strategic Noise Maps (S.N.M) and Noise Action Plans(N.A.P.)] 
		(Directive 2002/49/EC), which is only a parameter of the sonic 
		environment according to Rodriguez-Manzo et.al.(2015). The interest in 
		noise links to the fact that noise pollution is an essential problem in 
		urban areas (Schweizer, et.al., 2011; Pödör and Révész, 2014; Pödör, 
		et.al., 2015; Rodriguez-Manzo, et.al., 2015; Poslončec-Petrić, et.al., 
		2016; Pödör and Zentai, 2017). Indeed, Vasilev (2017) points out that 
		the increase of noise levels (0,5-1,0 dBA) in cities is a reality.
		Regarding the measurements and monitoring of noise levels, different 
		methodologies have been occasionally suggested. Such methodologies are: 
		noise recordings, population surveys and interviews, soundwalks and 
		noise mapping (Rodriguez-Manzo, et.al., 2015; Schulte-Fortkamp and 
		Jordan, 2016). Even for individual procedures, different techniques have 
		been proposed. In noise mapping, for instance, different methods and 
		tools can be used (Bennett et.al., 2010; Schulte-Fortkamp and 
		Jordan,2016) for data collection and representation. Indeed, according 
		to Schulte-Fortkamp and Jordan (2016), the natural conditions of a 
		soundscape can be measured by using binaural recording devices or 
		microphone arrays. Maps can be created by algorithms that produce maps 
		based on estimations or by using measured data (Cho, et.al., 2007; 
		Stoter, et.al., 2008). In practice, due to high cost (Schweizer, et.al., 
		2011), local authorities choose to monitor soundscape by placing sensors 
		in specific points, that usually do not cover the total surface of a 
		city.  According to Aiello et.al. (2016), this particular method is 
		a result of the European Directive 2002/49/ΕC, which requires European 
		countries to monitor noise levels produced by specific sources (road 
		traffic, railways, airports and industry). The same researchers (Aiello 
		et.al., 2016) point out that, due to many deficiencies observed, 
		epidemiological models are occasionally used for estimating noise 
		levels. These models are based on samples of small population or data 
		derived from smartphones or social media, in order to decrease the cost 
		of such research. The research of Podor and Revesz (2014), Podor et al. 
		(2015) and Podor and Zentai (2017) converge to the same opinion and 
		argue that it is fundamental to use data derived from crowdsensoring and 
		crowdsourcing for monitoring noise levels. That is why, according to the 
		European Directive 2002/49/ΕC, noise maps must be renewed every 5 years, 
		a task that is restricted by the economic conditions of certain 
		countries such as Hungary, to which these researches are referred, if 
		the used methods are the conventional ones. 
		During recent years, the European Commission has financed projects 
		that are based on crowdsourcing in which people have been used as 
		“sensors” (Podor, et.al., 2015). In these projects, people carry their 
		smartphones that are personal devices equipped with applications that 
		provide data without cost (Schweizer, et.al., 2011).  According to 
		Schweizer, et.al. 2011, smartphones constitute ideal platforms for 
		environmental data measurements as, beyond sound levels that are 
		recorded by the microphone which is incorporated in the device, they are 
		also equipped with GPS providing spatial information at the same time. 
		The advantages of smartphones is that they can be used in order for 
		researchers to achieve goals like: (a) low-cost data collection process, 
		(b) citizens’ participation for improving the quality of urban 
		environment and (c) constant monitoring of the soundscape, when people 
		use applications providing real time data. 
		 
