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Posts

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Blog Post number 4

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Blog Post number 1

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portfolio

RACE TO NET ZERO

Taking into account two scales and optimizing green spaces, transportation, and buildings, this strategic initiative seeks to diminish carbon emissions, enhance carbon absorption, and ultimately attain carbon neutrality.

REVIVING AND RECREATING TRADITIONAL STREETS THROUGH DL AND AI

This project focuses on urban revitalization in Guangzhou’s Historical District, focusing on 1980s characteristics, urban typology analysis, site redevelopment, GAN-based morphology generation, and street design using Stable Diffusion & Midjourney, with future goals in AI-enhanced urban planning.

REPLENISHING EV INFRASTRUCTURE

This downtown Los Angeles project strategically enhances and supplements EV charging facilities, aligning with global carbon neutrality goals and recognizing the critical need for electric vehicle infrastructure development.

THE BIGGEST LITTLE FARM

This project focuses on urban agriculture landscape in Scampia, Naples, embracing cyberfeminist principles to empower local women through the creation of a digital platform within the central park. The initiative aims to showcase Italian food culture and daily lives, fostering female empowerment through high-quality videos and online awareness.

THE SOUL OF THE NIGHT: AN ASTRONOMICAL PILGRIMAGE

Addressing the global concern of light pollution, this project envisions a memorial landscape in the Ali Dark Night Reserve, leveraging pilgrimage culture to reawaken reverence for the pristine starry sky and foster environmental awareness.

publications

A two-stage simulation approach of urban transport emission evaluation towards carbon peak: A case study in Suzhou, China

Published in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2022

Recommended citation: Xu, Y., Ma, X., Pan, M., & Jiang, K. (2022). A two-stage simulation approach of urban transport emission evaluation towards carbon peak: A case study in Suzhou, China. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 10, 285-292. https://doi.org/10.5194/isprs-annals-X-4-W3-2022-285-2022

Examining the rationality of Giant Panda National Park’s zoning designations and management measures for habitat conservation: Insights from interpretable machine learning methods

Published in Science of The Total Environment, 2024

Recommended citation: Xu, Y., & Tang, J. (2024). Examining the rationality of Giant Panda National Park's zoning designations and management measures for habitat conservation: Insights from interpretable machine learning methods. Science of The Total Environment, 170955. https://doi.org/10.1016/j.scitotenv.2024.170955

talks

teaching

Teaching experience 1

Undergraduate course, University 1, Department, 2014

This is a description of a teaching experience. You can use markdown like any other post.

Teaching experience 2

Workshop, University 1, Department, 2015

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