Innovate UK - SHiFT: Sentinel 2 -compatible Historical datasets for Future crop Targeting
Lead Research Organisation:
University of Nottingham
Department Name: Sch of Geography
Abstract
The project will investigate the use of archive satellite imagery to predict spatial variability within arable fields. Many applications of precision agriculture use current satellite imagery to provide guidance on localised management operations, for example application of Nitrogen fertiliser, but assumptions have to be made about the causes of spatial variation. A 20-year archive of satellite image data will be used to develop potential productivity maps, derived from vegetation indices, to assess the degree of persistence of spatial patterns over years and their dependence on weather and cropping factors. Maps of potential yield variation and other interpretive tools will allow more intelligent, context-based assessments that are expected to lead to improved land management with both economic and environmental benefits. The project is being conducted by a consortium led by SOYL, together with ADAS, RSAC, AHDB and the University of Nottingham.
Planned Impact
Who might benefit from this research and how?
Farmers that use precision agriculture have quite high data costs for satellite imagery monitoring current cops, soil and other specialist surveys, typically in the region of £10 per hectare. If successful the project is expected to reduce information costs to farmers in precision agriculture by ca. 50%, leading to a saving per farm (typically 200 ha) of around £1000 in data costs. Additional benefits will accrue in terms of the sustainable farm management by optimising inputs to reduce wastage and increase yields; our industrial partners, who offer advice services in precision agriculture, report typical yield gains of 3 and 8% over the farmer's best practice using precision agriculture techniques. This saving to farmers is expected to grow their market for precision agriculture services by 20-30% per annum over 5 years. This will allow an increase in R&D investment in the advice industry, generating further jobs in the industry. It is estimated that the additional tax returned to the government by this development could be in the region of £4 million, representing roughly £40 return for every £1 invested in this project.
In addition to the economic benefits of applying precision agriculture, the reduced wastage of agricultural chemicals by targeting them on areas of need, leads directly to benefits to the environment in terms of cleaner water, reduced contamination of land and improved biodiversity.
Farmers that use precision agriculture have quite high data costs for satellite imagery monitoring current cops, soil and other specialist surveys, typically in the region of £10 per hectare. If successful the project is expected to reduce information costs to farmers in precision agriculture by ca. 50%, leading to a saving per farm (typically 200 ha) of around £1000 in data costs. Additional benefits will accrue in terms of the sustainable farm management by optimising inputs to reduce wastage and increase yields; our industrial partners, who offer advice services in precision agriculture, report typical yield gains of 3 and 8% over the farmer's best practice using precision agriculture techniques. This saving to farmers is expected to grow their market for precision agriculture services by 20-30% per annum over 5 years. This will allow an increase in R&D investment in the advice industry, generating further jobs in the industry. It is estimated that the additional tax returned to the government by this development could be in the region of £4 million, representing roughly £40 return for every £1 invested in this project.
In addition to the economic benefits of applying precision agriculture, the reduced wastage of agricultural chemicals by targeting them on areas of need, leads directly to benefits to the environment in terms of cleaner water, reduced contamination of land and improved biodiversity.
| Description | The aims of the project were to develop a database of historical satellite NDVI (Normalised Difference Vegetation Index) imagery as a cheap way of mapping spatial variability in arable crops. The database would then be used to meet the following objectives: 1. assessment of year to year persistence of variation patterns; 2. dependence of spatial variability on weather. 3. dependence on cropping factors. 4. development of yield potential maps 5. validation and farmer interpretation of spatial variations. A database from 1995 to 2016 was built for a sample of 30 fields, with data standardised for differences between observing systems and rectified to the UK national grid. Some fields had up to 18 years of data. Apart from objective 2 - weather dependence - where some work remains, all the objectives were achieved satisfactorily. Highlight achievements are the development of robust, quantitative metrics for persistence of spatial variability (figure 1) and for canopy potential, expressed in units of yield. Farmers involved in validation of the study expressed considerable interest in these developments and our partner SOYL (the lead organisation for the Innovate-UK project) has expressed the intention of implementing these tools as part of its service to farmers. Figure 1. "Persistence image for field 162WH (38 ha). Red areas indicate consistently above average, green areas consistently about average and blue areas, consistently below average. |
| Exploitation Route | Farmers involved in validation of the study expressed considerable interest in these developments and our partner SOYL (the lead organisation for the Innovate-UK project) has expressed the intention of implementing these tools as part of its service to farmers. |
| Sectors | Agriculture, Food and Drink,Environment |