Saint-Pierre-du-Chemin, France
Saint-Pierre-du-Chemin, France

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Lucie X.,UMR TETIS | Durrieu S.,UMR TETIS | Jolly A.,ONF Departement RandD | Labbe S.,UMR TETIS | Renaud J.-P.,ONF Departement RandD
Revue Francaise de Photogrammetrie et de Teledetection | Year: 2017

Renewed interest in photogrammetry and recent developments of unmanned aerial vehicles (UAVs) open new possibilities in the field of forest planning and management. As the assessment of forest dendrometrie parameters is usually a costly task, involving intensive field measurements, we were interested to evaluate how the use of accurate photogrammetric digital surface models (DSMs) could facilitate these estimations. Based on DSMs, dendrometrie models were calibrated using circular plots (700 m2) measured in an area of interest (AOI). UAVs flight above these AOI were acquired at very high resolution (VHRI) giving images with a spatial resolution of 2.5 cm, as compared to 25,0 cm for the standard IGN aerial images. We were also interested in assessing the impact of DSMs resolution. For this purpose, DSMs were computed at the original resolution as well as degraded resolutions from 5.0 cm to 40.0 cm. Each DSM's elevation was then compared to manual stereoscopic measurements realized on the VHRI. By subtracting a digital terrain model (DTM) from each DSM, we derived canopy height models (CHMs). From these CHMs, we observed that plot height distributions were interesting indicators of forest structures and we were also able to established dominant height (Ho) models. These results underline the interest of new photogrammetric approaches, and the importance of spatial resolutions, to improve forest planning and management.


Morel J.,UR SCA | Lebourgeois V.,UMR TETIS | Martine J.-F.,UR SCA | Todoroff P.,UR SCA | And 2 more authors.
International Geoscience and Remote Sensing Symposium (IGARSS) | Year: 2013

Coupling remotely sensed data with crop model is known to improve the estimation of crop variables by the model. The recalibration coupling approach tends to reduce the differences between observation and simulation by optimizing the value of one of the model's parameter. In this study, we used this approach with a sugarcane model and Crop Water Stress Index calculated using remotely sensed thermal infrared data in order to optimize the value of the root depth parameter thanks to measured and simulated AET/MET ratio. The effect of the root depth recalibration has also been assessed on the yield estimation, which showed good trends with a significant enhancement of the estimated yield. © 2013 IEEE.


Morel J.,UPR SCA | Begue A.,CIRAD - Agricultural Research for Development | Todoroff P.,UPR SCA | Martine J.-F.,UPR SCA | And 2 more authors.
European Journal of Agronomy | Year: 2014

The objective of this study was to assess the efficiency of the assimilation of the fraction of intercepted photosynthetically active radiation (fIPAR) data derived from Satellite Pour l'Observation de la Terre SPOT images into the MOSICAS sugarcane crop growth model for estimating the yield at field scale on Reunion Island. Over 3 years, time series of SPOT satellite imagery were used to estimate the daily evolution of NDVI for 60 plots located on two climatically contrasted farms. Ground measurements of the fIPAR were performed on 5 reference fields and used to calibrate a relationship with the corresponding NDVI values. Forced and not forced simulations were run and compared with respect to their ability to predict the final observed yield. Forcing MOSICAS with fIPAR values derived from SPOT images improved the accuracy of the model for the yield estimation (RMSE=12.2 against 14.8tha-1) closer to the 1:1 line. However, underestimations of the yield by the forced model suggest that some of the model parameters were not optimal. The maximal radiation use efficiency parameter (RUEm) was optimised for each field, and an analysis of variance showed the significant effect of the ratoon number of the field, of its cultivar and of the farm where it is planted. Accordingly, the RUEm was recalibrated for each cultivar for the number of ratoons and farms. New RUEm values ranged from 3.09 to 3.77gMJ-1, and new computations were run using the optimised values of RUEm. The results indicate that recalibrating the maximal radiation use efficiency according to the number of ratoons improved the yield estimation accuracy by as much as 10.5tha-1 RMSE. This study highlights the potential of time series of satellite images to enhance the estimation of the yield by a forced ecophysiological model and to obtain better knowledge about the ecophysiological processes that are involved in crop dynamics with the recalibration method. © 2014 Elsevier B.V.


Dupaquier C.,UMR TETIS | Desbrosse A.,UMR TETIS | Maurel P.,UMR TETIS | Plant R.,IRSTEA | And 2 more authors.
Revue Francaise de Photogrammetrie et de Teledetection | Year: 2014

At present and within a context of integrated coastal management, the population growth and increasing land pressure with their subsequent land cover changes on the Thau basin make this territory an important policy issue. In order to cope with the issues at stake the Thau regional authorities have entrusted SMBT from 2006 onwards with the joint development of several planning tools (SCoT, SAGE and Natura 2000 Convention) to conduct an integrated approach to territorial development. The aim of the present paper is to present the methodology used for mapping the initial 2012/2013 land use cover of the Thau basin from Pleiades imagery. This map will be a basic input for the observatory of the Thau territory and support the implementation of planning tools. The methodology was divided into two parts: first, a photo-interpretation approach for artificialised area mapping and evolution monitoring over several years and second, a remote sensing detection approach with the achievement of an object-oriented classification of agricultural and natural environments. This methodology allowed to obtain an up-to-date land use cover according to a 4 level typology adapted from the CORINE land cover nomenclature. This land cover will be updated every second year to help produce assessment and monitoring indicators for the Thau territory.


Tahrat S.,CNRS Montpellier Laboratory of Informatics, Robotics and Microelectronics | Kergosien E.,CNRS Montpellier Laboratory of Informatics, Robotics and Microelectronics | Kergosien E.,Avenue Of Luniversite | Bringay S.,CNRS Montpellier Laboratory of Informatics, Robotics and Microelectronics | And 2 more authors.
Revue des Nouvelles Technologies de l'Information | Year: 2013

We focus on the evaluation of methods for extracting spatial information from texts. After describing the study and analyzing all possibles forms of textual description of space and all the conventions adopted for the manual annotation of named entities of Location and Organization types, we propose to develop a hybrid method. This method combines information extraction approach based on patterns, with a supervised classification approach, to explore the context. We then discuss the different results obtained on the dataset of the Thau lagoon.


Vernier F.,IRSTEA | Miralles A.,UMR TETIS | Pinet F.,IRSTEA | Carluer N.,IRSTEA | And 3 more authors.
Agricultural Systems | Year: 2013

The French "Ecophyto 2018" program calls for a 50% reduction in pesticide use. Local authorities are required to design cost-effective measures to minimize the impact of farmers' pesticides on water resources. A successful implementation of these new measures can only be achieved through a better understanding of the interactions between water, land use and the environment. One way of doing this is to calculate pesticide pressure and agro-environmental indicators (AEIs). However, this approach requires an effective information system that can process both the characteristics of the river basin and the agricultural activities using at least two embedded scales: the scale of the small agricultural catchment for action by farmers and the scale of a larger watershed for public decision making.To this end, an environmental information system (EIS Pesticide) for pesticide issues was created using spatial data warehouse technology. This system allowed qualifying agricultural activities along with river basin characteristics. Specific spatial objects were designed to characterize practices at the relevant scales. The axes of analysis allowed providing results at different levels of integration, for different dimensions e.g. time, sprayed surface area, or pesticide type. The system was tested using datasets collected in the Charente watershed and its sub-basins and calculated pesticide pressure indicators on demand for each aggregation level defined. © 2013 Elsevier Ltd.

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