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funding agency
PhD Students
| Acronym: | PhD |
| Project type: | Capacity Building |
| Time frame: | 2004 - todate |
| Funding agency: | Avia-GIS |
| Geographic keyword: West Africa | Mali | Somalia | Burkina Faso | Guinée | Benin | Togo | Africa | |
| General keyword: Training | Vegetation pattern analysis | Disease modeling | GIS | Remote sensing | |
| Specific keyword: Drug resistance | African animal trypanosomiasis | Tsetse | Biotope fragmentation |
PhD_BALABADI
Time-frame: 2004 – to date
Funding Agency: Avia-GIS, Institute for Tropical Medicine (ITM, Antwerp, Belgium)
Project Type: PhD follow-up
Geographical Keyword: Africa, Burkina Faso, Togo, Benin
General Keyword: Vegetation pattern analysis, Remote sensing
Specific Keyword: Tsetse, Biotope fragmentation
ONGOING ACTIVITY
CIRDES (Bobo Dioulasso, Burkina Faso) requested Avia-GIS to provide scientific and technical back-up on aspects related to spatial modelling which are part of a doctoral thesis by Balabadi Dao (CIRDES). Avia-GIS will mainly contribute towards mapping tsetse fragmented habitats at the Northern fringe of its distribution in Burkina Faso, Benin and Togo using approached developed during the FRAGFLY project (see elsewhere).
PhD_ESSODINA
Time-frame: 2004 – to date
Funding Agency: International Livestock Research Institute (ILRI, Nairobi, Kenya), German Federal Ministry for Economic, Cooperation and Development (BMZ, Berlin, Germany)
Project Type: PhD follow-up
Geographical Keyword: Africa, West Africa
General Keyword: Training, GIS, Disease modeling, Remote sensing
Specific Keyword: African Animal Trypanosomiasis, Drug resistance
ONGOING ACTIVITY
ILRI (Nairobi, Kenya) requested Avia-GIS to provide scientific and technical back-up on aspects related to spatial analysis within the framework of a doctoral thesis by Essodina Talaki (BMZ project: Mali, Burkina Faso, Guinée). The aim of the project is to assess trypanocidal drug resistance in the project countries. The contribution of Avia-GIS will enable improved mapping and at a later stage modelling of spatial distribution patterns of trypanocidal drug resistance.
PhD_BABA – Remote sensing as a tool to model Rift Valley Fever distribution
Time-frame: 2004 – 2006
Funding Agency: Avia-GIS, Institute for Tropical Medicine (ITM, Antwerp, Belgium)
Project Type: PhD follow-up
Geographical Keyword: Africa, Somalia
General Keyword: Disease modeling, Remote sensing
Specific Keyword: Rift Valley Fever
COMPLETED
ITM (Antwerp, Belgium) requested Avia-GIS to provide scientific and technical back-up on aspects related to spatial modelling which are part of a doctoral thesis by Baba Soumaere (PACE – Kenya). The objective is to explore potential relationships between remotely sensed derived data layers and RVF serologically positive herds in Somalia. During two field studies with a random sampling strategy both positive and negative data was collected. After a qualitative inspection altitude came out as a major determinant for the presence of serologically positive animals. It is also known from literature that seasonally flushed habitats are ideal breeding sites for the vectors of the disease with a rainfall-driven population growth of the vectors. Starting from this hypothesis several data layers were collected and transformed.
As a basis NOAA imagery from the year 2000 was retrieved, cloud-free 21-days composites were created and Fourier-transformed in order to reduce the data volume, remove noise and highlight seasonal patterns. The first three harmonics and phases were used as they explained most of the variance in the data set. As a next step, the minimum, maximum and mean of each channel over the period of 1 year was determined. These images were used to assess the usefulness of the climate information derived from the weather satellite for the modelling of RVF. A digital terrain model of the area was added as possible input variable because of the qualitative inspection of the serology results.
Several logistic regression approaches, however did not yield satisfactory results and after a thorough literature review a DTM-derived index, namely the Compound Topographic Index, was calculated. This index is based on the flow accumulation in a certain cell as well as the slope of that particular cell. This index is commonly referred to as the Wetness index and is determined as:
In areas of no slope, a CTI value is obtained by substituting a slope of 0.001. This value is smaller than the smallest slope obtainable from a 1000 m data set with a 1 m vertical resolution.
Even though a good correlation was obtained between the CTI and the serological information, this was not sufficient for modelling purposes. This is probably due to the cattle movement across the country. Further research based only on the high serology titers, indicating recent infection, might improve the results.
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