Engineering Commons^™

Estimation Of Cotton Canopy Parameters Based On Unmanned Aerial Vehicle (Uav) Oblique Photography, Jinyong Wu, Sheng Wen, Yubin Lan, Xuanchun Yin, Jiantao Zhang, Yufeng Ge

Department of Biological Systems Engineering: Papers and Publications

Background: The technology of cotton defoliation is essential for mechanical cotton harvesting. Agricultural unmanned aerial vehicle (UAV) spraying has the advantages of low cost, high efficiency and no mechanical damage to cotton and has been favored and widely used by cotton planters in China. However, there are also some problems of low cotton defoliation rates and high impurity rates caused by unclear spraying amounts of cotton defoliants. The chemical rate recommendation and application should be based upon crop canopy volume rather than on land area. Plant height and leaf area index (LAI) is directly connected to plant canopy structure. …

Research And Education For Optimizing The Development And Implementation Of An Unmanned Aircraft Program At The Nebraska Department Of Transportation, Wayne Woldt, Jon Starr, Christopher M. U. Neale

Nebraska Department of Transportation: Research Reports

This report describes the development and implementation of an Unmanned Aircraft System Program at the Nebraska Department of Transportation (NDOT). The project involved the selection and purchase of appropriate UAS and imaging systems for NDOT, education and training for NDOT personnel with classroom and hands-on operation of UAS with the goal of obtaining proficiency and pilot licenses. In addition, the development of policy for the use of UAS within NDOT was accomplished as well as standard operating procedures (SOP) documentation and the development of example case studies of interest to NDOT using the purchased systems and technology.

Research And Education For Optimizing The Development And Implementation Of An Unmanned Aircraft Program At The Nebraska Department Of Transportation, Wayne Woldt, Jon Starr, C.M.U. Neale

Nebraska Department of Transportation: Research Reports

This report describes the development and implementation of an Unmanned Aircraft System Program at the Nebraska Department of Transportation (NDOT). The project involved the selection and purchase of appropriate UAS and imaging systems for NDOT, education and training for NDOT personnel with classroom and hands-on operation of UAS with the goal of obtaining proficiency and pilot licenses. In addition, the development of policy for the use of UAS within NDOT was accomplished as well as standard operating procedures (SOP) documentation and the development of example case studies of interest to NDOT using the purchased systems and technology.

Field Demonstration Of Gpr And Uav Technologies For Evaluation Of Two Us 75/77 Bridges, Sepehr Pashoutani, Jinying Zhu, Chungwook Sim, Ji-Yong Lee

Nebraska Department of Transportation: Research Reports

Two Nebraska bridges with asphalt overlay were selected for nondestructive testing and evaluation (NDT/NDE). Three NDT techniques were conducted on these two bridges, including Ground Penetrating Radar (GPR), Half-Cell Potential (HCP) and Unmanned Aerial Vehicle (UAV) imaging. NDT data were collected during three construction stages of the bridges: (1) before repair on existing asphalt overlay; (2) on bare concrete after asphalt removal; (3) and after repairing delaminated concrete.

A machine learning technique, autoencoder, was used to build quantitative relationships between different NDT datasets. On bare concrete, the GPR amplitude and HCP voltage show a strong linear relationship. Then a threshold …

Real-Time Work Zone Traffic Management Via Unmanned Air Vehicles, Charles Malveaux Ph.D, Marcio De Queiroz Ph.D, Xin Li Ph.D, Hanny Hassan Ph.D, Zewei He Ph.D

Data

Highway work zones are prone to traffic accidents when congestion and queues develop. Vehicle queues expand at a rate of 1 mile every 2 minutes. Back-of-queue, rear-end crashes are the most common work zone crash, endangering the safety of motorists, passengers, and construction workers. The dynamic nature of queuing in the proximity of highway work zones necessitates traffic management solutions that can monitor and intervene in real time. Fortunately, recent progress in sensor technology, embedded systems, and wireless communication coupled to lower costs are now enabling the development of real-time, automated, “intelligent” traffic management systems that address this problem. The …

Real-Time Work Zone Traffic Management Via Unmanned Air Vehicles, Charles Malveaux Ph.D, Marcio De Queiroz Ph.D, Xin Li Ph.D, Hany Hassan Ph.D, Zewei He Ph.D

Publications

Highway work zones are prone to traffic accidents when congestion and queues develop. Vehicle queues expand at a rate of 1 mile every 2 minutes. Back-of-queue, rear-end crashes are the most common work zone crash, endangering the safety of motorists, passengers, and construction workers. The dynamic nature of queuing in the proximity of highway work zones necessitates traffic management solutions that can monitor and intervene in real time. Fortunately, recent progress in sensor technology, embedded systems, and wireless communication coupled to lower costs are now enabling the development of real-time, automated, “intelligent” traffic management systems that address this problem. The …

