Journal of Geographic Information System, 2011, 3, 382-389
doi:10.4236/jgis.2011.34037 Published Online October 2011 (http://www.SciRP.org/journal/jgis)
Web-Based GIS System for Real-Time Field Data
Collection Using a Personal Mobile Phone
Ko Ko Lwin, Yuji Murayama
Graduate School of Life and Environmental Sciences, University of Tsukuba, Tsukuba, Japan
Received June 18, 2011; revised July 25, 2011; accepted August 8, 2011
Abstract
Recently, the use of mobile communication devices, such as smart phones and cellular phones, in field data
collection is increasing due to the emergence of embedded Global Position Systems (GPS) and Wi-Fi Inter-
net access. Accurate, timely and handy field data collection is required for disaster management and quick
response during emergencies. In this article, we introduce a web-based GIS system to collect the field data
from personal mobile phones through a Post Office Protocol POP3 mail server. The main objective of this
work is to demonstrate a real-time field data collection method to students using their mobile phones to col-
lect field data in a timely and handy manner, either in individual or group surveys at local or global scale re-
search.
Keywords: Web-Based GIS System, Real-Time Field Data Collection, Personal Mobile Phone, POP3 Mail
Server
1. Introduction
Geospatial data collection is one of the important tasks
for many spatial information users. Geospatial data col-
lection may include remote sensing data, field data and
other in-house GIS data conversion processes (i.e. scan-
ning, georeferencing, digitizin g, etc.). Among them, field
data collection is one of the first steps for spatial infor-
mation users, especially for geographers, geologists, bi-
ologists, crop scientists, ecologists, etc. Field data co llec-
tion is required for several reasons, such as collecting
Ground Control Poin ts (GCPs), ground truth data collec-
tion for result validation, collecting soil contaminated
sites, plant or animal species, and gathering public opin-
ions for retail market analysis in order to analyze the
spatial distribution patterns of obj ects and information on
their associated attributes. Accurate field data collection
is also necessary for adequate spatial data analysis and
proper decision making.
Traditional field data collection (i.e. pen-and-paper
based) is a time consuming and bulky task. For example,
we need to prepare basemaps, collect an ancillary dataset,
and other paperwork. This is not practical to use in
real-time disaster information collection, which occu rs in
unpredictable places and requires a quick emergency re-
sponse. However, recent developments in mobile com-
munication, Global Navigation Systems, the Internet and
portable computational devices such as Netbooks or Ul-
tra Mobile Personal Computers (UMPC) allow us to
conduct field data collection in a timely manner. More-
over, under the client-server setting for field data collec-
tion, a field user may take advantage of digital reposito-
ries prepared for data collection (i.e. basemaps, satellite
images and other ancillary data), as well as information
resources more generally available via the Web [1]. For
example, use of Web Map Service (WMS) to access
Google Maps or Microsoft Bing Maps data from GIS
applications via a HTTP interface. It can provide Google
Map or Microsoft Bing Maps image data to any GIS ap-
plications that can use a WMS service for raster data.
This can eliminate the time for basemap preparation and
other image processing t a sks.
Perhaps the most exciting area of computer system de-
velopment continues to be in hand-held devices such as
personal digital assistants (PDA), UMPCs, Netbooks and
smart phones. A smartphone is a mobile phone that offers
a more advanced computing ability and connectiv ity than
a phone with contemporary features. They are much more
efficient in form factor (size, shape, weight, etc.), chip
type, internal storage capacity, battery lifetime and oper-
ating system compared to desktop computers. A long with
hardware development, the operation systems used in

