Predicting habitat quality of protected dry grasslands using Landsat NDVI phenology

Accuracies for the habitat quality prediction models ranged between 34% and 57% and significant correlations with multiple NDVI metrics were found. Including NDVI phenology improved all models by 7-12%. Single contributions of NDVI phenology were highest for management tolerance and nutrient content. However, we found high variation of contributions between management types. NDVI metrics were highly informative for the habitat qualities of abandoned sites, but grazing and mowing reduced or even cancelled their predictive power. Moreover, our results demonstrate the limitation of single-date NDVI values in predicting habitat quality of dry grasslands, in particular pastures and meadows. For monitoring applications of dry grasslands, we propose using a combination of NDVI metrics, as our results showed that they greatly improve prediction results of essential habitat qualities. The Landsat legacy dataset facilitates the assessment of habitat changes during past decades and can be complemented in the future with higher resolution data, such as Sentinel-2, to increase the temporal and spatial resolution so analyses are more appropriate for the typically limited size of dry grassland habitat sites in Switzerland.