This document describes a project that used GIS to map and compare the solar energy potential of Kenya and Pakistan. The objectives were to map the main factors influencing solar energy generation in both countries, reclassify these factors by their influence on potential, and combine the factors to map overall potential. Data on solar radiation, cloud cover, accessibility, land cover and other factors were analyzed for each country. The factors were reclassified and weighted overlay was used to create potential maps. Results showed that 72% of Kenyan land and 50% of Pakistani land had high potential, though clouds and snow in Pakistan's Himalayas limited potential there relative to Kenya.

1. Comparative analysis of solar energy
potential in Kenya and Pakistan
OLOO Francis
Romana Basir
GIS Project WS 2012/2013
Masters in Applied Geoinformatics
University of Salzburg
1GIS Project WS 2012/2013

2. 2GIS Project WS 2012/2013
Project objectives
Use multi-criteria evaluation to map solar energy potential in
Kenya and Pakistan; specifically
• To map the main driving factors for solar energy generation in
Kenya and Pakistan
• Reclassify the factors based on their relative influence to
potential of solar energy
• Combine the factors in order to map the potential of solar
energy in both countries

3. 3GIS Project WS 2012/2013
Area of Study : Kenya

4. 4GIS Project WS 2012/2013
Area of Study : Pakistan

5. 5GIS Project WS 2012/2013
Data
Data Data source Remarks
Kenya administrative
boundary
International Livestock Research Institute (ILRI) GIS
database
www.ilri.org/GIS
National boundaries as per 1992 Survey
of Kenya records
Kenya elevation CGIAR-Shuttle Topographic Mission (SRTM) 90m resolution
Kenya road networks ILRI GIS database
www.ilri.org/GIS
With classes A to E of the roads in Kenya
Kenya towns Inter-Governmental Authority on Development
www.igad-data.org
Include GPS coordinates of all market
centers
Kenya land use Food and Agriculture Organization (FAO)
http://www.fao.org/geonetwork/srv/en/main.home
Produced by FAO classification scheme
NOAA AVHRR data NOAA Comprehensive Large Array-data stewardship System
(CLASS)
www.class.ncdc.noaa.gov
For the periods June - August (2009-
2011) for both countries
Pakistan land cover DIVA GIS Free spatial data
www.diva-gis.org/gdata
The original format was diva grid format
Protected areas World database on protected areas
http://protectedplanet.net/
Including national reserves and national
parks
Pakistan road network DIVA-GIS Free spatial data
www.diva-gis.org/gdata
Pakistan Places/Towns Mapcruzin.com
http://mapcruzin.blogspot.co.at
Layer consisting of cities, suburbs and
towns
Pakistan elevation DIVA GIS Free spatial data
www.diva-gis.org/gdata
90m spatial resolution

6. 6GIS Project WS 2012/2013
Methodology

7. 7GIS Project WS 2012/2013
Data Preparation

8. 8GIS Project WS 2012/2013
Data Preparation: Global radiation

9. 9GIS Project WS 2012/2013
Data Preparation: Global radiation

10. 10GIS Project WS 2012/2013
Data Preparation: Cloud cover

11. 11GIS Project WS 2012/2013
Data Preparation: Cloud cover

12. 12GIS Project WS 2012/2013
Data Preparation: Accessibility

13. 13GIS Project WS 2012/2013
Data Preparation: Accessibility

14. 14GIS Project WS 2012/2013
Data Preparation: Land cover

15. 15GIS Project WS 2012/2013
Data Preparation: Land cover

16. 16GIS Project WS 2012/2013
Reclassification

17. 17GIS Project WS 2012/2013
Reclassification: Global radiation

18. 18GIS Project WS 2012/2013
Reclassification: Cloud cover

19. 19GIS Project WS 2012/2013
Reclassification: Accessibility

20. 20GIS Project WS 2012/2013
Reclassification: Land cover

21. 21GIS Project WS 2012/2013
Weighted overlay

22. 22GIS Project WS 2012/2013
Map algebra: Subtraction

23. 23GIS Project WS 2012/2013
Results

24. 24GIS Project WS 2012/2013
Results

25. 25GIS Project WS 2012/2013
Results
Laikipia Narok Nakuru
Nyandaru
a
Kajiado
Uasin
Gishu
Trans-
Nzoia
Nyeri Kiambu Samburu
Very High 5613.44 4700.42 3535.14 2175.8 1881.14 1835.05 1732.77 1409.53 1374.92 1308.81
0
1000
2000
3000
4000
5000
6000
Area(sq.km)
Top 10 counties in Kenya with large areas (km 2)of very high potential land surfaces

26. 26GIS Project WS 2012/2013
Results
Top 10 divisions with large areas (km 2)of high potential land surfaces
Kalat Quetta Zhob Makran Sibi F.A.T.A.
Dera Ghazi
Khan
Northern
Areas
Nasirabad Hyderabad
High 74942.45 59265.16 36529.67 23219.44 18616.79 9269.7 8138.36 6795.7 6748.73 5921.52
0
10000
20000
30000
40000
50000
60000
70000
80000
Area(sq.km)

27. 27GIS Project WS 2012/2013
Discussion
• Due to the nature of terrain in Kenya approximately 72% of
land received more than 1950kwh/m2 solar radiation for the
duration of analysis, in Pakistan 50% of the land received
more than 1600kwh/m2 solar radiation
• Due to the heavy clouds and snow in Himalayan ranges, this
inhibits the potential in Pakistan , only high potential areas
were mapped while in Kenya an extra class with very high
potential was mapped

28. 28GIS Project WS 2012/2013
Project work plan
October November December January
Task
2-
Oct
9-
Oct
16-
Oct
23-
Oct
30-
Oct
6-
Nov
13-
Nov
20-
Nov
27-
Nov
4-
Dec
11-
Dec
18-
Dec
25-
Dec
1-
Jan
8-
Jan
15-
Jan
22-
Jan
29-
Jan
Coming up with the topic
Presentation of the topic
Data collection (Putting the data
together)
Preparation of solar radiation data
and cloud cover analysis
Literature review for solar radiation
potential
Individual layer preparation
Combining the layers to create a
solr energy potential map
Adding other anxiliary data
Zonal statistics for different smaller
administrative units
Spatial Analysis
Cartography and visualizatiom
Compiling all the project data
Preparation for presentation
Poster design
Final presentation
Report compilation
Handing in the final report

29. 29GIS Project WS 2012/2013
References
• Etier, I., Al, A. & Ababne, M., 2010. Analysis of Solar Radiation
in Jordan. , 4(6), pp.733–738.
• Fu, P. & Rich, P.M., 2000. The solar analyst 1.0 manual. Helios
Environmental Modeling Institute (HEMI), USA.
• Ramachandra, T. V, 2007. Solar energy potential assessment
using GIS. , 18(2), pp.101–114.

30. 30GIS Project WS 2012/2013
Thank you
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