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The use of GIS in Archiving and Accessing Hostels Information: A Case KNUST Campus

Classification of Hostels
Hostels in and around campus have different facilities which makes them fall into different classes. The criteria used in classifying these hostels were provided by the Estate Organization Unit of KNUST. There are five classes in all (see figure 1). First class is the best, graduating down to the fifth class. A hostel qualifies to be in a class when it satisfies majority of the conditions in that class.

The KNUST Estate Organisation Unit (2005) criterion was used in the classification of the observed hostels. With this criterion, hostels were grouped under five classes. In all spatial and non-spatial information of fifty-five hostels were collected. The classification of hostels according to classes is shown in table 1.

Table 1: Classified hostels in and around KNUST campus
Class type1st Class2nd Class3rd Class4th Class 5th Class
Name of Hotel Brunei Gaza Sun city Westend Alster Amade Diploma Int. Nana Adoma No Weapon Outlook Rowlex Sir Max Spring Steven Paris Asabek Asona Christ the King Cornel Eden Ford Hydes Jita Kentcity Kuyajoe Mango road Nasco Nyberg Penthouse SDR Shaba Shalom Shepherdsville SRC St. Francis Memorial St. Peter’s Credit union Acropolis Cowas Diaspora Ebenezer Jalex Kankam Kingdom Pantan White house Adonai Asbed Bujumbura City CFFR Continental El Shadai Millenium Nazareth Peace Stone Castle Wisdom


Table 2 shows that the continuing (non-resident) students in the hostels outnumber the resident students in the halls. This calls for the proper management of hostels in and around campus to effectively cater for the accommodation needs of non-resident students. This is in line with one of the expected outputs of the University’s Corporate Strategic Plan 2004-2014 (PLAN2K14) launched in the year 2004. That is to expand residential facilities (halls and hostels) for students.

Table 2: KNUST student enrolment in 2004/2005 academic year (source: KNUST Estate Organisation Unit, 2005)
Halls of residenceNumber of malesNumber of femalesTotal
Queen Elizabeth hall

Independence hall

Republic hall

Africa hall

Unity hall

University hall

Students enrolled

657

628

643

0

1,694

1,199

11,681
549

500

560

700

0

0

4,614
1,206

1,128

1,203

700

1,694

1,199

16,295



The use of GIS in archiving information on hostels
To start with the execution of the task, maps covering the area was digitized in the GIS environment for visualization. Coordinates of the hostels were picked with GPS and then downloaded into the GIS environment. Results of the questionnaires about the hostels pertaining to the information about their condition was tabulated in MS Access and then exported into the GIS environment. The advantage of using GIS is that public utilities such as water, power, facility management, landscape architecture and sanitation can be well stored, retrieved, managed, analysed and presented (see figure 2).


Figure 2: Spatial locations of Hostels displayed in ArcView 3.3


The study was carried mainly to integrate the topographic maps of the study area and the geographic positions as well as the attribute information of the hostels for visualization in a GIS environment for easy access of hostel information. As a result there was the need to determine the number of students per room and availability of water and electricity as well as to determine the sanitation conditions of the hostels compared to the halls. There was also the need to determine the serenity, distance from the campus and charges of the hostels, how students can obtain quick hostel information and lastly to develop a user-friendly platform for updating the database of hostels. These datasets were incorporated into macromedia flash software including the images captured with the digital camera for easy access to the public through the WWW. This was done because students and the University community need information about hostels in and around KNUST campus.

The GIS was used to store, update, retrieve and analyse the spatial and non-spatial datasets of hostel. With the collection of the non-spatial data, thorough review of existing data and verbal interview would be used to investigate and analyse the requirements of the hostels in our study area. The interview would be conducted by interviewing the target group that is the students in the various hostels through questionnaires.

GIS makes it possible to store, handle, analyse, visualize and model spatial data and therefore may contribute to the better understanding of geographical phenomena. It also supports the creation and maintenance of a more accurate land records base map using the tools and functions of GIS (e.g., topology checking, map projections and adjustments, map editing tools)

The questionnaires which were sent out to the various hostels were used in building the attribute table. The table containing the geographical locations as well as attributes information on the hostels was created in Microsoft Access and later exported into ArcView 3.3 GIS software.

The use of GPS in archiving information on hostels
GPS provides a means of locating the spatial (or geographical) locations of all the hostels. Handheld GPS was used to determine the geographical locations of the hostels. This survey technique was chosen because it is easy in data acquisition, direct coordinate location, and compatible with the GIS software. ‘Advantage of GPS compared with conventional surveys is that it can be used in any weather conditions day or night. This enables GPS surveying to be carried out over extended periods at any time of the year without restrictions such as rain, fog, and poor visibility delaying work. Another advantage when surveying with GPS is that intervisibility between stations or points surveyed is not necessary. This allows control stations to be placed where convenient and not at locations which may be difficult to get to in order to establish lines of sight’ (Schofield, 1993). Although handheld GPS was used for these measurements a more precise GPS measurement would be an update for further research. This is because; handheld GPS has error in the range of 5-25m in measuring horizontal distances. The type of hand-held GPS used in the observation was the ‘Megalin Silva’, which was found to have accuracy of 20 meters. This was achieved by comparing the observations of the transformed results from the handheld GPS and known coordinates in order to obtain a transformation parameter of 20 meters between the two results.

