Oliver Lopez, Ph.D.

Oliver Lopez

[cv ] . [gh/lopezvoliver] . [in/lopezvoliver] . [ oliver.lopez@kaust.edu.sa]

Geospatial data scientist with strong scientific computing skills and expertise in satellite-based remote sensing applications. Background in environmental science and engineering physics.

Skills

geospatial data science cloud computing satellite data scientific computing geographic information systems data visualization google earth engine high-performance computing hydrology python dask xarray

Programming: Bash, Python, R, FORTRAN, Javascript Data science: scipy, scikit-learn, randomforest, keras, tensorflow, xarray, dask, geopandas, R-tidyverse Cloud computing: Google Earth Engine, Google Cloud Platform

Experience

Geospatial data scientist, KAUST-HALO

2020 - now, Thuwal, Saudi Arabia

High-resolution, national-scale application of a satellite-based crop water use model
Adapted geospatial image-based processing workflows to leverage xarray and dask achieving 50x+ faster computation times

Technologies used: Google Earth Engine, Google Cloud Platform, dask, xarray, Docker

Postdoctoral fellow, KAUST-HALO

2018-2019, Thuwal, Saudi Arabia

Combined high-resolution remote sensing retrievals, numerical weather prediction data, and a land surface model to estimate farm-scale groundwater abstractions
Scaled a methodology for groundwater abstraction estimation to national scale

Technologies used: Ibex (High Performance Computing system at KAUST), QGIS

PhD. Candidate, King Abdullah University of Science and Technology (KAUST)

2013-2018, Thuwal, Saudi Arabia

Evaluated large-scale and long-term groundwater depletion in the Middle East using satellite gravimetry data
Combined satellite data with a land surface model to estimate groundwater abstraction

Technologies used: GDAL, climate data operators (cdo), netCDF operators (nco)

Selected peer-reviewed publications

López, O., Aragon, B., Li, T., McCabe, M.F.: Cloud-based agricultural crop water use monitoring across Saudi Arabia, in preparation; presented at the EGU General Assembly 2024, Vienna, Austria, 14-19 Apr 2024, EGU24-6454, 2024

Li T, López Valencia OM, Johansen K, McCabe MF. A Retrospective Analysis of National-Scale Agricultural Development in Saudi Arabia from 1990 to 2021. Remote Sensing. 2023; 15(3):731.

Johansen, K., López, O., Tu, Y., Li, T., and McCabe, M.F.: Center pivot field delineation and mapping: A satellite-driven object-based image analysis approach for national scale accounting, ISPRS J. Photogramm. Remote Sens., 175, 1-19, doi:10.1016/j.isprsjprs.2021.02.019, 2021

López, O., Johansen, K., Aragon, B., Li, T., Houborg, R., Malbeteau, Y., Mashhawari, S., Atlaf, M. U., Fallatah, E. M., Prasad, H., Hoteit, I. and McCabe, M.F.: Mapping groundwater abstractions from irrigated agriculture: big data, inverse modeling, and a satellite–model fusion approach, Hydrol. Earth. Syst. Sci., 24, 5251–5277, 2020

López, O., Houborg, R., and McCabe, M. F.: Evaluating the hydrological consistency of evaporation products using satellite-based gravity and rainfall data, Hydrol. Earth Syst. Sci., 21, 323-343, 2017

Open-source contributions

Authored

geeet: Evapotranspiration (ET) models for python and Google Earth Engine

eetasks: Earth Engine Task manager for vscode

Contributed

xarray ipyleaflet geemap leafmap py6s geeSEBAL

Education

PhD., Environmental Science and Engineering, KAUST

Thesis: Monitoring arid-land groundwater abstraction through optimization of a land surface model with remote sensing-based evaporation

M.Sc., Environmental Science and Engineering, KAUST

Thesis: Evaluation and preliminary design of a stormwater aquifer storage and recovery (ASR) system at the Wadi Khulays dunefield in Saudi Arabia

B.Sc., Instituto Tecnológico y de Estudios Superiores de Monterrey, México

Major: Engineering physics GPA: 94/100