The Urbangene Project
Experience from a Crowdsourced Mapping Campaign
Jens Ingensand
1
, Marion Nappez
1
, St
´
ephane Joost
2
, Ivo Widmer
2
, Olivier Ertz
3
and Daniel Rappo
3
1
GIS Lab, Department EC+G, University of Applied Sciences Western Switzerland, Yverdon-les-Bains, Switzerland
2
Laboratory of Geographical Information Systems (LASIG), School of Architecture, Civil and Environmental Engineering
(ENAC), Ecole Polytechnique F
´
ed
´
erale de Lausanne, Lausanne, Switzerland
3
Department Comem+, University of Applied Sciences Western Switzerland, Yverdon-les-Bains, Switzerland
{jens.ingensand, marion.nappez, olivier.ertz, daniel.rappo}@heig-vd.ch, {stephane.joost, ivo.widmer}@epfl.ch
Keywords:
Citizen Science, Crowdsourcing, Participatory WebGIS, Social Media, Urban Biodiversity, VGI.
Abstract:
Geospatial crowdsourcing applications are emerging systems that enable researchers to collect important in-
formation that otherwise would be difficult to obtain. In biodiversity monitoring, crowdsourcing is a promising
approach as it benefits from a large group of people with an often underestimated biodiversity and taxonomy
knowledge. Despite its huge potential, crowdsourcing approaches are still underrepresented in biodiversity
monitoring. We here evaluate a participatory crowdsourcing web mapping platform that was developed to get
information about geographic locations and biodiversity characteristics of urban ponds in the Geneva cross-
border region. An important fraction of urban ponds is assumed to be located on private grounds, which
makes the participatory crowdsourcing approach very valuable. A media campaign was initiated, encouraging
citizens participate and to digitize ponds. In this paper we a) evaluate and discuss the impact of the media
campaign on the usage behaviour and history of citizens using the crowdsourcing platform and b) assess the
quality of the digitized data that has been collected. This study shows that through media campaigns, citizens
can be mobilized and motivated to participate in biodiversity crowdsourcing projects. Results indicate that
large quantities of users were recruited through social media. However, only a small fraction of about 3% of
the mobilized people digitized ponds on the platform. The majority of these users (68%) digitized one pond
while 32% digitized two or more ponds. This study shows that it is important for crowdsourcing platforms
to be designed and planned in order to facilitate its usage. However, it is crucial for the success of such cam-
paigns to offer something in return to the users and to encourage them to interact among themselves. We
suggest that future crowdsourcing biodiversity mapping campaigns should have mobile-optimized interfaces.
Mobile devices have the potential to e. g. automatically register coordinates for biodiversity sighting and for
uploading respective pictures directly in the field.
1 INTRODUCTION
Spatial crowdsourcing systems are an emerging type
of systems. These systems have their roots in the
experience from PPGIS (public participatory GIS,
Sieber (2006)) and many non-spatial crowdsourcing
projects, such as wikipedia (wikipedia.org; Wikime-
dia Foundation Inc., San Francisco, USA). Accord-
ing to Goodchild and Sui (2011), there are two con-
verging trends that also contribute to the success of
spatial crowdsourcing systems: geographic informa-
tion systems are increasingly social and online social
networking sites such as Facebook are increasingly
location-based. The success of the OpenStreetMap
project (openstreetmap.org; Open Data Commons
Open Database License) is an example of a spatial
crowdsourcing system where data can potentially be
collected and used by everybody. Bartoschek and
Kessler (2013) state that most publications related to
volunteered geographic information (VGI) focus on
this project.
A key challenge is to get people to use a crowd-
sourcing system or application and to participate in
a mapping campaign. This challenge can be divided
into two components - on the one hand the targeted
citizens need to find the application and on the other
hand, citizens must want to use the system once dis-
covered. The incitement to participate in crowd-
sourced mapping campaigns is often given by existing
communities such as, for instance, the global ornitho-
logical network eBird (Robbins, 2013) or the crisis
mapping tool Ushahidi which has been successful for
178
Ingensand J., Nappez M., Joost S., Widmer I., Ertz O. and Rappo D..
The Urbangene Project - Experience from a Crowdsourced Mapping Campaign.
DOI: 10.5220/0005468501780184
In Proceedings of the 1st International Conference on Geographical Information Systems Theory, Applications and Management (GISTAM-2015), pages
178-184
ISBN: 978-989-758-099-4
Copyright
c
2015 SCITEPRESS (Science and Technology Publications, Lda.)
mapping observations of violence (Liu et al., 2010).
