Zim adopts mapping technology to predict disasters

By Wallace Mawire

After Cyclone Idai ravaged southern Africa, killing at least 1,000 people, Zimbabwe’s scientific community is actively using   geospatial mapping technology to better predict future disasters. 

The cyclone hit southern African countries include Mozambique, Malawi and Zimbabwe.

In Zimbabwe, at least 268 people were killed and many are still missing. Local scientists hope that despite lags in scientific advancement, their use of geospatial technology and space technology will allow them to foresee climate-induced risks and disasters. 

Amon Murwira, Zimbabwe’s Minister of Higher and Tertiary Education Science and Technology Development, confirmed the country’s use of science and technology to guard Zimbabwe from climate shocks.

Murwira said local scientists were conducting Cyclone Idai impact assessments using color-coded geospatial and space technology. This includes the use of High Performance Computing (HPC), geospatial and space technology.

He was speaking at a national environment forum in Harare. Geospatial analysis is the gathering, display, and manipulation of imagery, GPS, satellite photography and historical data, described explicitly in terms of geographic coordinates or implicitly, in terms of a street address, postal code, or forest stand identifier as they are applied to geographic models.

“Zimbabwe is suffering from climate shocks such as drought, floods and disease outbreaks, we can guard Zimbabwe from these shocks in future using science and technology,” Murwira said.

He said scientists were already using data analysis  in cyclone-hit areas like Ngangu, a suburb in Chimanimani. The government-sponsored scientists were also trying to  help locate and retrieve several corpses which were buried underground during the devastating cyclone.

The scientists are modeling areas anticipated to be high-risk using geospatial mapping to help them prepare for future disasters.

The minister said scientists in cyclone-hit areas were starting to predict future malaria outbreaks and mapping vegetation density using the same geo-spatial and space technology.

Post Author: Chido Luciasi

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