selected publications academic article Wu, W., Hague, S. S., Jung, J., Ashapure, A., Maeda, M., Maeda, A., ... Landivar, J. (2022). Cotton row spacing and unmanned aerial vehicle sensors. Agronomy Journal. 114(1), 331-339. 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. Jung, J., Maeda, M., Chang, A., Bhandari, M., Ashapure, A., & Landivar-Bowles, J. (2021). The potential of remote sensing and artificial intelligence as tools to improve the resilience of agriculture production systems. Current Opinion in Biotechnology. 70, 15-22. 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. 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. 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. 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. Maeda, M. M., Cothren, J. T., Heilman, J. L., Fernandez, C. J., Morgan, G. D., & da Costa, V. A. (2019). 1-Methylcyclopropene Effects on Field-Grown Cotton: Morphological Characteristics and Yield. Journal of Cotton Science. 23(1), 118-130. 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. 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. Maeda, M. M., Cothren, J. T., Heilman, J. L., Fernandez, C. J., Morgan, G. D., & Da Costa, V. A. (2018). Molecular biology and physiology: 1-methylcyclopropene effects on field-grown cotton: Physiological characteristics. Journal of Cotton Science. 22(1), 86-96. Pugh, N. A., Horne, D. W., Murray, S. C., Carvalho, G., Malambo, L., Jung, J., ... Rooney, W. L (2018). Temporal Estimates of Crop Growth in Sorghum and Maize Breeding Enabled by Unmanned Aerial Systems. The Plant Phenome Journal. 1(1), 1-10. 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. Stanton, C., Starek, M. J., Elliott, N., Brewer, M., Maeda, M. M., & Chu, T. (2017). Unmanned aircraft system-derived crop height and normalized difference vegetation index metrics for sorghum yield and aphid stress assessment. Journal of Applied Remote Sensing. 11(2), 026035-026035. 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. conference paper Chang, A., Jung, J., Yeom, J., Maeda, M., & Landivar, J. (2018). Phenotyping of sorghum panicles using Unmanned Aerial System (UAS) data. Proceedings of SPIE. 106640b. Jung, J., Ashapure, A., Maeda, M., Landivar, J., Chang, A., Yeom, J., Hague, S., & Smith, W. (2018). Unmanned aerial system based cotton genotype selection using machine learning (Conference Presentation). 36. 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. Enciso, J., Maeda, M., Landivar, J., Avila, C., Jung, J., & Chang, A. (2016). Unmanned Aerial System (UAS) for Precision Agriculture and Management Decisions
education and training Ph.D. in Agronomy, Texas A&M University - (College Station, Texas, United States) 2015