Use of Remote Sensing and GIS Techniques for Land Use Mapping at Four Selected TaCRI Stations, Tanzania

Maro G.P.^1, , Mbwambo S.G.¹, Monyo H.E.¹ and Mosi E.J.¹

¹Tanzania Coffee Research Institute, Lyamungu Soil Fertility Laboratory, P.O. Box 3004 Moshi, TANZANIA

Cite this paper

Maro G.P., Mbwambo S.G., Monyo H.E. and Mosi E.J.. Use of Remote Sensing and GIS Techniques for Land Use Mapping at Four Selected TaCRI Stations, Tanzania. Journal of Geosciences and Geomatics. 2024; 12(1):6-11. doi: 10.12691/JGG-12-1-2

Abstract

Most major agricultural research stations in Tanzania have adopted the geographic information systems (GIS). Tanzania Coffee Research Institute (TaCRI) was late to come on board because its establishment does not include a cartographic unit. Collaboration with TARI-Mlingano in 2008/09 enabled the initiation of a mini-GIS unit at Lyamungu. One of its tasks was to develop digital maps of the TaCRI substations scattered over major coffee zones in Tanzania. Four substations were chosen to start with. For Lyamungu, a non-georeferenced paper map was scanned and 8 control points selected, whose x-y coordinates were taken with a GPS tool. They were loaded into Excel spreadsheet and saved as a .csv file. The image and the point shapefile were properly aligned in ArcMap 10.7.1 and digitized onscreen. Ugano, Mbimba and Mwayaya maps were digitized from satellite images remotely sensed with Google Earth Pro, saved first as .kmz files, and converted in ArcMap to features and later to shapefiles. Land use was elaborated using expert knowledge. The resultant was the first ever digital maps of the four substations. Created shapefile layers included boundary, rivers, roads and fields (categorized as coffee land, other crops, forest reserve, other reserves, wetlands and waterbodies, nurseries and general infrastructure). Land use per category showed to have a bearing on station history, current land ownership status and staff population. Percentage land assigned to coffee decreased in the order Lyamungu > Mwayaya > Ugano > Mbimba. This work has formally introduced TaCRI to the GIS world – an important step as GIS is becoming ubiquitous in global research, planning and problem solving. It was also a very good starting experience with ArcMap and Google Earth.

Keywords

Digital maps, GIS techniques, land use mapping, remote sensing, TaCRI stations

Copyright

This work is licensed under a Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

