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学者姓名：陈明
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Abstract ：
Urban green spaces (UGS) offer significant economic benefits that are well captured by housing value. Traditional valuation research focuses on the impact of UGS size and proximity on housing prices, neglecting the contribution of other green space characteristics such as quality, type, and shape, as well as how to guide the balanced construction of UGS. To address this gap, we use Wuhan, a Chinese city with high housing sales volume, as a case study. We use multi-source geographic big data and machine learning to comprehensively evaluate the characteristics and value added by UGS, deploying a combined random forest and multi-scale geographically weighted regression model. We find that the quality, type, and shape of UGS have far greater ability to add value to housing than do UGS scale and distance. In particular, quality-related characteristics exhibit an extremely large and stable positive effect on housing value. In addition, we also discovered threshold effects of scale, type, shape, and quality characteristics, beyond which the value-added benefits of green spaces will be greatly reduced. Based on these findings, we group green space characteristics by value added and propose a method of regulating green spaces in Wuhan. This method will help urban planners and policy makers better identify the differences in value added by the multiple characteristics of green spaces and provide new guidance for optimising their features.
Keyword ：
Housing value Housing value Important characteristics Important characteristics Planning strategy Planning strategy Urban green spaces Urban green spaces
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| GB/T 7714 | Wang, Yunda , Chen, Xudounan , Dai, Fei et al. Valuing the characteristics of urban green spaces to delineate their differential economic benefits based on housing value [J]. | ENVIRONMENTAL AND SUSTAINABILITY INDICATORS , 2025 , 28 . |
| MLA | Wang, Yunda et al. "Valuing the characteristics of urban green spaces to delineate their differential economic benefits based on housing value" . | ENVIRONMENTAL AND SUSTAINABILITY INDICATORS 28 (2025) . |
| APA | Wang, Yunda , Chen, Xudounan , Dai, Fei , Chen, Ming . Valuing the characteristics of urban green spaces to delineate their differential economic benefits based on housing value . | ENVIRONMENTAL AND SUSTAINABILITY INDICATORS , 2025 , 28 . |
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The morphology of urban blocks significantly influences carbon emissions and fine particulate matter (PM2.5) pollution, pose critical challenges to the sustainable development of urban areas. However, the underlying mechanisms of this relationship remain insufficiently understood. This study focused on blocks within Wuhan's central urban area, calculating morphological indicators, carbon emission intensity (CEI), and average PM2.5 concentration for each block. Generalized additive models, mediation effect models, and multiscale geographically weighted regression were employed to identify block morphological indicators that exhibit either synergistic or divergent effects on carbon emissions and PM2.5, to explore mediating mechanisms, and to assess spatial heterogeneity. The results show that: (1) Significant spatial autocorrelation was observed in the synergy between CEI and PM2.5 concentrations, displaying pronounced clustered distribution patterns; (2) The indicators building density (BD), floor area ratio (FAR), mean building height (BH), space crowding degree (SCD), and blue-green space ratio (BGR) exerted distinctly different influences on CEI compared to their effects on PM2.5, while building evenness index (BEI) demonstrated consistent effects on both CEI and PM2.5. mean canopy height (CH) and green volume ratio (GVR) exhibited partially overlapping effects on CEI and PM2.5; (3) Block morphology significantly influenced PM2.5 concentrations through CEI, with all indicators showing mediation proportions exceeding 7 %. Conversely, the influence of block morphology on CEI via PM2.5 was minimal, with the highest mediation proportion reaching only 4.88 %; (4) The impact of block morphology on the synergy of CEI and PM2.5 presented significant spatial heterogeneity, with BGR and GVR primarily exerting negative effects on the synergy index across different blocks, while the other six indicators showed a comparable number of blocks experiencing both positive and negative effects.