		From the above can be concluded that participation of people consists 
		a significant process on which this paper focuses. The reasons are: (a) 
		volunteered participation is a necessary parameter in order to collect 
		data with low-cost budget (Schulte-Fortkamp and Jordan, 2016), (b) 
		volunteered participation has a great additional value as it constitutes 
		a process that increases the geospatial maturity of the society to 
		understand the design procedures and various planning matters 
		(Athanasopoulos and Stratigea, 2015; Bakogiannis, et.al., 2017) and (c) 
		the participation of people is an example of direct democracy that seals 
		transparency and social consensus through  a structured dialogue 
		procedure and interaction (Kyriakidis, 2012).
		The methodology proposed in this paper builds up on the 
		aforementioned literature elements focusing on noise data collection by 
		volunteers using a specific application. The pilot testing on the 
		methodology in the Greek cities of Kozani and Drama is later presented 
		in detail. 
		2.  METHODOLOGY
		2.1. Aim and Objectives
		Considering that noise mapping is required only for major cities of 
		each EU member country, and considering the lack of financial resources 
		of some EU states (e.g. Greece) to meet this requirement and expand this 
		practice to other cities (e.g. mid-sized cities), it is worthwhile 
		questioning to what extent crowdsourcing techniques could assist in 
		developing noise maps for mid-sized cities. Thus, the aim of this paper 
		is to develop a methodology for noise monitoring. This methodology 
		should be easily applicable, reliable and cost-effective.
		The case studies presented here focus on Greek cities, where 
		Sustainable Urban Mobility Plans (SUMP) are implemented. The above 
		research question is well-founded given the fact that the soundscape is 
		essential for the promotion of integrated urban and transportation 
		planning (e.g., reduction of noise levels in areas where it is 
		particularly intense). Moreover, soundscape could be used as an 
		indicator for the SUMP by comparing the previous to the subsequent noise 
		levels. 
		The main objectives of this study are to:  
		
			- examine if the results of surveys carried out by smart 
			phone equipment are satisfactory and
- promote the concept of open noise data as far as concerning the 
			studied cities, by uploading it in Open Street Map (OSM). 
2.2. Proposed Methodology
		In literature (Rodriguez-Manzo, et.al., 2015; Schulte-Fortkamp and 
		Jordan, 2016), there are many ways for recording and mapping the cities’ 
		soundscape. Such examples are soundwalks, sound recordings and 
		interviews with experts and locals. However, according to current 
		research, citizens’ participation consists of a usual process in smart 
		cities’ projects (Poslončec-Petrić, et.al., 2016).
		This trend relates to the time-consuming process of traditional noise 
		mapping as well as to the cost of its implementation. Indeed, the 
		methodology typically used for producing strategic noise maps includes 
		the existence of data-sets such as 3D digital ground models, city 
		traffic models, train traffic models (in case a train station is located 
		in the city under study) and the use of an ideal software for mapping 
		the sound levels (Garai and Fattori, 2009). In many European cities (and 
		in most Greek cities) there is no available data of such type and its 
		collection is costly. According to the Report entitled “Best Practice in 
		Strategic Noise Mapping”, developed by the subgroup END noise mapping of 
		the CEDR Project Group Road Noise 2 (2013), the cost of noise mapping is 
		significant; an approximate estimation of the average total cost for 
		noise mapping per km mapped is € 604.
		In this research, as drafted and tested in Kozani and Drama, a new 
		methodology was used in order to map the noise levels. The methodology 
		diagram is graphically presented in Figure 1, including the following 
		steps: a) Study area selection, b) field sampling organization, c) 
		preparing the volunteers, d) recordings- data collection, e) data 
		digitization by volunteers in OSM, f) publishing the maps. In these 
		steps a team of experts shall enhance the maps produced and assist 
		volunteers in developing a readable and useful map. Although this 
		methodology differs from the one usually preferred, however, it could be 
		an easily applicable and cost-effective alternative for monitoring 
		noise, mainly in small and mid-sized cities. It is also important that 
		through importing data into OSM, it is possible to create an interactive 
		noise map. The next step will be to put in place a dynamic map in which 
		the data collected by the residents through their smartphones will be 
		presented simultaneously on the map. In that way, noise will be 
		constantly monitored and presented in the wide public.
		For the research in Kozani and Drama, the methodology was organized 
		as presented below.
		
