Simulating cropping sequences using earth observation data

A - Papers appearing in refereed journals

Sharp, R. T., Henrys, P. A., Jarvis, S. G., Whitmore, A. P., Milne, A. E., Coleman, K., Mohankumar, S. E. P. and Metcalfe, H. 2021. Simulating cropping sequences using earth observation data. Computers and Electronics in Agriculture. 188, p. 106330.

AuthorsSharp, R. T., Henrys, P. A., Jarvis, S. G., Whitmore, A. P., Milne, A. E., Coleman, K., Mohankumar, S. E. P. and Metcalfe, H.

Model-based studies of agricultural systems often rely on the analyst defining realistic crop sequences. This usually involves relying on a few ‘typical rotations’ that are used in baseline scenarios. These may not account for the variation in farming practices across a region, however, as farmer decision making about which crops to grow is influenced by a combination of economic, environmental and social drivers. We describe and test an approach for generating random realisations of plausible crop sequences based on observed data as quantified by earth observation. Our approach combines crop classification data with a series of crop management rules that reflect the advice followed by farmers (e.g. to reduce the chance of crop-pests and disease). We adapt the approach to generate crop sequences specific to regions and soil type. This demonstrates how the method can be adapted to generate crop sequences typical of a study area of interest.

KeywordsCrop rotations; Land Cover® plus: Crops; Modelling; Crop management; Baseline scenario modelling
Year of Publication2021
JournalComputers and Electronics in Agriculture
Journal citation188, p. 106330
Digital Object Identifier (DOI)
Open accessPublished as green open access
FunderBiotechnology and Biological Sciences Research Council
Natural Environment Research Council
Funder project or codeBB/S014292/1
S2N - Soil to Nutrition - Work package 3 (WP3) - Sustainable intensification - optimisation at multiple scales
ASSIST - Achieving Sustainable Agricultural Systems
Accepted author manuscript
Copyright license
Output statusPublished
Publication dates
Online27 Jul 2021
Publication process dates
Accepted22 Jul 2021
PublisherElsevier Sci Ltd

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