Towards Detection of Cutting in Hay Meadows by Using of NDVI and EVI Time Series

摘要: The main requirement for preserving European hay meadows in good condition is through prerequisite cut management. However, monitoring these practices on a larger scale very difficult. Our study analyses the use of MODIS vegetation indices products, namely EVI and NDVI, to discriminate uncut Slovakia. We tested added value simple transformations raw data series (seasonal statistics, first difference series), compared analyzed optimal periods, number scenes effect smoothing classification performance. transformation saw substantial improvement results. best case NDVI yielded overall accuracy 85% with balanced rates producer’s user’s accuracies both classes. slightly lower values, though not significantly different, although user achieved only 67%. Optimal periods discriminating lay between 16 May 4 August, meaning seven consecutive images are enough accurately detect cutting meadows. More importantly, 16-day compositing period seemed be detection cutting, which would time span that might hopefully by upcoming on-board HR sensors (e.g., Sentinel-2).