The draught phenomena affecting the traditional agricultural areas in south of Romania has been increasing in intensity over the time, leading to the desertification of several thousands of hectares in the south part of the country. In this study we have computed the vegetation fraction cover for the South-West and South - East regions of Romania, based on the minimum and maximum NDVI extracted from MODIS satellite images. The time frame to refer to is 2000 - 2017, perennially, with special significance given the numerous and prolonged draught intervals these areas have been facing and the social economic evolution, from small farms to large agricultural holdings. The resulted vegetation fraction cover (fc) is correlated to the SPI values in order to determine a pattern to be used in anticipating deviations from the seasonal vegetation productivity. As a conclusion, the study presents a fair balance, indicating the most sensitive areas in soil vegetation cover, due to the SPI change.
If the inline PDF is not rendering correctly, you can download the PDF file here.
(2018). Retrieved from www.m3aerial.com/agriculture/
ADR-SE A. p.-E. (2017). Strategia de specializare inteligenta a regiunii de dezvoltare Sud - Est.
Bordun C. C. (2017). Remote sensing for desertification monitoring in Braila County. Scientific Papers. Series E. Land Reclamation Earth Observation & Surveying Environmental Engineering. Vol. VI.
Brown M. E. (2008). Famine Early Warning Ststems and Remote Sensing Data. Berlin Hidelberg:Springer-Verlag.
Burghila C. B.-M. (2016). Why mapping ecosystems services is a must in EU Biodiversity Strategy for 2020? AgroLife Scientific Journal - Volume 5 Number 2.
EDP E. U. (2018). European Data Portal. Retrieved from https://www.europeandataportal.eu/data/ro/dataset/50e4fae3-1f36-4ad6-935a-ca071a954313
EEA E. E. (2009). Water resources across Europe - confronting water scarcity and drought. https://www.eea.europa.eu/publications/waterresources-across-europe.
Jeeva K. M. (2016). Agriculture and crop assessment studies using remote sensing technology. IJARMATE India 316-322.
Jia K. S. (2015). Global land surface fractional vegetation cover estimation using general regression neural networks from MODIS surface reflectance. IEEE Transactions on Geoscience and Remote Sensing Volume: 53.
Jiapaer G. C. (2011). A comparison of methods for estimating fractional vegetation cover in arid regions. Agricultural and Forest Meteorology vol 151 1698-1710.
Kun J. L. (2017). Combining Estimation of Green Vegetation Fraction in an Arid Region from Landsat 7 ETM+ Data. Remote Sensing 1121.
MADR M. M. (2008). Strategia Nationala privind Reducerea Efectelor Secetei Prevenirea si Combaterea Degradarii Terenurilor si Desertificarii pe termen scurt mediu si lung .
McKee T. B. (1993). The relationship of drought frequency and duration to time scale. Proceedings of the Eighth Conference on Applied Climatology American Meteorological Society 179-184.
USGS. (2018). LP DAAC. Retrieved from https://lpdaac.usgs.gov/dataset_discovery/modis/modis_products_table/mod13a3
Vancutsem C. M. (2013). Harmonizing and combining existing land cover/land use datasets for cropland area monitoring at the African continental scale. Remote Sensing 5.
WMO. (2012). Standardized Precipitation Index User Guide. Geneva: World Meteorological Organisation.
WMO W. M. (2012). Standardized Precipitation Index User Guide. Geneva.