Automated Processing of Sentinel-2 Products for Time-Series Analysis in Grassland Monitoring

Research output: Chapter in Book/Report/Conference proceedingConference paper

Abstract

Effective grassland management practices require a good understanding of soil and vegetation properties, that can be quantified by farmers’ knowledge and remote sensing techniques. Many systems have been proposed in the past for grassland monitoring, but open-source alternatives are increasingly being preferred. In this paper, a system is proposed to process data in an open-source and automated way. This system made use of Sentinel-2 data to support grassland management at Haus Riswick in the region around Kleve, Germany, retrieved with help of a platform called Sentinelsat that was developed by ESA. Consecutive processing steps consisted of atmospheric correction, cloud masking, clipping the raster data, and calculation of vegetation indices. First results from 2018 resembled the mowing regime of the area with four growing cycles, although outliers were detected due to a lack of data caused by cloud cover. Moreover, that year’s extremely dry summer was visible in the time-series pattern as well. The proposed script is a primary version of a processing chain, which is suitable to be further expanded for more advanced data pre-processing and data analysis in the future.
Original languageEnglish
Title of host publicationInternational Symposium on Environmental Software Systems (ISESS 2020)
Subtitle of host publicationEnvironmental Software Systems. Data Science in Action
Place of PublicationWageningen
PublisherSpringer
Chapter5
Pages48-56
ISBN (Electronic)9783030398156
ISBN (Print)9783030398149
DOIs
Publication statusPublished - 29 Jan 2020

Publication series

Name IFIP Advances in Information and Communication Technology
Volume554
ISSN (Print)1868-4238
ISSN (Electronic)1868-422X

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Hardy, T., Franceschini, M. D., Kooistra, L., Novani, M., & Richter, S. (2020). Automated Processing of Sentinel-2 Products for Time-Series Analysis in Grassland Monitoring. In International Symposium on Environmental Software Systems (ISESS 2020): Environmental Software Systems. Data Science in Action (pp. 48-56). ( IFIP Advances in Information and Communication Technology ; Vol. 554). Wageningen: Springer. https://doi.org/10.1007/978-3-030-39815-6_5