Early Detection Of Near-Surface Void Defects In Concrete Pavement Using Drone Based Thermography And Gpr Methods, Zhigang Shen, Ece Erdogmus, George Morcous, Chngsheng Cheng, Zhexiong Shang, Theresa Mccabe, Antony Mohsen Kamal Masoud Kodsy

Nebraska Department of Transportation: Research Reports

The goal of this research is to evaluate the feasibility and the performance of using UAV-mounted infrared thermography (IRT) and ground penetration radar (GPR) to detect sub-surface voids caused by consolidation issues in concrete pavement. The motivation of the study is to identify the consolidation defects as early as the initial set of concrete to avoid having this problem in large pavement sections, which is costly and time consuming to repair. Using the two technologies in combination to detect subsurface voids in the concrete initial set stage is new and aims to take advantage of the strengths and minimize the …

Incorporation Of Unmanned Aerial Vehicle (Uav) Point Cloud Products Into Remote Sensing Evapotranspiration Models, Mahyar Aboutalebi, Alfonso F. Torres-Rua, Mac Mckee, William P. Kustas, Héctor Nieto, Maria Mar Alsina, Alex White, John H. Prueger, Lynn Mckee, Joseph Alfieri, Lawrence E. Hipps, Calvin Coopmans, Nick Dokoozlian

Civil and Environmental Engineering Faculty Publications

In recent years, the deployment of satellites and unmanned aerial vehicles (UAVs) has led to production of enormous amounts of data and to novel data processing and analysis techniques for monitoring crop conditions. One overlooked data source amid these efforts, however, is incorporation of 3D information derived from multi-spectral imagery and photogrammetry algorithms into crop monitoring algorithms. Few studies and algorithms have taken advantage of 3D UAV information in monitoring and assessment of plant conditions. In this study, different aspects of UAV point cloud information for enhancing remote sensing evapotranspiration (ET) models, particularly the Two-Source Energy Balance Model (TSEB), over …

Uav/Satellite Multiscale Data Fusion For Crop Monitoring And Early Stress Detection, V. Sagan, M. Maimaitijiang, P. Sidike, M. Maimaitiyiming, H. Erkbol, S. Hartling, K. T. Peterson, J. Peterson, Joel Gerard Burken, F. Fritschi

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Early stress detection is critical for proactive field management and terminal yield prediction, and can aid policy making for improved food security in the context of climate change and population growth. Field surveys for crop monitoring are destructive, labor-intensive, time-consuming and not ideal for large-scale spatial and temporal monitoring. Recent technological advances in Unmanned Aerial Vehicle (UAV) and high-resolution satellite imaging with frequent revisit time have proliferated the applications of this emerging new technology in precision agriculture to address food security challenges from regional to global scales. In this paper, we present a concept of UAV and satellite virtual constellation …

Using A Balloon-Launched Unmanned Glider To Validate Real-Time Wrf Modeling, Travis J. Schuyler, S. M. Iman Gohari, Gary Pundsack, Donald Berchoff, Marcelo I. Guzman

Chemistry Faculty Publications

The use of small unmanned aerial systems (sUAS) for meteorological measurements has expanded significantly in recent years. SUAS are efficient platforms for collecting data with high resolution in both space and time, providing opportunities for enhanced atmospheric sampling. Furthermore, advances in mesoscale weather research and forecasting (WRF) modeling and graphical processing unit (GPU) computing have enabled high resolution weather modeling. In this manuscript, a balloon-launched unmanned glider, complete with a suite of sensors to measure atmospheric temperature, pressure, and relative humidity, is deployed for validation of real-time weather models. This work demonstrates the usefulness of sUAS for validating and improving …

Design Of Plant Protection Uav Variable Spray System Based On Neural Networks, Sheng Wen, Quanyong Zhang, Xuanchun Yin, Yubin Lan, Jiantao Zhang, Yufeng Ge

Department of Biological Systems Engineering: Papers and Publications

Recently, unmanned aerial vehicles (UAVs) have rapidly emerged as a new technology in the fields of plant protection and pest control in China. Based on existing variable spray research, a plant protection UAV variable spray system integrating neural network based decision making is designed. Using the existing data on plant protection UAV operations, combined with artificial neural network (ANN) technology, an error back propagation (BP) neural network model between the factors affecting droplet deposition is trained. The factors affecting droplet deposition include ambient temperature, ambient humidity, wind speed, flight speed, flight altitude, propeller pitch, nozzles pitch and prescription value. Subsequently, …

