Directory

CREDENTIALS

• B.A., Psychology and Religion, University of Hawaii at Manoa
• MSW, University of Hawaii
• Ph.D., Human Services, Capella University (Minn.)

CREDENTIALS

• B.S., Biology, University of the Philippines
• M.S., Remote Sensing, University of the Philippines
• Ph.D., Remote Sensing, Chiba University (Japan)

ABOUT

Jose Edgardo L. Aban is a seasoned research and project manager and an advocate of satellite remote sensing education. He served for almost two decades at the Department of Science and Technology of the Philippines and has taught as a senior lecturer in the Department of Geography, Development, and Environmental Studies at the Universiti of Brunei Darussalam, where he was instrumental in the establishment of an image processing laboratory.

Dr. Aban teaches GE-480/580 Introduction to Remote Sensing during spring session and GE-480/580 Introduction to Geographic Information Systems during fall session. He also handles Introduction to Geography, and a host of Geography subjects such as GE-201 World Regional Geography, GE-203 Physical Geography, as well as GE-321 Economic Geography.

Prior to joining UOG, Aban served as a technical consultant at the Asian Development Bank, as project manager of the GIS-based project dubbed “Communication and Information Systems for the Control of Avian Influenza” of the ASEAN Foundation, and as a consultant of a mapping unit of an agricultural company in Indonesia.

Dr. Aban is also an avid amateur astronomer. During his youthful years, he built a Dobsonian telescope  on a shoestring budget. He was a long-time member of the Philippine Astronomical Society (PAS), and   a delegate/observer   to  a number of  rare astronomical events in the Philippines, including the 1986 Comet Halleywatch and the 1988 Total Solar Eclipse, to name a few.

RESEARCH INTERESTS

• Land use/cover change analysis
• Global change analysis
• Ecosystems change research
• Applications of non-parametric methods for global change analysis and modeling (power and singular spectrum analysis of multi-temporal datasets) using satellite data (e.g. normalized difference vegetation index - NDVI) and climatic data
• Development of pre-processing algorithms for noise reduction in satellite images
• Phenological change analysis and its relationship with changes in floral and faunal populations
• Climate change impacts (sea-level rise scenarios) modeling with the use of digital elevation modeling, climatic oscillations (e.g. ENSO, PDO), drones, among others.