Open Access. Powered by Scholars. Published by Universities.®
Bioresource and Agricultural Engineering Commons™
Open Access. Powered by Scholars. Published by Universities.®
- Institution
- Publication
- Publication Type
Articles 1 - 10 of 10
Full-Text Articles in Bioresource and Agricultural Engineering
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 …
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 …
Using Remote Sensing To Estimate Crop Water Use To Improve Irrigation Water Management, Arturo Reyes-Gonzalez
Using Remote Sensing To Estimate Crop Water Use To Improve Irrigation Water Management, Arturo Reyes-Gonzalez
Electronic Theses and Dissertations
Irrigation water is scarce. Hence, accurate estimation of crop water use is necessary for proper irrigation managements and water conservation. Satellite-based remote sensing is a tool that can estimate crop water use efficiently. Several models have been developed to estimate crop water requirement or actual evapotranspiration (ETa) using remote sensing. One of them is the Mapping EvapoTranspiration at High Resolution using Internalized Calibration (METRIC) model. This model has been compared with other methods for ET estimations including weighing lysimeters, pan evaporation, Bowen Ratio Energy Balance System (BREBS), Eddy Covariance (EC), and sap flow. However, comparison of METRIC model outputs to …
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 …
Narrow-Band And Derivative-Based Vegetation Indices For Hyperspectral Data, Kelly Robert Thorp, Lei Tian, Haibo Yao, Lie Tang
Narrow-Band And Derivative-Based Vegetation Indices For Hyperspectral Data, Kelly Robert Thorp, Lei Tian, Haibo Yao, Lie Tang
Lie Tang
Hyperspectral remote sensing imagery was collected over a soybean field in central Illinois in mid-June 2001 before canopy closure. Estimates of percent vegetation cover were generated through the processing of RGB (red, green, blue) digital images collected on the ground with an automated crop mapping system. A comparative study was completed to test the ability of broad-band, narrow-band, and derivative-based vegetation indices to predict percent soybean cover at levels less than 70%. Though remote sensing imagery is commonly analyzed using reference data collected at random points over a scene of interest, the analysis of the hyperspectral imagery in this research …
Soil Moisture Estimation From Remotely Sensed Hyperspectral Data, Amy L. Kaleita, Lei F. Tian, Haibo Yao
Soil Moisture Estimation From Remotely Sensed Hyperspectral Data, Amy L. Kaleita, Lei F. Tian, Haibo Yao
Amy L. Kaleita
A methodology for mapping surface soil moisture content across an agricultural field from optical remote sensing and ground sampling is developed. This study uses both ground-based and remotely sensed spectral measurements of soil reflectance in visible and near-infrared wavelengths and concurrent measurements of volumetric soil moisture within the top 6 cm. After determining appropriate wavelengths for soil moisture estimation from spectral reflectance, a cokriging scheme was used to generate soil moisture maps. Results indicate that combining reflectance and ground measurements can yield more detailed maps of soil moisture than ground measurement alone.
Soil Moisture Estimation From Remotely Sensed Hyperspectral Data, Amy L. Kaleita, Lei Tian, Haibo Yao
Soil Moisture Estimation From Remotely Sensed Hyperspectral Data, Amy L. Kaleita, Lei Tian, Haibo Yao
Amy L. Kaleita
A methodology for mapping surface soil moisture content across an agricultural field from optical remote sensing and ground sampling is developed. This study uses both ground-based and remotely sensed spectral measurements of soil reflectance in visible and near-infrared wavelengths and concurrent measurements of volumetric soil moisture within the top 6 cm. After determining appropriate wavelengths for soil moisture estimation from spectral reflectance, a cokriging scheme was used to generate soil moisture maps. Results indicate that combining reflectance and ground measurements can yield more detailed maps of soil moisture than ground measurement alone.
Remote Sensing Of Site-Specific Soil Characteristics For Precision Farming, Amy L. Kaleita, Lei F. Tian
Remote Sensing Of Site-Specific Soil Characteristics For Precision Farming, Amy L. Kaleita, Lei F. Tian
Amy L. Kaleita
A methodology for assessing distributed surface soil moisture content from optical remote sensing is developed. This study uses both ground-based and remotely sensed spectral measurements of soil reflectance in visible and near-infrared wavelengths and concurrent measurements of volumetric soil moisture within the top 6 cm to establish a relationship between spectral response and moisture. Various approaches, including principal component analyses and regression techniques are investigated to determine the potential for quantifying soil moisture from the spectral reflection data. Preliminary investigations have yielded R 2 values as high as 0.62 when comparing predictions to actual moisture values. Investigation of predicting soil …
Remote Sensing Of Site-Specific Soil Characteristics For Precision Farming, Amy L. Kaleita, Lei Tian
Remote Sensing Of Site-Specific Soil Characteristics For Precision Farming, Amy L. Kaleita, Lei Tian
Amy L. Kaleita
A methodology for assessing distributed surface soil moisture content from optical remote sensing is developed. This study uses both ground-based and remotely sensed spectral measurements of soil reflectance in visible and near-infrared wavelengths and concurrent measurements of volumetric soil moisture within the top 6 cm to establish a relationship between spectral response and moisture. Various approaches, including principal component analyses and regression techniques are investigated to determine the potential for quantifying soil moisture from the spectral reflection data. Preliminary investigations have yielded R 2 values as high as 0.62 when comparing predictions to actual moisture values. Investigation of predicting soil …
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 …