Current multispectral data are a solid input data source for agricultural services, but they cannot capture the individual spectral absorption bands that characterise the plant biochemical parameters. Those are necessary to go from crop observation to a deep understanding of the causes of what is happening in the fields, and from qualitative description to quantitative assessment, as a baseline for precision farming on a parcel level.
To be able to address the commercial needs – for accessing the huge smart farming market, for instance – a spatial resolution of 20m or better, and bands in the spectral range of 0,4 to 1,7 µm are required. Such operational, hyperspectral remote sensing data serving the requirements of enhanced agricultural Earth observation (EO) products are currently not available. A major challenge is the typical budget (volume, mass and resulting cost) of a traditional hyperspectral instrument (such as EnMAP or CHIME), leading to satellite costs that are not compliant with a reasonable commercial business plan. A filter-on-chip-based hyperspectral instrument optimised for agricultural applications is expected to solve the issue. RAINBOW is based on a cost-efficient design of the compact optical payload onboard a LEO small satellite supported by appropriate data fusion and processing.
Farmers, farm advisors and the agricultural industry are interested in managing fields in a sustainable way, where yield is high, and inputs are low. With RAINBOW smart farming services, the causes of issues in the field, as well as the spread of the issues can be discovered, allowing precise reactions that lead to profit from stabilised yields and savings from using input resources efficiently.
Certification bodies, governmental agencies, NGOs, and carbon traders need to prove carbon sequestration in soils, for carbon certification. RAINBOW carbon maps show carbon content in soils in a continuous area-wide manner and allow a reduction in laboratory analysis as well as an increase in the temporal frequency of sampling and analysis, leading to better results at lower costs.
Farmers, farm advisors, traders, NGOs, and governmental agencies are interested in the yield quality information such as protein content, to fetch the highest prices or predict the availability of wheat yield for human consumption. RAINBOW Yield Quality Services will allow, for the first time, the prediction of not only yield quantity, but also yield quality from space, allowing farmers, NGOs and governmental agencies to better plan for the future.
The key customer segments targeted by the RAINBOW products are farmers, farm advisors and the agricultural industry worldwide, providing detailed and topical information on the status of their crops and how to manage them best. RAINBOW addresses farmers mainly in Europe, which has the highest ratio of farms with smart farming technology on the field already, but also in North America, Africa and Australia. Additionally, we will also develop services geared towards traders, NGOs, governmental agencies and certification bodies.
With the spectrometer-on-chip approach, the goal is to map the required spectral bands of the application 1:1 onto a transmission filter integrated directly in front of the detector. This way, the properties of the spectral channels such as spectral lineshape, are directly related to the transmission of the filter. The difference to multispectral instruments is that a larger number of channels can be observed. This is accomplished by the design of a filter, which is implemented as a ‘pixelated’ filter that reproduces a step pattern, allowing for a dedicated transmission over every column of pixels on the detector.
From the RAINBOW spectral data, smart farming products such as irrigation recommendations, yield forecasts or soil organic carbon content measurements will be generated, and a hyperspectral data cube will be produced for further customised analysis.
The data products are addressing the sector of agriculture and data-driven farming, which has the following characteristics:
• Is a global market
• Needs to monitor small parcels, at least weekly, in high-resolution imagery
• Has a very strong price competition (small cost/ha)
• Is strongly pushing towards a smaller impact to environment (without fertilizers and pesticides, low carbon footprint, preservation of biodiversity, etc.)
• Follows the traditional behaviour of end users
In order to be successful on the market, the availability of remote-sensing data covering the relevant area at least on bi-weekly basis is mandatory. The filter-on-chip-based instrument concept is an enabling technology that is a pre-requisite for keeping the cost for acquiring the hyperspectral data reasonably low.
The InCubed+ de-risking activity was kicked-off in December 2022. In preparation of the activity preliminary market assessment and derivation of mission requirements have been performed. Also preliminary requirements to derive the payload design like spatial resolution, spectral resolution and radiometric performances are established. Initial design parameters for the filter and chip are defined and a candidate detector is selected. Trade-off how to mount the filter on the detector and design optimization for the telescope are required to achieve the goal of a low cost instrument design.