| Autor: |
Lawes, R., Hochman, Z., Jakku, E., Butler, R., Chai, J., Chen, Y., Waldner, F., Mata, G., Donohue, R. |
| Předmět: |
|
| Zdroj: |
Crop & Pasture Science; 2023, Vol. 74 Issue 6, p509-523, 15p |
| Abstrakt: |
The Australian dryland grain-cropping landscape occupies 60 Mha. The broader agricultural sector (farmers and agronomic advisors, grain handlers, commodity forecasters, input suppliers, insurance providers) required information at many spatial and temporal scales. Temporal scales included hindcasts, nowcasts and forecasts, at spatial scales ranging from sub-field to the continent. International crop-monitoring systems could not service the need of local industry for digital information on crop production estimates. Therefore, we combined a broad suite of satellite-based crop-mapping, crop-modelling and data-delivery techniques to create an integrated analytics system (Graincast™) that covers the Australian cropping landscape. In parallel with technical developments, a set of user requirements was identified through a human-centred design process, resulting in an end-product that delivered a viable crop-monitoring service to industry. This integrated analytics solution can now produce crop information at scale and on demand and can deliver the output via an application programming interface. The technology was designed to underpin digital agriculture developments for Australia. End-users are now using crop-monitoring data for operational purposes, and we argue that a vertically integrated data supply chain is required to develop crop-monitoring technology further. The Graincast™ suite of tools was developed to monitor crop productivity in near real-time across the Australian landscape. Four separate tools were created: the C-Crop model, which monitors crop yields with satellite; CropID, which monitors the crop species and areas of production; the Graincast™ app, which provides field-scale estimates of crop production and soil-water use; and Field Boundaries (ePaddocks), which identifies every cropped field across the landscape. The paper describes the design process, including data acquisition, machine learning, testing, validation, human-centred design and the delivery of outputs to end-users. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
|
|
Nepřihlášeným uživatelům se plný text nezobrazuje |
K zobrazení výsledku je třeba se přihlásit.
|
