Satellite Derived Land Surface Phenology
In collaboration with University of Technology Sydney, I created Australia's first nation-wide 500m-resolution phenology maps, covering all years from 2003 to the present. With this series of maps, one can discover the details of Australia's growing seasons with 8 metrics, including the start, peak, and end of each growing season. Applications include bushfire fuel load, land management, precision agriculture, pollen estimation, and tracking the effects of climate change on Australia's plant life.
Know Your Growing Seasons, Anywhere and Everywhere
In my research for TERN, in collaboration with University of Technology Sydney, I created Australia's first nation-wide 500m-resolution phenology maps, covering all years from 2003 to the present. With this series of maps, one can discover the details of Australia's growing seasons with 8 metrics, including the start, peak, and end of each growing season. Applications include bushfire fuel load, land management, precision agriculture, pollen estimation, and tracking the effects of climate change on Australia's plant life.
This work has received support from collaborators particularly those in the TERN OzFlux community, including Caitlin E Moore and Jason Beringer at The University of Western Australia, Jamie Cleverly at James Cook University, Suzanne M Prober and Craig Macfarlane at CSIRO, and Wayne S Meyer at The University of Adelaide.
Selected Publications & Awards
Xie, Qiaoyun, et al. "Land surface phenology indicators retrieved across diverse ecosystems using a modified threshold algorithm." Ecological Indicators 147 (2023): 110000. https://doi.org/10.1016/j.ecolind.2023.110000
Xie, Qiaoyun, et al. "Land surface phenology retrievals for arid and semi-arid ecosystems." ISPRS Journal of Photogrammetry and Remote Sensing 185 (2022): 129-145. https://doi.org/10.1016/j.isprsjprs.2022.01.017
Book: CRCSI (2021). Earth Observation: Data, Processing and Applications. Volume 3A: Applications—Terrestrial Vegetation. (Eds: Harrison, B.A., Gibson, R., Bastin, G., Thackway, R., Huete, A., Donald, G., Lyons, M., Sparks, T., Byrne, G., Lewis, M.M., and Xie, Q.). CRCSI, Melbourne. https://drive.google.com/file/d/1ULyD8tkbg236lt9dxvWkoe3TEdSLRzy5/view
Award: The Best Oral Presentation Award under the Early Career Scientists category, iLEAPS – OzFlux joint conference, Auckland, New Zealand, 2023. https://twitter.com/QiaoyunX/status/1621386811389132801
Phenology & Climate Change
Species composition is a key determinant of grassland ecosystem function and resilience. Climate change is predicted to alter the distribution of cool season (C3) and warm season (C4) grasses, however, the lack of spatial distributions and temporal variations of grass functional type information severely limits our understanding of climate impacts on grasslands.
Species composition is a key determinant of grassland ecosystem function and resilience. Climate change is predicted to alter the distribution of cool season (C3) and warm season (C4) grasses, however, the lack of spatial distributions and temporal variations of grass functional type information severely limits our understanding of climate impacts on grasslands.
In collaboration with scientists across Australia including Australian Research Council Laureate Distinguished Professor Belinda Medlyn and Professor Sally Power at Western Sydney University, A/Prof Paul Beggs at Macquarie University, Professor Janet Davis at Queensland University of Technology, Dr Danielle E Medek at The Prince Charles Hospital, Dr Christopher Hall and Distinguished professor Alfredo Huete at University of Technolgogy Sydney, we designed an algorithm to discriminate C3 and C4 grasses using phenology information, and for the first time, mapped annual distributions of C3 and C4 grasses in Australia. The maps then enabled us to track grass composition changes in time and space, and their association with climate change.
Our results revealed a devastating shift towards increasing C4 grasses. Counterintuitively, our climate analysis showed that this shift was primarily associated with seasonal rainfall patterns rather than warming. Our research suggests increased attention to water is needed in ecosystem and climate change research.
Selected Publications:
Xie, Qiaoyun, et al. "Satellite-observed shifts in C3/C4 abundance in Australian grasslands are associated with rainfall patterns." Remote Sensing of Environment 273 (2022): 112983. https://doi.org/10.1016/j.rse.2022.112983
Phenology & Agricultural and Environmental Management
In agriculture, phenological observations have a long tradition since many management decisions and the timing of field works (planting, fertilizing, irrigating, crop protection, harvesting, etc.) are based on plant development.
