selected publications academic article 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. conference paper 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. 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. Bhandari, M., Marconi, T., Chang, A., Enciso, J., & Landivar, J. (2020). Unmanned Aerial System (UAS)-Based Yield Prediction in Tomato. Hortscience. S18-S19. 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. 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. 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. Yeom, J., Jung, J., Chang, A., Maeda, M., & Landivar, J. (2017). COTTON GROWTH MODELING USING UNMANNED AERIAL VEHICLE VEGETATION INDICES. 5050-5052. Chang, A., Jung, J., Yeom, J., Maeda, M., & Landivar, J. (2017). SORGHUM PANICLE EXTRACTION FROM UNMANNED AERIAL SYSTEM DATA. 4350-4353. Boone, M., & Landivar, J. A. (1999). Performance of ICEMM: A cotton simulation model in a precision farming study. 1291-1296. 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.