Drought is one of the most significant extreme event facing the world, affecting the society and the environment. Located in SE Romania, Dobrogea Region is characterized by a temperate climate with strong continental influences, being affected by drought episodes which cause significant damages and economic costs over extensive agricultural areas. Risk reduction, continuous vegetation monitoring, and management implementation are facilitated by complementary use of vegetation indices and biophysical parameters derived from satellite products (gridded data) within-situ data (point data). The paper focuses on:i) evaluating the extent and intensity of drought in Dobrogea, Romania, based on Normalized Difference Drought Index (NDDI) and Fraction of Absorbed Photosynthetically Active Radiation (FAPAR); ii) fires analysis, based on the Thermal Anomalies/Fire locations product (MCD14DL); iii)the correlation between the fires with the NDDI; iv) and the correlation between fires with the Land Surface Temperature (LST) product. The vegetation indices, biophysical parameters and fires are computed from Moderate Resolution Imaging Spectroradiometer (MODIS) daily and eight days’ synthesis products, during 22th of March - 29th of August 2000-2015. The results highlight the areas most affected by drought (moderate, severe and extreme) and fires in the Dobrogea.
Flooding remains the most widely distributed natural hazard in Europe, leading to significant economic and social impact. Earth observation data is presently capable of making fundamental contributions towards reducing the detrimental effects of extreme floods. Technological advance makes development of online services able to process high volumes of satellite data without the need of dedicated desktop software licenses possible. The main objective of the case study is to present and evaluate a methodology for mapping of flooded areas based on MODIS satellite images derived indices and using state-of-the-art geospatial web services. The methodology and the developed platform were tested with data for the historical flood event that affected the Danube floodplain in 2006 in Romania. The results proved that, despite the relative coarse resolution, MODIS data is very useful for mapping the development flooded area in large plain floods. Moreover it was shown, that the possibility to adapt and combine the existing global algorithms for flood detection to fit the local conditions is extremely important to obtain accurate results.