Winter wheat straw return monitoring by UAVs observations at different resolutions

ABSTRACT

Straw return is a critical component of implementing protective air plans in China and increasing soil organic matter accumulation. This study aims to evaluate the effectiveness of unmanned aerial vehicles (UAVs) data in monitoring straw return. Three study areas in Jiangsu Province were compared under different rotation methods at two distinct resolutions (5 cm and 10 cm), including the Xinghua area (wheat-rice rotation), the Peixian area (wheat-maize rotation), and the Guanyun area (wheat-rice and wheat-maize rotations). After combining the ground survey data with the needs for subsidy policy evaluation, four classifications were chosen, which were the whole straw return classification, the partial straw return classification, the open burning classification, and the uncertain classification. The results showed the following: (1) the whole straw return classification covered 24.71% (21.87 km²) of the study area, the partial straw return classification covered 44.14% (39.07 km²), the straw open burning classification covered 21.34% (18.89 km²), and the uncertain classification covered 9.81% (8.69 km²); (2) both 5 cm and 10 cm ground-resolution UAV data were able to monitor straw return, but the 10 cm ground-resolution UAV data were the most time- and cost-effective choice; and (3) partial straw return was the most acceptable method, indicating that the policies intending to increase the subsidy and penalty had little effect on increasing straw return and preventing the open burning of straw.

Acknowledgements

We are grateful for the financial support provided by the Natural Science Foundation of Jiangsu Province (BK20140759), the Jiangsu Agricultural Science and Technology Innovation Fund (CX-14-5072), the Open Foundation of the Key Laboratory of the Coastal Zone Exploitation and Protection, Ministry of Land and Resource (2015CZEPK03), the National Natural Science Foundation of China (Grant No. 41401416), the Jiangsu Academy of Agricultural Sciences Basic Scientific Research Work Special Fund (ZX-15-3003), and the Agricultural Remote Sensing Technique Innovation Program of Remote Sensing Application Centre of Chinese Ministry of Agriculture. We thank Prof Cracknell (University of Dundee) for his comments and suggestions.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by the Natural Science Foundation of Jiangsu Province [BK20140759]; Jiangsu Agricultural Science and Technology Innovation Fund [CX-14-5072]; Open Foundation of the Key Laboratory of the Coastal Zone Exploitation and Protection, Ministry of Land and Resource [2015CZEPK03]; National Natural Science Foundation of China [41401416]; Jiangsu Academy of Agricultural Sciences Basic Scientific Research Work Special Fund [ZX-15-3003]; Agricultural Remote Sensing Technique Innovation Program of Remote Sensing Application Centre of Chinese Ministry of Agriculture.