Proceedings
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| Filter results4 paper(s) found. |
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1. GNSS Positioning Techniques For AgricultureBroadacre, row crop and high value crops each have different positioning needs. Within these agricultural groups, individual practices such as mapping, guidance and machine control for tillage, application and harvest each have their own Global Navigation Satellite Systems (GNSS) needs for an optimal price/performance and value equation. New research and algorithm development by NovAtel has resulted in a significant simplification of positioning methodology with increased... P.M. Casiano, T.G. Morley, Z. Sadeque |
2. Planet Labs' Monitoring Solution in Support of Precision Agriculture PracticesSatellite imagery is particularly useful for efficiently monitoring very large areas and providing regular feedback on the status and productivity of agricultural fields. These data are now widely used in precision farming; however, many challenges to making optimal use of this technology remain, such as easy access to data, management and exploitation of large datasets with deep time series, and sharing of the data and derived analytics with users. Providing satellite imagery through a cloud... K.J. Frotscher, R. Schacht, L. Smith, E. Zillmann |
3. Prediction of Nitrogen Needs with Nitrogen-rich Strips and Ramped Nitrogen StripsBoth nitrogen rich strips and ramped nitrogen strips have been used to estimate topdress nitrogen needs for winter wheat based on in-season optical reflectance data. The ramped strip system places a series of small plots in each field with increasing levels of nitrogen to determine the application rate at which predicted yield response to nitrogen reaches a plateau. The nitrogen-rich strip system uses a nitrogen fertilizer optimization algorithm based on optical reflectance measures from the nitrogen-rich... D.C. Roberts, B.W. Brorsen, W.R. Raun, J.B. Solie |
4. RMAPs: an Integrated Tool to Delimitate Homogeneous Management ZonesManagement zones are one of the most studied methods in precision agriculture to optimize crop yield from the soil, plant, management, and climate input parameters. We present Rmaps, an R package that integrates soil and crop yield spatial variability using geostatistical methods and one-hidden-layer perceptron (OHLP) to identify how input parameters influence crop yield and delimitate homogenous zones. From georeferenced data of soil, plant, management, climate, and crop yield parameters, Rmaps... E. Erazo, C. Mosquera, O. Ochoa |