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1. Estimating Spatial Variation In Annual Pasture YieldYield mapping is an essential tool for precision management of arable crops. Crop yields can be measured once, at harvest, automatically by the harvesting machinery, and be used to inform a wide range of activities. However yield mapping has had minimal adoption by pastoral farmers. Yield mapping is also a potentially valuable tool for precision management of pastures. However it is difficult to practically map yields on pastures, as they... S.J. Dennis, W. Clarke-hill, A. Taylor, R. Dynes, K. O'neill, T. Jowett |
2. NOAA's National Geodetic Survey?s National Spatial Reference System And The National Height ModernizatioThe National Geodetic Survey (NGS) is responsible for the establishment and maintenance of the National Spatial Reference System (NSRS). NGS manages a network of Continuously Operating Reference Stations (CORS) that provides Global Navigation Satellite System (GNSS) data and serves as the backbone of the NSRS. Our goal is to maintain a network of stations to serve as control for any project undertaken by local surveyors. In addition, numerous other applications benefit from an... J.D. Rigney |
3. An Inexpensive Aerial Platform For Precise Remote Sensing Of Almond And Walnut Canopy TemperatureCurrent irrigation practices depend largely on imprecise applications of water over fields with varying degrees of heterogeneity. In most cases, the amount of water applied over a given field is determined by the amount the most water-stressed part of the field needs. This equates to over-watering most of the field in order to satisfy the needs of one part of the field. This approach not only wastes resources, but can have a detrimental effect on the value of that crop. A system to... K. Crawford, S. Upadhyaya, R. Dhillon, F. Rojo, J. Roach |
4. Multi-Temporal Yield Pattern Analysis - Adaption of Pattern Recognition to Agronomic DataIn precision agriculture, the understanding of yield variability, both spatial and temporal, can deliver essential information for the decision making of site-specific crop management. Since commercial yield mapping started in the early 1990s, most research studies have focused on spatial variance or short-term temporal variance analyzed statistically in order to produce trend maps. Nowadays, longer records of high-quality yield data are available offering a new potential to evaluate yield variability... G. Blasch, J.A. Taylor |
5. Real-Time Fruit Detection Using Deep Neural NetworksProximal imaging using tractor-mounted cameras is a simple and cost-effective method to acquire large quantities of data in orchards and vineyards. It can be used for the monitoring of vegetation and for the management of field operations such as the guidance of smart spraying systems for instance. One of the most prolific research subjects in arboriculture is fruit detection during the growing season. Estimations of fruit-load can be used for early yield assessments and for the monitoring of... B. Keresztes, J. Da costa, D. Randriamanga, C. Germain, F. Abdelghafour |
6. Through the Grass Ceiling: Using Multiple Data Sources on Intra-Field Variability to Reset Expectations of Pasture Production and Farm ProfitabilityIntra-field variability has received much attention in arable and horticultural contexts. It has resulted in increased profitability as well as reduced environmental footprint. However, in a pastoral context, the value of understanding intra-field variability has not been widely appreciated. In this programme, we used available technologies to develop multiple data layers on multiple fields within a dairy farm. This farm was selected as it was already performing at a high level, with well-developed... W. King, R. Dynes, S. Laurenson, S. Zydenbos, R. Macauliffe, A. Taylor, M. Manning, A. Roberts, M. White |
7. Knowledge-based Approach for Weed Detection Using RGB ImageryA workflow was developed to explore the potential use of Phase One RGB for weed mapping in a herbicide efficacy trial in wheat. Images with spatial resolution of 0.8 mm were collected in July 2020 over an area of nearly 2000 square meters (66 plots). The study site was on a research farm at the University of Saskatchewan, Canada. Wheat was seeded on June 29, 2020, at a rate of 75 seeds per square meter with a row spacing of 30.5 cm. The weed species seeded in the trial were kochia, wild oat, wild... T. Ha, K. Aldridge, E. Johnson, S.J. Shirtliffe, S. Ryu |