Open Access. Powered by Scholars. Published by Universities.®
- Institution
- Publication
-
- Biosystems and Agricultural Engineering Faculty Publications (3)
- Biological Systems Engineering: Papers and Publications (2)
- Department of Agricultural and Biological Systems Engineering: Dissertations, Theses, and Student Research (2)
- Agricultural and Environmental Sciences Faculty Research (1)
- College of Forest Resources and Environmental Science Publications (1)
Articles 1 - 11 of 11
Full-Text Articles in Engineering
Enhancing Urban Water Quality Through Biological-Chemical Treatment: Aquatic Macroinvertebrate Community And Temporal Chlorophyll-A Response, Matthew Chaffee
Enhancing Urban Water Quality Through Biological-Chemical Treatment: Aquatic Macroinvertebrate Community And Temporal Chlorophyll-A Response, Matthew Chaffee
Department of Agricultural and Biological Systems Engineering: Dissertations, Theses, and Student Research
With a growing human population, urbanization is impeding a plethora of natural waterways. Of these, urban ponds play a vital role in nutrient sequestration, flood prevention, and habitat sanctuaries. However, nutrient loading can reduce habitat effectiveness and promote harmful algae blooms. To reduce internal nutrient loads, a biological-chemical treatment strategy consisting of floating treatment wetlands (FTWs) and lanthanum were applied to two urban retention ponds, Densmore and Wilderness Ridge Ponds. To measure effectiveness, chlorophyll-a samples were collected and correlated with Sentinel-2. A novel band algorithm termed 3BR1 produced a strong correlation (R2 = 0.72) to physical chlorophyll-a …
Characterization Of Physical And Biochemical Traits In Wheat And Corn Plants Using High Throughput Image Analysis, Kantilata Thapa
Characterization Of Physical And Biochemical Traits In Wheat And Corn Plants Using High Throughput Image Analysis, Kantilata Thapa
Department of Agricultural and Biological Systems Engineering: Dissertations, Theses, and Student Research
Plant phenotyping has been recognized as a rapidly growing field of research due to the labor-intensive, destructive, and time-consuming nature of traditional phenotyping methods. These phenotyping bottlenecks can be addressed by advancements in image-based phenotyping like RGB and hyperspectral imaging for the assessment of plant traits important for breeding purposes. This study aims (1) to characterize the physical and biochemical traits of wheat and corn plants using RGB and hyperspectral imaging in the greenhouse, and (2) to estimate leaf nitrogen (N), phosphorus (P), and potassium (K) content using hyperspectral imaging and an analytical spectral device (ASD spectrometer) and compare the …
Classifying Reflectance Targets Under Ambient Light Conditions Using Passive Spectral Measurements, Ali Hamidisepehr, Michael P. Sama, Joseph S. Dvorak, Ole O. Wendroth, Michael D. Montross
Classifying Reflectance Targets Under Ambient Light Conditions Using Passive Spectral Measurements, Ali Hamidisepehr, Michael P. Sama, Joseph S. Dvorak, Ole O. Wendroth, Michael D. Montross
Biosystems and Agricultural Engineering Faculty Publications
Collecting remotely sensed spectral data under varying ambient light conditions is challenging. The objective of this study was to test the ability to classify grayscale targets observed by portable spectrometers under varying ambient light conditions. Two sets of spectrometers covering ultraviolet (UV), visible (VIS), and near−infrared (NIR) wavelengths were instrumented using an embedded computer. One set was uncalibrated and used to measure the raw intensity of light reflected from a target. The other set was calibrated and used to measure downwelling irradiance. Three ambient−light compensation methods that successively built upon each other were investigated. The default method used a variable …
A Decade Of Unmanned Aerial Systems In Irrigated Agriculture In The Western U.S., Jose L. Chavez, Alfonso F. Torres-Rua, Wayne E. Woldt, Huihui Zhang, Christopher Robertson, Gary W. Marek, Dong Wang, Derek M. Heeren, Saleh Taghvaeian, Christopher M. U. Neale
