Utilising earth observation for the study of forests in China

Professor Wangfei Zhang and Dr Yonhjie Ji, Southwest Forestry University, Kunming, China

Wednesday 29th January, 1-2pm, Cottrell 2V1 and streamed on Teams (contact the seminar organiser for the Teams link).
This seminar is open to all staff, students and affiliates of the University of Stirling. The seminar is hosted by Biological and Environmental Sciences (BES). 

Who this might appeal to: This joint presentation will hopefully be of interest to people involved in Earth observation, particularly of forests. 

Professor Zhang: The Application of Gaofen series satellite data in Forestry

Abstract: The study focuses on the applications of Gaofen (GF) series satellite data in the field of agriculture and forestry. As the key force of China’s earth observation, GF series satellites can provide rich surface information by virtue of their high-resolution and multi-spectral characteristics. The study first elaborates on the technical characteristics and performance advantages of the GF series satellites, then comprehensive pre-processing procedure was carried out for the data acquired by this series of satellites, covering key aspects such as radiometric correction and geometric refinement correction, so as to provide a high-quality data base for subsequent research. Based on the processed data, advanced algorithmic models were constructed to successfully realise the accurate inversion of a variety of agroforestry parameters. For example, the inversion of leaf area index, plant height and biomass of crops, as well as canopy coverage ratio and above-ground biomass of forests were fully explored. The studies fully explored the potential of the Gaofen series satellite data in agroforestry monitoring, the results may provide strong technical support for agroforestry resource monitoring using Gaofen datasets.

Bio: Wangfei Zhang received both the B.S. degree in Land Resource Management and the M.S. degree in Cartography and Geography Information System from Wuhan University, Wuhan, China, in 2001 and 2004, respectively, and the Ph.D. degree in Geophysical Prospecting and Information Technology from Kunming University of Science and Technology, Kunming, China, in 2011. She was a Post-Doctoral Researcher at Institute of Forest Resources Information Technique, Chinese Academy of Forestry, Beijing, China. From 2023 to 2024, She worked as a visiting scholar at Earth and Planetary Observation in University of Stirling, Stirling, UK; From 2014 to 2015, She worked as a visiting scholar at remote sensing group in University of Victoria and Pacific Forestry Centre, Victoria, Canada. In 2004, she joined the College of Forestry, Southwest Forestry University, Kunming, China, where she is a doctoral supervisor and professor currently. She has co-authored more than 100 papers in referred journals or presentations in international conferences and symposia. Her research interests include microwave remote sensing for inversion of crop and forest biophysical parameters, polarimetric and interferometric techniques and numerical models of vegetation microwave scattering problems.

Dr Ji: Multi-frequency polarimetric SAR for forest AGB inversion

Abstract: The penetration capability of electromagnetic wave signal into forest increases with increasing wavelength. SAR data at each frequency senses different components of forest structure. Therefore, the biomass distributed at various tree components could be estimated using different radar frequencies. And it is crucial to combine different frequency SAR backscatter and polymetric features to invert forest above ground biomass (AGB) for exploring the accuracy improving methods. We constructed a variety of different types of models, such as multiple linear stepwise regression (MLSR), random forest (RF), K-nearest neighbour with fast iterative features selection (KNN-FIFS), genetic algorithm and support vector regression (GA-SVR) and polarimetric water cloud models (Pol-WCM), to implement many experiments. We found lots of interesting patterns, which results can provide reference for further using SAR to invert forest AGB.

Bio: Dr. Yongjie Ji received an MSc degree in cartography and geographic information systems from Southwest Forestry University, Kunming, Yunnan Province, where he also received a PhD degree in Remote Sensing and Information Technology for Forestry. He is a PHD Supervisor, and his research interests focus on forest canopy height and forest biomass estimation using PolInSAR, SAR, and LiDAR data. He is currently an associate professor at College of Soil and Water Conservation, Southwest Forestry University.