References

[1]	Van Meirvenne, M. (2003). Land Information Systems and their uses. Lecture Notes, Faculty of Agricultural and Applied Biological Science, Ghent University, Coupure Links, 9000 Gent, Belgium. 101pp.
[2]	Maliene, V., Grigonis, V., Palericus, V. and Griffiths, S. (2011). Geographic Information Systems: Old principles with new capabilities. Urban Design International Vol. 16 (1): 1-6.
[3]	Maro, G. P. (2004). Yield gap analysis for selected sugarcane estates in Tanzania. Dissertation for Award of MSc Degree at Ghent University, Belgium, 112pp.
[4]	Kyariga, A.T. (2001). GIS as a decision making support tool for urban planning and management: A practical case of Tanzania. CORP2001, Vienna University of Technology:101-106.
[5]	National Bureau of Statistics (2012). The population census map of Tanzania at ward level. Online GIS database, National Bureau of Statistics, Dar es Salaam, Tanzania.
[6]	National Bureau of Statistics (2020). The population census map of Tanzania at ward level. Online GIS database, National Bureau of Statistics, Dar es Salaam, Tanzania.
[7]	Solari, O.M., Demirci, A. and Schee, J. van der (eds) (2015). Geospatial technologies and geography education in a changing world: Geospatial practices and lessons learned. Advances in Geographical and Environmental Sciences, Tokyo, New York, Springer-Verlag.
[8]	Sumari, N.S., Shao, Z. and Kira, E. (2017). Challenges and opportunities for the advancement of GIS education in Tanzania. Journal of Education and Practice Vol. 8 (28): 67-75.
[9]	Maro, G.P. and Mbogoni, J.D.J. (2009). Soils of Kasulu, Kibondo, Tarime and Rorya districts and their suitability for coffee. Soil Survey Report TCR 1 (2009), Soils Collaborative Research Project (PADEP), March, 2009. 77pp.
[10]	Yang, D., Fu, C.S., Smith, A.C. and Yu, Q. (2017). Open land use map: A regional land use mapping strategy for incorporating open street map with earth observations. Geospatial Information Science Vol. 20 (3), 2017: 269-281.
[11]	Maro, G. P., Msanya, B. M. and Mrema, J. P. (2014). Soil fertility evaluation for coffee (Coffea arabica) in Hai and Lushoto Districts, Northern Tanzania. International Journal of Plant and Soil Science (IJPSS) Vol 3 Issue 8 May 2014: 934-947.
[12]	Mfaume, D.P., Msanya, B.M.M. and Msaky, J.J. (2019). Pedological characterization and fertility assessment of Mbimba Substation soils under coffee production in Mbozi District, Tanzania. IJASRE Vol. 5 (10), October 2019: 177-192.
[13]	IUSS Working Group (2014). World Reference Base for Soil Resources, International Soil Classification System for naming soils and creating legends for soil maps. World Soil Resources Report No. 106. FAO, Rome, Italy. 191pp.
[14]	Mwamlima, P. (2016). ArcMap digitization of paper maps. Ardhi University Training Manual Vol. 1, June 2016: 32pp.
[15]	Franceschini, G. and Ali, M. (2022). Introductory course to Google Earth Engine. FAO, Rome: 55pp.
[16]	Hillier, A. (2011). Manual for working with ArcGIS 10. University of Pennsylvania, January 2011: 83pp.
[17]	Ghorbani, A. and Pakravan, M. (2013). Land use mapping using visual versus digital image interpretation of TM and Google Earth derived imegery in Shrivan Darasi watershed, Northwest of Iran. European Journal of Experimental Biology Vol. 3 (1):576-582.
[18]	Waters, N. (2017). GIS: History. The International Encyclopaedia of Geography 2017. John Wiley and Son, Ltd: 12pp.
[19]	Morehouse, S. (1985). ArcInfo: A geo-relational model for spatial information. In Proc. AUTOCARTO 8, ASPRS, Falls Church, Virginia, USA: 388-397.
[20]	Morehouse, S. (1992). ArcInfo: Geographic Information System. Computer Geosciences Vol. 18 (4): 435-443.
[21]	Environmental Systems Research Institute (1996). ArcView GIS: The Geographic Information System for everyone. ESRI, Redlands, California, USA. 320pp.
[22]	Environmental Systems Research Institute (2006). What is ArcGIS 9.2? ESRI, Redlands, California, USA. 38pp.
[23]	Ormsby, T., Napoleon, E., Burke, K., Groessl, C. and Bowden, L. (2010). Getting to know ArcGIS Desktop. ESRI Press, Redlands, California, USA, Vol. 48 (3): 97-103.
[24]	Siljander, M., Hurskainen, P., Pelikka, P. and Finegold, Y. (2012). Introduction to Geographic Information Systems (GIS): The QGIS 1.7.2 Software. University of Helsinki, Finland. Course materials provided to the CHIESA Project, Mweka College of Wildlife Management, Moshi, 17-20 April, 2012: 72pp.
[25]	Lillesand, T.M and Kiefer, R.W. (1999). Remote sensing and image interpretation. 4th Edition. John Wiley and Sons, Inc. New York: 605pp.
[26]	Mohammed, N.Z., Ghazi, A. and Mustafa, H.E. (2013). Positioning accuracy testing of Google Earth. International Journal of Interdisciplinary Science and Engineering Vol. 4 (6): 6-9.
[27]	Agyenang, A.B., Quaye-Ballard, J.a., Ohemeng, R.Y. and Asante, E.Y. (2020). Google Earth as image source in photogrammetric mapping of KNUST Campus. Journal of Science and Technology Vol. 38 (1-3): 11-20.
[28]	Harrington, S., Teitelman, J., Rummel, E., Morse, B., Chen, P., Eisentraught, D. and McDonnough, D. (2017). Validating Google Earth Pro as a scientific utility for use in accident reconstruction. SAE International Journal of Transport Safety Vol. 5 (1): 9pp.
[29]	Dodsworth, E. and Nicholson, A. (2012). Academic uses of Google Earth and Google Maps in a library setting. Information Technology and libraries, June 2012: 102-117.
[30]	Malarvizhi, K., Kumar, S.V. and Porchelvan, P. (2015). Use of high resolution Google Earth satellite imagery in land use map preparation for urban related applications. Elsevier. Procedia Technology Vol. 24: 1835-1842.
[31]	Madarasinghe, S.K., Yapa, K.K.A.S. and Jayatissa, L.P. (2020). Google Earth imagery coupled with onscreen digitization for urban land use mapping: Case study of Hambantota, Sri Lanka. Journal of National Science Foundation Sri Lanka Vol. 48 (4):357-366.
[32]	Chiang, Y.Y., Leyk, S. and Knoblock C.A. (2014). A survey of digital map processing techniques. ACM Computing Surveys Vol. 44 (1), April 2014: 44pp.
[33]	Serwa, A. and Elbialy, S. (2020). Enhancement of classification accuracy of multi-spectral satellites’ images using Laplacian pyramids, The Egyptian Journal of Remote Sensing and Space Sciences.
[34]	Serwa, A. (2020). Potentiality of using digital wavelet/QMF pyramids in remotely sensed satellite image classification. Geodesy and Cartography Vol. 46 (4): 163-169.
[35]	Peller, P. (2018). From paper map to geospatial vector layer: Demystifying the process. IASSIST Quarterly 42 (3): 1-22.
[36]	Tanzania Coffee Research Institute (2023). The Fifth TaCRI Strategic Action Plan, 2023-2028. Internal working document, March 2023: 85pp.
[37]	United Republic of Tanzania (2022). Guidelines for GIS application in local government authorities. President’s Office, Regional Administration and Local Governments. June 2022: 12pp.