Alterations of urban greenspace and heat stress risk during Hanoi's Master Plan 2030 implementation

Hanoi City has experienced a remarkable transformation due to implementing Hanoi's Master Plan 2030, which brought forth numerous challenges, notably in preserving urban green space (UGS). The objectives of this work are to (1) explore the changes in UGS distribution, (2) identify areas prone to heat stress by examining abnormal land surface temperature (LST) distributions in conjunction with population vulnerability, and (3) suggest solutions through an advanced UGS management platform. To investigate the UGS changes, we utilized Sentinel-2 satellite images, while the assessment of heat stress risk involved extracting LST data from the thermal infrared band of Landsat 8. Our research was concentrated on the inner region of Hanoi City, tracking UGS alterations from October 2016 to October 2018. The study's evaluation involved utilizing Google Earth images and conducting on-site research. The results demonstrated a significant decline in woodland and shrubland, decreasing by 1.3% and 4.4%, respectively, while grass cover experienced a growth of 2.4%. Our land cover classification exhibited high accuracy, reaching 96% in 2018 and 88% in 2016. Furthermore, this work unveiled a heightened risk primarily focused in the central inner-city zones, marked by densely populous residential regions and extensive built-up environments. Given that air temperature (Ta) significantly affects human health compared to LST, our forthcoming research will incorporate a spatially continuous Ta dataset to delve deeper into studying heat stress risks. This Ta dataset will be generated through our advanced Ta estimation framework employing Machine Learning algorithms, which have demonstrated exceptional performance. Identifying the heat stress risk patterns is essential, as this draws the attention of city planners, governing bodies, and healthcare institutions.