A Decade Of Unmanned Aerial Systems In Irrigated Agriculture In The Western U.S., Jose L. Chavez, Alfonso F. Torres-Rua, Wayne E. Woldt, Huihui Zhang, Christopher Robertson, Gary W. Marek, Dong Wang, Derek M. Heeren, Saleh Taghvaeian, Christopher M. U. Neale
Biological Systems Engineering: Papers and Publications
Several research institutes, laboratories, academic programs, and service companies around the United States have been developing programs to utilize small unmanned aerial systems (sUAS) as an instrument to improve the efficiency of in-field water and agronomical management. This article describes a decade of efforts on research and development efforts focused on UAS technologies and methodologies developed for irrigation management, including the evolution of aircraft and sensors in contrast to data from satellites. Federal Aviation Administration (FAA) regulations for UAS operation in agriculture have been synthesized along with proposed modifications to enhance UAS contributions to irrigated agriculture. Although it is feasible …
Unmanned Aircraft System (Uas) Technology And Applications In Agriculture, Samuel C. Hassler, Fulya Baysal-Gurel
Unmanned Aircraft System (Uas) Technology And Applications In Agriculture, Samuel C. Hassler, Fulya Baysal-Gurel
Agricultural and Environmental Sciences Faculty Research
Numerous sensors have been developed over time for precision agriculture; though, only recently have these sensors been incorporated into the new realm of unmanned aircraft systems (UAS). This UAS technology has allowed for a more integrated and optimized approach to various farming tasks such as field mapping, plant stress detection, biomass estimation, weed management, inventory counting, and chemical spraying, among others. These systems can be highly specialized depending on the particular goals of the researcher or farmer, yet many aspects of UAS are similar. All systems require an underlying platform—or unmanned aerial vehicle (UAV)—and one or more peripherals and sensing …
Variable Rate Irrigation Of Maize And Soybean In West-Central Nebraska Under Full And Deficit Irrigation, J Burdette Barker, Sandeep Bhatti, Derek M. Heeren, Christopher M.U. Neale, Daran Rudnick
Variable Rate Irrigation Of Maize And Soybean In West-Central Nebraska Under Full And Deficit Irrigation, J Burdette Barker, Sandeep Bhatti, Derek M. Heeren, Christopher M.U. Neale, Daran Rudnick
Biological Systems Engineering: Papers and Publications
Variable rate irrigation (VRI) may improve center pivot irrigation management, including deficit irrigation. A remote-sensing-based evapotranspiration model was implemented with Landsat imagery to manage irrigations for a VRI equipped center pivot irrigated field located in West-Central Nebraska planted to maize in 2017 and soybean in 2018. In 2017, the study included VRI using the model, and uniform irrigation using neutron attenuation for full irrigation with no intended water stress (VRI-Full and Uniform-Full treatments, respectively). In 2018, two deficit irrigation treatments were added (VRI-Deficit and Uniform-Deficit, respectively) and the model was modified in an attempt to reduce water balance drift; model …
A Method For Reflectance Index Wavelength Selection From Moisture-Controlled Soil And Crop Residue Samples, Ali Hamidisepehr, Michael P. Sama, Aaron P. Turner, Ole O. Wendroth
A Method For Reflectance Index Wavelength Selection From Moisture-Controlled Soil And Crop Residue Samples, Ali Hamidisepehr, Michael P. Sama, Aaron P. Turner, Ole O. Wendroth
Biosystems and Agricultural Engineering Faculty Publications
Reflectance indices are a method for reducing the dimensionality of spectral measurements used to quantify material properties. Choosing the optimal wavelengths for developing an index based on a given material and property of interest is made difficult by the large number of wavelengths typically available to choose from and the lack of homogeneity when remotely sensing agricultural materials. This study aimed to determine the feasibility of using a low-cost method for sensing the moisture content of background materials in traditional crop remote sensing. Moisture-controlled soil and wheat stalk residue samples were measured at varying heights using a reflectance probe connected …
