Generating crop calendars with Web search data
This paper demonstrates the potential of using Web search volumes for generating crop specific planting and harvesting dates in the USA integrating climatic, social and technological factors affecting crop calendars. Using Google Insights for Search, clear peaks in volume occur at times of planting and harvest at the national level, which were used to derive corn specific planting and harvesting dates at a weekly resolution. Disaggregated to state level, search volumes for corn planting generally are an agreement with planting dates from a global crop calendar dataset. However, harvest dates were less discriminatory at the state level, indicating that peaks in search volume may be blurred by broader searches on harvest as a time of cultural events. The timing of other agricultural activities such as purchase of seed and response to weed and pest infestation was also investigated. These results highlight the future potential of using Web search data to derive planting dates in countries where the data are sparse or unreliable, once sufficient search volumes are realized, as well as the potential for monitoring in real time the response of farmers to climate change over the coming decades. Other potential applications of search volume data of relevance to agronomy are also discussed.
KEYWORDS: Corn; Maize; Crop planting; Internet; Web search data; Crowd-sourcing; Crop model; Harvest; Web tools; Google Insights for Search