Eyes in the Sky Enable Us to Make Informed Decisions
In agriculture, phenological observations have a long tradition since many management decisions and the timing of field works (planting, fertilizing, irrigating, crop protection, harvesting, etc.) are based on plant development.
In environmental management, phenology indicates plant growth conditions and provides essential information of biomass, and vegetation function and structure. These are essential for bushfire, degradation, ecological restoration, conservation projects.
Our group has developed state-of-the-art algorithms using advanced satellite remote sensing technologies, to track plant growth in the context of agricultural and environmental managements. We collaborate widely with prestige research groups around the world, including agriculture focused groups led by Professor Jadu Dash at University of Southampton in the UK, Professor Wenjiang Huang and Professor Dailiang Peng at Chinese Academy of Sciences, Professor Pablo Zarco-Tejada at University of Melbourne, Professor Raffaele Casa at Tuscia University in Italy, Research Director at Italian National Research Council Stefano Pignatti; and environment focused groups led by Professor Trevor Keenan at UC Berkeley, Professor William Smith at University of Arizona, and Professor Emily Nicholson at Deakin University.
Selected Publications
Qian, Binxiang, et al. "A sentinel-2-based triangular vegetation index for chlorophyll content estimation." Agricultural and Forest Meteorology 322 (2022): 109000. https://doi.org/10.1016/j.agrformet.2022.109000
Xie, Qiaoyun, et al. "Retrieval of crop biophysical parameters from Sentinel-2 remote sensing imagery." International Journal of Applied Earth Observation and Geoinformation 80 (2019): 187-195. https://doi.org/10.1016/j.jag.2019.04.019
Xie, Qiaoyun, et al. "Vegetation indices combining the red and red-edge spectral information for leaf area index retrieval." IEEE Journal of selected topics in applied earth observations and remote sensing 11.5 (2018): 1482-1493. 10.1109/JSTARS.2018.2813281
Anniballe, Roberta, et al. "Sinergistic use of radar and optical data for agricultural data products assimilation: A case study in Central Italy." 2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS). IEEE, 2015. 10.1109/IGARSS.2015.7326544
Wu, Chaoyang, et al. "Improved estimation of light use efficiency by removal of canopy structural effect from the photochemical reflectance index (PRI)." Agriculture, Ecosystems & Environment 199 (2015): 333-338. https://doi.org/10.1016/j.agee.2014.10.017
Phenology & Human Health
Xie is using her combined expertise in science and engineering, including machine learning and remote sensing to establish a national pollen surveillance system in Australia. This work was in collaboration with AusPollen research network, and supported by amazing air quality scientists like A/Prof Paul Beggs at Macquarie University and Prof Janet Davis at Queensland University of Technology.
LSP Assisted Biogeography Research and its Changes Associated with Climate Change
In November 2016, a high grass pollen count, stormy weather and strong winds conspired to create a deadly thunderstorm asthma event in Melbourne. Nine people died from severe asthma attacks and hundreds more overwhelmed ambulance services and hospital emergency departments. According to Dr. Qiaoyun Xie, a national pollen forecasting system could have given hospitals, ambulance services and allergy sufferers precious time to prepare for the danger that lay ahead. But, while such systems exist in other countries, Australia is lagging behind.
In response, Xie is using her combined expertise in science and engineering, including machine learning and remote sensing to establish a national pollen surveillance system in Australia. This work was in collaboration with AusPollen research network, and supported by amazing air quality scientists like A/Prof Paul Beggs at Macquarie University and Prof Janet Davis at Queensland University of Technology.
Selected Publications
Xie, Qiaoyun, et al. "Forecasting Grass Pollen with Satellite Sensor Time-series, Meteorology data, and Machine Learning Tools." AGU Fall Meeting Abstracts. Vol. 2020. https://ui.adsabs.harvard.edu/abs/2020AGUFMB107...06X/abstract
Liu, Yuxia, et al. “Multi-scale phenology from digital time-lapse camera to Sentinel-2 and MODIS over Australian pastures.” No. EGU2020-7261. Copernicus Meetings, 2020. https://meetingorganizer.copernicus.org/EGU2020/EGU2020-7261.html?report=6975
Media: Bless you! New pollen surveillance system to reduce respiratory disease risk