Project Description

Forests play a crucial role in our lives as they provide various essential ecosystem services such as food, fiber, and freshwater and air. Nevertheless, our understanding of forests is still limited, as accurately measuring countless trees in the traditional way is labor-intensive and time-consuming. In this project, we propose to take advantage of newly available remote sensing data and digital technology to revolutionize the conventional forest measurement process with an interdisciplinary digital approach. We will utilize high-resolution remote sending data (Orthophotography and LiDAR) to conduct statewide individual tree-level inventory. We will use Martell Forest owned by Purdue University and statewide CFI plots across Indiana as validation sites as they already have a rich set of ground reference data collected. We will also collect ultra-fine spatial resolution geospatial data (MS and LiDAR) at Martell Forest to be used as reference data to validate forest maps generated from the Indiana statewide geospatial data. The resulting products will be the first in the nation to provide statewide forest map at an individual tree level. The outcome of this project will also have tremendous utilization and impacts on various disciplines such as forestry and natural resources, climate change, environmental engineering, parks & recreations. 

Start Date

June 2021

Postdoc Qualifications

PhD in Civil Engineering, Forest ecology, Forestry, Geography, or related field.
Proficient in remote sensing, GIS, and programming.
Evidence of strong scholarship (peer-reviewed publications).

Co-Advisors

Jinha Jung, jinha@purdue.edu, Lyles School of Civil Engineering, https://gdslab.org

Songlin Fei, Fei, sfei@purdue.edu, Forestry and Natural Resources

Guofan Shao, shao@purdue.edu, Forestry and Natural Resources 

References

J. Jung, B. K. Pekin, B. C. Pijanowski, “Mapping gaps in an old-growth, secondary-growth, and selectively-logged tropical rainforest using discrete return LIDAR,” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 6(6), pp. 2453-2461, 2013

B. K. Pekin, J. Jung, L. J. Villanueva-Rivera, B. C. Pijanowski, J. A. Ahumada, “Modeling acoustic diversity using soundscape recordings and LIDAR-derived metrics of vertical canopy structure in a neotropical rainforest,” Landscape Ecology, 27(10), pp. 1513-1522, 2012

J. Jung, M. Crawford, “Extraction of Features From LIDAR Waveform Data for Characterizing Forest Structure,” Geoscience and Remote Sensing Letters, 9(3), pp. 492-496, 2012

LaRue, E. A., Wagner, F. W., Fei, S., Atkins, J. W., Fahey, R. T., Gough, C. M., & Hardiman, B. S. (2020). Compatibility of aerial and terrestrial LiDAR for quantifying forest structural diversity. Remote Sensing, 12(9), 1407.

Shao, G., Iannone III, B. V., & Fei, S. (2018). Enhanced forest interior estimations utilizing lidar-assisted 3D forest cover map. Ecological Indicators, 93, 1236-1243.