Both projects, Ushahidi and eBird, have one thing
in common - the participants motivation is already
given through the fact that there is a common inter-
est to collect data and to visualize and analyze data
that has been collected by others.
However, if there is no existing community avail-
able, scientists who want to collect specific data
through a crowdsourced mapping campaign face a
challenge in getting people to use their system. First
of all, potential participants need to be informed of
the system’s existence e.g. through media campaigns
or through social networks. Secondly, the system that
is used needs to be optimized for the tasks of sharing
and editing spatial data. According to Haklay (2013),
it is important that the equipment that volunteers uti-
lize in order to gather information is adapted to their
skills and personal knowledge.
Aquatic ecosystems in urban areas are influenced
and threatened by human activity, which often causes
fragmentation, degradation or loss of environments
and reduces connectivity between remaining habitat
patches. Ponds and streams are important biodiver-
sity hotspots in urban environments. In order to allow
a spatially explicit conservation planning for urban
aquatic ecosystems, with the goal to maintain, im-
prove and connect urban aquatic habitats, it is thus
important, in a first step, to locate and characterize
these vulnerable environments. We evaluated a par-
ticipatory web mapping platform, which allows for
the input and retrieval of information about the loca-
tion and characteristics of urban ponds. An impor-
tant fraction of ponds is assumed to be located on pri-
vate grounds, which makes the participatory crowd-
sourcing approach very valuable, as such information
would be difficult to obtain otherwise.
The platform, called Urbangene, allows citizens
to digitize ponds and to report specific species that
have been identified in or around these ponds. It was
developed in the framework of the biodiversity re-
search project Urbangene, giving its name to the plat-
form. The main goal of the Urbangene project is to
investigate the impact of urbanization on biodiversity
an thereby to allow for more sustainable urban devel-
opment and the conservation, management and pro-
motion of biodiversity in urban areas.
Urban biodiversity has both a direct and an in-
direct value for a city’s residents; it is for instance
important for the physical and psychological health
(Aldous, 2007; Fuller and Irvine, 2010). However,
urban aquatic biodiversity (such as ponds and its in-
habiting species) is less apparent to the citizens than,
for example, bird biodiversity. Moreover the map-
ping of observations of violence Liu et al. (2010)
seems to have a more direct gain to the residents of a
city. Thus, developers of the Urbangene platform first
had to call the attention of the residents to the urban
aquatic biodiversity problem through a media cam-
paign. Developers optimized the platforms interface
following the most important interface design guide-
lines (e.g. Shneiderman’s eight golden rules of in-
terface design (Shneiderman and Plaisant, 2009)) and
developed several mock-ups in order to test and dis-
cuss multiple design options. A challenge in estab-
lishing the design of the system was to identify the
potential end user of the platform.
In the following sections we will focus on the Ur-
bangene biodiversity mapping platform and the media
campaign that has been started in order to encourage
volunteers to digitize ponds. Thereafter we will ana-
lyze the results of the mapping campaign and respond
to the research questions:
1. Which medium was more successful in encour-
aging citizens to use the system? The type of
medium can give important indications for further
campaigns.
2. Is it possible to characterize the users of the plat-
form? When were they using the system? Where
were they located? How many times were they ac-
cessing the system? A user profile can help further
crowdsourcing campaigns to improve user inter-
faces and to adjust the systems to the users needs.
3. What is the quality of the digitized data? How
accurate are the results? Is there any evidence of
fraud? This question is important since it tells if
users were willing to collect usable data and if the
tool was adapted to the users skills and expecta-
tions.
Finally we will discuss the results and give our inten-
tions for further work.
2 THE URBANGENE PROJECT
AND PLATFORM
The main aim of the Urbangene project is to investi-
gate the impact of urbanization on biodiversity in the
Geneva cross-border area with the goal to allow for
more sustainable urban development and the conser-
vation, management and promotion of biodiversity in
urban areas. The Geneva cross-border area (Greater
Geneva area) includes urban, suburban and rural terri-
tories in both Switzerland and France around the city
of Geneva.
The main objectives of the Urbangene project are
thus the assessment of the current state and the dy-
namics of biodiversity, the quantification of landscape
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179
elements on gene dispersal and functional connectiv-
ity of both animal and plant species and, further, the
identification of factors that influence gene flow and
adaptation of species in urban areas.