		
		Figure 1: Block diagram of the proposed 
		methodology. Source: Own Elaboration.
		2.2.1. Study areas selection
		The cities chosen for this research are medium-sized cities of 
		Greece. Kozani is located in the Region of West Macedonia, Greece; and 
		its population is 41.066 residents (2011 census). Drama is located in 
		the Region of Eastern Macedonia and Thrace; and its population is 44.823 
		residents (2011 census). The two cities were selected for this paper due 
		to their common characteristics (e.g. population; their central 
		districts have been developed without strict city plans over the 
		centuries; arterial roads are passing through their central districts; 
		their central districts display analogous land use dispersion and 
		clustering; neither Strategic Noise Map. nor Noise Action Plans have 
		been conducted for Kozani and Drama as they are medium-sized cities and 
		there is no obligation to implement them, according to Dir. 2002/49/EC).
		The study areas in these two cities involve a number of central 
		functions and a mix of land uses, with commercial, recreational and 
		administrative uses being dominant. These areas are expected to present 
		several land use conflicts due to their functional centrality and the 
		accumulation of high people-concentration especially at peak times.
		Considering the above, central districts of Kozani and Drama were 
		selected as study areas for the field research. Due to differences in 
		the geography of these two cities, different number of recordings have 
		been conducted in each one (Figure 2).
		
		 
 
		Figure 2. Field sampling organization: Recording 
		points in the study areas of Kozani (left) and Drama (right). 
		Source: Own Elaboration. (click for larger size)
		2.2.2. Data collection
		The data collection was carried out with the help of volunteers 
		(crowdsourcing), who used their smartphones, following the paradigm of a 
		series of similar surveys (Pödör and Révész, 2014; Garcia-Marti, 2014; 
		Aletta, et.al., 2016). The volunteers participated in the research, upon 
		invitation. Volunteers had no hearing or vision problems.
		The chosen method conforms to that of systematic sampling, where 
		sampling points are selected using a grid for selecting points. This 
		method was used as it adequately covers all study areas.
		The grid dimensions for the calculation of the points in the two 
		cities were defined as 200 x 200 m. separating the study areas in 
		squares of 200 m. sides, similar to the research by Margaritis et.al. 
		(2015). The recording points were located at the center of the squares 
		(as shown in Figure 2), whereas in cases where measurements at the 
		designated points were not possible due to physical and/or legal 
		restrictions (e.g., buildings, private space etc.), closest points were 
		selected.
		The calculation and assessment process took place at different time 
		periods for the two cities: March 2017 in Kozani and July 2017 in Drama 
		(for one week in both cities). The volunteers (3 volunteers in each 
		city) recorded noise levels (quantitative data) in the various sites for 
		2 minutes each, using the Sound Meter digital sound recorder, a free 
		smartphone application. This application measures the sound level (or 
		SPL), which is calculated from the following equation (Raymond, n.r.):
		
		Where the variables stand for:
		SPL = sound pressure level, decibels (db)
		P = sound wave pressure, newtons/meter2
		Pref = reference pressure or hearing threshold, newton/meter2
		The duration of recordings was 3-4 hours/day. The same process was 
		repeated every day for a week. In order to reduce faulty results, a 
		member of the team of experts collects the data with the volunteers 
		during the first day of recordings. Thus, it is possible to answer to 
		any question concerning the recording process. This process consists of 
		a pilot study.
		Volunteers also kept a draft calendar in which they reported the type 
		of the sounds they heard (qualitative data) during the recording 
		process. These data were collected in order for the SUMPs of Kozani and 
		Drama to be implemented. Measurements were taken during both working and 
		non-working hours. However, the analysis assessed measurements that were 
		taken only in working hours because: (a) cities have more residents and 
		visitors on the move during these hours, and (b) the study areas are 
		more congested at working hours and therefore noise levels are higher.
		
