Assessments on the impact of high-resolution-sensor pixel sizes for common agricultural policy and smart farming services in European regions

Abstract

High-resolution (5–50 m) remote sensing satellite sensors provide a reliable, free and open data infrastructure for public and private agriculture and land use services. The further market penetration of these services critically depends on the fraction of agricultural fields and area that the services can cover. EU’s Common Agricultural Policy (CAP) and smart farming services require a minimum of spectrally pure measurements per agricultural field. The impact of pixel size on the coverage of agriculture is studied in this paper considering present free and open optical sensors (Sentinel-2 and LANDSAT). It further studies the implications of the selection of spatial resolution of planned extensions of these sensors, i.e. the next generation of Sentinel-2, as well as Copernicus’s hyperspectral CHIME and thermal LSTM future candidate missions. The paper analyzes the 2018 vector boundaries and crop types of 3.6 million agricultural fields in the German States of Bavaria and Lower Saxony and the Netherlands. The fields were rasterized using Sentinel-2 flight geometry and a pixel spacing of 5, 10, 20, 30 and 50 m. The study specifically considered: (1) fields with no pure pixel inside where no CAP services can be provided and (2) fields with less than 50 pure pixels inside, which is estimated to be the critical number for site-specific smart farming. The percentage of agricultural fields and agricultural area was determined for the main crop types. It shows, that with 10 m pixel spacing 2–4% and 20 m pixel spacing 12–22% of the agricultural fields in the study area do not contain a single pure spectral sample (Sentinel-2 case). This fraction decreases to 1–3% at 5 m spacing and increases to 25–40% for 30 m (LANDSAT and CHIME) and 50–70% for 50 m (LSTM) spacing. The percentage of fields with less than 50 pure pixels is 20–50% at 10 m and 70–85% at 20 m spacing (Sentinel-2). This fraction decreases to 5–12% for 5 m spacing and reaches the level of 92–97% for 30 m (LANDSAT) and 99% for 50 m spacing (LSTM). Our analysis shows, that with a pixel spacing of 5 m the Sentinel-2-based site-specific smart farming services could increase their potential customer base from ~50% to ~90% of the agricultural fields and could potentially cover 99% of the regions’ agricultural area. A 20 m pixel spacing would increase the agriculture area from 23% to 56% in the Central and Western European study regions on which the Copernicus hyperspectral candidate mission CHIME is capable to measure pure and full spectra for highly advanced future site-specific management services. LSTM would also profit from a spatial resolution of 30 m, which would raise coverage of the agricultural area in Central Europe with pure thermal measurements from 3% at 50 m to 23% at 30 m.

Topics & Concepts