selected publications academic article 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., 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. 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. 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. 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). Computers and Electronics in Agriculture. 176, 105665-105665. 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. 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. 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. 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. 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. 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. Enciso, J., Jung, J., & Chang, A (2018). Assessing land leveling needs and performance with unmanned aerial system. Journal of Applied Remote Sensing. 12(01), 1-1. 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), 42-42. 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. 35th European Mask and Lithography Conference (EMLC 2019). 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. 35th European Mask and Lithography Conference (EMLC 2019). 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. 35th European Mask and Lithography Conference (EMLC 2019). 110080o-110080o-10. Chang, A., Jung, J., Yeom, J., Maeda, M., & Landivar, J (2017). Sorghum panicle extraction from unmanned aerial system data. 2012 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS). 4350-4353. Yeom, J., Jung, J., Chang, A., Maeda, M., & Landivar, J. (2017). Cotton growth modeling using unmanned aerial vehicle vegetation indices. 2012 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS). 5050-5052. 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.