A remote sensing-assisted risk rating study to monitor pinewood forest decline: The study case of the castelporziano state nature reserve (Rome)

Abstract

The Multi-Spectral Instrument (MSI) aboard the ESA Sentinel-2 (S-2) allows satellite the Normalized Different Vegetation Index (NDVI) to be measured at much higher spatial resolution (10 m) than has been previously possible with space-borne sensors such as Medium Resolution Imaging Spectrometer aboard ENVISAT or Enhanced Thematic Mapper Plus aboard Landsat. Therefore, multi-spectral analysis of remote sensing data today represents an efficient tool for monitoring vegetation in a Mediterranean environment, where spatial resolution often represents a limiting factor due to high fragmentation and spatial distribution of forest stand. The aim of this study has been to map the health conditions of the Castelporziano coastal pinewood forest (Roma). To this aim, we used a diachronic NDVI index, provided by ESA Sentinel-2 images and field observations, to monitor the health status in a historic pinewood forest that has recently been affected by a rapid diffusion of pests (Tomicus destruens Woll.). The monitoring performed allowed us to map the pinewood forest in risk classes and at the same time to provide data concerning the localization of areas showing a strong decline. Thus, we provide information useful for the correct management and planning of forestry thinning to preserve those areas of the pinewood forest not involved in the decline process.