		2.2.3. Noise maps production
		Upon completion of the field survey, the recordings were mapped using 
		QGIS and ArcGIS software. Different software was used to produce maps in 
		each city, as the cities were studied through different research 
		programs. The maps produced included variables according to: (a) the 
		average value of the recorded noise levels; (b) the minimum values; and 
		(c) the peak values for working hours. 
		The mapping process is usually implemented by using various 
		interpolation techniques (Margaritis, et.al., 2015). Li and Heap (2008) 
		present 26 interpolation techniques that are quite similar and can be 
		performed for mapping processes. Geymen and Bostanci (2012) support that 
		Inverse Distance Wight Method (IDW), Ordinary Kriging Method (OK) and 
		Redial Basis Functions Method (RBF) are the three most useful methods 
		for noise mapping, as they have selected these techniques for 
		representation of noise values. Margaritis et.al. (2015) underline that 
		Kriging and IDW techniques are the most widely known in the field of 
		noise mapping. However, the literature review (Geymen and Bostanci, 
		2012; Aletta and Kang, 2015; Margaritis, et.al., 2015) showed that the 
		Kriging technique is a powerful method, most frequently preferred for 
		similar purposes. Based on the above, Kriging methodology was selected 
		for mapping in these studies. The 2D raster surfaces were created based 
		on the OK Method considering all the points of each study area. Adobe 
		Photoshop CC14 was also used for improving the aesthetic of the maps. 
		The analysis and mapping process presented above was conducted by the 
		team of experts who were coordinating the data collection process. 
		Finally, maps were uploaded by volunteers in the Open Street Map 
		platform in order to provide free access information for anyone 
		interested. Due to the fact that volunteers were people with some 
		technical skills, not much special training was necessary. However, in 
		case volunteers need to be trained, a short training session with 
		instructions could be organized at the initial stage of the field 
		research. 
		2.2.4. Limitations
		Research limitations are mainly related to the time frame of the 
		research. The field research has been conducted at different times for 
		each city, as they were part of different projects with different time 
		frames and deadlines. 
		As for risk management, a moving vehicle could cause bodily injury 
		and property damage to volunteers and researchers. Moreover, the 
		volunteers had to conduct the research during spring and summer when the 
		temperature is high and they had to be exposed in the sun for many hours 
		a day.  
		3. ANALYSIS AND RESULTS
		Although the derived noise data were collected over a one-week period 
		in 2017 by volunteers who recorded noise at the street level, they 
		handed in quite rational noise maps, as expected. On that basis, it 
		could be considered that results are reliable enough to draw the 
		conclusions presented below. 
		Using QGIS and ArcGIS, collected data were presented as a point 
		feature layer. In order to realize where there is a spatial relationship 
		among the values (minimum, maximum and mid values) represented by each 
		point feature, the OK method was used. Figures 3 and 4 depict noise maps 
		for each city. The noise maps were developed by taking into account that 
		mid values are the most important as they capture a more in-depth 
		analysis by excluding extreme (min and max) values.
		The results for Kozani could be concluded in the following points:
		
