Abstract
Across Eastern Africa, croplands cover 45 million ha. The regional economy is heavily dependent on small holder traditional rain-fed peasant agriculture (up to 90%), which is vulnerable to extreme weather events such as drought and floods that leads to food insecurity. Agricultural production in the region is moisture limited. Weather station data are scarce and access is limited, while optical satellite data are obscured by heavy clouds limiting their value to study cropland dynamics. Here, we characterized cropland dynamics in Eastern Africa for 2003–2015 using precipitation data from Tropical Rainfall Measuring Mission (TRMM) and a passive microwave dataset of land surface variables that blends data from the Advanced Microwave Scanning Radiometer (AMSR) on the Earth Observing System (AMSR-E) from 2002 to 2011 with data from AMSR2 from 2012 to 2015 with a Chinese microwave radiometer to fill the gap. These time series were analyzed in terms of either cumulative precipitable water vapor-days (CVDs) or cumulative actual evapotranspiration-days (CETaDs), rather than as days of the year. Time series of the land surface variables displayed unimodal seasonality at study sites in Ethiopia and South Sudan, in contrast to bimodality at sites in Tanzania. Interannual moisture variability was at its highest at the beginning of the growing season affecting planting times of crops, while it was lowest at the time of peak moisture. Actual evapotranspiration (ETa) from the simple surface energy balance (SSEB) model was sensitive to track both unimodal and bimodal rainfall patterns. ETa as a function of CETaD was better fitted by a quadratic model (r2 > 0.8) than precipitable water vapor was by CVDs (r2 > 0.6). Moisture time to peak (MTP) for the land surface variables showed strong, logical correspondence among variables (r2 > 0.73). Land surface parameters responded to El Niño-Southern Oscillation and the Indian Ocean Dipole forcings. Area under the curve of the diel difference in vegetation optical depth showed correspondence to crop production and yield data collected by local offices, but not to the data reported at the national scale. A long-term seasonal Mann–Kendall rainfall trend showed a significant decrease for Ethiopia, while the decrement was not significant for Tanzania. While there is significant potential for passive microwave data to augment cropland status and food security monitoring efforts in the region, more research is needed before these data can be used in an operational environment.
Highlights
Across Eastern Africa, croplands cover 45 million ha [1]
While there is significant potential for passive microwave data to augment cropland status and food security monitoring efforts in the region, more research is needed before these data can be used in an operational environment
The African economy is heavily dependent on small holder traditional rain-fed peasant agriculture, which is vulnerable to extreme weather events such as drought and floods [2,3,4]
Summary
Across Eastern Africa, croplands cover 45 million ha [1]. Ethiopia (ET) and Tanzania (TZ) are the two major crop producing countries in the region, accounting for 14 million ha and 13 million ha of Remote Sens. 2017, 9, 914; doi:10.3390/rs9090914 www.mdpi.com/journal/remotesensingRemote Sens. 2017, 9, 914 croplands, respectively [1]. Across Eastern Africa, croplands cover 45 million ha [1]. Ethiopia (ET) and Tanzania (TZ) are the two major crop producing countries in the region, accounting for 14 million ha and 13 million ha of Remote Sens. Food crops mainly produced in the region include maize, sorghum, wheat, barley, millet, rice, teff (a small grain produced and used primarily in Ethiopia), beans, and peas [8]. Farming systems in Ethiopia are mainly highland temperate mixed and maize mixed, while in Tanzania it is mainly maize mixed, and in South Sudan cereal-root crop mixed [8]. The highland temperate mixed farming system produces small grains, such as wheat, barley, teff, and livestock. Production in the cereal-root crop mixed farming system is based on vegetables, animal products, and cereals, such as maize, sorghum, and millet
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