Monitoring

For an overview of my current research, please go to:

Innovative platforms that offer more flexible and targeted geospatial data collection, such as unmanned aircraft system (UAS), hyperspectral / Lidar sensors, and wireless sensor networks, will be employed to collect data in unapproachable sites or sites need long-term monitoring. I am a certified remote pilot and I can foresee the evolutions that UAS could bring to the geospatial domain in data acquisition manner.

Data from civilian sectors that are versatile in sources, types, and formats serves as a meaningful bridge between academic research and the community, while offering practical usage. Big data from citizen science will be analyzed geovisual analytics, to unlock their usage limitations in relevant studies.

Citations: Li XY, Clinton N, Si YL, Liao JS, Liang L, Gong P. (2015) Projected impacts of climate change on protected bird and nature reserves in China. Chinese Science Bulletin. 10.1007/s11434-015-0892-y

Li XY, Liang L, Gong P, et al. (2012) Bird watching in China reveals bird distribution changes. Chinese Science Bulletin, 58(6): 649-656.

The pollution of fine particulate matter with an aerodynamic diameter of less than 2.5 µm, also known as PM_2.5, is considered as the current leading environmental risk factor and the 5^th highest mortality risk factor globally. However, not every place experience the same amount of air toxics. Increasing empirical evidence have demonstrated the localized pollution patterns (Hart et al., 2020). As a result, the conflict between the surging demand for denser monitoring network and sparsely distributed government stations gets inevitably evident. The recent remarkable surge in the use of low-cost sensors (LCSs), with the cost of each unit varying from tens to hundreds dollars per pollutant, has the potential to fill this monitoring gap.

Please check this poster our master student Sean Hickey presented in 2020 Texas Energy Summit.