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Cranfield, G
Garcia-Torres, L
Clay, S.A
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Authors
Gómez-Candón, D
Caballero-Novella, J.J
Peña-Barragán, J.M
Jurado-Expósito, M
López-Granados, F
Garcia-Torres, L
deCastro, A.I
Gómez-Candón, D
Caballero-Novella, J.J
Peña-Barragán, J.M
Jurado-Expósito, M
Garcia-Torres, L
López-Granados, F
deCastro, A.I
Garcia-Torres, L
Gomez-Candon, D
Caballero-Novella, J.J
Gomez-Casero, M
Pe, J.M
Jurado-Exp, M
Lopez-Granados, F
Castillejo-Gonz, I
Garc, A
Garcia-Torres, L
Gomez-Candon, D
Caballero-Novella, J.J
Pe, J.M
Jurado-Exp, M
Castillejo-Gonz, I
Garc, A
Lopez-Granados, F
Prassack, L
Reese, C.L
Clay, D.E
Beck, D.L
Clay, S.A
Long, D.S
Shahinian, M
Morris, E
Clarke, A
Sunley, S
Hill, C
Cranfield, G
Erickson, B
Clay, D.E
Clay, S.A
Fausti, S
Garcia-Torres, L
Peña-Barragán, J.M
Gómez-Candón, D
López-Granados, F
Jurado-Expósito, M
Topics
Remote Sensing Applications in Precision Agriculture
Remote Sensing Applications in Precision Agriculture
Engineering Technologies and Advances
Agricultural Education
Precision Horticulture
Type
Poster
Oral
Year
2012
2010
2016
2008
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Authors

Filter results8 paper(s) found.

1. Sectioning And Assessment Remote Images For Precision Agriculture: The Case Of Orobanche Crenate In Pea Crop

  The software SARI® has been developed to implement precision agriculture strategies through remote sensing imagery. It is written in IDL® and works as an add-on of ENVI®. It has been designed to divide remotely sensed imagery into “micro-images”, each corresponding to a small area (“micro-plot”), and to determine the quantitative agronomic and/or environmental biotic (i.e. weeds, pathogens) and/or non-biotic (i.e. nutrient levels) indicator/s... L. Garcia-torres, D. Gomez-candon, J.J. Caballero-novella, M. Gomez-casero, J.M. Pe, M. Jurado-exp, F. Lopez-granados, I. Castillejo-gonz, A. Garc

2. Management Of Remote Imagery For Precision Agriculture

Satellite and airborne remotely sensed images cover large areas, which normally include dozens of agricultural plots. Agricultural operations such as sowing, fertilization, and pesticide applications are designed for the whole plot area, i.e. 5 to 20 ha, or through precision agriculture. This takes into account the spatial variability of biotic and of abiotic factors and uses diverse technologies to apply inputs at variable rates, fitted to the needs of each small defined area, i.e. 25 to 200... L. Garcia-torres, D. Gomez-candon, J.J. Caballero-novella, J.M. Pe, M. Jurado-exp, I. Castillejo-gonz, A. Garc, F. Lopez-granados, L. Prassack

3. Nitrogen And Water Stress Impacts Hard Red Spring Wheat (Triticum Aestivum) Canopy Reflectance

  Remote sensing-based in-season N recommendations have been proposed as a technique to improve N fertilizer use efficiency. Remote sensing estimation of South Dakota hard red spring wheat N requirements needs assessment. Research objectives were: (1) determine the effect of an in-season N application on grain yield, yield loss to nitrogen stress (YLNS), and grain protein; and (2) assess if remote sensing collected at different growth stages may be used to predict yield... C.L. Reese, D.E. Clay, D.L. Beck, S.A. Clay, D.S. Long, M. Shahinian

4. Attaching Multiple Conductivity Meters To An Atv To Speed Up Precision Agriculture Soil Surveys

Ground conductivity meters are used in a number of precision agriculture applications, including the estimation of water content, nutrient levels, salinity and depth of topsoil. Typically the Geonics EM38 conductivity meter, and to a lesser extent the EM31, are used for soil surveys. Most conductivity surveys involve towing a ground conductivity meter behind an all-terrain vehicle (ATV). In some situations, such as rutted or sloping fields, it is preferable to mount the conductivity meter directly... E. Morris, A. Clarke, S. Sunley, C. Hill, G. Cranfield

5. Automatic Remote Image Processing For Agriculture Uses Through Specific Software

Abstract ... D. Gómez-candón, J.J. Caballero-novella, J.M. Peña-barragán, M. Jurado-expósito, F. López-granados, L. Garcia-torres, A.I. Decastro

6. Position Error of Input Prescription Map Delineated From Remote Images

     The spatial variability of biotic factors... D. Gómez-candón, J.J. Caballero-novella, J.M. Peña-barragán, M. Jurado-expósito, L. Garcia-torres, F. López-granados, A.I. Decastro

7. Knowledge, Skills and Abilities Needed in the Precision Ag Workforce: an Industry Survey

Precision agriculture encompasses a set of related technologies aimed at better utilization of crop inputs, increasing yield and quality, reducing risks, and enabling information flow throughout the crop supply and end-use chains.  The most widely adopted precision practices have been automated systems related to equipment steering and precise input application, such as autoguidance and section controllers.  Once installed, these systems are relatively easy for farmers and their supporting... B. Erickson, D.E. Clay, S.A. Clay, S. Fausti

8. A Software for Managing Remotely Sensed Imagery of Orchards Plantations for Precision Agriculture

Agronomic and environmental characteristics of fruit orchards/ forests can be automatically assessed from remote-sensing images by a computer programme named Clustering Assessment (CLUAS®). The aim of this paper is to describe the operational procedure of CLUAS and illustrate examples of the information provided for citrus orchards and Mediterranean forest. CLUAS® works as an additional menu (“add-on”) of ENVI®, a world-wide known image-processing programme, and operates... L. Garcia-torres, J.M. Peña-barragán, D. Gómez-candón, F. López-granados, M. Jurado-expósito