Article
BAMOS August 2025
9
Best Poster Prize Winner at AMOS 2025
Xinyue Zhang, UNSW( xinyue. zhang20 @ unsw. edu. au)
I’ m honored to have received the Best Poster Prize at the AMOS 2025 Conference for sharing the findings of my second PhD research project.
In this project, I investigate how different datasets with varying spatial and temporal resolutions and sources affect the way we identify dryland vegetation.
It is an important foundation of my PhD, which focuses on disentangling the effects of land management and climate change on dryland vegetation dynamics at the regional scale. Understanding these complex interactions is essential for developing more effective strategies to monitor and manage land degradation— especially for drylands, which are among the most sensitive ecosystems to both human and climatic pressures.
Key findings
This second research project examined how NDVI( Normalized Difference Vegetation Index) datasets with varying spatial and temporal resolutions, as well as different precipitation sources, influence the detection and attribution of vegetation changes.
We first compared the spatial variability of gridded rainfall data( Australian Gridded Climate Data, AGCD) and satellitebased precipitation data( Climate Hazards Group InfraRed Precipitation with Station data, CHIRPS) against ground-based observations. Then we evaluated multiple NDVI products with different spatial and temporal resolutions to assess how these differences influence the detections of degradation signals.
We found that:
• AGCD and CHIRPS failed to capture the high spatial rainfall variability present in drylands.
• Higher-resolution NDVI datasets captured more localized degradation signals that coarser data may overlook.
• The timing of annual peak NDVI varied significantly across satellite products, affecting how change is detected and attributed.
• 16-day data offered minimal advantage over monthly composites in this context, suggesting monthly data may be sufficient to detect degradation at the regional scale.
These findings underscore the importance of selecting the appropriate dataset at the correct resolution when designing degradation assessments, and provide an important basis for my future focus on separating climate and land use effects in dryland systems.
On a personal note, I was genuinely surprised and grateful to receive the Best Poster Prize. It was incredibly rewarding to see this work recognized by peers and experts in the field— a real affirmation of the research direction I’ m pursuing.
I thoroughly enjoyed the conference, especially the opportunity to connect with other researchers working at the intersection of climate, ecology, and remote sensing. The thoughtful feedback and engaging discussions were definite highlights— and I’ m leaving even more motivated to keep pushing this work forward.
Me presenting my poster at the conference. Credit: Huazhen Li