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Trotter, T
Trotter, M.G
Ting, K.C
Trevisan, R.G
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Authors
Stanley, J.S
Lamb, D.W
Trotter, M.G
Rahman, M.M
Zhao, Y
Li, L
Ting, K.C
Tian, L.F
Ahamed, T
Eitelwein, M.T
Molin, J.P
Spekken, M
Trevisan, R.G
Trotter, M
Gregory, S
Trotter, T
Acuna, T
Swain, D
Fasso, W
Roberts, J
Zikan, A
Cosby, A.M
Topics
Remote Sensing Applications in Precision Agriculture
Spatial Variability in Crop, Soil and Natural Resources
Agricultural Education
Type
Oral
Year
2014
2016
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1. NDVI 'Depression' In Pastures Following Grazing

Pasture biomass estimation from normalized difference vegetation index (NDVI) using ground, air or space borne sensors is becoming more widely used in precision agriculture. Proximal active optical sensors (AOS) have the potential to eliminate the confounding effects of path radiance and target illumination conditions typically encountered using passive sensors. Any algorithm that infers the green fraction of pasture from NDVI must factor in plant morphology and live/dead plant ratio, irrespective... J.S. Stanley, D.W. Lamb, M.G. Trotter, M.M. Rahman

2. Near-Real-Time Remote Sensing And Yield Monitoring Of Biomass Crops

The demand for bioenergy crops production has increased tremendously by the biofuel industry for substitution of traditional fuels due to the economic availability and environmental benefits. Pre-Harvest monitoring of biomass production is necessary to develop optimized instrumentation and data processing systems for crop growth, health and stress monitoring; and to develop algorithms for field operation scheduling. To cope with the problems of missing critical... Y. Zhao, L. Li, K.C. Ting, L.F. Tian, T. Ahamed

3. Assessing Definition Of Management Zones Trough Yield Maps

Yield mapping is one of the core tools of precision agriculture, showing the result of combined growing factors. In a series of yield maps collected along seasons it is possible to observe not only the spatial distribution of the productivity but also its spatial consistency among different seasons. This work proposes the study of distinct methods to analyze yield stability in grain crops regarding its potential for defining management zones from a historical sequence of yield maps. Two methods... M.T. Eitelwein, J.P. Molin, M. Spekken, R.G. Trevisan

4. SMARTfarm Learning Hub: Next Generation Precision Agriculture Technologies for Agricultural Education

The industry demands on higher education agricultural students are rapidly changing. New precision agriculture technologies are revolutionizing the farming industry but the education sector is failing to keep pace. This paper reports on the development of a key resource, the SMARTfarm Learning Hub (www.smartfarmhub.com) that will increase the skill base of higher education students using a range of new agricultural technologies and innovations. The Hub is a world first; it links real industry... M. Trotter, S. Gregory, T. Trotter, T. Acuna, D. Swain, W. Fasso, J. Roberts, A. Zikan, A. Cosby