Courses

At UNG (2019~Now): 

  • Introduction to Geography, GEOG1111K (Undergraduate)
  •  Fundamentals of UAV Flight and Operation, ENVE1105K (Undergraduate)
  • Advanced UAV Remote Sensing, GISC3105/5105K (Undergraduate & Graduate) 
  • Physical Environmental Science, ENVS2111K (Undergraduate)
  • Environmental Management & Sustainability, ENVS2112K (Undergraduate)
  • Graphics & Info Visualization, ENVE2771K (Undergraduate)
  • Special Topics in GIS, GISC4903 (Undergraduate & Graduate)

 At CalPoly Pomona (2017~2018):

  • Introduction to Geographic Information Systems, GEO 240 (Undergraduate)
  • Advanced Geographic Information System I, GEO 442 (Undergraduate)
  • Civil Engineering CAD, CE 127 (Undergraduate) 

At University of California, Irvine (2013~2015): 

  • Civil Engineering Practicum, ENGRCEE 81 (Undergraduate) 
  • Watershed Modeling, ENGRCEE173 (Graduate and Undergraduate) 

Educational Software

Performance Metrics for Evaluation of Remote Sensing Observations and Climate Model Simulations: A simple and easy to use Validation Toolbox (MATLAB source code) that can be used for validation of gridded data including satellite observations, reanalysis data, and weather and climate model simulations. In addition to the commonly used categorical indices, the toolbox includes the Volumetric Hit Index (VHI), Volumetric False Alarm Ration (VFAR), Volumetric Missed Index (VMI), and Volumetric Critical Success Index (VCSI). Authors: Mehran A., and AghaKouchak A. 

Reference Publication: AghaKouchak A., Mehran A., 2013, Extended Contingency Table: Performance Metrics for Satellite Observations and Climate Model Simulations, Water Resources Research, 49, 7144-7149, doi:10.1002/wrcr.20498. AghaKouchak A., Behrangi A., Sorooshian S., Hsu K., Amitai E., 2011, Evaluation of satellite-retrieved extreme precipitation rates across the Central United States, Journal of Geophysical Research, 116, D02115, doi:10.1029/2010JD014741. (Software Download Link)

Multivariate Standardized Reliability and Resilience Index (MSRRI):  The model combines information on the inflow and reservoir storage relative to the demand. MSRRI combines (I) a “top-down”approach that focuses on processes/phenomena that cannot be simply controlled or altered by decision makers, such as climate change and variability, and (II) a “bottom-up” methodology that represents the local resilience and societal capacity to respond or adapt to droughts. MSRRI is based on a nonparametric multivariate distribution function that links inflow-demand reliability indicator to water storage resilience indicator.

Reference Publication:  Mehran A., Mazdiyasni O., AghaKouchak A,. A Hybrid Framework for Assessing Socioeconomic Drought: Linking ClimateVariability, Local Resilience, and Demand.,  J. Geophys. Res. Atmos., 120, doi:10.1002/2015JD023147.