The main aim of the diploma thesis is to map and monitor slums using geoinformation technologies. The main aim was divided into sub-goals which are:
i. To develop a test methodology for mapping and monitoring slums primarily using open data.
ii. To explore the possibility of mapping slums within cities by using imagery, geophysical datasets, and complementary data.
iii. To compare the performance of different methodologies for identifying slums and determine which algorithm provides the optimal results.
iv. To contribute towards curbing disease outbreaks.
Practically, different methodologies (algorithms) that were already embedded into geospatial software (ArcGIS Pro) will be employed. The data will be inputted into this software while applying the methodologies to determine the best algorithms that give an optimal and accurate result.
Furthermore, the work outputs will be maps displaying the results from the algorithms, graphs, and optimal workflow of mapping and monitoring slums in spreading the epidemic.
The result therefore will serve the following benefits:
i. Create a set of best practice guidelines for selecting the most suitable techniques for mapping slums in a selected location.
ii. To support the achievement of Sustainable Development Goals (SDGs) No. 11 of the United Nations.
iii. To contribute towards curbing disease outbreaks in slum areas.
iv. Serve the need for benchmarking framework for evaluating slum mapping algorithms.