In order to collect data, the web-based Urbangene
platform had been developed. The focus of this data
collection platform was on the identification and lo-
calization of species such as toads and newts, and also
on their habitats: ponds. Due to the fact that ponds of-
ten exist on private property, an important point was to
conceive the platform as a crowdsourced data collec-
tion system, and thereby to implicate the population
of the area. The main function requirement was the
digitization of ponds and the specification of species
that inhabit the ponds. Users would be able to see the
ponds and species digitized by other users and would
thus be encouraged to digitize other ponds.
On the client side, the Urbangene platform was
developed using HTML5/CSS3 technologies. Map-
ping functionality was implemented through the
JavaScript library Leaflet and enhanced by the jQuery
JavaScript library and its numerous extensions. On
the server side Apache, PHP and the database sys-
tem PostgreSQL/PostGIS were used for receiving and
storing user input.
Much emphasis has been put on the design of the
user interface in order to facilitate the task of digitiz-
ing ponds; e.g. an adaptive questionnaire has been
implemented that shows questions depending on the
answers that the user gave to previous questions or
messages that appear in order to guide the users. Fig-
ure 1 shows a screenshot of the platform.
Figure 1: A screenshot of the Urbangene platform.
Once the user gets to the web-based Urbangene
platform, a welcome screen is shown. The user then
proceeds to the map where the already digitized ponds
and the limits of the Greater Geneva area are shown.
The system then indicates through a message that a
new pond can be added through sliding a pond-icon
on the map. Thereby the location of a pond is digi-
tized as a point feature (Figure 1). Once the user has
put the icon on the map, the system requires the user
to zoom and to check the pond’s position. At the same
time, the questionnaire is shown and the user can fill
in the questions, such as:
the species identified in the pond (sample images
were shown, see Figure 1)
the distance to a natural space from the user’s res-
idence
how much time a week the user spends in nature
Another important question was whether the user
would allow scientists to tissue samples in order to
genotype the animals in the case where the pond was
located on their property. In addition, the platform al-
lows the user to upload pictures of observed species
which could not be clearly identified, and need to be
cross-checked by biodiversity experts. Once the ques-
tionnaire is completed, the user’s feedback is stored in
the database and its pond icon is made visible on the
map.
3 MEDIA CAMPAIGN
In order to call the citizens attention to the urban bio-
diversity thematic and to encourage them to partici-
pate in the pond survey, a media campaign was started
by the university’s media and communication center
and the creators of the Urbangene project. The me-
dia and communication center sent a press release
to a large number of newspapers and radio stations
throughout Switzerland. A project page and a Face-
book page were created, and the link to the platform
was published on web pages and forums.
The first articles about the Urbangene platform ap-
peared in four newspapers on the 20th of March 2014;
four articles appeared the day after and the national
Swiss Radio dedicated a short radio transmission to
the project. Overall, news about the Urbangene plat-
form appeared 13 times on Swiss media (see Figure
2).
4 DATA COLLECTION
In order to answer our research questions, we did
not only use the platform’s database that contained
the digitized ponds and the responses to the ques-
tionnaire, but also the system’s web server log. The
Apache log file contains useful information such as
the users’ ip-addresses, the time and date users ac-
cessed the system, the user’s browser type and the
URL from which the user arrived at the system.
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Figure 2: Extract from a newspaper article encouraging
readers to digitize ponds on the Urbangene biodiversity
mapping platform. (Tribune de Geneve, April 2, 2014).
The user’s ip-address can give information about
the Internet provider of the user and thus if users were
accessing the system using a wired Internet connec-
tion or through a mobile 3G or 4G network. More-
over ip2location databases (IP2Location.com, Pulau
Pinang, Malaysia) can give an approximate location
(e.g. at zip-code level) of the ip-address. The user’s
browser type allows to analyze if the user was using
a mobile device such as a tablet computer or a smart-
phone; in some cases it also gives information about
the operating system installed on the device (e.g. type
and version). The web page the user was visiting
before clicking on the platforms URL (the referrer)
gives an indication how the user found the system;
e.g. through a search-engine, through a newspaper’s
web page or through social media.
We parsed the Apache log file into a database and
aligned its data to the data that had been stored in the
database through the platform. This new database was
this study’s main source of information.