The procedures put in place to ensure that more accurate readings were observed such that the observations would not be thrown off from their original positions on ground are outlined below:

  • Three of the four corners of the hostel building were chosen as points for the GPS observation.
  • On each of these selected points, three readings were taken at different times of the day.
  • The average of the three readings at a point was calculated in the Universal Transverse Mercator (UTM) projection system for that point. These GPS coordinates obtained were then transformed to the national (Ghanaian) coordinates using the transformation parameters
  • The length and width of the hostel building was measured using a tape-measure.
The GPS thus provided easy and fast acquisition of the spatial locations of the hostels. The transformed GPS coordinates of the fifty-five (55) hostels from the observed Universal Transverse Mercator (UTM) to the computed local coordinate system are tabulated in table 3.

Table 3: Transformed GPS coordinates of the fifty-five (55) hostels
HostelsEastings (feet)Northings (feet)HostelsEastings (feet)Northings (feet)
Acropolis 695,493.49 728,437.42 Mangoroad 696,857.44 728,850.92
Adonai 695,800.80 728,167.35 Millenium 696,737.41 727,423.66
Alster 688,482.44 732,596.06 Nana adoma 695,680.74 726,732.22
Amade 690,978.26 731,645.36 Nasco 690,582.78 730,708.03
Asabek 697,614.50 727,355.49 Nazareth 696,429.83 728,691.78
Asbed 695,808.07 727,736.03 No weapon 698,054.10 724,705.44
Asona 698,103.18 728,242.85 Nyberg 697,163.23 727,273.52
Brunei 692,376.29 725,827.65 Outlook 698,969.88 728,826.43
Bujumbura 695,549.68 727,661.54 Pantang 695,752.01 728,546.67
CFFR 695,577.88 727,571.57 Peace 696,630.18 727,414.63
Christ the king 697,802.14 726,202.28 Pent house 695,923.50 727,284.63
Continental 695,863.86 727,923.10 Rowlex 690,975.75 731,614.44
Cornel 696,681.85 725,424.16 SDR 691,176.59 732,807.23
Cowas 697,278.06 726,122.21 Shaba 692,069.23 726,255.16
Diaspora 695,612.49 728,511.77 Shalom 695,616.49 726,207.69
Diploma 689,256.23 733,153.74 Shepherd 697,397.19 727,482.89
Ebenezer 696,019.93 725,856.25 Sir max 698,635.02 733,471.21
Eden 695,875.99 728,545.24 Spring 691,992.05 726,228.22
El shadai 696,432.99 727,142.71 SRC 692,579.12 729,793.18
Ford 696,090.84 727,480.81 St. Francis 696,514.54 725,681.26
Gaza 698,195.21 732,316.04 St. Peters 697,100.58 725,753.56
Hydes 697,163.23 725,935.68 Steven Paris 692,322.17 726,096.14
Janelex 695,811.00 726,033.14 Stone castle 695,670.91 726,110.08
Jita 695,723.27 728,757.34 Suncity 698,730.68 732,550.21
Kankam 695,930.38 728,174.42 Westend 695,607.44 728,474.07
Kent city 697,553.74 733,313.81 White house 695,798.32 726,867.24
Kingdom 696,331.33 727,147.02 Wisdom 698,289.07 726,974.53
Kuyajoe 698,204.06 728,883.38    


The information on the selected datum, datum parameters and transformation parameters used for the transformation are shown in table 4.

Table 4: Information on the selected datum, datum parameters and transformation parameters used for the transformation
Transformation Parameters
Datum Clarke 1880
Major axis diameter (a) 6378249.145
Minor axis diameter (b) 6356514.87
1/ f 293.465
Datum Parameters
Translation in x-axis (Tx) -159.506
Translation in y-axis (Ty) 262.531
Translation in z-axis (Tz) 221.791
Rotation in x-axis (Rx) 1.82800 sec
Rotation in y-axis (Ry) 2.39900 sec
Rotation in z-axis (Rz) 7.46000 sec
Scale change (S)0 ppm
Datum Selected
Origin Latitude 4°40`00` N
Origin Longitude 1°00`00` W
Scale 0.99975
False Easting 27432.00 m
False Northing 0 m


The use of WWW in archiving information on hostels
Macromedia Dreamweaver MX is a professional HTML editor for designing, coding, and developing websites, web pages, and web applications. Apart from these, it can also be used for running a web server on a local computer, or uploading files to a staging server. This software provided the means of designing the web pages required to upload the spatial and non-spatial information about the hostels onto the WWW for easy access.

In designing web pages, the software enables you to set a variety of properties for a page including its title, background colour, text colour, and so on. Buttons, images, sounds and customized navigational buttons can be added to web pages. The designed interface of accessing hostel information is shown in figure 3.


Figure 3: Home page for accessing hostel information


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