Pinned Tweet
Right trees are key for cooling! 🌳
By "Inventory + LiDAR" for 4000 trees in #Shanghai, we found leaf traits (N, P, K) > canopy structure for cooling.
@JAppliedEcology
➡️doi.org/10.1111/1365-2664.70…
HUGE thanks to @Javier_Lopatin for Research Highlight🙌
➡️doi.org/10.1111/1365-2664.70…
Xiaoling Wang retweeted
📝Check out our new #TGRS paper: Large-scale High-resolution Essential Urban Land Cover Category Mapping Using a Semantic-Augmented and Noise-Tolerant Approach.
🗺️New data: 1-m essential urban land cover category (EULCC) mapping for all US urban areas.
ieeexplore.ieee.org/document…
Xiaoling Wang retweeted
Check out our @Sci_Bull paper: Enhanced mapping of essential urban land use categories in China (EULUC-China 2.0): integrating multimodal deep learning with multisource geospatial data. EULUC-China 2.0 data download: zenodo.org/records/16794007 sciencedirect.com/science/ar…
Xiaoling Wang retweeted
Our August issue is now available! 🐞
Includes topics such as...
👉The role of plant traits in urban planning 🌱
👉Using fine-scale spatial risk models to predict avian collisions with power lines 📊
👉Restoring free-flowing rivers 🌊
Read more 👇
besjournals.onlinelibrary.wi…
How urban forests can maximize their cooling effects? We offered a perspective from plant traits: papers.ssrn.com/sol3/papers.…
How can we maximise cooling effects in urban areas?
Using forest inventory + LiDAR, we found that leaf traits like nitrogen and phosphorus enhance cooling. Even more than the canopy structure.
Prioritise trees with high N and P for urban cooling!
Here: bit.ly/3XPHCyq
Using forest inventory + LiDAR, we found that leaf stiochiometry traits like nitrogen and phosphorus can enhance cooling, even more than the canopy structure we usually know.
Xiaoling Wang retweeted
Pls help spread: Two tenure-track positions available at HKU Landscape division, one is for technology (jobs.hku.hk/en/job/527151/te…) and another for ecology (jobs.hku.hk/en/job/527152/te…). @cpgis_media @earth_jobs @Earthworksjobs
Xiaoling Wang retweeted
Watch the full documentary about our interdisciplinary summer school! It was produced with @climateimpacts_ and @Cost_BottomsUp - and we’re so excited to share the result with you! 🤩
Interdisciplinary Summer School on forest ecosystems 2023: youtu.be/ltNN7quSp_g?si=lCT7… via @YouTube
Xiaoling Wang retweeted
What have been achieved in the past 30 years for urban forestry research in China? What need to be done more? Find the answer in the special issue “Thirty years of urban forestry research and practices in China” sciencedirect.com/journal/ur…
📢🥳New paper out in the Top Journal (IF9.1)!! Which plant #canopy #structure of the density, horizontal and vertical structures, contributed most to the #cooling effect of #urban #forests? We combine mobile monitoring and #lidar to reveal this question! sciencedirect.com/science/ar… – at Shanghai, People's Republic of China
2. Canopy with either high or low foliage height diversity (evenly distributed or unevenly distributed) can lead to high cooling effects. – at Shanghai, People's Republic of China
Xiaoling Wang retweeted
Our college just shared these CV guidelines and I think this is great. Your CV can be any format you want, but if you're not sure how to make one, this is a great starting point! #AcademicChatter #HiddenCurriculum
Xiaoling Wang retweeted
Our open-source teaching materials from the COST action @3DForEcoTech summer school are online!
Hopefully a useful resource for all, but especially for educators who want to include UAV/TLS/mobile laser scanning or photogrammetry in their teaching.
➡️ bit.ly/3R6ahdi
Xiaoling Wang retweeted
📢New review paper is officially out!!!
We are focusing on close-range remote sensing technologies for forests: state-of-the-art, challenges and opportunities.
Here: bit.ly/3huBNn5
#lidar #photogrammetry #UAV #forest
@IEEEXplore @3DForEcoTech
Xiaoling Wang retweeted
1/5⭐️#SAR_STAR @Arunima26728187 is a #PhD scholar @CZUvPraze & was a #ResearchScholar @NIH_Hydrology. @Arunima26728187's current research is focused on #LiDAR & #SAR for #forestry. 👋Give her a follow & ⬇️read on! #WomeninSTEM #EOChat
Xiaoling Wang retweeted
"How to have absolute importance of predictor variables in boosted regression trees (BRT) model?" ift.tt/O7WknI4



























