Barrett_etal_clean.pdf (8.22 MB)
Forecasting vegetation condition for drought early warning systems in pastoral communities in Kenya
journal contribution
posted on 2023-06-07, 06:59 authored by Adam B Barrett, Steven Duivenvoorden, Edward E Salakpi, James M Muthoka, John Mwangi, Seb OliverSeb Oliver, Pedram RowhaniPedram RowhaniDroughts are a recurring hazard in sub-Saharan Africa, that can wreak huge socioeconomic costs. Acting early based on alerts provided by early warning systems (EWS) can potentially provide substantial mitigation, reducing the financial and human cost. However, existing EWS tend only to monitor current, rather than forecast future, environmental and socioeconomic indicators of drought, and hence are not always sufficiently timely to be effective in practice. Here we present a novel method for forecasting satellite-based indicators of vegetation condition. Specifically, we focused on the 3-month Vegetation Condition Index (VCI3M) over pastoral livelihood zones in Kenya, which is the indicator used by the Kenyan National Drought Management Authority (NDMA). Using data from MODIS and Landsat, we apply linear autoregression and Gaussian process modelling methods and demonstrate high forecasting skill several weeks ahead. As a bench mark we predicted the drought alert marker used by NDMA (VCI3M<35). Both of our models were able to predict this alert marker four weeks ahead with a hit rate of around 89% and a false alarm rate of around 4%, or 81% and 6% respectively six weeks ahead. The methods developed here can thus identify a deteriorating vegetation condition well and sufficiently in advance to help disaster risk managers act early to support vulnerable communities and limit the impact of a drought hazard.
Funding
Applying Astronomy Data Analysis to enhance disaster forecasting; G2368; STFC-SCIENCE AND TECHNOLOGY FACILITIES COUNCIL; ST/$004811/1
Towards Forecast-based Preparedness Action (ForPAc): Probabilistic forecasts information for defensible preparedness decision-making and action; G2043; NERC-NATURAL ENVIRONMENT RESEARCH COUNCIL; NE/P000673/1
History
Publication status
- Published
File Version
- Accepted version
Journal
Remote Sensing of EnvironmentISSN
0034-4257Publisher
ElsevierExternal DOI
Volume
248Page range
1-10Article number
a111886Department affiliated with
- Geography Publications
Research groups affiliated with
- Sussex Sustainability Research Programme Publications
Full text available
- Yes
Peer reviewed?
- Yes
Legacy Posted Date
2020-05-14First Open Access (FOA) Date
2021-07-19First Compliant Deposit (FCD) Date
2020-05-13Usage metrics
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