Proceedings
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| Filter results10 paper(s) found. |
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1. Ground-Based Spectral Reflectance Measurements for Evaluating the Efficacy of Aerially-Applied Glyphosate TreatmentsAerial application of herbicides is a common tool in agricultural field management. The objective of this study was to evaluate the efficacy of glyphosate herbicide applied aerially with both conventional and emerging aerial nozzle technologies. A Texas A&M University Plantation weed field was... Y. Lan, H. Zhang |
2. Differentiation of Cotton from Other Crops at Different Growth Stages Using Spectral Properties and Discriminant AnalysisTimely detection and remediation of volunteer cotton plants in both cultivated and non-cultivated habitats is critical for completing boll weevil eradication in Central and South Texas. However, timely detection of cotton plants... H. Zhang, Y. Lan |
3. Site-specific Management For Biomass Feedstock Production: Development Of Remote Sensing Data Acquisition SystemsEfficient biomass feedstock production supply chain spans from site-specific management of crops on field to the gate of biorefinery. Remote sensing data acquisition systems have been introduced for site-specific management, which is a part of the engineering solutions for biomass feedstock production. A stand alone tower remote sensing platform was developed to monitor energy crops using multispectral imagery. The sensing system was capable of collecting RGB and CIR images during the crop growing... T. Ahamed, L. Tian, Y. Zhang, Y. Xiong, B. Zhao, Y. Jiang, K. Ting |
4. Investigation Of Crop Varieties At Different Growth Stages Using Optical Sensor DataCotton, soybean and sorghum are economically important crops in Texas. Knowing the growing status of crops at different stages of growth is crucial to apply site-specific management and increase crop yield for farmers. Field experiments were initiated to measure cotton, soybean and sorghum plants growth status and spatial variability through the whole growing cycle. A ground-based active optical sensor, Greenseeker®, was used to collect the Normalized Difference Vegetation Index (NDVI) data... H. Zhang, Y. Lan, J. Westbrook, C. Suh, C. Hoffmann, R. Lacey |
5. Tools For Evaluating The Potential Of Automatic Section ControlOne of the newest technologies in precision agriculture is automatic section control on application equipment. This technology has tremendous potential to reduce wasted inputs, especially on irregularly shaped fields. Paybacks are not necessarily as great on rectangular fields. Producers considering adoption of the technology need to decide whether they will receive sufficient payback for their field shapes. They must also decide... T. Stombaugh, R.S. Zandonadi, J.D. Luck, T.P. Mcdonald, T. Mcgraw |
6. Multisensor Data Fusion Of Remotely Sensed Imagery For Crop Field MappingA wide variety of remote sensing data from airborne hyperspectral and multispectral images is available for site-specific management in agricultural application and production. Aerial imaging system may offer less expensive and high spatial resolution imagery with Near Infra-Red, Red, Green and Blue spectral wavebands. Hyperspectral sensor provides hundreds of spectral bands. Multisensor data fusion provides an effective paradigm for remote sensing applications by synthesizing... Y. Lan, H. Zhang, C. Yang, D. Martin, R. Lacey, Y. Huang, W.C. Hoffmann, P. Moulton |
7. Development of Micro-tractor-based Measurement Device of Soil Organic Matter Using On-the-go Visual-near Infrared Spectroscopy in Paddy Fields of South ChinaSoil organic matter (SOM) is an essential soil property for assessing the fertility of paddy soils in South China. In this study, a set of micro-tractor-based on-the-go device was developed and integrated to measure in-situ soil visible and near infrared (VIS–NIR) spectroscopy and estimate SOM content. This micro-tractor-based on-the-go device is composed of a micro-tractor with toothed-caterpillar band, a USB2000+ VIS–NIR spectroscopy detector, a self-customized steel plow and a self-customized... Z. Lianqing, S. Zhou, C. Songchao, Y. Yafei |
8. Retrieving Crops' Quantitative Biophysical Parameters Through a Newly Developed Multispectral Sensor for UAV PlatformsToday’s intensive agricultural production needs to increase its efficiency in order to keep its profitability in the current market of decreasing prices on one hand, and to reduce the environmental impact on the other. Crop growers are starting to adopt side dressing nitrogen fertilization as part of their fertilization programs, for which they need accurate information about biomass development and nitrogen condition in the crop. This information is usually acquired through ground sampling,... A. Pimstein, Y. Zur, M. Le roux |
9. Evaluation of Image Acquisition Parameters and Data Extraction Methods on Plant Height Estimation with UAS ImageryAerial imagery from unmanned aircraft systems (UASs) has been increasingly used for field phenotyping and precision agriculture. Plant height is one important crop growth parameter that has been estimated from 3D point clouds and digital surface models (DSMs) derived from UAS-based aerial imagery. However, many factors can affect the accuracy of aerial plant height estimation. This study examined the effects of image overlap, pixel resolution, and data extraction methods on estimation... C. Yang, C. Suh, W. Guo, H. Zhao, J. Zhang, R. Eyster |
10. Influence of Ground Control Points and Processing Parameters on UAS Image Mosaicking for Plant Height EstimationDigital surface models (DSMs) and 3D point clouds, generated using overlapping images from unmanned aircraft systems (UASs), are often used for plant height estimation in phenotyping and precision agriculture. This study examined the effects of the quantity and placement of ground control points (GCPs) and image processing parameters on the creation of DSMs and 3D point clouds for plant height estimation. A 2-ha field containing multiple experimental plots with four crops (corn, cotton, sorghum,... C. Yang, H. Zhao, W. Guo, J. Zhang, C. Suh, B.K. Fritz |