Abstract
Grassland use intensity and its impact on biodiversity and water pollution is a topic of growing interest. In ecological
studies, intensity of use has been assessed by means of three indicators: i) mowing frequency, ii) grazing
intensity, and iii) fertilization input. A multidimensional approach is key for the understanding of intensification
effects in terrestrial and water ecosystems. Remote sensing is a powerful tool to monitor management indicators.
Nevertheless, interdependencies between remote sensing methods and between indicators require new approaches
to assess intensity of use. The objective of this study is to monitor ecological indicators of land use intensity
based on multispectral imagery using a multidimensional approach. We performed a multi-temporal
analysis using a series of RapidEye images within a growing season in the Canton of Zurich, Switzerland, in
2013.We defined mowing frequency classes distinguishing spectral changes between pairs of images. The analysis
of the whole image sequence within the growing season helped differentiate grazing intensities. Furthermore,
we analysed the suitability of modelled livestock density based on remote sensing derived products to
determine fertilizer input. Three grassland management practices were distinguished: i) medium intensive
(46%), ii) lowintensive (37%), and iii) high intensive (17%).We discuss the combination of highmowing frequency
and fieldswith high grazing intensity to define areas prone to nutrient surpluses. Finally,we demonstrate that
the estimation of interrelated indicators of grassland use intensity could be carried out preserving independence
between methods.
Gomez Giménez, Marta