Abstract
It is of paramount importance to have sustainable agriculture since agriculture is the backbone of many nations’ economic development. Majority of agricultural professionals rarely capture the cropping patterns necessary to promote Good Agricultural Practises. Objective of this research is to explore the potential of mapping cropping patterns occurring on different field parcels on small-scale farmlands in Zimbabwe. The first study location under investigation are the International Maize and Wheat Improvement Center (CIMMYT) research station and a few neighboring fields, the second is Middle Sabi Estate. Fourier time series modeling was implemented to determine the trends befalling on the two study sites. Results reveal that Sentinel-1 synthetic aperture radar (SAR) time series allow detection of subtle changes that occur to the crops and fields respectively, hence can be utilized to detect cropping patterns on small-scale farmlands. Discrimination of the main crops (maize and soybean) grown at CIMMYT was possible, and crop rotation was synthesized where sowing starts in November. A single cropping of early and late crops was observed, there were no winter crops planted during the investigation period. At Middle Sabi Estate, single cropping on perennial sugarcane fields and triple cropping of fields growing leafy vegetables, tomatoes and onions were observed. Classification of stacked images was used to derive the crop rotation maps representing what is practised at the farming lands. Random forest classification of the multi-temporal image stacks achieved overall accuracies of 99% and 95% on the respective study sites. In conclusion, Sentinel-1 time series can be implemented effectively to map the cropping patterns and crop rotations occurring on small-scale farming land. We recommend the use of Sentinel-1 SAR multi-temporal data to spatially explicitly map cropping patterns of single-, double- and triple-cropping systems on both small-scale and large-scale farming areas to ensure food security.
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Acknowledgement
We are grateful to Dr. Mainassara Zaman-Allah, Richard Makanza and Savemore Ngirazi for providing unmanned aerial vehicle (UAV) images.
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Foundation item: Under the auspices of Fundamental Research Funds for the Central Universities, China (No. 2017TD-26), the Plan for Changbai Mountain Scholars of Jilin Province, China (No. JJLZ[2015]54)
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Useya, J., Chen, S. Exploring the Potential of Mapping Cropping Patterns on Smallholder Scale Croplands Using Sentinel-1 SAR Data. Chin. Geogr. Sci. 29, 626–639 (2019). https://doi.org/10.1007/s11769-019-1060-0
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DOI: https://doi.org/10.1007/s11769-019-1060-0