5 RESULTS
5.1 Data Collected
The data collected on the Urbangene platform
stretches over a period of five months; from the 20th
of March until end of August 2014. The main data for
this analysis can be characterized as follows:
After cleaning the log file for robots, test users and
other irregular data, we were able to identify 933
distinct IP addresses that used the system during
the given period of time.
53 ponds were digitized within the limits of the
Greater Geneva area.
34 distinct users digitized the 53 ponds.
Most digitized ponds were located in and around
the city of Geneva (within the borders of Switzer-
land). Only six ponds were digitized in France.
Figure 3 shows the locations of the ponds.
Figure 3: Map showing the results. Blue dots: ponds that
have been located and described by citizens using the Ur-
bangene biodiversity mapping platform. Pink area: the
French part of the Greater Geneva area, Orange area: the
Swiss part of the Greater Geneva area.
5.2 Effectiveness of the Media
Campaign
In order to measure the effectiveness of the media
campaign, we analyzed the referrers in the log file
(i.e. the page the user was visiting before connect-
ing to the platform). Figure 4 shows the results of
this analysis. Twenty-five percent of the users reached
the platform through the project’s homepage, 12%
through a media’s (newspaper or radio station home-
page) and 11% through a search engine. These num-
bers added together suggest that almost half of the
users (48%) found the system through either news-
paper or radio. 18% of the users found the URL of
the system through other homepages (e.g forums, etc)
and 34% of the users came from social networks such
as Facebook and Twitter. The high number of social
media users was surprising since the Facebook page
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only had about 30 followers at the time of writing this
paragraph.
The fact that only six ponds were digitized in
France could be an indication that the media cam-
paign did not sufficiently reach many citizens living
in France - however, the part of the Greater Geneva
region that is situated in France is partly mountain-
ous and much less populated than Geneva, the second
most populated city in Switzerland.
Figure 4: How the users found the platform, i.e. last Inter-
net pages users visited before connecting to the Urbangene
biodiversity mapping platform.
We also analyzed on which days the users used
the system and when the users digitized ponds. Fig-
ure 5 shows clear peaks at around the 20th and 21st
of March. Interestingly most of the ponds were digi-
tized a few days after the first articles appeared. These
results lead to the argumentation that the media cam-
paign quickly motivated many users to take a look at
the system; however, the interest faded after the first
week. The observation that users still digitized ponds
some days after the first peaks appeared, might be in-
terpreted that these users either were looking at the
newly indicated pond locations for the occurrence of
different species that were demanded in the question-
naire or went home after discovering the platform and
then digitized a pond.
Figure 5: Number of different IP-addresses that accessed
the Urbangene biodiversity mapping system and number of
digitized ponds from March to August 2014.
5.3 Characterization of the Users of the
System
Most users (59%) who accessed the system (we are
referring to the 933 distinct IP addresses) were using
a desktop or laptop computer, 8% a mobile system
such as a smartphone or a tablet computer and 33 %
were using a non-identified system.
Figure 6: Number of platform requests according to the
time of day.
Most users used the platform during office hours
with peaks at 10 a.m and 2 p.m. (see Figure 6); an
analysis of the Internet provider of the users showed
many different companies. A possible interpretation
of these numbers is that people used the system at
their workplace, after drinking a coffee and reading
the newspaper at 9 or 10 a.m. or after having lunch.
This hypotheses can be strengthened by an analysis of
the day of week people accessed the system - the data
showed that on average only 9% of the traffic gen-
erated on the site occurred on a Saturday or Sunday,
while 15% - 18% occurred on a working day. The
vast majority of users (68%) digitized one pond; few
users digitized two or three ponds and only one user
digitized six ponds. (see Figure 7).
The ip2location database that we used for iden-
tifying the position of the users gave an interesting
result for the users who digitized ponds: nine out of
34 users (26%) were located in the canton of Geneva,
three in France and seven in other Swiss cantons. 15
users (44%) were using a mobile broadband connec-
tion and it was thus not possible to identify a more
precise location than Switzerland. A presumably high
percentage of mobile device users was also confirmed
when we analyzed the browser type of the users who
digitized ponds - at least seven users (21%) were us-
ing a tablet computer.
More than half of the users who digitized a pond
(18 out of 33) answered that a natural space can be
found around their house; 5 out of 33 replied that na-
ture is close to where they live (some hundred me-
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Figure 7: Number of digitized ponds per user.
ters) and seven people did not answer the questions
at all. 10 people were spending at least one hour in a
natural space a day, while 13 were spending at least
some hours a week. The most common species that
had been identified was the common toad (bufo bufo)
(found in 33 ponds). The common frog (rana tempo-
raria) had been identified in 17 ponds and the alpine
newt (ichthyosaura alpestris) in 16 ponds.