			-  High intensity noise was noticed in Kozani averaging from 
			39 to 64 dB. As seen in Figure 3b, sounds recorded in a large part 
			of the study area are higher than 55 Db, which is the noise level 
			defined by the World Health Organization as the limit at which 
			people are at serious health risk. 
- Higher intensity sounds were recorded at the northwest region of 
			the study area, due to the following facts: (a) the existence of 
			busy streets (i.e. Dimokratias Str., Fon Kozani Str., Paulou Mela 
			Str., M. Alexandrou Str.), (b) the concentration of a large number 
			of commercial/ recreation stores and (c) administrative uses and 
			points of high interest.
- Values higher than 84dB (Figure 3c) -sometimes ephemeral- were 
			recorded in a large part of the city. This is a worrying fact, 
			considering that the 87 dB threshold is the limit set by the Greek 
			law (Presidential Decree 149/2006) for a maximum fixed exposure 
			value for a worker in an 8-hour work day.  
- Noise levels are 
			relatively high, even in the case of the minimum values (30dB) 
			recorded (Figure 3a), given the fact that levels higher than 23 dB 
			can cause problems in the understanding of speech and thus the 
			communication of people (Anon, n.r.). The intensity of the recorded 
			sounds is higher in the northwest side of the study area, where the 
			concentration of commercial/ recreational land uses is higher, and 
			therefore the higher number of daily discussions is held, especially 
			during working days and hours.  
- The north-western part of the study area shows small 
			fluctuations, as shown in Figures 3a-3c. Recorded sounds are mostly 
			high during working hours (Figures 3a-3c). Minor fluctuations in 
			sound intensity are also recorded in areas located in the east of 
			the study area. St. George’s area, the University of West Macedonia 
			campus area and spaces around OSE (inactive train station) are the 
			quietest areas throughout the study area.
- Noise levels are a significant parameter of the urban 
			environment. In the case of Kozani this is quite evident while 
			observing the noise maps for the semi- pedestrianized city center 
			where the smallest range of peak sound levels is observed, as 
			opposed to the areas near major streets where larger peak sound 
			levels are observed. 
			
			Figure 3. Noise maps for Kozani. Source: Own 
			Elaboration. (click for larger size)
			Similarly, the results for Drama can be concluded by the 
			following key points: 
			
			
			Figure 4. Noise maps for Drama. 
			Source: Own Elaboration. (click for larger size)
	  
			- Higher volumes were recorded in Drama compared to the city of Kozani. These, on 
average, range from 59 to 98 dB. Recordings show that the intensity of the 
recorded noise exceeds the threshold of 55 dB which, as previously noted, is the 
noise level defined by the World Health Organization as the limit an excess of 
which places people in a serious risk to their health
-  The 87dB 
			threshold for the continuous 8-hour exposure, as set out in the 
			Greek Legal Framework, is surpassed in much of the city center study 
			area, even momentarily.  
-  Noise levels in central areas exceed the sound level of 
			41dB that allows people to communicate properly. 
- As shown in Figure 
			4a there is no recording of less than 41 dB.
-  Highest noise levels were recorded in central areas close 
			to main streets that attract large numbers of motorized vehicles
-  The area around the OSE (inactive train station) appears 
			to have low noise levels, although adverse results were expected. 
			The local maximum levels are lower than those recorded at the city 
			centre, while the overall highest in the area are relatively low. In 
			overall there are small fluctuations observed in the area.
-  As previously noted, the urban environment is 
			significantly associated with noise levels. This is quite obvious in 
			the case of Agia Varvara park, which seems to function as a sound 
			fence for its surroundings. The recorded average high and low sound 
			levels in the vicinity of the park are significantly lower than 
			those recorded throughout the city.
Summarizing the above, both cities encounter issues in terms of noise 
		pollution. Pollution is higher in the city of Drama although there are 
		larger green areas and measurements were taken in the summer period. The 
		greater extent of urban morphology in Kozani, along with the latest 
		pedestrianization projects in the city centre, appear to be the two key 
		elements contributing to the maintenance of lower noise levels.
		As mentioned before, noise data for these two cities is now available 
		through OSM. Figures 5 and 6 present a part of each city map in OSM, 
		where the noise recordings are presented.  Data were digitized by 
		the volunteers who were not trained due to the fact that they were 
		already familiar with the OSM. Instructions about the recording process 
		have been given and a pilot study was also implemented. It should be 
		mentioned that in case volunteers need to be trained, a short training 
		session could be organized, as Figure 1 presents. 
		
