Estimating crop yields and production by integrating the FAO Crop Specific Water Balance model with real-time satellite data and ground-based ancillary data

C. A. Reynolds, Muluneh Yitayew, Donald C Slack, C. F. Hutchinson, A. Huetes, M. S. Petersen

Research output: Contribution to journalArticle

97 Citations (Scopus)

Abstract

An operational crop yield model was developed by introducing real-time satellite imagery into a Geographical Information System (GIS) and the Crop Specific Water Balance (CSWB) model of the Food and Agriculture Organization (FAO). Input databases were developed with three different resolutions; agro-ecological zone (AEZ) polygons, 7.6 km and 1.1 km pixels; from archived satellite data commonly used by Early Warning Systems (EWS) to simulate maize yield and production in Kenya from 1989 to 1997. Simulated production results from the GIS-based CSWB model were compared to historical maize production reports from two Government of Kenya (GoK) agencies. The coefficients of determination (r2) between the model and GoK district reports ranged from 0.86 to 0.89. The results indicated the 7.6 km pixel-by-pixel analysis was the most favorable method due to the Rainfall Estimate (RFE) input data having the same resolution. The GIS-based CSWB model developed by this study could also be easily expanded for use in other countries, extended for other crops, and improved in the future as satellite technologies improve.

Original languageEnglish (US)
Pages (from-to)3487-3508
Number of pages22
JournalInternational Journal of Remote Sensing
Volume21
Issue number18
DOIs
StatePublished - 2000

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crop production
crop yield
Agriculture
Crops
water budget
satellite data
Satellites
agriculture
crop
food
pixel
Information systems
Pixels
GIS
Water
maize
Satellite imagery
early warning system
Alarm systems
polygon

ASJC Scopus subject areas

  • Computers in Earth Sciences

Cite this

Estimating crop yields and production by integrating the FAO Crop Specific Water Balance model with real-time satellite data and ground-based ancillary data. / Reynolds, C. A.; Yitayew, Muluneh; Slack, Donald C; Hutchinson, C. F.; Huetes, A.; Petersen, M. S.

In: International Journal of Remote Sensing, Vol. 21, No. 18, 2000, p. 3487-3508.

Research output: Contribution to journalArticle

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