Ping Yu Fan’s research while affiliated with The University of Hong Kong and other places

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.

While the land use‐street network nexus is well acknowledged, evidence for the one‐way impacts of land‐use patterns on street accessibility is still inadequate. The measurements of land‐use patterns and street accessibility lack systematic knowledge. Their empirical correlations also lack geographical variability, constraining site‐specific land‐use practices. Therefore, this study overcame the aforementioned limitations by examining the two‐level spatial models to formulate accessibility‐oriented land plans, using a well‐developed Chinese city as an example. Firstly, two landscape metrics—Euclidean Nearest‐Neighbor Distance (ENN) and Similarity Index (SIMI)—were used to quantify the intra‐ and inter‐land‐use configurations, respectively. Both city‐level and local accessibility were measured using spatial design network analysis. Performing both ordinary least squares (OLS) and geographically weighted regression (GWR) models, results identified the statistically significant effects of inter‐land‐use patterns on two‐level street accessibility. An exception was that land‐use configurations within residential and industrial regions were irrelevant to street accessibility. We also found GWR was a better‐fitting model than OLS when estimating locally‐varied accessibility, suggesting hierarchical multiscale land‐use planning. Overall, locally heterogeneous evidence in this study can substantialize land use‐street network interactions and support the decision‐making and implementation of place‐specific accessibility‐oriented land use.

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.

Temperature and population growth are key drivers of energy consumption. However, the relative importance of climatic and socioeconomic factors driving energy consumption at different temporal scales is not well-understood. Therefore, we developed a time-series decomposition method to attribute the relative importance of climatic (heat index and monsoon index) and socioeconomic variables to domestic energy consumption in Hong Kong from 1981-2015. The same method was used for Singapore from 2005-2015 to test the transferability of our time-series method. Population growth and GDP were the primary drivers for domestic energy consumption in Hong Kong from 1981-2015, but the heat index became the primary driver from 2005-2015 instead. The monsoon and heat indexes were the primary drivers of domestic energy consumption in Singapore from 2005-2015. Climate change will increase air temperatures by 2-5 • C for Hong Kong and Singapore by 2100. For RCP4.5 and RCP8.5 scenarios, Singapore shows a linear relationship between temperature and domestic energy consumption, whereas the relationship is non-linear in Hong Kong. Our findings highlight the importance of understanding the impact of climatic change on monsoon mechanism and heat index, which can predict future cooling demand and help achieve sustainable development goals.

Vegetation ecosystems are sensitive to large-scale climate variability in climate transition zones. As a representative transitional climate zone in Northwest China, Gansu is characterized by a sharp climate and vegetation gradient. In this study, the spatiotemporal variations of vegetation over Gansu are characterized using the satellite-based Normalized Difference Vegetation Index (NDVI) observations during 2000-2020. Results demonstrate that a significant greening trend in vegetation over Gansu is positively linked with large-scale climate factors through modulating the water and energy dynamics. As a climate transition zone, the northern water-limited and southern energy-limited regions of Gansu are affected by water and energy dynamics, differently. In the water-limited region, a weakening Asian monsoon along with colder Central Pacific (CP) and warmer North Pacific (NP) Oceans enhance prevailing westerlies which bring more atmospheric moisture. The enhanced atmospheric moisture and rising temperature promote the local vegetation growth. In contrast, large-scale climate variations suppress the southwest monsoon moisture fluxes and reduce precipitation in southern energy-limited regions. In these energy-limited regions, temperature has more effects on vegetation growth than precipitation. Therefore, the greenness of vegetation is because of more available energy from higher temperatures despite overall drying conditions in the region. Based on the above mechanism, future scenarios for climate impacts on vegetation cover over Gansu region are developed based on the two latest generation from coupled climate models (Coupled Model Intercomparison Project Phase 5 and Phase 6; CMIP5 and CMIP6). In the near-term future (2021-2039), the vegetation is likely to increase due to rising temperature. However, the vegetation is expected to decrease in a long-term future (2080-2099) when the energy-limited regions become water-limited due to increasing regional temperatures and lowering atmospheric moisture flux. This study reveals an increasing desertification risk over Gansu. Similar investigations will be valuable in climate transition regions worldwide to explore how large-scale climate variability affects local ecological services under different future climate scenarios.

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.

Emerging drought stress on vegetation over western Eurasia is linked to varying teleconnection patterns. The North-Sea Caspian pattern (NCP) is a relatively less studied Eurasian teleconnection pattern which has a role on drought conditions and the consequence of changing conditions on vegetation. Between 1981 and 2015, we found that the Standardized Precipitation Index (SPI) and the Normalized Difference Vegetation Index (NDVI) have different trend patterns over various parts of western Eurasia. Specifically, the vegetation greenness is linked with wetter conditions over Scandinavia, and vegetation cover decreases over a drying central Asia. However, in western Russia and France, there are paradoxically becoming greener under drier conditions. Using the Budyko framework such paradoxical patterns are found in energy-limited environmental systems, where vegetation growth is primarily promoted by warmer temperatures. While most studies focused on the impacts of the North Atlantic Oscillation (NAO), we test whether the NCP explains better the variability of meteorological drought and vegetation response over western Eurasia. We hypothesised that the positive phases of the NCP are correlated to high pressure anomalies over the North Sea, which can be associated with weakening onshore moisture advection, leading to warmer and dryness conditions. These conditions are driving vegetation greening, as western Eurasia is mainly energy-limited. However, we show that as the climate is warming along with the teleconnection impacts, the future ecosystem over western Eurasia will be transferred from energy-limited to water-limited systems. This suggests that the observed vegetation greening over the past three decades is unlikely to sustain in the future.

