HR job title
- Agrilife Center Director
- Contact Info
Landivar, Juan Agrilife Center Director
Positions
- Professor, Weslaco Research and Extension Center, Texas A&M AgriLIFE Extension
- Agrilife Center Director, Corpus Christi Research and Extension Center, Texas A&M AgriLIFE Extension
- Overview
- Publications
- Contact
- Other
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Overview
Publications
selected publications
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academic article
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Chang, A., Jung, J., Yeom, J., Maeda, M. M., Landivar, J. A., Enciso, J. M., Avila, C. A., & Anciso, J. R.
(2021).
Unmanned Aircraft System- (UAS-) Based High-Throughput Phenotyping (HTP) for Tomato Yield Estimation. Journal of Sensors.
2021, 1-14.
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Chang, A., Jung, J., Yeom, J., & Landivar, J.
(2021).
3D Characterization of Sorghum Panicles Using a 3D Point Cloud Derived from UAV Imagery. Remote Sensing.
13(2), 282-282.
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Bhandari, M., Baker, S., Rudd, J. C., Ibrahim, A., Chang, A., Xue, Q., ... Auvermann, B.
(2021).
Assessing the Effect of Drought on Winter Wheat Growth Using Unmanned Aerial System (UAS)-Based Phenotyping. Remote Sensing.
13(6), 1144-1144.
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Chang, A., Yeom, J., Jung, J., & Landivar, J.
(2020).
Comparison of Canopy Shape and Vegetation Indices of Citrus Trees Derived from UAV Multispectral Images for Characterization of Citrus Greening Disease. Remote Sensing.
12(24), 4122-4122.
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Bhandari, M., Ibrahim, A., Xue, Q., Jung, J., Chang, A., Rudd, J. C., ... Landivar, J.
(2020).
Assessing winter wheat foliage disease severity using aerial imagery acquired from small Unmanned Aerial Vehicle (UAV). 176, 105665-105665.
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Ashapure, A., Jung, J., Chang, A., Oh, S., Yeom, J., Maeda, M., ... Smith, W.
(2020).
Developing a machine learning based cotton yield estimation framework using multi-temporal UAS data. ISPRS Journal of Photogrammetry and Remote Sensing.
169, 180-194.
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Chang, A., Jung, J., Maeda, M. M., Landivar, J. A., Carvalho, H., & Yeom, J.
(2020).
Measurement of Cotton Canopy Temperature Using Radiometric Thermal Sensor Mounted on the Unmanned Aerial Vehicle (UAV). Journal of Sensors.
2020, 1-7.
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Oh, S., Chang, A., Ashapure, A., Jung, J., Dube, N., Maeda, M., Gonzalez, D., & Landivar, J.
(2020).
Plant Counting of Cotton from UAS Imagery Using Deep Learning-Based Object Detection Framework. Remote Sensing.
12(18), 2981-2981.
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Yeom, J., Jung, J., Chang, A., Ashapure, A., Maeda, M., Maeda, A., & Landivar, J.
(2019).
Comparison of Vegetation Indices Derived from UAV Data for Differentiation of Tillage Effects in Agriculture. Remote Sensing.
11(13), 1548-1548.
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Enciso, J., Avila, C. A., Jung, J., Elsayed-Farag, S., Chang, A., Yeom, J., ... Chavez, J. C.
(2019).
Validation of agronomic UAV and field measurements for tomato varieties. Computers and Electronics in Agriculture.
158, 278-283.
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Ashapure, A., Jung, J., Chang, A., Oh, S., Maeda, M., & Landivar, J.
(2019).
A Comparative Study of RGB and Multispectral Sensor-Based Cotton Canopy Cover Modelling Using Multi-Temporal UAS Data. Remote Sensing.
11(23), 2757-2757.
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Ashapure, A., Jung, J., Yeom, J., Chang, A., Maeda, M., Maeda, A., & Landivar, J.
(2019).
A novel framework to detect conventional tillage and no-tillage cropping system effect on cotton growth and development using multi-temporal UAS data. ISPRS Journal of Photogrammetry and Remote Sensing.
152, 49-64.
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Anderson, D. J., Brewer, M. J., Bowling, R. D., & Landivar, J. A.
(2018).
Recording within-cotton distribution of plant bug injury using plant mapping computer-based tools. Crop Protection.
112, 220-226.
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Chen, R., Chu, T., Landivar, J. A., Yang, C., & Maeda, M. M.
(2018).
Monitoring cotton (Gossypium hirsutum L.) germination using ultrahigh-resolution UAS images. Precision Agriculture.
19(1), 161-177.
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Yeom, J., Jung, J., Chang, A., Maeda, M., & Landivar, J.
(2018).
Automated Open Cotton Boll Detection for Yield Estimation Using Unmanned Aircraft Vehicle (UAV) Data. Remote Sensing.
10(12), 1895-1895.
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Foster, J. L., Bean, M. E., Morgan, C., Morgan, G., Mohtar, R., Landivar, J., & Young, M.
(2018).
Comparison of Two Tillage Practices in a Semi-Arid Cotton-Grain Sorghum Rotation. Agronomy Journal.
110(4), 1572-1579.
