Title of article :
Remote sensing applications for precision agriculture: A learning community approach
Author/Authors :
Seelan، نويسنده , , Santhosh K and Laguette، نويسنده , , Soizik and Casady، نويسنده , , Grant M and Seielstad، نويسنده , , George A، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2003
Pages :
13
From page :
157
To page :
169
Abstract :
Farmers throughout the world are constantly searching for ways to maximize their returns. Remote Sensing, Geographic Information Systems (GIS), and Global Positioning Systems (GPS) may provide technologies needed for farmers to maximize the economic and environmental benefits of precision farming. However, most farmers do not have the skills to utilize these technologies effectively. h a learning community approach led by the Upper Midwest Aerospace Consortium (UMAC), information was shared among scientists, agricultural producers, and data providers. Farmers and ranchers received value-added information derived from AVHRR, MODIS, ETM+, IKONOS, DigitIncʹs DALSA camera system and Positive Systemsʹ ADAR 5500 digital aerial camera, over four growing seasons. Emphasis has been placed on reducing the time between data acquisition and delivery of value-added products to farmers, developing practical uses for the data and providing basic training so that the end users could understand how to interpret the information. Farmers and ranchers in rural areas were connected via wide-bandwidth satellite link to a central distribution center at the University of North Dakota. The farmers participated actively in evaluating the usefulness of inputs derived from remotely sensed data, sometimes even by conducting experiments on fertilizer and fungicide applications and assessing the economic benefits. Resulting applications included management zone delineation, verifying the effectiveness of variable-rate fertilizer applications, verifying the effectiveness of fungicide applications, quantifying the loss due to accidental spray drift damage, selecting acres within sugar beet fields under the Payment in Kind program, and monitoring physical damage due to insect, inundation, wind and hail. Several other in-field, early season management practices were also reviewed using high-resolution images.
Keywords :
Precision agriculture , Remote sensing , Near real time data delivery , Training , Applications , learning community , Technology adoption
Journal title :
Remote Sensing of Environment
Serial Year :
2003
Journal title :
Remote Sensing of Environment
Record number :
1574305
Link To Document :
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