ASTER and Worldview-2 satellite data comparison for identification of groundwater salinization effects on the Classe pine forest vegetation (Ravenna, Italy)
- 1Civil, Chemical, Environmental and Materials Engineering Department (DICAM), University of Bologna, Bologna, Italy
- 2Interdepartmental Centre for Environmental Science Research (CIRSA), Lab. IGRG, University of Bologna, Ravenna, Italy
Keywords: Aster, WorldView – 2, NDVI, stressed vegetation, groundwater salinity
Abstract. The availability of a large number of data acquired by satellite sensors with different spatial and spectral resolutions has always required an evaluation of their synergistic use. The integration of dataset of images coming from different sources can be an optimal solution for the study of various environmental problems which need a continuous monitoring (coastal development, forest evolution, land use changes etc.). The Classe pinewood, an important safeguarded biodiversity hot spot near Ravenna city (Italy), is historically affected by the groundwater salinization. Since changes in the water concentration are able to induce variations of the leaf properties and vegetation cover, recognizable by surveys carried out with different spectral bands, the comparison between ASTER and Worldview-2 data was performed using the (Normalized Difference Vegetation Index) NDVI. For each satellite data, the same Areas of Interest (AOIs) were selected within the most widespread cover, Thermophilic Deciduous Forest (TDF). The NDVI was calculated, statistically evaluated and the AOI rankings were built. In order to evaluate the difference between the results provided by the two images, statistical tests were applied on the average NDVI values. Finally the calculated NDVI were compared with groundwater salinity data collected during a contemporary field monitoring campaign. Based on groundwater salinity the same AOIs ranking was reached for both satellite sensors. This study suggests the opportunity to employ the medium resolution Aster images in continuity with high resolution WarldView-2 dataset.