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GC13I-0857: Designing a Frost Forecasting Service for Small Scale Tea Farmers in East Africa
NTRS Full-Text: Click to View  [PDF Size: 6.1 MB]
Author and Affiliation:
Adams, Emily C.(Alabama Univ., Huntsville, AL, United States)
Wanjohi, James Nyaga(Regional Centre for Mapping Resources for Development, Nairobi, Kenya)
Ellenburg, Walter Lee(Alabama Univ., Huntsville, AL, United States)
Limaye, Ashutosh S.(NASA Marshall Space Flight Center, Huntsville, AL, United States)
Mugo, Robinson M.(Regional Centre for Mapping Resources for Development, Nairobi, Kenya)
Flores Cordova, Africa Ixmucane(Alabama Univ., Huntsville, AL, United States)
Irwin, Daniel(NASA Marshall Space Flight Center, Huntsville, AL, United States)
Case, Jonathan(ENSCO, Inc., Huntsville, AL, United States)
Malaso, Susan(Regional Centre for Mapping Resources for Development, Nairobi, Kenya)
Sedah, Absae(Kenya Meteorological Dept., Nairobi, Kenya)
Abstract: Kenya is the third largest tea exporter in the world, producing 10% of the world's black tea. Sixty percent of this production occurs largely by small scale tea holders, with an average farm size of 1.04 acres, and an annual net income of $1,075. According to a recent evaluation, a typical frost event in the tea growing region causes about $200 dollars in losses which can be catastrophic for a small holder farm. A 72-hour frost forecast would provide these small-scale tea farmers with enough notice to reduce losses by approximately 80 USD annually. With this knowledge, SERVIR, a joint NASA-USAID initiative that brings Earth observations for improved decision making in developing countries, sought to design a frost monitoring and forecasting service that would provide farmers with enough lead time to react to and protect against a forecasted frost occurrence on their farm. SERVIR Eastern and Southern Africa, through its implementing partner, the Regional Centre for Mapping of Resources for Development (RCMRD), designed a service that included multiple stakeholder engagement events whereby stakeholders from the tea industry value chain were invited to share their experiences so that the exact needs and flow of information could be identified. This unique event allowed enabled the design of a service that fit the specifications of the stakeholders. The monitoring service component uses the MODIS Land Surface Temperature product to identify frost occurrences in near-real time. The prediction component, currently under testing, uses the 2-m air temperature, relative humidity, and 10-m wind speed from a series of high-resolution Weather Research and Forecasting (WRF) numerical weather prediction model runs over eastern Kenya as inputs into a frost prediction algorithm. Accuracy and sensitivity of the algorithm is being assessed with observations collected from the farmers using a smart phone app developed specifically to report frost occurrences, and from data shared through our partner network developed at the stakeholder engagement meeting. This presentation will illustrate the efficacy of our frost forecasting algorithm, and a way forward for incorporating these forecasts in a meaningful way to the key decision makers - the small-scale farmers of East Africa.
Publication Date: Dec 11, 2017
Document ID:
20170011720
(Acquired Dec 21, 2017)
Subject Category: EARTH RESOURCES AND REMOTE SENSING
Report/Patent Number: MSFC-E-DAA-TN50383
Document Type: Oral/Visual Presentation
Meeting Information: American Geophysical Union (AGU) Fall Meeting; 11-15 Dec. 2017; New Orleans, LA; United States
Meeting Sponsor: American Geophysical Union; Washington, DC, United States
Contract/Grant/Task Num: PIA-MSFC; NNM17AA29T; NNM11AA01A
Financial Sponsor: NASA Marshall Space Flight Center; Huntsville, AL, United States
Organization Source: NASA Marshall Space Flight Center; Huntsville, AL, United States
Description: 1p; In English
Distribution Limits: Unclassified; Publicly available; Unlimited
Rights: Copyright; Portions of the document may include copyright protected material
NASA Terms: FROST; NUMERICAL WEATHER FORECASTING; AFRICA; FARM CROPS; ENVIRONMENTAL MONITORING; MODIS (RADIOMETRY); ALGORITHMS; THEMATIC MAPPING; HIGH RESOLUTION; SENSITIVITY; ACCURACY; WIND VELOCITY; DECISION MAKING; INDUSTRIES
Other Descriptors: SERVIR; FROST; TEA; REMOTE SENSIN
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