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Separability of Mowing and Ploughing Events on Short Temporal Baseline Sentinel-1 Coherence Time Series

KappaZeta Ltd., 51007 Tartu, Estonia
Tartu Observatory, University of Tartu, Tõravere, 61602 Tartumaa, Estonia
University Medical Center Groningen, Department of Epidemiology, University of Groningen, 9713GZ Groningen, The Netherlands
Institute of Ecology and Earth Sciences, University of Tartu, 51003 Tartu, Estonia
Software Technology and Applications Competence Center, 51009 Tartu, Estonia
Flow Traders, 1018LL Amsterdam, The Netherlands
Institute for Environmental Solutions, Lidlauks, LV-4101 Priekuļu parish, Latvia
School of Electrical Engineering, Aalto University, 02150 Espoo, Finland
Author to whom correspondence should be addressed.
Remote Sens. 2020, 12(22), 3784;
Received: 21 October 2020 / Revised: 13 November 2020 / Accepted: 15 November 2020 / Published: 18 November 2020
Short temporal baseline regular Synthetic Aperture Radar (SAR) interferometry is a tool well suited for wide area monitoring of agricultural activities, urgently needed in European Union Common Agricultural Policy (CAP) enforcement. In this study, we demonstrate and describe in detail, how mowing and ploughing events can be identified from Sentinel-1 6-day interferometric coherence time series. The study is based on a large dataset of 386 dual polarimetric Sentinel-1 VV/VH SAR and 351 Sentinel-2 optical images, and nearly 2000 documented mowing and ploughing events on more than 1000 parcels (average 10.6 ha, smallest 0.6 ha, largest 108.5 ha). Statistical analysis revealed that mowing and ploughing cause coherence to increase when compared to values before an event. In the case of mowing, the coherence increased from 0.18 to 0.35, while Sentinel-2 NDVI (indicating the amount of green chlorophyll containing biomass) at the same time decreased from 0.75 to 0.5. For mowing, there was virtually no difference between the polarisations. After ploughing, VV-coherence grew up to 0.65 and VH-coherence to 0.45, while NDVI was around 0.2 at the same time. Before ploughing, both coherence and NDVI values were very variable, determined by the agricultural management practices of the parcel. Results presented here can be used for planning further studies and developing mowing and ploughing detection algorithms based on Sentinel-1 data. Besides CAP enforcement, the results are also useful for food security and land use change detection applications. View Full-Text
Keywords: SAR; agriculture; interferometric coherence; Sentinel-1 SAR; agriculture; interferometric coherence; Sentinel-1
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MDPI and ACS Style

Voormansik, K.; Zalite, K.; Sünter, I.; Tamm, T.; Koppel, K.; Verro, T.; Brauns, A.; Jakovels, D.; Praks, J. Separability of Mowing and Ploughing Events on Short Temporal Baseline Sentinel-1 Coherence Time Series. Remote Sens. 2020, 12, 3784.

AMA Style

Voormansik K, Zalite K, Sünter I, Tamm T, Koppel K, Verro T, Brauns A, Jakovels D, Praks J. Separability of Mowing and Ploughing Events on Short Temporal Baseline Sentinel-1 Coherence Time Series. Remote Sensing. 2020; 12(22):3784.

Chicago/Turabian Style

Voormansik, Kaupo; Zalite, Karlis; Sünter, Indrek; Tamm, Tanel; Koppel, Kalev; Verro, Tarvi; Brauns, Agris; Jakovels, Dainis; Praks, Jaan. 2020. "Separability of Mowing and Ploughing Events on Short Temporal Baseline Sentinel-1 Coherence Time Series" Remote Sens. 12, no. 22: 3784.

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