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Accueil du site → Projets de développement → Projets de recherche pour le Développement → 2008 → IMPROVED PREDICTION OF IRRIGATION WATER USE FOR CALIFORNIA CROPS FROM REMOTE SENSING

United States Department of Agriculture (USDA) 2008

IMPROVED PREDICTION OF IRRIGATION WATER USE FOR CALIFORNIA CROPS FROM REMOTE SENSING

Irrigation Water Remote Sensing

United States Department of Agriculture (USDA) Research, Education & Economics Information System (REEIS)

Titre : IMPROVED PREDICTION OF IRRIGATION WATER USE FOR CALIFORNIA CROPS FROM REMOTE SENSING

Identification : 5302-13000-011-02

Pays : Etats Unis

Durée : Mar 24, 2008 à Mar 23, 2013

Objectif  : The objectives are to develop technology to estimate real-time crop coefficients for fields/crops in the San Joaquin Valley from remotely-sensed data and to develop and demonstrate a prototype decision support system that can efficiently deliver crop coefficient and estimated crop water use information to agricultural producers and water supplie

Descriptif
Refine and validate the relationship between crop canopy cover (fc) and remotely sensed NDVI. Use ground based multispectral camera to measure fc for a wide range of crops grown in the San Joaquin Valley and compare the fc values with NDVI values derived from both aerial and satellite (Landsat and Modis) multispectral images for the fields. * Conversion of fc to basal crop coefficient, Kcb. Collect a library of relationships between fc and basal crop coefficient generated from the UC Kearney/ARS peach and grape lysimeters, the ongoing ARS lysimeter studies of vegetable water use at the UC WSREC, and any relationships published in the literature. * Compare crop water use estimates with this methodology with that predicted by standard (FAO 56) and thermal surface energy balance approaches. Compare predicted ETc based on the proposed methodology (NDVI and localized CIMIS ETo, and estimates of soil evaporation) with estimates of crop water use based on remotely sensed thermal imagery and the Surface Energy Balance approach. * Develop software and packaging for retrieval and conversion of RS images to geo-rectified Kcb maps. Develop methodology to automatically retrieve appropriate imagery, efficiently calculate NDVI values from the remotely sensed (RS) images, convert the NDVI values to Kcb values, and present the data in a geometrically rectified GIS format that can be efficiently combined with the localized ETo data from CIMIS and other map layers. * Develop a prototype user interface. Develop a prototype user interface for spatially explicit query (eg, based on geo-coordinates, parcel number, etc) that allows users to efficiently download Kcb and ETo information and efficiently calculate ETc for their fields or districts. * Feasibility, Costs and Benefits. Estimate the benefits and costs of employing remote sensing technology to improve water use efficiency. Estimate the costs of delivering RS based crop coefficients for the San Joaquin Valley. Estimate the improved irrigation efficiency and water savings that can be expected with this scheduling technology compared to the use of CIMIS ETo data and a traditional crop coefficient approach

Présentation : USDA

Page publiée le 10 septembre 2015, mise à jour le 6 novembre 2017