<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors></contributors><titles><title><style face="normal" font="default" size="100%">Monitoring water stress in Mediterranean semi-natural vegetation with satellite and meteorological data</style></title><secondary-title><style face="normal" font="default" size="100%">International Journal of Applied Earth Observation and Geoinformation</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2014</style></year></dates><publisher><style face="normal" font="default" size="100%">Elsevier B.V.</style></publisher><volume><style face="normal" font="default" size="100%">26</style></volume><pages><style face="normal" font="default" size="100%">246-255</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">In arid and semi-arid environments, the characterization of the inter-annual variations of the light use efficiency ε due to water stress still relies mostly on meteorological data. Thus the GPP estimation based on procedures exclusively driven by remote sensing data has not found yet a widespread use. In this work, the potential to characterize the water stress in semi-natural vegetation of three spectral indices (NDWI, SIWSI and NDI7) – from MODIS broad spectral bands – has been analyzed in comparison to a meteorological factor (Cws). The study comprises 70 sites (belonging to 7 different ecosystems) uniformly distributed over Tuscany, and three eddy covariance tower sites. An operational methodology, which combines meteorological and MODIS data, to characterize the inter-annual variations of ε due to summer water stress is proposed. Its main advantage is that it relies on existing series of meteorological data characterizing each site and allows calculating a typical Cws profile that can be “updated” (C∗ ws) for the actual conditions using MODIS spectral indices. The results confirm that the modified C∗ ws can be used as a proxy of water stress that does not require concurrent information on meteorological data</style></abstract></record></records></xml>