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Ines Cherif  - - - 
Top co-authors See all
Antonio Araujo

182 shared publications

Department of Medical Oncology, Hospital de Santo António/Centro Hospitalar do Porto, Porto, Portugal

George Zalidis

20 shared publications

Laboratory of Remote Sensing, Spectroscopy, and GIS, Department of Agriculture, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece

Schalk Jan Van Andel

15 shared publications

UNESCO-IHE Institute for Water Education; Delft; The Netherlands

Yann Chemin

6 shared publications

Department of Earth and Planetary Sciences, Birkbeck College, University of London, London, United Kingdom

George Bilas

1 shared publications

Publication Record
Distribution of Articles published per year 
(2009 - 2016)
Total number of journals
published in
Article 0 Reads 5 Citations Spatial and Temporal Distribution of Soil Moisture at the Catchment Scale Using Remotely-Sensed Energy Fluxes Thomas K. Alexandridis, Ines Cherif, George Bilas, Waldenio ... Published: 21 January 2016
Water, doi: 10.3390/w8010032
DOI See at publisher website ABS Show/hide abstract
Despite playing a critical role in the division of precipitation between runoff and infiltration, soil moisture (SM) is difficult to estimate at the catchment scale and at frequent time steps, as is required by many hydrological, erosion and flood simulation models. In this work, an integrated methodology is described to estimate SM at the root zone, based on the remotely-sensed evaporative fraction (Λ) and ancillary information on soil and meteorology. A time series of Terra MODIS satellite images was used to estimate SM maps with an eight-day time step at a 250-m spatial resolution for three diverse catchments in Europe. The study of the resulting SM maps shows that their spatial variability follows the pattern of land cover types and the main geomorphological features of the catchment, and their temporal pattern follows the distribution of rain events, with the exception of irrigated land. Field surveys provided in situ measurements to validate the SM maps’ accuracy, which proved to be variable according to site and season. In addition, several factors were analyzed in order to explain the variation in the accuracy, and it was shown that the land cover type, the soil texture class, the temporal difference between the datasets’ acquisition and the presence of rain events during the measurements played a significant role, rather than the often referred to scale difference between in situ and satellite observations. Therefore, the proposed methodology can be used operationally to estimate SM maps at the catchment scale, with a 250-m spatial resolution and an eight-day time step.
Article 0 Reads 7 Citations Rapid error assessment for quantitative estimations from Landsat 7 gap-filled images Thomas K. Alexandridis, Ines Cherif, Christos Kalogeropoulos... Published: 01 September 2013
Remote Sensing Letters, doi: 10.1080/2150704x.2013.815380
DOI See at publisher website
Article 0 Reads 14 Citations Integrated Methodology for Estimating Water Use in Mediterranean Agricultural Areas Thomas Alexandridis, Ines Cherif, Yann Chemin, George N. Sil... Published: 20 August 2009
Remote Sensing, doi: 10.3390/rs1030445
DOI See at publisher website ABS Show/hide abstract
Agricultural use is by far the largest consumer of fresh water worldwide, especially in the Mediterranean, where it has reached unsustainable levels, thus posing a serious threat to water resources. Having a good estimate of the water used in an agricultural area would help water managers create incentives for water savings at the farmer and basin level, and meet the demands of the European Water Framework Directive. This work presents an integrated methodology for estimating water use in Mediterranean agricultural areas. It is based on well established methods of estimating the actual evapotranspiration through surface energy fluxes, customized for better performance under the Mediterranean conditions: small parcel sizes, detailed crop pattern, and lack of necessary data. The methodology has been tested and validated on the agricultural plain of the river Strimonas (Greece) using a time series of Terra MODIS and Landsat 5 TM satellite images, and used to produce a seasonal water use map at a high spatial resolution. Finally, a tool has been designed to implement the methodology with a user-friendly interface, in order to facilitate its operational use.