Use Of Remote Sensing To Support Forest And Wetlands Policies In The Usa, Audrey L. Mayer, Ricardo D. Lopez
Use Of Remote Sensing To Support Forest And Wetlands Policies In The Usa, Audrey L. Mayer, Ricardo D. Lopez
College of Forest Resources and Environmental Science Publications
The use of remote sensing for environmental policy development is now quite common and well-documented, as images from remote sensing platforms are often used to focus attention on emerging environmental issues and spur debate on potential policy solutions. However, its use in policy implementation and evaluation has not been examined in much detail. Here we examine the use of remote sensing to support the implementation and enforcement of policies regarding the conservation of forests and wetlands in the USA. Specifically, we focus on the “Roadless Rule” and “Travel Management Rules” as enforced by the US Department of Agriculture Forest Service …
Design Of Laser Multi-Beam Generator For Plant Discrimination, Sreten Askraba, Arie Paap, Kamal Alameh, John Rowe
Design Of Laser Multi-Beam Generator For Plant Discrimination, Sreten Askraba, Arie Paap, Kamal Alameh, John Rowe
Research outputs 2011
Optimisation of the optical signal from the laser multi-spot beam generator employed in a photonic based real-time plant discrimination sensor for use in selective herbicide spraying systems is presented. The plant detection sensor uses a three-wavelength laser diode module that sequentially emits identically-polarized laser light beams through a common aperture, along one optical path. Each laser beam enters a multi-spot beam generator which produces 15 parallel laser beams over a 240mm span. The intensity of the reflected light from each spot is detected by a high-speed line scan image sensor. Plant discrimination is based on calculating the slope of the …
Seasonal Adaptation Of Vegetation Color In Satellite Images, Srinivas Jakkula, Vamsi K.R. Mantena, Ramu Pedada, Yuzhong Shen, Jiang Li, Hamid R. Arabnia (Ed.)
Seasonal Adaptation Of Vegetation Color In Satellite Images, Srinivas Jakkula, Vamsi K.R. Mantena, Ramu Pedada, Yuzhong Shen, Jiang Li, Hamid R. Arabnia (Ed.)
Electrical & Computer Engineering Faculty Publications
Remote sensing techniques like NDVI (Normal Difference vegetative Index) when applied to phenological variations in aerial images, ascertained the seasonal rise and decline of photosynthetic activity in different seasons, resulting in different color tones of vegetation. The rise and fall of NDVI values decide the biological response, either the green up or brown down [1]. Vegetation in green up period appears with more vegetative vigor and during brown down period it has a dry appearance. This paper proposes a novel method that identifies vegetative patterns in satellite images and then alters vegetation color to simulate seasonal changes based on training …
Manipulation Of High Spatial Resolution Aircraft Remote Sensing Data For Use In Site-Specific Farming, Gabriel B. Senay, Andrew D. Ward, John G. Lyon, Norman R. Fausey, Sue E. Nokes
Manipulation Of High Spatial Resolution Aircraft Remote Sensing Data For Use In Site-Specific Farming, Gabriel B. Senay, Andrew D. Ward, John G. Lyon, Norman R. Fausey, Sue E. Nokes
Biosystems and Agricultural Engineering Faculty Publications
Three spatial data sets consisting of high spatial resolution (1 m) remote sensing images acquired in 12 spectral bands, an on-the-go yield map, and a Digital Elevation Model were co-registered and evaluated for spatial variability studies in a Geographic Information Systems environment. Separate on-the-go yield maps were developed for 3, 5, and 12 statistically significant mean yield classes. For each yield class, the corresponding mean spectral and elevation data were extracted. The relationship between mean spectral and yield data was strongly linear (r = 0.99). Also, a strong linear relationship between mean yield and elevation data (r = 0.92) was …