The planning of green-blue spaces (GBSs) requires considering the pedestrian needs in their walking routes for improving the walking experience. Incorporating the quantitative spatial characteristics of pedestrian movement is essential for pedestrian-friendly urban planning, which however received insufficient attention. Based on the space syntax theory, this study provided three indicators – accessibility, visibility, and intelligibility – to demonstrate the needs of physical access, visual access, and spatial cognition, respectively, in pedestrian movement. Measuring these three indicators, this study exemplified the planning of pedestrian-friendly GBSs using Guangzhou, China as a case study. Spatial design network analysis was used to quantify heterogeneous values of accessibility, visibility, and intelligibility of each GBS throughout the city. Moreover, we used principal component analysis to identify the leading indicators based on their weightings and then to calculate the scores to compare these three aspects of GBSs. The measurements of accessibility, visibility, and intelligibility of each GBS were then averaged across urban administrative districts for evaluating city-scale GBSs. The findings showed that GBSs in central districts were most accessible and visible but least intelligible. In contrast, the overall intelligibility of GBSs throughout the city was the greatest but the visibility was the least. Furthermore, intelligibility, as a more important factor than accessibility and visibility, should be particularly emphasized in future planning of pedestrian-friendly GBSs. Pedestrians from the central districts of Guangzhou city were most satisfied with the walking experience, in terms of accessing to, viewing, and cognizing the GBSs. ‘Yuexiu’, ‘Huadu’, and ‘Nansha’ districts were found as the key places where improved accessibility, visibility, and intelligibility were particularly needed to improve the GBS pedestrian-friendliness throughout the city. In summary, this study not only demonstrated a human-scale GBS evaluation framework for improving the human walking experience but also provided empirical evidence for building pedestrian-friendly green-blue spaces at the city scale.

One-size-fits-all approach is common in climate-sensitive urban design due to neglecting spatial heterogeneities in urban form and urban climate. This study explores a spatially-varied climate-sensitive urban design based on the Guangdong-Hong Kong-Macau Greater Bay Area (GBA). Three thermal indices, the Wet Bulb Globe Temperature (WBGT), the Apparent Temperature (AT), and the Universal Thermal Climate Index (UTCI) are used to assess the outdoor thermal environments. The local climate zone (LCZ) classification system is used to map urban form including built and land-cover types. Moreover, incorporating spatial effects, geographically weighted regression (GWR) models are used to account for spatially-varied thermal variations due to urban form changes. Our findings indicate that the large low-rise type (LCZ 8) needs more attention in built-up planning for thermal mitigation, and urban low plants type (LCZ D) should be a more effective nature-based climate mitigation strategy compared with the water bodies (LCZ G). The GWR results show a stronger consistency between UTCI and LCZ 8 and LCZ D, compared with WBGT and AT. UTCI is thus suggested for application in future urban climate studies. More importantly, the spatially-varied relationship between UTCI and urban form specifies the strategies and appropriate locations for thermal mitigation in climate-sensitive urban design.

Spatially-invariant land use and cover changes (LUCC) are not suitable for managing non-stationary drought conditions. Therefore, developing a spatially varying framework for managing land resources is necessary. In this study, the Dongjiang River Basin in South China is used to exemplify the significance of spatial heterogeneity in land planning optimization for mitigating drought risks. Using ERA5 that is the 5th major atmospheric reanalysis from the European Centre for Medium-Range Weather Forecast, we computed the Standardized Runoff Index (SRI) to quantify the hydrologic drought during 1992 to 2018. Also, based on Climate Change Initiative land use product, The Geographically Weighted Principal Component Analysis was used to identify the most dominant land types in the same period. Then, we used the Emerging Hot Spots Analysis to characterize the spatiotemporal evolution of historical LUCC and SRI. The spatially varying coefficients of Geographically and Temporally Weighted Regression models were used to reveal the empirical relationships between land types and the SRI. Results indicated that rainfed cropland with herbaceous cover, mosaic tress and shrub, shrubland, and grassland were four land types having statistical correlations with drought conditions over 27 years. Moreover, since 2003, the DRB was becoming drier, and the northern areas generally experienced severer hydrologic drought than the south. More importantly, we proposed region-specific land-use strategies for drought risk reductions. At a basin scale, we recommended to 1) increase rainfed herbaceous cropland and 2) reduce mosaic tree and shrub. At a sub-basin scale, the extents of shrub and grassland were suggested to increase in the northern DRB but to reduce in the south. Region-specific land use planning, including suitable locations, scales, and strategies, will contribute to handling current ‘one-size-fits-all’ LUCC. Planners are suggested to integrate spatial characteristics into future LUCC for regional hydrologic management.