| dc.description.abstract | Droughts pose significant challenges to agricultural productivity, food security, and overall
socioeconomic stability in many regions. Accurate assessment of drought risk is crucial for effective
mitigation and adaptation strategies. This research project aims to assess drought risk in Kotido District,
a region vulnerable to recurring droughts, utilizing Vegetation Health Indices (VHI) derived from
satellite imagery. Moreover, it compares the results obtained from Landsat and Moderate Resolution
Imaging Spectro-radiometer (MODIS) data to evaluate the suitability of each dataset for drought
monitoring and risk assessment in the district.
The study employs a time-series analysis of remotely sensed data acquired by Landsat and MODIS
sensors, spanning multiple years between 2002 and 2022. Vegetation Health Index components i.e.
Normalized Difference Vegetation Index (NDVI), Vegetation Condition Index (VCI), Land surface
Temperature (LST) and Temperature Condition Index (TCI), are calculated using pre-processed satellite
imagery. These indices serve as reliable indicators of vegetation health and surface temperature,
facilitating the identification and monitoring of drought conditions.
The VHI values obtained from Landsat and MODIS datasets are analyzed and compared to evaluate the
consistency, accuracy, and spatial-temporal resolution of each dataset in capturing drought events and
severity by deriving their correlation coefficient which was given by 0.635 implying a moderate positive
correlation.
The findings of this research is essential in the decision-making when formulating effective mitigation
strategies and resource allocation. By comparing the results from Landsat and MODIS, provides insights
into the strengths and limitations of each dataset, enabling stakeholders to make informed choices
regarding the most suitable data source for drought monitoring and risk assessment in Kotido District
and similar regions. | en_US |