5.4 Quality of the Digitized Ponds
The locations of the 53 digitized ponds were com-
pared to other data sources in order to verify its ac-
curacy. For the Swiss part of the Greater Geneva area
we used a pond database that had been established
by the Geneva Institute of Technology, Architecture
and Landscape (hepia). Moreover, we used Open-
StreetMap data and Google Maps imagery in order
to identify ponds that were not contained in the refer-
ence database from hepia.
These three reference data-sources confirmed the
location of 26 ponds (49%), 19 locations were not
confirmed and thus possibly errors (36%) and 8 lo-
cations (15%) were either not far from a confirmed
pond (and thus perhaps only an imprecision), not vis-
ible due to presumably covering trees, or objects that
are other water objects (e.g. fountains or swimming
pools)
6 DISCUSSION
We here analyzed the impact of a media campaign on
the usage behavior and history of citizens using the
Urbangene mapping platform. Although the area of
investigation was located in Switzerland and France,
the media campaign focused mainly on Switzerland.
This fact possibly explains why only few ponds were
digitized in France. The impact of the media cam-
paign could be seen in the fact that several hundred
people visited the mapping platform.
However, in relation to the effort of the media
campaign, the fact that only 3% of the users digitized
53 ponds might seem poor, moreover the traffic on the
site quickly declined after only a few days. Having
this in mind and along with the fact that most users
only digitized one single pond leads to the conclusion
that most users did not come back to check how the
project was evolving.
There are many motivational reasons for one user
to become a contributor (Shneiderman and Preece,
2009), yet one reason explanation for our observa-
tion might be found in Haklay (2013) who states that
public participation can be categorized into four lev-
els ranging from crowdsourcing (i.e. citizens that are
used as sensors) on the lowest level, distributed in-
telligence, participatory science and extreme citizen
science (e.g. citizen participating in the problem defi-
nition) on the highest level. In crowdsourcing citizens
are thereby used as data collectors and the sum of the
digitized data are not of direct interest to the users.
On the other hand, many successful crowdsourc-
ing systems such as OpenStreetMap offer something
in return for the work of the users: this is the possibil-
ity for one individual to reuse the data added by many
users. Another key for successful crowdsourcing bio-
diversity campaigns appears to be related to the level
of networking and organization of communities that
are interested in specific species. These communities
are often already well-organized and established and
in such cases crowdsourcing tools help to gather data
that the whole community is interested in.
The fact that many users found the platform
through social media is encouraging. The effort to
arrange Facebook pages or to tweet URLs is less than
starting a campaign including print media and radio
stations. Furthermore it is less demanding for the user
to click on a URL that is communicated through so-
cial media (e.g. a Facebook page) than retyping an
address that is printed in an article or communicated
during a radio transmission.
7 CONCLUSIONS AND FURTHER
WORK
This study indicates that through media campaigns,
many citizens can be mobilized and motivated to par-
ticipate in biodiversity crowdsourcing projects.
Even though it is important for crowdsourcing
platforms to be designed and planned in order to fa-
cilitate its usage, what is more crucial for the suc-
cess of such campaigns is to offer something in return
to the users. This would encourage users to interact
more among themselves in checking the data added
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183
by other users and possibly in adding new data to the
platform in the future.
Another important lesson learned is that social
media is able to recruit large quantities of users with
relatively little effort.
We suggest that future crowdsourced mapping
campaigns should have mobile-optimized interfaces.
Mobile devices such as smartphones or tablets are
promising tools for biodiversity monitoring during
outdoor activities. Applications for such systems have
the potential to for example automatically register co-
ordinates for biodiversity sighting and for uploading
respective pictures directly in the field. The usage
of mobile devices is increasing and users could be
recruited to spend some time using a crowdsourced
system during their journey to work or other activities
during which they could use their mobile devices. An-
other advantage is that most social media platforms
such as Facebook or Twitter are available on mobile
devices. Thereby users could be recruited through
mobile social media applications and then directed to
crowdsourced mapping platforms without the need to
switch device.
ACKNOWLEDGEMENTS
The authors would like to thank all the participants
who used the Urbangene platform and the Geneva
Institute of Technology, Architecture and Landscape
(hepia) for providing the pond-database.
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