Automatic Large-Scale Precise Mapping and Monitoring of Agricultural Fields at Country Level With Sentinel-2 SITS

Abstract

Availability of multi-temporal images, such as the Sentinel-2 (S2) ones, offers accurate spatial, spectral and temporal information to effectively monitor vegetation, more specifically agriculture. Agricultural practices can benefit from temporally dense Satellite Image Time Series (SITS) for accurate understanding of the phenological evolution and behavior of crops. Developing techniques that deal with high spatial correlation and high temporal resolution requires a shift in the processing paradigm and poses new challenges in terms of data processing and methodology. This paper presents an automatic approach to large-scale precise mapping of small agricultural fields based on the analysis of S2-SITS at Country level. The approach deals with a flexible and automatic processing chain for massive data and was tested at Country level. The large-scale application requires to consider: (i) the management of big amount of data with particular attention to download and preprocessing of S2-SITS; and (ii) multi-temporal fine characterization of crop fields accounting for the strong variability in size and phenological behaviors when mapping at large scale. Both challenges are addressed in an automatic way by exploiting and/or updating state-of-the-art methodologies. Promising results have been obtained and validated over 2017 and 2018 agrarian years for Italy.

Complementary Use of Ground-Based Proximal Sensing and Airborne/Spaceborne Remote Sensing Techniques in Precision Agriculture: A Systematic Review

“…The grouping helps to provide a summary of the challenge in a form that is quick and easy on the eye and captures how many works have mentioned it in the past. [142,159,160] Limitations due to the viewing angle [57] Future research More research on transforming image classification maps into application maps [121] Orthomosaic accuracy [161] Connectivity [142,148] Different device cooperation [142,162] Need to make satellites more approachable for farmers [155]…”

“…Their processing is a timeconsuming and computationally intensive endeavour [144]. Processing these data under time constraints may affect the quality of the final result [148]. Storing and managing the sheer volumes of imagery is a considerable challenge on its own.…”