Proceedings :: International Society of Precision Agriculture

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Nguyen, A.T

Ahmad, A

Ben-Gal, A

Tahir, M

Hamza, N

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Authors

Tahir, M

Jayasuriya, H.P

Zekri, S

Zaier, R

Al-buasidi, H

Teirab, A

Hamza, N

Nguyen, A.T

Thompson, A.L

Sudduth, K.A

Vories, E.D

Nguyen, A.T

Katz, L

Ben-Gal, A

Litaor, I

Naor, A

Peeters, A

Goldshtein, E

Alchanatis, V

Cohen, Y

Ahmad, A

Aggarwal, V

Saraswat, D

El Gamal, A

Johal, G

Topics

Sensor Application in Managing In-season Crop Variability

Engineering Technologies and Advances

Proximal and Remote Sensing of Soil and Crop (including Phenotyping)

Applications of Unmanned Aerial Systems

Type

Poster

Oral

Year

2012

2014

2016

2022

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Filter results5 paper(s) found.
1. Model for Remote Estimation of Nitrogen Contents of Corn Leaf Using Hyper-Spectral Reflectance under Semi-Arid Condition. Accuracy and precision of nitrogen estimation can be improved by hyperspectral remote sensing that leads... M. Tahir Download paper
2. Evaluation Of A Sensor-Based Precision Irrigation System For Efficiency And To Monitor And Control Groundwater Over-Pumping In Oman Oman is a country with a total area of 309,500 km2. However, cultivable land in Oman is estimated to be less than 2%, which amounts to about 6100 km2. More than 50 percent of the arable lands located in the northern coastal belt of Al Batinah region. The country with average annual rainfall around 100 mm, has limited natural fresh water resources and has been facing the serious problem of sea water intrusion into the scarce groundwater reserves due to undisciplined... H.P. Jayasuriya, S. Zekri, R. Zaier, H. Al-buasidi, A. Teirab, N. Hamza Download paper
3. Automated Support Tool for Variable Rate Irrigation Prescriptions Variable rate irrigation (VRI) enables center pivot management to better meet non-uniform water and fertility needs. This is accomplished through correctly matching system water application with spatial and temporal variability within the field. A computer program was modified to accommodate GIS data layers of grid-based field soil texture properties and fertility needs in making management decisions. The program can automatically develop a variable rate application prescription along the lateral... A.T. Nguyen, A.L. Thompson, K.A. Sudduth, E.D. Vories, A.T. Nguyen Download paper
4. Comparison of Canopy Extraction Methods from UAV Thermal Images for Temperature Mapping: a Case Study from a Peach Orchard Canopy extraction using thermal images significantly affects temperature mapping and crop water status estimation. This study aimed to compare several canopy extraction methodologies by utilizing a large database of UAV thermal images from a precision irrigation trial in a peach orchard. Canopy extraction using thermal images can be attained by purely statistical analysis (S), a combination of statistical and spatial analyses (SS), or by synchronizing thermal and RGB images, following RGB statistical... L. Katz, A. Ben-gal, I. Litaor, A. Naor, A. Peeters, E. Goldshtein, V. Alchanatis, Y. Cohen Download paper
5. Deep Learning-Based Corn Disease Tracking Using RTK Geolocated UAS Imagery Deep learning-based solutions for precision agriculture have achieved promising results in recent times. Deep learning has been used to accurately classify different disease types and disease severity estimation as an initial stage for developing robust disease management systems. However, tracking the spread of diseases, identifying disease hot spots within cornfields, and notifying farmers using deep learning and UAS imagery remains a critical research gap. Therefore, in this study, high resolution,... A. Ahmad, V. Aggarwal, D. Saraswat, A. El Gamal, G. Johal Download paper

Filter results5 paper(s) found.

1. Model for Remote Estimation of Nitrogen Contents of Corn Leaf Using Hyper-Spectral Reflectance under Semi-Arid Condition.

Accuracy and precision of nitrogen estimation can be improved by hyperspectral remote sensing that leads... M. Tahir

Download paper

2. Evaluation Of A Sensor-Based Precision Irrigation System For Efficiency And To Monitor And Control Groundwater Over-Pumping In Oman

Oman is a country with a total area of 309,500 km2. However, cultivable land in Oman is estimated to be less than 2%, which amounts to about 6100 km2. More than 50 percent of the arable lands located in the northern coastal belt of Al Batinah region. The country with average annual rainfall around 100 mm, has limited natural fresh water resources and has been facing the serious problem of sea water intrusion into the scarce groundwater reserves due to undisciplined... H.P. Jayasuriya, S. Zekri, R. Zaier, H. Al-buasidi, A. Teirab, N. Hamza

Download paper

3. Automated Support Tool for Variable Rate Irrigation Prescriptions

Variable rate irrigation (VRI) enables center pivot management to better meet non-uniform water and fertility needs. This is accomplished through correctly matching system water application with spatial and temporal variability within the field. A computer program was modified to accommodate GIS data layers of grid-based field soil texture properties and fertility needs in making management decisions. The program can automatically develop a variable rate application prescription along the lateral... A.T. Nguyen, A.L. Thompson, K.A. Sudduth, E.D. Vories, A.T. Nguyen

Download paper

4. Comparison of Canopy Extraction Methods from UAV Thermal Images for Temperature Mapping: a Case Study from a Peach Orchard

Canopy extraction using thermal images significantly affects temperature mapping and crop water status estimation. This study aimed to compare several canopy extraction methodologies by utilizing a large database of UAV thermal images from a precision irrigation trial in a peach orchard. Canopy extraction using thermal images can be attained by purely statistical analysis (S), a combination of statistical and spatial analyses (SS), or by synchronizing thermal and RGB images, following RGB statistical... L. Katz, A. Ben-gal, I. Litaor, A. Naor, A. Peeters, E. Goldshtein, V. Alchanatis, Y. Cohen

Download paper

5. Deep Learning-Based Corn Disease Tracking Using RTK Geolocated UAS Imagery

Deep learning-based solutions for precision agriculture have achieved promising results in recent times. Deep learning has been used to accurately classify different disease types and disease severity estimation as an initial stage for developing robust disease management systems. However, tracking the spread of diseases, identifying disease hot spots within cornfields, and notifying farmers using deep learning and UAS imagery remains a critical research gap. Therefore, in this study, high resolution,... A. Ahmad, V. Aggarwal, D. Saraswat, A. El Gamal, G. Johal

Download paper