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Yang, Y., Wilson, L. T., Jifon, J., Landivar, J. A., da Silva, J., Maeda, M. M., Wang, J., & Christensen, E.
(2018).
Energycane growth dynamics and potential early harvest penalties along the Texas Gulf Coast. Biomass and Bioenergy.
113, 1-14.
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Jung, J., Maeda, M., Chang, A., Landivar, J., Yeom, J., & McGinty, J.
(2018).
Unmanned aerial system assisted framework for the selection of high yielding cotton genotypes. Computers and Electronics in Agriculture.
152, 74-81.
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Enciso, J., Jung, J., Chang, A., Chavez, J. C., Yeom, J., Landivar, J., & Cavazos, G.
(2018).
Assessing land leveling needs and performance with unmanned aerial system. Journal of Applied Remote Sensing.
12(1), 016001-016001.
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Enciso, J., Maeda, M., Landivar, J., Jung, J., & Chang, A.
(2017).
A ground based platform for high throughput phenotyping. Computers and Electronics in Agriculture.
141, 286-291.
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Chang, A., Jung, J., Maeda, M. M., & Landivar, J.
(2017).
Crop height monitoring with digital imagery from Unmanned Aerial System (UAS). Computers and Electronics in Agriculture.
141, 232-237.
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Chu, T., Chen, R., Landivar, J. A., Maeda, M. M., Yang, C., & Starek, M. J.
(2016).
Cotton growth modeling and assessment using unmanned aircraft system visual-band imagery. Journal of Applied Remote Sensing.
10(3), 036018-036018.
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Davidonis, G. H., Johnson, A. S., Landivar, J. A., & Fernandez, C. J.
(2004).
Cotton fiber quality is related to boll location and planting date. Agronomy Journal.
96(1), 42-47.
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Davidonis, G. H., Johnson, A., Landivar, J. A., & Hood, K. B.
(1999).
The cotton fiber property variability continuum from motes through seeds. Textile Research Journal.
69(10), 754-759.
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Chang, A., Jung, J., Yeom, J., Maeda, M. M., Landivar, J. A., Enciso, J. M., Avila, C. A., & Anciso, J. R.
(2021).
Unmanned Aircraft System- (UAS-) Based High-Throughput Phenotyping (HTP) for Tomato Yield Estimation. Journal of Sensors.
2021, 1-14.
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conference paper
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Ashapure, A., Jung, J., Oh, S., Chang, A., Dube, N., & Landivar, J.
(2020).
COMBINING UAS AND SENTINEL-2 DATA TO ESTIMATE CANOPY PARAMETERS OF A COTTON CROP USING MACHINE LEARNING. 5199-5202.
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Marconi, T., Bhandari, M., Vales, M. I., & Landivar, J.
(2020).
Unmanned Aerial System (UAS) Based High Throughput Phenotyping (HTP) to Assess Correlations between Potato Crop Growth and Yield. HORTSCIENCE.
S290-S290.
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Bhandari, M., Marconi, T., Chang, A., Enciso, J., & Landivar, J.
(2020).
Unmanned Aerial System (UAS)-Based Yield Prediction in Tomato. HORTSCIENCE.
S18-S19.
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Marconi, T. G., Oh, S., Ashapure, A., Chang, A., Jung, J., Landivar, J., & Enciso, J.
(2019).
Application of Unmanned Aerial System for Management of Tomato Cropping System. Proceedings of SPIE.
1100812-1100812-9.
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Oh, S., Ashapure, A., Marconi, T. G., Jung, J., & Landivar, J.
(2019).
UAS Based Tomato Yellow Leaf Curl Virus (TYLCV) Disease Detection System. Proceedings of SPIE.
110080p-110080p-7.
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Ashapure, A., Oh, S., Marconi, T. G., Chang, A., Jung, J., Landivar, J., & Enciso, J.
(2019).
Unmanned Aerial System Based Tomato Yield Estimation Using Machine Learning. Proceedings of SPIE.
110080o-110080o-10.
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Yeom, J., Jung, J., Chang, A., Maeda, M., & Landivar, J.
(2017).
COTTON GROWTH MODELING USING UNMANNED AERIAL VEHICLE VEGETATION INDICES. 5050-5052.
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Chang, A., Jung, J., Yeom, J., Maeda, M., & Landivar, J.
(2017).
SORGHUM PANICLE EXTRACTION FROM UNMANNED AERIAL SYSTEM DATA. 4350-4353.
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Boone, M., & Landivar, J. A.
(1999).
Performance of ICEMM: A cotton simulation model in a precision farming study. 1291-1296.
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Lascano, R. J., Baumhardt, R. L., Hicks, S. K., & Landivar, J. A.
(1999).
Spatial and temporal distribution of surface water content in a large agricultural field. 19-30.
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Ashapure, A., Jung, J., Oh, S., Chang, A., Dube, N., & Landivar, J.
(2020).
COMBINING UAS AND SENTINEL-2 DATA TO ESTIMATE CANOPY PARAMETERS OF A COTTON CROP USING MACHINE LEARNING. 5199-5202.
Contact
first name
- Juan
has last name
- Landivar
Other
- jalandivar@tamu.edu