The spatial configuration of local climate zones reveals effects on wayfinding in human walking.

The importance of easy wayfinding in complex urban settings has been recognized in spatial planning. Empirical measurement and explicit representation of wayfinding, however, have been limited in deciding spatial configurations. Our study proposed and tested an approach to improving wayfinding by incorporating spatial analysis of urban forms in the Guangdong-Hong Kong-Macau Great Bay Area in China. Wayfinding was measured by an indicator of intelligibility using spatial design network analysis. Urban spatial configurations were quantified using landscape metrics to describe the spatial layouts of local climate zones (LCZs) as standardized urban forms. The statistical analysis demonstrated the significant associations between urban spatial configurations and wayfinding. These findings suggested, to improve wayfinding, 1) dispersing LCZ 1 (compact high-rise) and LCZ 2 (compact mid-rise) and 2) agglomerating LCZ 3 (compact low-rise), LCZ 5 (open mid-rise), LCZ 6 (open low-rise), and LCZ 9 (sparsely built). To our knowledge, this study is the first to incorporate the LCZ classification system into the wayfinding field, clearly providing empirically-supported solutions for dispersing and agglomerating spatial configurations. Our findings also provide insights for human-centered spatial planning by spatial co-development at local, urban, and regional levels.

Identifying research progress, focuses, and prospects of local climate zone (LCZ) using bibliometrics and critical reviews.

The local climate zone (LCZ) has been an important land surface classification used to differentiate urban climate between localities. The general knowledge maps of LCZ studies are needed when LCZ-related research has attracted great attention. This study integrated bibliometrics and critical review to understand the status quo and suggest future research directions. Bibliometrics provided a statistical technique to explore large volumes of article data from the Web of Science, ScienceDirect, and Scopus databases, based on the Co-Occurrence 13.4 (COOC) software. The bibliometric results indicated a rapid increase in LCZ publications and identified the high-frequency keywords which can be clustered into two groups, including a human thermal comfort-related group and the other urban climatology-related one. From 2011 to 2020, the effects of land use and urban morphology on urban climate and heat island effects predominated the LCZ-related research. Since 2021, the research focuses had shifted to the fields of thermal environment and heatwave, due to the growing demand for human thermal comfort and heat risk reduction. Moreover, this study identified 'Land Surface Temperature' and 'Heatwave' as two focuses of LCZ-related research during the last decade. Their critical reviews demonstrated the need for additional in-depth LCZ-heatwave studies that consider the risk of human exposure. This study also recommended incorporating hydrological concerns and social issues into the LCZ plan for a more integrated LCZ research outlook. Overall, this study provides not only a comprehensive understanding of LCZ knowledge networks, but also critical details on research focuses and potential research prospects.

Integrating the Budyko framework with the emerging hot spot analysis in local land use planning for regulating surface evapotranspiration ratio.

Land use planning regulates surface hydrological processes by adjusting land properties with varied evapotranspiration ratios. However, a dearth of empirical spatial information hampers the regulation of place-specific hydrological processes. Therefore, this study proposed a Local Land Use Planning framework for EvapoTranspiration Ratio regulations (ETR-LLUP), which was tested for the developments of spatially-varied land use strategies in the Dongjiang River Basin (DRB) in Southern China. With the first attempt at integrating the Emerging Hot Spots Analysis (EHSA) with the Budyko framework, the spatiotemporal trends of evapotranspiration ratios based on evaporative index and dryness index, from 1992 to 2018, were illustrated. Then, representative land-cover types in each sub-basin were defined using Geographically Weighted Principal Component Analysis, in two wet years (1998 and 2016) and three dry years (2004, 2009, and 2018), which in turn were identified using the Standard Precipitation Index. Finally, Geographically Weighted Regressions (GWRs) were used to detect spatially-varied relationships between land-cover proportions and evaporative index in both dry and wet climates. Results showed that the DRB was consistently a water-limited region from 1992 to 2018, and the situation was getting worse. We also identified the upper DRB as hotspots for hydrological management. Forests and croplands experienced increasingly water stress compared to other vegetation types. More importantly, the spatial results of GWR models enabled us to adjust basin land use by 1) expanding and contracting a combination of 'mosaic natural vegetation' and 'broadleaved deciduous trees' in the western and eastern parts of the basin, respectively; and 2) increasing 'broadleaved evergreen trees' in the upstream parts of the basin. These spatially-varied land use strategies based on the ETR-LLUP framework allow for place-specific hydrological management during both dry and wet climates.