Rapeseed Seedling Stand Counting And Seeding Performance Evaluation At Two Early Growth Stages Based On Unmanned Aerial Vehicle Imagery, Biquan Zhao, Jian Zhang, Chenghai Yang, Guangsheng Zhou, Youchun Ding, Yeyin Shi, Dongyan Zhang, Jing Xie, Qingxi Liao

Department of Biological Systems Engineering: Papers and Publications

The development of unmanned aerial vehicles (UAVs) and image processing algorithms for field-based phenotyping offers a non-invasive and effective technology to obtain plant growth traits such as canopy cover and plant height in fields. Crop seedling stand count in early growth stages is important not only for determining plant emergence, but also for planning other related agronomic practices. The main objective of this research was to develop practical and rapid remote sensing methods for early growth stage stand counting to evaluate mechanically seeded rapeseed (Brassica napus L.) seedlings. Rapeseed was seeded in a field by three different seeding devices. A …

Evaluation Of Tseb Turbulent Fluxes Using Different Methods For The Retrieval Of Soil And Canopy Component Temperatures From Uav Thermal And Multispectral Imagery, Héctor Nieto, William P. Kustas, Alfonso F. Torres-Rúa, Joseph G. Alfieri, Feng Gao, Martha C. Anderson, W. Alex White, Lisheng Song, María Del Mar Alsina, John H. Prueger, Mac Mckee, Manal Elarab, Lynn G. Mckee

AggieAir Publications

The thermal-based Two-Source Energy Balance (TSEB) model partitions the evapotranspiration (ET) and energy fluxes from vegetation and soil components providing the capability for estimating soil evaporation (E) and canopy transpiration (T). However, it is crucial for ET partitioning to retrieve reliable estimates of canopy and soil temperatures and net radiation, as the latter determines the available energy for water and heat exchange from soil and canopy sources. These two factors become especially relevant in row crops with wide spacing and strongly clumped vegetation such as vineyards and orchards. To better understand these effects, very high spatial resolution remote-sensing data from …

Rapeseed Seedling Stand Counting And Seeding Performance Evaluation At Two Early Growth Stages Based On Unmanned Aerial Vehicle Imagery, Biquan Zhao, Jian Zhang, Chenghai Yang, Guangsheng Zhou, Youchun Ding, Yeyin Shi, Dongyan Zhang, Jing Xie, Qingxi Liao

Department of Biological Systems Engineering: Papers and Publications

The development of unmanned aerial vehicles (UAVs) and image processing algorithms for field-based phenotyping offers a non-invasive and effective technology to obtain plant growth traits such as canopy cover and plant height in fields. Crop seedling stand count in early growth stages is important not only for determining plant emergence, but also for planning other related agronomic practices. The main objective of this research was to develop practical and rapid remote sensing methods for early growth stage stand counting to evaluate mechanically seeded rapeseed (Brassica napus L.) seedlings. Rapeseed was seeded in a field by three different seeding devices. A …

Spatial Scale Gap Filling Using An Unmanned Aerial System: A Statistical Downscaling Method For Applications In Precision Agriculture, Leila Hassan-Esfahani, Ardeshir M. Ebtehaj, Alfonso F. Torres-Rua, Mac Mckee

Civil and Environmental Engineering Faculty Publications

Applications of satellite-borne observations in precision agriculture (PA) are often limited due to the coarse spatial resolution of satellite imagery. This paper uses high-resolution airborne observations to increase the spatial resolution of satellite data for related applications in PA. A new variational downscaling scheme is presented that uses coincident aerial imagery products from “AggieAir”, an unmanned aerial system, to increase the spatial resolution of Landsat satellite data. This approach is primarily tested for downscaling individual band Landsat images that can be used to derive normalized difference vegetation index (NDVI) and surface soil moisture (SSM). Quantitative and qualitative results demonstrate promising …

Assessment Of Surface Soil Moisture Using High-Resolution Multi-Spectral Imagery And Artificial Neural Networks, Leila Hassan-Esfahani, Alfonso F. Torres-Rua, Austin M. Jensen, Mac Mckee

Civil and Environmental Engineering Faculty Publications

Many crop production management decisions can be informed using data from high-resolution aerial images that provide information about crop health as influenced by soil fertility and moisture. Surface soil moisture is a key component of soil water balance, which addresses water and energy exchanges at the surface/atmosphere interface; however, high-resolution remotely sensed data is rarely used to acquire soil moisture values. In this study, an artificial neural network (ANN) model was developed to quantify the effectiveness of using spectral images to estimate surface soil moisture. The model produces acceptable estimations of surface soil moisture (root mean square error (RMSE) = …