			Figures 5 and 6. Noise recordings in Kozani 
			(Fig.5-left) and Drama (Fig 6-right), presented in OSM. Source: Own 
			Elaboration. (click for larger size)
		4. CONCLUSIONS
		Noise mapping is a strategy established for monitoring noise levels 
		and protecting human health.  Indeed, the European Directive 
		2002/49/EC proposed plans and maps which had to be implemented for 
		specific cities and transport infrastructures. Through this Directive, a 
		detailed methodology is proposed in which specific indicators should be 
		used. Although the results of this method are accurate, however, this is 
		a time-consuming and costly method. Thus, it is not possible to be 
		applied in medium and small sized cities for which the compilation of 
		noise studies is not compulsory by the law. In these cases, citizen 
		participation may help in the collection and publishing of the needed 
		data.
		The aim of this paper is to develop a new methodology for noise 
		mapping. This methodology should be easily applicable and 
		cost-effective. Its rationale is based on community engagement and 
		volunteering. The following steps outline a simple and effective 
		strategy for mapping the noise levels in a city:
		
			-  Organizing the field systematic sampling,
-  Preparing the volunteers who are responsible for 
			collecting the data and digitizing them in the OSM,
-  Pilot study- Collecting the data,
-  Developing the maps while simultaneously volunteers are 
			uploading the data in the OSM,
-  Publishing the maps. 
In cases of Kozani and Drama, the above methodology was applied. 
		Three volunteers from each city participated in this project. They 
		collected noise data for one week in each city by using their 
		smartphones. More specifically, they have used one free smart phone 
		application, named Sound Meter. These data are differentiated from the 
		data that should be collected according to the Directive 2002/49/EC 
		because: (a) they were collected at the street level, while the 
		Directive imposed that the recording should take place in the height of 
		4 meters and (b) recordings lasted for approximately 3-4 hours/day while 
		the Directive imposed that the recording should take place 24 hours/day. 
		The first issue should be further examined in order to adjust the 
		proposed limits of noise exposure taking into account the height in 
		which the recording are conducted. The second issue can be faced by 
		attracting volunteers in large numbers with various motivations. The 
		more people participate, the more recordings will be implemented. 
		However, taking into account the fact that there is no available data 
		for many Greek cities, satisfactory information is provided through this 
		methodology that can be helpful for researchers in order to understand 
		the soundscape of each city.
		This has become obvious through the case studies presented above. 
		Through this methodology transport engineers, planners, decision makers 
		and citizens can understand how important it is to use sustainable means 
		of urban transport and to minimize road asphalt surfaces within city 
		centers. Indeed, through noise mapping in Kozani and Drama, results 
		showed that the street pattern (morphology, geometric characteristics, 
		land use, etc) is related to its soundscape. More specifically, it was 
		evident that in semi-pedestrianized areas, the noise levels were lower 
		while the opposite was observed in areas where roads with a high traffic 
		load are located. 
		It should be noticed that the recorded data is now presented at the 
		OSM and will be available (immediately and free of charge) for anyone. 
		OSM functions as an interactive map from which citizens can easily find 
		or transform the existing information presented in data point format. 
		However, until now it has not been possible for citizens to look at the 
		noise map produced by the team of experts. This is a problem which shall 
		be resolved in the next phase of this research. Also, an important 
		following step is the placement of a dynamic map on a public central 
		space. A dynamic map may be compiled with data collected by residents, 
		who will provide it by using specific apps through their smartphones by 
		which noise will be constantly monitored. This specific research may 
		play a catalytic role in informing and raising public awareness which is 
		crucial for the compilation of the Sustainable Urban Mobility Plans in 
		these cities. In the future, it would be crucial to test this 
		methodology in order to realize if it is applicable and provides 
		accurate data. To sum up, the methodology proposed above has the 
		potential to provide representative data in a cost-effective way. 
		Moreover, its use is based on community engagement and helps to inform 
		people about the quality of life in their cities and the projects that 
		may take place in the near future. Furthermore, these data are available 
		to everyone through OSM. Finally, there is room for improvement in order 
		for this methodology to be better applicable and readable, while it can 
		constantly provide noise information helping in noise monitoring at low 
		cost. Thus, this methodology may be an important tool for planners and 
		researchers aiming to contribute to the enhancement of the quality of 
		city life
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BIOGRAPHICAL NOTES
		
