Open Access. Powered by Scholars. Published by Universities.®
Bioresource and Agricultural Engineering Commons™
Open Access. Powered by Scholars. Published by Universities.®
- Discipline
-
- Life Sciences (14)
- Agriculture (11)
- Civil and Environmental Engineering (11)
- Environmental Engineering (8)
- Other Civil and Environmental Engineering (8)
-
- Physical Sciences and Mathematics (6)
- Geography (5)
- Plant Sciences (5)
- Remote Sensing (5)
- Social and Behavioral Sciences (5)
- Agronomy and Crop Sciences (4)
- Environmental Sciences (4)
- Water Resource Management (3)
- Earth Sciences (2)
- Oceanography and Atmospheric Sciences and Meteorology (2)
- Soil Science (2)
- Aerospace Engineering (1)
- Agricultural Science (1)
- Applied Mechanics (1)
- Chemistry (1)
- Computer-Aided Engineering and Design (1)
- Dynamics and Dynamical Systems (1)
- Engineering Mechanics (1)
- Engineering Science and Materials (1)
- Environmental Chemistry (1)
- Environmental Microbiology and Microbial Ecology (1)
- Environmental Monitoring (1)
- Fresh Water Studies (1)
- Institution
- Publication Year
- Publication
-
- Department of Biological Systems Engineering: Papers and Publications (13)
- Biosystems and Agricultural Engineering Faculty Publications (5)
- Department of Biological Systems Engineering: Dissertations, Theses, and Student Research (5)
- Amy L. Kaleita (4)
- BioResource and Agricultural Engineering (4)
-
- Department of Biological Systems Engineering: Conference Presentations and White Papers (1)
- Department of Mechanical and Materials Engineering: Dissertations, Theses, and Student Research (1)
- Electronic Theses and Dissertations (1)
- Graduate Theses and Dissertations (1)
- Lie Tang (1)
- Open Access Dissertations (1)
- Open Access Theses & Dissertations (1)
- School of Natural Resources: Faculty Publications (1)
- Theses and Dissertations--Biosystems and Agricultural Engineering (1)
- Publication Type
Articles 31 - 40 of 40
Full-Text Articles in Bioresource and Agricultural Engineering
Evaluating Net Groundwater Use From Remotely Sensed Evapotranspiration And Water Delivery Information, Daniel J. Howes, Charles M. Burt, Lucas Hoffman
Evaluating Net Groundwater Use From Remotely Sensed Evapotranspiration And Water Delivery Information, Daniel J. Howes, Charles M. Burt, Lucas Hoffman
BioResource and Agricultural Engineering
A detailed, comprehensive, and accurate identification of groundwater aquifer properties will likely never be fully achieved because of the high degree of variability and costs that testing involves. Furthermore, accurate estimates of boundary conditions are essential for groundwater modeling so that investigations of improved management scenarios can be conducted. The lack of key input values at the ground surface boundary limits the ability to accurately assess aquifer dynamics. Of major importance is actual evapotranspiration (water consumption or the loss of water to the atmosphere through transpiration and evaporation). The Irrigation Training and Research Center (ITRC) modified remotely sensed satellite imagery …
Basin-Wide Remote Sensing Of Actual Evapotranspiration And Its Influence On Regional Water Resources Planning, Daniel J. Howes, Charles M. Burt, Kyle Feist
Basin-Wide Remote Sensing Of Actual Evapotranspiration And Its Influence On Regional Water Resources Planning, Daniel J. Howes, Charles M. Burt, Kyle Feist
BioResource and Agricultural Engineering
The Irrigation Training & Research Center (ITRC) at Cal Poly State University, San Luis Obispo has been using METRIC to compute actual evapotranspiration from remote sensing sources (namely LandSAT images). The driving force behind this is the increasing need for improved evapotranspiration information on a large scale. A recent study in the Mexicali Valley of Baja California, Mexico utilized the ITRC-modified METRIC procedure to compute the crop and riparian evapotranspiration component of a basin-wide water balance. The resulting comparison between the mass balance computed change in groundwater storage and that computed using groundwater elevation data showed excellent agreement. For water …
Comparison Of Field Level And Regional Actual Etc Values Developed From Remote Sensing And Dual Crop Coefficient Procedure, Daniel J. Howes, Lucas Hoffmann, Franklin Gaudi
Comparison Of Field Level And Regional Actual Etc Values Developed From Remote Sensing And Dual Crop Coefficient Procedure, Daniel J. Howes, Lucas Hoffmann, Franklin Gaudi
BioResource and Agricultural Engineering
Crop evapotranspiration (ETc) estimates are important for regional water planning as well as irrigation scheduling. Traditional ETc computations utilize published crop coefficients (basal) that are adjusted on a daily basis depending on soil water availability (i.e., dual crop coefficient method). Recent advancements include using remote sensing data such as LandSAT combined with a surface energy balance algorithm (METRIC), allowing crop evapotranspiration to be computed for each pixel throughout images taken during the season. There are limitations and advantages for both methods. Comparisons of soil water balance evapotranspiration values to METRIC values for two scenarios in different regions of California have …
Sensor Ranging Technique For Determining Corn Plant Population, Joe D. Luck, Santosh Pitla, Scott A. Shearer
Sensor Ranging Technique For Determining Corn Plant Population, Joe D. Luck, Santosh Pitla, Scott A. Shearer
Department of Biological Systems Engineering: Conference Presentations and White Papers
Mapping of corn plant population can provide useful information for making field management decisions. This research focused on using low cost infra-red sensors to count plants. The voltage output data from the sensors were processed using an algorithm developed to extract plant populations. Preliminary investigations were conducted using sensors mounted on a stationary track for laboratory testing and on a row crop tractor for field testing. Repeated measurements were taken on a manually counted corn row. Visual inspection of the data from the field test indicated the potential to identify corn stalks based on approximate physical widths of the stalks. …
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 …