Abstract
Abstract. Monitoring staple crop production can support agricultural research, business such as crop insurance, and government policy. Obtaining accurate estimates through field work is very expensive, and estimating it through remote sensing is promising. We estimated county-level maize yield for the 37 maize producing countries in Kenya from 2010 to 2017 using Moderate Resolution Imaging Spectroradiometer (MODIS) data. Support Vector Regression (SVR) and Random Forest (RF) were used to fit models with observed county level maize yield as a function of vegetation indices. The following five MODIS vegetation indices were used: green normalized difference vegetation index, normalized difference vegetation index, normalized difference moisture index, gross primary production, and fraction of photosynthetically active radiation. The models were evaluated with 5-fold leave one year out cross-validation. For SVR, R2 was 0.70, the Root Mean Square Error (RMSE) was 0.50 MT/ha and Mean Absolute Percentage Error (MAPE) was 27.6%. On the other hand for RF these were 0.69, 0.51 MT/ha and 29.3% respectively. These results are promising and should be tested in specific applications to understand if they are good enough for use.
Highlights
In Kenya, crop production is a vital contributor to food security and employment
All the metrics show an asymptotic relationship with maize yields
In Normalized Difference Moisture Index (NDMI), a linear relationship is depicted between -0.1 to 0.1 are consistent with maize yield between 0–2 ton/ha like Normalized Difference Vegetation Index (NDVI)
Summary
In Kenya, crop production is a vital contributor to food security and employment. The sector directly accounts for about 26% and indirectly for another 25% of gross domestic product (Machado and Paglietti, 2015; Kenya National Bureau of Statistics, 2017). Maize is the main staple food in Kenya. Kenya has about 2.1 million ha of maize, more than 40% of the total cropland area. As they are affected by droughts and pests. Fall Army Worm infestations led to a drop in maize production by 6.3% in 2017 (Kenya National Bureau of Statistics, 2017) leading to a severe maize shortage. If yield estimates are timely, they can be used to avert food shortage through appropriate interventions such as imports
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