English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

The surface urban heat island (SUHI) of urban agglomeration has always been an important topic in the studies of urban heat island, especially with the development of satellite-based land surface temperature (LST) products. However, most studies are limited to the perspective of a single city, ignoring the impact of urban agglomeration and the changes of LST at day and night on the reference LST (RLST) (e.g., rural areas). Consequently, this article proposed a novel method about SUHI intensity estimation for the multicenters (mcSUHII) of urban agglomeration in Guangdong-Hong Kong-Macao Greater Bay Area (GHMBay) using nighttime light (NTL) data (i.e., DMSP/OLS) obtained in October, 2010. The mcSUHII method considered the RLST of SUHII estimation based on multicenter structure, and was more flexible to adapt the impact of human activity intensity. The study showed that compared with other RLSTs, such as suburban and forest, mcSUHII mitigates the underestimation bias caused by ignoring the multicenter structure. Importantly, the change in SUHII for urban agglomerations is greater than for a single city. Moreover, it was illustrated that the variation of SUHII presented an obvious inverted U-shape along the gradient from the inland to the coastal cities. The highest SUHIIs in the delta cities at day and night are ~7.27 &#x00B1; 1.71 &#x00B0;C and ~4.46 &#x00B1; 1.42 &#x00B0;C, respectively. Additionally, NTL served as the dominator together with other factors that were capable of explaining more than 90% of the spatial variation in SUHII in GHMBay. Therefore, considering multicenters more in estimation of SUHII of urban agglomeration for the sustainable development.

A Novel SUHI Referenced Estimation Method for Multicenters Urban Agglomeration using DMSP/OLS Nighttime Light Data