			
				|  | Bakogiannis Efthimios is a surveyor (Und. 
				Dipl, NTUA) and he has a Ph.D. in urban and transportation 
				planning (Ph.D.). He is a member in the Sustainable Mobility 
				Unit and he is an active practitioner in the fields of urban and 
				transportation planning. | 
			
				|  | Charalampos Kyriakidis is an Urban Planner 
				(Und. Dipl., University of Thessaly – M.Sc. UCL). He is 
				conducting a Ph.D. research in the field of urban design and 
				planning in the Department of Geography and Regional Planning in 
				NTUA. He is a member in the Sustainable Mobility Unit and he is 
				an active practitioner in the fields of his expertise.  
				 | 
			
				|  | Maria Siti is a surveyor (Und. Dipl, NTUA – 
				M.Sc. Un. of Strathclyde). She is conducting a Ph.D. research in 
				the field of urban planning in the Department of Geography and 
				Regional Planning in NTUA. She is a member in the Sustainable 
				Mobility Unit and she is an active practitioner in the fields of 
				surveying engineering and urban planning. | 
			
				|  | Nikolaos Kougioumtzidis is an undergraduate 
				student in the School of Rural and Surveying Engineering, NTUA. | 
			
				|  | Chryssy Potsiou is a Professor at NTUA. She 
				has 30 years experience in education, training and research. 
				Since 1982 she is active in the International Federation of 
				Surveyors (FIG) and currently she is the President of FIG. She 
				has organized several international conferences. She has been 
				contributor, co-author or main author of many publications and 
				has written more than 110 scientific papers. | 
		
		CONTACTS
		Dr. Efthimios Bakogiannis
		National Technical University of Athens
		School of Rural and Surveying Engineering
		Department of Geography and Regional Planning
		9 Iroon Polytechniou Str., Zografou Campus, 15780
		Athens
		GREECE
		Tel. +30 210 772 11 53
		Fax + 30 210 772 27 52
		Email: ebako@mail.ntua.gr 
		Web Site: www.smu.gr
		Mr. Kyriakidis Charalampos (c.Ph.D.)
		National Technical University of Athens
		School of Rural and Surveying Engineering
		Department of Geography and Regional Planning
		9 Iroon Polytechniou Str., Zografou Campus, 15780
		Athens
		GREECE
		Tel. +30 210 772 11 53
		Fax + 30 210 772 27 52
		Email: 
		kyriakidisharry@gmail.com 
		Web Site: www.smu.gr 
		Mrs. Siti Maria (c.Ph.D.) 
		National Technical University of Athens
		School of Rural and Surveying Engineering
		Department of Geography and Regional Planning
		9 Iroon Polytechniou Str., Zografou Campus, 15780
		Athens
		GREECE
		Tel. +30 210 772 11 53
		Fax + 30 210 772 27 52
		Email: sitim.atm@gmail.com
		
		Web Site: www.smu.gr 
		Nikolaos Kougioumtzidis
		National Technical University of Athens
		School of Rural and Surveying Engineering
		9 Iroon Polytechniou Str., Zografou Campus, 15780
		Athens
		GREECE
		Email: nickkouyioyi@gmail.com 
		
		Chryssy Potsiou 
		National Technical University of Athens
		School of Rural and Surveying Engineering
		Department of Geography and Regional Planning
		9 Iroon Polytechniou Str., Zografou Campus, 15780
		Athens
		GREECE
		Tel. +30 210 772 2688
		Fax +30 210 7722677
		Email: chryssyp@survey.ntua.gr