K. K. LWIN ET AL.383
smart phones are becoming more and more compact and
functional such as iPhone (Apple Inc.) and Android
(Google). Computer scientists at the University of Wa-
shington have used Android, the open-source mobile
operating system provided by Google, to turn a cell
phone into a versatile data collectio n d evice by collecting
deforested area and instantly submitting that information
to a global environmental database in a flexible manner
[2]. In the meantime, world cellular mobile phone sub-
scribers are increasing year by year. According to the
International Telecommunication Union ITU’s 2010 re-
port, by the end of 2009 there were an estimated 4.6 bil-
lion mobile cellular subscriptions, globally corresponding
to 67 per 100 inhabitants [3]. Recently, a couple of stud-
ies have demonstrated field data collection with mobile
phones in both the educati o nal and industry sectors [4,5].
On the other hand, the increasing popularity of the
Internet and user-friendly web-based GIS applications
such as the Google Maps/Earth and Microsoft Bing
Maps platform have made GIS an integral part of life
today, for finding the closet facilities, driving routes and
so on. For example in Tsukuba City, Japan, local resi-
dents and green exercise takers can search for the short-
est or greenest route between multistop trips through a
smart phone while walking down the street by accessing
the Eco-friendly Walk Score Calculator web-based GIS
[6]. However, PDAs, Netbooks and smartphones are
sometimes considered as costly, including both device
and wireless access service charges, not suitable to use in
student field survey project. Moreover, mobile field
computing environments vary widely, but generally offer
extremely limited computing resources, visual displays,
and bandwidths relative to the usual resources required
for distribut ed geo s pat i al data [7].
In this paper, we discuss the collection of field data by
a GPS embedded personal mobile phone and POP3 mail
service. We also construct a Web-based GIS system to
integrate, store, share and retrieve the collected data in
real-time, which could be used for example in metro-
logical data collection (i.e. surface temperature, wind
speed/direction) and damage information in disaster ar-
eas at various locations. The main objective of this de-
velopment is to collect the field data in a timely, handy
and cost effective manner.
2. Web-Based GIS System and Real-Time
Field Data Collection
2.1. How It Works
We have developed a personal field data collection soft-
ware called Ultra Mobile Field GIS (UM-FieldGIS) for
the UMPC or Netbook computer, to collect field data
using either Google Maps or a pre-installed map (PIM)
[8]. UM-FieldGIS allows users to create, edit and modify
the survey items and attach multimedia information.
However, UMPC or Netbook computers and Wi-Fi In-
ternet access services are expensive and not suitable for
students. We need to fi n d an alternate way to collect field
data in a handy and timely manner at low cost, such as
using a personal mobile phone.
Figure 1 shows the detailed system design of field
data collection using a personal mobile phone. Basically
this system can be divided into three sections; named
Field Data Collection, Automation Process and End Us-
ers. Field Data Collection includes a GPS embedded
mobile phone or GPS plus mobile phone. All functions
of receiving mails, data injection and format conversion
processes will be performed automatically, called the
Automation Process. Finally the End Users Section in-
terfaces with the Web-GIS for survey data downloading,
GIS data visualization and performing spatial analysis
functions through a web-GIS browser at low cost, such
as by using a personal mobile phone.
Field Data Collection: We utilized a GPS embedded
mobile phone which typically supports additional ser-
vices such as Short Messaging Service (SMS), Multi
Messaging Service (MMS), e-mail and Internet access;
short-range wireless (infrared or Bluetooth) communica-
tions; as well as business and gaming applications, and
photography. Users are required to type predefined text
format for collecting the data. For example, the user
needs to add the “/” character between fields and add “,”
between attribute values (Figure 2). This text message
will be sent to a predefined mail address with a prede-
fined subject. The user can also attach photos, as many
as required.
Automation Process: This text message is read by a
POP3 mail server and then converted into Microsoft Ac-
cess Database format. Under the Web-GIS system, this
MS Access Database is converted into an ESRI Shape
file and integrated with another GIS dataset, such as
roads, building footprints, aerial images, etc.
End Users: Users can download up-to-date survey data
in an ESRI Shape file format through their Web-GIS
browser. User can also perform basic GIS functions such
as distance measurement, finding the closet facilities
within user defined search distances, labeling of attribute
names, linking between survey records and maps, and
viewing the attached image files through a Web-GIS
browser (Figure 3).
The overall system is built on Microsoft ASP.NET
with an AJAX Extension and VDS Technologies (Web
Mapping Components for ASP.NET). ASP.NET is a web
application framework marketed by Microsoft that pro-
grammers can use to build dynamic websites, web appli-

K. K. LWIN ET AL. 384
cations and XML web services. AJAX (short for Asyn-
chronous Java Script and XML) is a group of interrelated
web-development techniques used on the client side to
create interactive web applications. With AJAX, web
applications can asynchronously retrieve data from the
server in the background without interfering with the
display and behavior of the existing page. The use of
AJAX techniques has led to an increase in interactive
and dynamic interf aces on web pages. AspMap fo r .NET
from VDS Technologies is a set of high performance
web mapping components and controls for embedding
maps in ASP.NET applications (Web Forms).
2.2. Survey Modes
This system can be used either for individual or a group
surveys (Figure 4). The individual survey mode is ideal
for each user to collect their own field survey data for a
specific purpose, and the group survey mode is ideal for
real-time information collection such as surface tem-
perature, wind speed/direction, earthquake damage in-
formation, etc., and can be switched between simply by
changing the “Type” field. For example, for an individ-
ual survey the “Type” field may be the individual’s ini-
tial name and later they can extract their own data using
this value field. For a gro up survey, the “Type” field may
be the category which is being surveyed, such as tem-
perature, land use type, rock or soil properties, etc.
3. A Case Study
Every year, students conduct a field survey to collect
information about public facilities such as bicycle stands
and their capacity, car parking lots, sidewalk condition,
Figure 1. Details of the system for field data collection using a personal mobile phone.

