Drought conditions appraisal using geoinformatics and multi-influencing factors.

The world including South Africa is faced with unprecedented environmental changes, which can be linked to climate-related disasters such as drought and extreme heat. Several studies have indicated that these changes are likely to accelerate in the future and cause an adverse impact on the environment. The Eastern Cape Province of South Africa, especially Amathole District Municipality (ADM), has recorded a high number of climate change-related disasters including prolonged drought conditions witnessed during the winter season of 2008, 2009, 2014 and 2015 among others. Consequently, this study aimed at exploring remote sensing information to assess and document drought occurrences in the ADM from 2007 to 2017. To accomplish the aim, the Normalized Difference Vegetation Index, Land Surface Temperature and Precipitation were utilised to access drought spatiotemporal variations. For the analysis, a total of 396 satellite imageries (MODIS and TRMM) were used. The results revealed that different correlations exist between the three variables. The significance of correlations differed from one season to another. Furthermore, it was revealed that the drought conditions in the district differed in the spatial distribution. The study accurately identified the drought episodes that occurred in the ADM in the years 2008, 2009, 2014, 2015 and 2016. The chosen methodology and variables proved to be suitable for analysing drought conditions offering space and temporal variation dimension, which is vital in monitoring drought events.

Environmental factors and population at risk of malaria in Nkomazi municipality, South Africa.

OBJECTIVE: Nkomazi local municipality of South Africa is a high-risk malaria region with an incidence rate of about 500 cases per 100 000. We examined the influence of environmental factors on population (age group) at risk of malaria. METHODS: r software was used to statistically analyse data. Using remote sensing technology, a Landsat 8 image of 4th October 2015 was classified using object-based classification and a 5-m resolution. Spot height data were used to generate a digital elevation model of the area. RESULTS: A total of 60 718 malaria cases were notified across 48 health facilities in Nkomazi municipality between January 1997 and August 2015. Malaria incidence was highly associated with irrigated land (P = 0.001), water body (P = 0.011) and altitude ≤400 m (P = 0.001). The multivariate model showed that with 10% increase in the extent of irrigated areas, malaria risk increased by almost 39% in the entire study area and by almost 44% in the 2-km buffer zone of selected villages. Malaria incidence is more pronounced in the economically active population aged 15-64 and in males. Both incidence and case fatality rate drastically declined over the study period. CONCLUSION: A predictive model based on environmental factors would be useful in the effort towards malaria elimination by fostering appropriate targeting of control measures and allocating of resources.

Spatial assessment of drought severity in Cape Town area, South Africa.

In recent decades, drought has been identified as part of the several regular climate-related hazards happening in many African countries including South Africa, often with devastating implications on food security. Studies have shown that the earth temperature has increased over the recent years which can trigger drought occurrences and other climate-related hazards. Drought occurrence is principally a climate-related event that cannot be totally effaced though it can be managed. This study is aimed at appraising drought severity in Cape Town area, South Africa using Geographic Information System (GIS) and remotely sensed data obtained from United States Geological Survey (USGS) database between the years 2014 and 2018. The study revealed that the land use dynamics witnessed drastic changes where vegetation, water body and bare surface decreased from 2095 to 141 km2, 616 to 167 km2 and 2337 to 1381km2 respectively while built up and sparse vegetation increased from 5301 to 8191 km2 and 7382-7854 km2 during the period. Vegetation health and drought severity of the study area was assessed using vegetation indices and Normalized Drought Dryness Index (NDDI). The result reveals that Normalized Difference Water Index (NDWI) and other vegetation indices decreased considerably more in recent years (2017 and 2018) which might have triggered drought events during the period compared to the other years (2014-2016). Furthermore, the spatial trend of land surface temperature (LST) and NDDI increased in recent years with NDDI values ranging between moderate drought and severe drought threshold. Consequently, if the increment persists, it can lead to adverse impacts such as food insecurity, land degradation and environmental health deterioration. Evidently, this study reveals the current state of vegetation health regarding drought severity in the area using remotely sensed data.