Landsat-based wheat mapping in the heterogeneous cropping system of Punjab, Pakistan

ABSTRACT

Wheat is a staple food of Pakistan’s population of more than 180 million. The average annual harvest of 24 million tonnes places Pakistan eighth in the world in wheat production. Roughly, 76% of wheat is produced by Punjab province, the breadbasket of Pakistan. The current wheat area and yield reporting system operated by the Punjab Crop Reporting Service (CRS) delivers estimates several months after harvest. The delayed production data cannot contribute to in-season decision support system, such as timely production estimation. However, freely available satellite imagery at medium spatial resolution offers a data source for addressing this limitation. Using Landsat data from the 2013 to 2014 winter wheat growing season and a supervised bagged classification tree approach, we estimated the area of wheat cultivated in Punjab. Validation consisted of a two-stage probability-based cluster field sample. Field data from 110 sample points distributed among twelve 20 km × 20 km blocks were collected. Overall accuracy of the Landsat-based wheat map was 76% with wheat commission error of 38% and wheat omission error of 30%. The Landsat-based map totalled 6.13 Mha of wheat area, and the field-based sample estimate 6.96 ± 2.15 Mha. Both figures are comparable to the official Punjab CRS figure of 6.77 Mha. The study presents a robust approach for early wheat area estimation providing information relevant to decision support systems concerning food production and trade.

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Acknowledgements

We would like to thank the CRS Punjab for sharing the second wheat statistics for the Rabi season 2013–2014. We thank Mr Muhammad Saleem Khan from Daira Din Panah, Punjab, whose knowledge of the area was critical for executing our field campaign. We also thank Mr. Umer Saeed and Mr Muhammad Fahad of Faisalabad Agriculture University for facilitating the fieldwork. We thank Allison Gost for her timely assistance and support with logistics and travel arrangements and our colleagues Jan Dempewolf, Jon Nordling, and Bernard Adusei for their help at various stages of the research. We are thankful to the anonymous reviewers and editor Timothy Warner for providing numerous helpful comments that improved the manuscript.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

We acknowledge the funding support from the National Aeronautics and Space Administration’s Land Cover and Land Use Change and Applied Sciences programs through grant NNX12AC78G and the United States Agriculture Department’s Foreign Service through grant number 5831481225.