CO2Print: Mobile Carbon Footprint Application

This presentation was created for a concept on mobile carbon footprint mapping. The task was carried out as one of the requirements for the "Location Based Services study". course

GIS Project: Comparative analysis of solar energy potential in Kenya and Pakistan

The power of GIS is in the ability to combine different layers in order to create new insight about a phenomenon of interest. In this exercise, four main GIS layers were combined to map the potential of solar energy generation in Kenya and Pakistan. The four main layers were global solar radiation, cloud cover, land cover and the euclidean distance (from major towns and transport infrastructure). The choice of Kenya and Pakistan in this study was based on the fact that the two countries are located in different climatic zones with Kenya in the equatorial zone and Pakistan in the temperate zone. Additionally, my partner for the project was from Pakistan while I am originally from Kenya.

The data for this project were mainly from publicly available sources especially in the internet. ArcGIS and ENVI softwares were the main softwares used in the project. The figure below shows the methodology adopted for the project.

Project work for solar energy potential mapping

In the methodology above, Solar analyst in ArcGIS was used to carry out solar analysis on elevation layers for both countries. Secondly, distance analyst was used to create euclidean distance layers with reference to the major towns and roads, a representative euclidean layer was then generated by computing the average of the two layers. Thirdly the land cover layers obtained from different sources for the two different countries were rasterized to allow them to be combined with the other layers. Finally, NOAA-AVHRR CLASS imagery for both countries were analyzed to come up with a representative cloud cover layers for both countries.

With all the four layers ready, a weighted overlay procedure was carried out to combine the layers. Finally, map algebra was used to subtract water bodies and gazetted (protected areas) from the potential sites. The maps below show the map of potential sites in Kenya and Pakistan respectively.

Solar energy potential map of Kenya

Solar energy potential map of Pakistan

As a final step, zonal statistics was used to determine the administrative units with the highest potential in both countries. From the study, it was observed that due to the location of Kenya along the equator and also in view of the favorable terrain in close proximity to the equator, a relatively large portion of Kenya was classified within the very high or high potential areas as opposed to Pakistan.

The presentation that was made as part of this study is embedded below

References

• Fu, P. & Rich, P.M., 2000. The solar analyst 1.0 manual. Helios Environmental Modeling Institute (HEMI), USA. 
• Fu, Q., 1996. RADIATION ( SOLAR ). , (1981), pp.1859–1863. 
• Hammer, A. et al., 2003. Solar energy assessment using remote sensing technologies. Remote Sensing of Environment, 86(3), pp.423–432. Available at: http://linkinghub.elsevier.com/retrieve/pii/S003442570300083X [Accessed November 1, 2012]. 

Geo-visualization by Cartograms

Cartograms are types of maps in which  statistical information is represented relative to the area of the spatial unit to which the statistical information belongs. Cartograms can be used to create more insight on the spatial distribution of a particular variable with respect to the different spatial areas under consideration.

During the Cartography and Geo-visualization course,  cartograms were used to represent various variables in Kenya. For instance, the maps below show the spatial distribution of poverty in Kenya and accessibility to electricity within the country.

Households with access to electricity in Kenya per county

Cartogram of poverty represented against the areas of counties