CaRMA

Vergrößern

The CHIME and ROSE-L Measurement Assistance for the AgriROSE-L Campaign (CaRMA) objectives focus on continuation of providing calibration data for agricultural applications in succession to the preceding work.

One such effort, among others, is the joint working group on calibration/validation that has been established between ESA and the National Aeronautics and Space Administration (NASA). This collaboration aims to develop an end-to-end Cal/Val strategy, including the establishment of measurement networks, standardization of reference data sets, and the implementation of joint airborne spectroscopy campaigns. Notably, a joint airborne campaign was conducted in 2021, involving the Airborne Visible/Infrared Imaging Spectrometer Next Generation (AVIRIS-NG), to support both CHIME and NASA's Surface Biology and Geology (SBG) missions. This campaign covered multiple European countries and coordinated with existing satellite missions like PRISMA and DESIS (DLR Earth Sensing Imaging Spectrometer) to collect comprehensive calibration data.

The procedure in the CaRMA campaign is similar but even more extensive, as multiple airborne sensors contribute to the campaign. Not only the hyperspectral HySpex, operated by the German Aerospace Center (DLR) and HyPlant, operated by CzechGlobe, airborne sensors provide high-resolution data for preparation of the CHIME mission. In addition, DLR’s large-scale airborne synthetic-aperture radar (SAR) facility, designated as F-SAR, will provide calibration data as a pioneering study for the upcoming ROSE-L mission. The SAR system operates in a fully polarimetric mode within the X-, C-, S-, L-, and P-bands and performs quasi-simultaneous recordings across four distinct channels.

The CaRMA field activities will provide comprehensive ground sampling data for many biophysical and biochemical variables across a wide range of crop types. This data is supposed (i) to support the airborne flights’ calibration efforts, (ii) to generate a comprehensive database that allows for exploring the development of innovative retrieval techniques and (iii) to serve as validation standard for established retrieval algorithms targeting agriculturally relevant variables. For that, a dense sampling scheme at overpass times of a multi-sensor constellation and across a plentitude of field crops has been developed, which at the same time accounts for in-field variabilities of relevant plant characteristics.