K. K. LWIN ET AL.385
Figure 2. Format conversion between text message and MS
Access Database.
illegal garbage dumps and other environmental data.
This year, we introduced this system to the students for
their field survey course, which is a part of the Univer-
sity Campus GIS project. In this two-day field course, we
conducted both individual and group surveys. For the
individual survey, students individually collected infor-
mation on location of Automated External Defibrillator
(AED), illegal garbage dumps, illegal bike parking
places, graffiti in public places, broken pavements,
man-made footprints caused by people walking on the
grass and passing inside the trees instead of using legal
paths. Later this information was used by university ad-
ministrators for maintaining the campus landscape and
managing the stud ent facilities. With respect to the group
survey, we collected real-time surface temperatures with
other attribute information, such as wind speed/direction
and surrounding land use type. In this case study, four
faculty members and sixteen students from the Univer-
sity of Tsukuba, Japan, and two faculty members and
nine students from the South China Normal University,
China, participated.
3.1. Prior to the Field Work
Planning ahead is important for an adequate and suc-
cessful field data collection. Spatial planning and sam-
pling design include setting where and what attribution
information to be collected. It is difficult or impossible to
collect again after the field work has been done. We also
demonstrated handling of GPS and other field survey
instruments (Figure 5).
Figure 3. End user interface of Web-GIS for field survey data visualization in real-time.

K. K. LWIN ET AL. 386
Figure 4. Modes of survey: individual or group.
Figure 5. (a) Planning ahead; (b) GPS training; (c) Learn-
ing about real-time automatic metrological data collection.
3.2. During the Field Work
During the field work, students are required to send field
survey data by using their GPS embedded mobile phone
or reading coordinates from a Garmin handheld GPS. For
the individual surveys (Figure 6(a) and (b)), all students
collected the data inside the campus based on specific
information (i.e. location of garbage boxes, parking lots,
etc.). For the group survey (Figure 6(c)), we divided the
survey area into student groups. Each group is required
to collect temperature, wind speed/direction and land use
type information in thirty minute intervals. Faculty me-
mbers were also monitoring their status using a Netbook
computer with wireless Internet access along with them
(Figure 7). Faculty members were also offering advise to
the students through mobile phone communication.
3.3. After the Field Work
After the field work, students are required to download
the survey data through Web-GIS and open in ESRI Arc-
Map in the laboratory (Figure 8). This process includes
downloading the data, importing, formatting and visual-
izing the data in ArcMap. We used Visual Basic for Ap-
plications (VBA) script to convert the comma separated
values into attribu te fields (Figure 9).
Figure 6. (a) and (b) Individual survey of graffiti in public
places and illegal garbage dumps; (c) Group survey of sur-
face temperature collection.
Figure 7. Monitoring of real-time data injection by indi-
vidual student (Individual survey mode).
Figure 8. Field data visualization and downloaded from
Web-GIS in the laboratory.

K. K. LWIN ET AL.387
String substitution is also carried out b y VBA Script to
replace the short text to full text, such as “urb” to “Ur-
ban”. This is because sometimes students collect the data
using short text messages to reduce typing errors and
time. Furthermore, students were also able to select their
own data by choosing their name in the “Type” field.
Following is the VBA script code for columns separa-
tion and formatting in ArcGIS using Field Calculator
function.
‘Column Separation by Specific Character (,)
Dim tString() As String
tString = Split( [VALUE_01], ",")
tString(0)
Do again for other fields by changing the index
tString(1)
tString(2)
Trim(tString(3 )) f or text attribute field.
Trim removes the space before and after words.
‘Substitution by string
Dim tString As String
tString = Replace([C4], “ubn”, “Urban”)
tString
4. Results and Discussion
Figure 10 shows the results of a student’s individual
field survey data, such as determining the location of
AED, bike parking places and capacity, benches, lamp
posts, illegal foot paths, etc. This result will be used by
the university administrators to improve the campus and
students‟ daily lives. Students can also find the closet
facilities by user defined search distance, known as
closet facility analysis. Figure 11 shows the results of a
survey of surface temperature and associated surround-
ing conditio ns, su ch as wind speed /direction and lan d us e
type, taken at thirty minutes intervals in a group survey.
Figure 9. Columns separation and formatting of the survey data in ArcGIS using Visual Basic for Applications (VBA) script.
Figure 10. Web-based campus GIS built on student individual field survey data. http://land.geo.tsukuba.ac.jp/campusgis/.

