Sciences and Exploration Directorate

Yoseline Betzaida Angel Lopez

(Post-Doctoral Associate)

Org Code: 618

Mail Code: 618
Greenbelt, MD 20771


Brief Bio

Scientist and engineer. Dr. Yoseline Angel has experience modeling plant functional traits and plant-environmental interactions using in-situ, UAV, airborne, and spaceborne imaging spectroscopy technology. Her expertise includes monitoring crop status-productivity and plant health in desertic, forest, and wetland habitats. 

Yoseline has 10 years of experience as an engineer managing and developing multidisciplinary Geographic Information System (GIS) projects in the O&G industry, spatially characterizing ecosystems and conservation areas in the Orinoco and Amazon basins, implementing high-accuracy GNSS field networks, and lecturing remote sensing and GIS.


Research Interests

Remote sensing of biosphere vegetation

Earth Science: Biosphere Vegetation Physiology & Function

Modeling plant functional traits and plant-environmental interactions from hyperspectral remote sensing products to support ecological and agriculture mapping and monitoring across spatiotemporal scales.


2021 Ph.D. in Environmental Sciences and Engineering - KAUST

2012 Master in Geomatics - National University of Colombia

2006 Cadastral Engineer and Geodesist - District University 'Francisco Jose de Caldas'


Global Winner / NASA SpaceApps Challenge COVID-19, 2020

Category: Food for Thought, Project: SOSQUA-Harvesting beyond food



Angel, Y., and A. N. Shiklomanov. 2022. Remote Detection and Monitoring of Plant Traits: Theory and Practice Annual Plant Reviews online 5 (3): 313-344 [10.1002/9781119312994.apr0778]

Angel, Y., and M. F. McCabe. 2022. Machine Learning Strategies for the Retrieval of Leaf-Chlorophyll Dynamics: Model Choice, Sequential Versus Retraining Learning, and Hyperspectral Predictors Frontiers in Plant Science 13 [10.3389/fpls.2022.722442]

Tu, Y.-H., K. Johansen, B. Aragon, et al. B. M. Stutsel, Y. Angel, O. A. Camargo, S. K. Al-Mashharawi, J. Jiang, M. G. Ziliani, and M. F. McCabe. 2021. Combining Nadir, Oblique, and Façade Imagery Enhances Reconstruction of Rock Formations Using Unmanned Aerial Vehicles IEEE Transactions on Geoscience and Remote Sensing 59 (12): 9987-9999 [10.1109/tgrs.2020.3047435]

Angel Lopez, Y. B. 2021. Monitoring crop development and health using UAV-based hyperspectral imagery and machine learning Ph.D. Dissertation [10.25781/KAUST-K738X]

Schunter, C., L. C. Bonzi, J. Norstog, et al. J. Sourisse, M. L. Berumen, Y. Angel, S. D. Parkes, M. F. McCabe, and T. Ravasi. 2021. Desert fish populations tolerate extreme salinity change to overcome hydrological constraints [10.1101/2021.05.14.444120]

Johansen, K., M. J. Morton, Y. Malbeteau, et al. B. Aragon, S. Al-Mashharawi, M. G. Ziliani, Y. Angel, G. Fiene, S. Negrão, M. A. Mousa, M. A. Tester, and M. F. McCabe. 2020. Predicting Biomass and Yield in a Tomato Phenotyping Experiment Using UAV Imagery and Random Forest Frontiers in Artificial Intelligence 3 [10.3389/frai.2020.00028]

Angel, Y., D. Turner, S. Parkes, et al. Y. Malbeteau, A. Lucieer, and M. F. McCabe. 2019. Automated Georectification and Mosaicking of UAV-Based Hyperspectral Imagery from Push-Broom Sensors Remote Sensing 12 (1): 34 [10.3390/rs12010034]

Barreto, M., K. Johansen, Y. Angel, and M. McCabe. 2019. Radiometric Assessment of a UAV-Based Push-Broom Hyperspectral Camera Sensors 19 (21): 4699 [10.3390/s19214699]

Angel, Y., R. Houborg, and M. F. McCabe. 2019. Reconstructing Cloud Contaminated Pixels Using Spatiotemporal Covariance Functions and Multitemporal Hyperspectral Imagery Remote Sensing 11 (10): 1145 [10.3390/rs11101145]

Shah, S. H., Y. Angel, R. Houborg, S. Ali, and M. F. McCabe. 2019. A Random Forest Machine Learning Approach for the Retrieval of Leaf Chlorophyll Content in Wheat Remote Sensing 11 (8): 920 [10.3390/rs11080920]

Johansen, K., M. J. Morton, Y. M. Malbeteau, et al. B. Aragon, S. K. Al-Mashharawi, M. G. Ziliani, Y. Angel, G. M. Fiene, S. S. Negrão, M. A. Mousa, M. A. Tester, and M. F. McCabe. 2019. Unmanned Aerial Vehicle-Based Phenotyping Using Morphometric and Spectral Analysis Can Quantify Responses of Wild Tomato Plants to Salinity Stress Frontiers in Plant Science 10 [10.3389/fpls.2019.00370]

Houborg, R., M. F. McCabe, Y. Angel, and E. M. Middleton. 2016. Detection of chlorophyll and leaf area index dynamics from sub-weekly hyperspectral imagery Remote Sensing for Agriculture, Ecosystems, and Hydrology XVIII [10.1117/12.2241345]

Angel Lopez, Y. B. 2012. Methodology to identify coca crops using Red Edge indices and imaging spectroscopy Master Dissertation []