1 October 2012. An international group, composed of the Universidad Politécnica de Madrid (Spain), Universidad de Córdoba (Spain), Leibniz Universität Hannover (Germany), University of California Davis (USA) and coordinated by the Universidad de Concepción (Chile) with members from the Universidad Politécnica de Madrid's Facultad de Informática, is developing a project to use information technologies to raise farm profitability. Major Chilean agribusinesses are also participating in its development.
Its goal is to develop and evaluate a methodology using remotely detected data to enable water resource management in agriculture.
The central hypothesis is that the use of spatially distributed information gathered from remote sensors and improved using image fusion methodologies combined with algorithms that define the surface energy balance can determine and consequently optimize farm water resource demand.
Preliminary results
The project has already developed a methodology for estimating spatially distributed water demand (real evapotranspiration or ET) with full plant cover and is now developing the methodology for partial plant cover. Additionally, image processing methods have been developed to improve the spatial resolution of the ET maps and methodologies for processing these images using an object-oriented paradigm in the field of digital image processing.
Also, the beta version of a platform has been built that will serve as the irrigation decision support system. It has been implemented using a scalable vector graphics (SVG) strategy that uses the Mappetizer tool as a solution for deploying the necessary cartography (web mapping).
The use of high resolution images to determine evapotranspiration is an innovative project factor. Precise measurements in situ (e.g. humidity control, weather stations, evaporation trays) or models are usually used to estimate water resources and programme irrigation, irrespective of spatial variability at farm level.
Image fusion
The use of images captured from aeroplanes or satellites is now a popular practice for gauging plant cover indices and production estimates. Lately, however, the estimation of evapotranspiration using satellite images has become a feasible solution for estimating spatially distributed ET.
One of the innovations of this project is the use of methodologies to fuse images from different sensors, which is the major contribution of Facultad de Informática researchers.
Image fusion is a technique whose goal is to integrate information from different sensors, exploiting the synergy of the captured data. In this project particularly, these methods offer a real alternative for improving the spatial resolution of ET estimation maps obtained from satellite images, enabling their application locally (at farm level).
Resource optimization
This project develops innovative new technologies for improving the use of water resources and also applies information gathered from the Chilean Air Force-operated FASAT-CHARLIE satellite directly to agriculture.
The project is expected to output a methodology validated with ground measurements for estimating water resources in intensive agricultural production systems from remote sensors.
This information will improve the use of water resources and energy and consequently improve farm profitability.
The generated information will be accessible from an on-line platform that will improve the management of water resources both at farm level and regionally.
2014 time horizon
The “Estimation of Agricultural Water Demand using Remote Sensing. A Tool for Agricultural Management” project kicked off in December 2010 and is due to finish in March 2014. It is funded by the Chilean Fondo de Fomento al Desarrollo Científico (FONDEF-Chile) and partnered by the Facultad de Informática Department of Computer Architecture and Systems, represented by Consuelo Gonzalo.
The other project partners are the Universidad de Concepción's Facultad de Ingeniería Agrícola (Chile), Leibniz Universität Hannover's Institute of Water Resources Management, Hydrology and Agricultural Hydraulic Engineering (Germany), University of California Davis's Department of Land, Air and Water Resources and the Universidad de Córdoba's Escuela de Ingenieros Agrónomos y Montes and the Instituto de Agricultura Sostenible (Spain). Major Chilean agribusinesses are also participating in its development.
References
Mario Lillo-Saavedra, Consuelo Gonzalo Martín, Octavio Lagos, 2011, Toward Reduction of Artifacts in Fused Images, International Journal of Applied Earth Observation & Geoinformation, 13, 368- 375 (IF: 1.557).
Mario Lillo Saavedra and Consuelo Gonzalo Martín, 2012, Toward multi-scale object-based images fusion. Remote Sensing and Geoinformation not only for Scientific Cooperation, 401- 406, European Association of Remote Sensing Laboratories (Prague).
Consuelo Gonzalo Martín and Mario Lillo Saavedra, 2012, Multiscale object-based classification of satellite images merging multispectral information with panchromatic textural features. Remote Sensing and Geoinformation not only for Scientific Cooperation, 394- 400, European Association of Remote Sensing Laboratories (Prague).
Consuelo Gonzalo Martín, Mario Lillo Saavedra, Ángel Mario García Pedrero and David, Fonseca Luengo. Una metodología multiescala basada en objetos para la determinación automática de áreas de interés. Congreso Nacional de Tecnologías de la Información Geográfica (accepted).
M. Carrasco-Benavides, S. Ortega-Frías, L. Lagos, J. Kleissl, L. Morales, C. Poblete-Echeverría and R. Allen. Crop coefficients and actual evapotranspiration for drip-irrigated Merlot vineyard using multiespectral satellite images. Irrigation Science (In press)
Study regions for different crops.
This item on other websites
Scoop.it 06.10.2012
AlphaGalileo 04.10.2012
MundoInsólito 03.10.2012
EcoTicias 03.10.2012
Bitácoras 02.10.2012
CienciayTecnología 02.10.2012
UPM Montegancedo 02.10.2012
SINC 02.10.2012
Tendencias Informáticas 02.10.2012
EuroCampus 01.10.2012
