Investigation of the Lake Victoria Region (Africa: Tanzania, Kenya & Uganda)

Polina Lemenkova (1)

1 OUC - Ocean University of China

This poster presents an ArcGIS based spatial analysis of the Victoria Lake region including environmental, biological, social and economic characteristics of the region. The methodology includes data organizing and management in ArcGIS 9.3. Operations and technique: ArcGIS Spatial Analyst. Project architecture: ArcCatalog. Spatial referencing and re-projection: ArcToolbox. Data include DEMs: elevations (USGS). 2 tiles of the USGS DEM, Land cover data (raster), Population data: UNEP, ArcGIS vector.shp files of administrative boundaries fof Uganda, Tanzania, Kenya. Data preprocessing include following data preparation. Initial vector data: UNEP .shp. Spatial reference properties: Africa Albers Equal Area Conic projection, standard parallels 20 and -23, central meridian 25 and Datum WGS-84, Projection GEOGRAPHIC, Spheroid CLARKE1866. Data conversion from ASCII text data format to raster using ArcToolbox / Conversion Tools / ASCII to Raster (Climate precipitation data). Data were projected, processed and several layer formatting and overlays were created. Mapping was created using ArcMap. Victoria Lake has unique environment, important role in the economy of countries supporting 25 M people through fish catchment reaching up to 90-270$ per capita per annum. Kenya, Tanzania and Uganda control 6%, 49% and 45% of the lake surface. Lake catchment provides livelihood of 1/3 of the population of 3 countries with agricultural economy supported by fishing and agriculture (tea and coffee plantations). Quality of the environment is a fundamental factor in maintaining and increasing living standards of the population. Main problem is sustainable development, well-balanced between using natural resources and human economic progress. Essential factors in this problem are population and natural resources management. Following research tasks are performed: Computing how much cropland is needed by 2030. Areas of cropland were estimated using statistics of the raster layer Land cover. Amount of crop per capita was computed by dividing total cropland in each country and total population. Estimation of cropland needed in 2030: multiplying crop per capita needed for the total population by 2030. How much forest can be converted to cropland from protected areas ? Clipped vector layer of the protected areas was converted to raster using Spatial Analyst / Vector to Raster. New raster was re-classified to one class. Land cover raster layer was multiplied to the Protected areas layer. After calculation, raster of Land Cover for the territory of protected area zones was received. Areas for each country were calculated. Outside and inside located areas were estimated by subtraction those areas from the total for each country: Tanzania, Kenya and Uganda. Results: computed areas of cropland needed in 2030: Kenya – 248,778 km2. Tanzania – 991,469km2; Uganda - 153,992 km2. Percentage converted to cropland in 2030 (from the total forest area): Kenya – 370%; Tanzania – 148%; Uganda - 618%. Amount of forests can be converted to cropland from the protected zones: Inside protected areas: Kenya: 9km2; Tanzania –1025 km2; Uganda - 15km2; Outside protected areas: Kenya – 795km2; Tanzania – 6484km2; Uganda - 242km2. Conclusion. Sustainable development: prerequisite for successful environmental monitoring in the Victoria Lake. Economic development model: 1) resource-saving technologies; 2) planting and protecting forests areas; 3) environmental policy and conservation.

Mots clés: GIS; ArcGIS; Geoinformation

Domaines: Sciences de l'environnement; Ingénierie de l'environnement; Arithmétique des ordinateurs; Recherche d'information [cs.IR]; Modélisation et simulation; Analyse numérique [cs.NA]; Traitement des images [eess.IV]; Milieux et Changements globaux; Environnement et Société; Biodiversité et Ecologie; Informatique [cs]; Interface homme-machine [cs.HC]; Synthèse d'image et réalité virtuelle [cs.GR]; Algorithme et structure de données [cs.DS]; Environnements Informatiques pour l'Apprentissage Humain

Polina Lemenkova. Investigation of the Lake Victoria Region (Africa: Tanzania, Kenya & Uganda). Advanced GIS, Apr 2010, Lund, Sweden. ⟨10.13140/RG.2.2.15000.75521⟩. ⟨hal-02448362⟩