Proceedings
Authors
| Filter results9 paper(s) found. |
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1. Development Of Unmanned Aerial Vehicles For Site-specific Crop Production Management... Y. Huang, W.C. Hoffmann, Y. Lan, S.J. Thomson, B.K. Fritz |
2. 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 |
3. 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 |
4. Development Of A Decision Support System For Precision Areawide Pest Management In Cotton ProductionCrop models simulate growth and development, and provide relevant information for the routine management of the crop. The use of crop models on large areas for diagnosing crop growing conditions or predicting crop production is hampered by the lack of sufficient spatial information about model inputs. Integrating crop models with other information technologies such as geographic information systems (GIS), variable rate technology, remote sensing, and global positioning... Y. Lan, W.C. Hoffmann, J. Westbrook, M. Zaller |
5. Current Status and Future Directions of Precision Aerial Application For Site-Specific Crop Management In The USAPrecision agriculture includes different technologies that allow agricultural professional to use information management tools to optimize agriculture production. The new technologies allow aerial application applicators to improve application accuracy and efficiency, which saves time and money for the farmer and the pilot. The USDA-ARS-Aerial Application Technology group has an active research component in precision... W.C. Hoffmann, Y. Lan |
6. 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 |
7. 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 |
8. Development of a PWM Precision Spraying ControllerThis paper presents a new p... Y. Lan, H. Zhu |
9. Using a UAV-Based Active Canopy Sensor to Estimate Rice Nitrogen StatusActive canopy sensors have been widely used in the studies of crop nitrogen (N) estimation as its suitability for different environmental conditions. Unmanned aerial vehicle (UAV) is a low-cost remote sensing platform for its great flexibility compared to traditional ways of remote sensing. UAV-based active canopy sensor is expected to take the advantages of both sides. The objective of this study is to determine whether UAV-based active canopy sensor has potential for monitoring rice N status,... S. Li, Q. Cao, X. Liu, Y. Tian, Y. Zhu |