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Article

Regional Scale Mapping of Grassland Mowing Frequency with Sentinel-2 Time Series

1
Environmental Geography group, VU University Amsterdam, De Boelelaan 1085, 1081 Amsterdam, The Netherlands
2
Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Zürcherstrasse 111, CH-8903 Birmensdorf, Switzerland
3
Institute of Geography and Spatial Management, Jagiellonian University, Gronostajowa 7, 30-387 Kraków, Poland
*
Author to whom correspondence should be addressed.
Received: 28 June 2018 / Accepted: 31 July 2018 / Published: 3 August 2018
(This article belongs to the Special Issue Monitoring Agricultural Land-Use Change and Land-Use Intensity)
Grassland use intensity is a topic of growing interest worldwide, as grasslands are integral in supporting biodiversity, food production, and regulating of the global carbon cycle. Data available for characterizing grasslands management are largely descriptive and collected from laborious field campaigns or questionnaires. The recent launch of the Sentinel-2 earth monitoring constellation provides new possibilities for high temporal and spatial resolution remote sensing data covering large areas. This study aims to evaluate the potential of a time series of Sentinel-2 data for mapping of mowing frequency in the region of Canton Aargau, Switzerland. We tested two cloud masking processes and three spatial mapping units (pixels, parcel polygons and shrunken parcel polygons), and investigated how missing data influence the ability to accurately detect and map grassland management activity. We found that more than 40% of the study area was mown before 15 June, while the remaining part was either mown later, or was not mown at all. The highest accuracy for detection of mowing events was achieved using additional clouds masking and size reduction of parcels, which allowed correct detection of 77% of mowing events. Additionally, we found that using only standard cloud masking leads to significant overestimation of mowing events, and that the detection based on sparse time series does not fully correspond to key events in the grass growth season. View Full-Text
Keywords: grassland; mowing; Sentinel-2; time series; NDVI grassland; mowing; Sentinel-2; time series; NDVI
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MDPI and ACS Style

Kolecka, N.; Ginzler, C.; Pazur, R.; Price, B.; Verburg, P.H. Regional Scale Mapping of Grassland Mowing Frequency with Sentinel-2 Time Series. Remote Sens. 2018, 10, 1221. https://0-doi-org.brum.beds.ac.uk/10.3390/rs10081221

AMA Style

Kolecka N, Ginzler C, Pazur R, Price B, Verburg PH. Regional Scale Mapping of Grassland Mowing Frequency with Sentinel-2 Time Series. Remote Sensing. 2018; 10(8):1221. https://0-doi-org.brum.beds.ac.uk/10.3390/rs10081221

Chicago/Turabian Style

Kolecka, Natalia, Christian Ginzler, Robert Pazur, Bronwyn Price, and Peter H. Verburg. 2018. "Regional Scale Mapping of Grassland Mowing Frequency with Sentinel-2 Time Series" Remote Sensing 10, no. 8: 1221. https://0-doi-org.brum.beds.ac.uk/10.3390/rs10081221

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