<?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 Leaf Area Index of Mediterranean oak woodlands: Comparison of remotely-sensed estimates with simulations from an ecological process-based model</style></title><secondary-title><style face="normal" font="default" size="100%">International Journal of Remote Sensing</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2003</style></year></dates><publisher><style face="normal" font="default" size="100%">Taylor &amp; Francis</style></publisher><volume><style face="normal" font="default" size="100%">24</style></volume><pages><style face="normal" font="default" size="100%">3441-3456</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Annual vegetation abundance mapping was carried out within the DeMon II European project over a period of 12 years (1984-1996). The project relied on advanced satellite-based methods for spatial and temporal monitoring of Mediterranean oak woodlands by means of a series of Landsat Thematic Mapper (TM) satellite data. A standardized approach developed previously focuses on the Languedoc site, Hautes Garrigues, a typical sensitive Mediterranean region, but now recovering after centuries of grazing and agricultural activities. After geometric and radiometric rectification of nine full Landsat TM scenes with a refined correction in a smaller area of 75 km 2 75 km, a GIS database was created containing satellite data, thematic maps of vegetation, geological maps, climatic data and field measurements. An empirical relation between radiometric ground truth measurements and satellite derived Normalized Difference Vegetation Index (NDVI) allows us to derive Leaf Area Index (LAI). An ecological process-based model (Forest BGC) has been adapted to simulate ecosystem processes in a satisfying way at a local scale. Consistent results were obtained from remote sensing data and from simulations at a local scale, suggesting the possible use of remote-sensing data to monitor vegetation abundance changes at a regional scale. Without considering human disturbances, it can be noted that not much variation of LAI induced by natural factors can be detected over the considered 12-year period.</style></abstract><notes><style face="normal" font="default" size="100%">doi: 10.1080/0143116021000024267</style></notes><research-notes><style face="normal" font="default" size="100%">doi: 10.1080/0143116021000024267</style></research-notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>3</ref-type><contributors></contributors><titles><title><style face="normal" font="default" size="100%">Adaptation and local validation in a Mediterranean environment of a process-level ecosystem model driven by remotely sensed inputs</style></title><secondary-title><style face="normal" font="default" size="100%">REMOTE SENSING `96: INTEGRATED APPLICATIONS FOR RISK ASSESSMENT AND DISASTER PREVENTION FOR THE MEDITERRANEAN</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">1997</style></year></dates><publisher><style face="normal" font="default" size="100%">A A BALKEMA</style></publisher><pub-location><style face="normal" font="default" size="100%">PO BOX 1675, 3000 BR ROTTERDAM, NETHERLANDS</style></pub-location><pages><style face="normal" font="default" size="100%">299-303</style></pages><isbn><style face="normal" font="default" size="100%">90-5410-855-X</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">A process-level ecosystem model (FOREST-BGC) has been used to simulate the short-term variability of functional processes and the slower responding allocation of photosynthesis products to plant components maintenance or growth, and to decomposition. The model emphasises Leaf Area Index (LAI) as a key structural attribute with substantial control over ecosystem process rates. Model simulations (soil water balance, photosynthesis, net primary production,...) have been obtained for a 10 years period (1984-1993) and partially validated with ground measurements from an experimental test site located in Southern France (dominant species: holm oak). Further work include scaling up from local to regional level, using remote sensing inputs and ancillary data.</style></abstract></record><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%">Estimating tree density in oak savanna-like lsquo;dehesa’ of southern Spain from SPOT data</style></title><secondary-title><style face="normal" font="default" size="100%">International Journal of Remote Sensing</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">1993</style></year></dates><publisher><style face="normal" font="default" size="100%">Taylor &amp; Francis</style></publisher><volume><style face="normal" font="default" size="100%">14</style></volume><pages><style face="normal" font="default" size="100%">685-697</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Abstract The main objective of this study was to establish a method of estimating tree density in savanna-like vegetation systems using the highest spatial resolution available from satellite data (SPOT-1 panchromatic = 10 m resolution) based on the assumption that for sparse trees on a contrasting herbaceous background, spatial filters may provide a direct mapping of tree cover. The study was performed in the ?dehesas? oak-woodland of southern Spain. This particular landscape is characterized by the presence of scattered evergreen oak trees (Quercus ilex and Q. suber) whose density ranges from 0 to 80 even-aged mature trees per hectare which gives the appearance of a savanna-like vegetation. Tree density can be accurately estimated by SPOT-1 panchromatic data after numerical filtering. This method allows the mapping of tree density of the dehesas, a key parameter reflecting the functional vegetation-soil-climate equilibrium which exists for both woody and herbaceous strata.</style></abstract><notes><style face="normal" font="default" size="100%">doi: 10.1080/01431169308904368</style></notes><research-notes><style face="normal" font="default" size="100%">doi: 10.1080/01431169308904368</style></research-notes></record></records></xml>