K. K. LWIN ET AL. 388
Figure 11. Mapping the surface temper atur e, and wind speed/direction in ArcMap based on student group survey data.
These factors can vary quantity of surface temperature.
By importing the group survey data into ArcGIS pro-
gram, student can perform more a number of spatial
analysis functions.
5. Conclusions
Although we hav e developed a Web-GIS system for field
data collection which allows users to directly view the
basemaps, get coordinates from the map, create new
survey items and input the data through a web browser
by using wireless Internet access services and Netbook
computers, until now Netbook computers, smart phones
and wireless Internet access services are expensive and
not suitable for educational uses. In this paper, we intro-
duced a novel approach for field data collection using a
GPS embedded mobile phone and POP3 mail server to
collect the real-time geospatial information from indi-
vidual or group surveys. All survey data are collected,
stored, shared and retrieved via the Web-GIS system for
further analysis. This is ideal for student research activi-
ties in order to practice their research work and improve
their understanding of spatial distribution patterns and
their associated attribute information.
6. Acknowledgements
This research is supported by the Japan Society for the
Promotion of Science JSPS under the Grant-in-Aid for
Scientific Research projects of “Systematization of
fieldwork methodology: A study on capture, manage-
ment, analysis and circulation of geographical data” [9]
and “Population estimation of rapidly growing cities in
Southeast Asia using GIS/RS” [10].
7. References
[1] S. M. Nusser, L. L. Miller, K. Clarke and M. F. Good-
child, “Future Views of Field Data Collection in Statisti-
cal Surveys,” Proceedings of Digital Government Dot
Org 2001 National Conference on Digital Government
Research, Los Angeles, 2001.
[2] University of Washington, “Cell Phones Become Hand-
held Tools for Global Development”, Science Daily,
2009.
http://www.sciencedaily.com/releases/2009/10/09102914
1249.htm
[3] The International Telecommunication Union (ITU)
“Measuring the Information Society, ICT Development
Index,” Geneva, 2010.
http://www.itu.int/ITU-D/ict/publications/idi/2010/Materi
al/MIS_2010_without_annex_4-e.pdf
[4] K. Moe, B. Dwolatzky and R. Olst, “Designing a Usable
Mobile Application for Field Data Collection,” IEEE
AFRICON, 2004, pp. 1187-1192.
[5] S. Mourão and K. Okadata, “Mobile Phone as a Tool for
Data Collection in Field Research,” World Academy of
Science, Engineering and Technology, Vol. 70, 2010, pp.
222-226.
[6] K. K. Lwin and Y. Murayama, “Modelling of Urban
Green Space Walkability: Eco-friendly Walk Score Cal-
culator,” Computers, Environment and Urban Systems,
Vol. 35, No. 5, 2011, pp. 408-420.
[7] S. M. Nusser, L. L. Miller, K. Clarke and M. F. Good-
child, “Geospatial IT for Mobile Field DataCollection,”
Communications of the ACM, Vol. 46, No. 1, 2003, pp.
64-65. doi:10.1145/602421.602446
[8] K. K. Lwin and Y. Murayama, “Personal Field Data Col-

K. K. LWIN ET AL.389
lection by UM-FieldGIS (UMPC, UltraMobile PC and
Embedded Google Map API),” Proceedings of the 16th
Annual Meeting of GIS Association of Japan, Hokkaido
University, 20-21 October 2007.
[9] Y. Murayama, “Systematization of Fieldwork Meth-
odology: A Study on Capture, Management, Analysis
and Circulation of Geographical Data,” Grant-in-Aid
for Scientific Research A, JSPS, 2010.
[10] Y. Murayama and K. K. Lwin, “Population Estimation of
Rapidly Growing Cities in Southeast Asia Using GIS/RS”,
Grant-in-Aid for Scientific Research, JSPS, 2010.