Keyword ：
Block spatial form Block spatial form Carbon emissions Carbon emissions Mediation effects Mediation effects Nonlinear effects Nonlinear effects PM2.5 PM2.5 Pollution reduction Pollution reduction
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| GB/T 7714 | Chen, Ming , You, Da , Chen, Zhiqin et al. Synergistic and divergent effects of block morphology on carbon emissions and PM2.5 pollution in Wuhan, China [J]. | SUSTAINABLE CITIES AND SOCIETY , 2025 , 134 . |
| MLA | Chen, Ming et al. "Synergistic and divergent effects of block morphology on carbon emissions and PM2.5 pollution in Wuhan, China" . | SUSTAINABLE CITIES AND SOCIETY 134 (2025) . |
| APA | Chen, Ming , You, Da , Chen, Zhiqin , Dai, Fei . Synergistic and divergent effects of block morphology on carbon emissions and PM2.5 pollution in Wuhan, China . | SUSTAINABLE CITIES AND SOCIETY , 2025 , 134 . |
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The frequent occurrence of extreme heat events has notably affected human's living environment, and a considerable number of studies have reported that green space is an efficient measure by investigating the correlation between green space and land surface temperature (LST). However, spatiotemporal effects of green space on LST still remain unclear. In this study, green space patterns (e.g., core, islet, perforation, edge, loop, bridge, and branch) were identified through morphological spatial pattern analysis (MSPA). Moreover, the effects of green space pattern on LST in three periods were investigated through three kinds of models. As indicated by the results: (1) the geographically and temporally weighted regression model exhibited the optimal performance compared with other two models. (2) in general, the core, the edge, the bridge, and the branch significantly contributed to cooling, and the islet hindered cooling. However, the perforation and the loop exerted significant dual nature effects with the similar quantity of the negative and positive coefficients, showing relatively complex impact mechanism. (3) the intensity of the effect of the respective MSPA class varied across the study area. The core had the most substantial effect, which distributed in the south and middle corners. (4) the result suggested that a neighborhood scale in China, which was 960 m in this study, served as a basic unit in green space management. The spatiotemporal non-stationarity of the effects of green space morphological patterns on LST provided important insights into urban thermal environment improvement through urban green space planning and design.
Keyword ：
Spatial pattern Spatial pattern Spatiotemporal non-stationarity Spatiotemporal non-stationarity Spatiotemporal regression analysis Spatiotemporal regression analysis Urban thermal environment Urban thermal environment
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| GB/T 7714 | Chen, Ming , Sun, Yubo , Yang, Bo et al. MSPA-based green space morphological pattern and its spatiotemporal influence on land surface temperature [J]. | HELIYON , 2024 , 10 (11) . |
| MLA | Chen, Ming et al. "MSPA-based green space morphological pattern and its spatiotemporal influence on land surface temperature" . | HELIYON 10 . 11 (2024) . |
| APA | Chen, Ming , Sun, Yubo , Yang, Bo , Jiang, Jiayi . MSPA-based green space morphological pattern and its spatiotemporal influence on land surface temperature . | HELIYON , 2024 , 10 (11) . |
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Green spaces have been demonstrated to significantly decrease PM 2.5 levels. However, the impact of green spaces on PM 2.5 levels in different spatial forms of urban blocks is not yet fully understood. This research utilized ensemble machine learning algorithms to investigate the impact of green space spatial patterns, assessed through landscape pattern analysis, to PM 2.5 concentrations during summer and winter based on local climate zones (LCZ). The results revealed significant differences in PM 2.5 concentration across the seven types of primary LCZs, primarily influenced by meteorological factors. In winter, eight green space indicators exhibited a more substantial contribution to PM 2.5 levels in comparison to the summer season. Significant discrepancies were noted in the contributions of these indicators across different LCZs. Patch density (PD) and landscape shape index (LSI) made a more substantial contribution, while relative patch richness (RPR) and Shannon's evenness index (SHEI) showed a less significant contribution. The spatial pattern of green spaces was significantly related to their contributions. Among the seven predominant LCZs, the five key indicators included PD, LSI, Shannon's diversity index (SHDI), area-weighted mean patch area (AREA_AM), and connectance index (CONNECT). Spatial heterogeneity was further observed in the positive and negative contributions of each green space indicator. This study enhances understanding of the impact of green spaces on PM 2.5 across LCZs and provides valuable insights for urban management and planning.
Keyword ：
Block spatial form Block spatial form Green space Green space Local climate zones Local climate zones PM (2.5) PM (2.5) Regulatory planning management unit Regulatory planning management unit
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| GB/T 7714 | Chen, Ming , Ren, Zhuoyue , Bi, Shibo . Impact of green space patterns on PM 2.5 levels: A local climate zone perspective [J]. | JOURNAL OF CLEANER PRODUCTION , 2024 , 478 . |
| MLA | Chen, Ming et al. "Impact of green space patterns on PM 2.5 levels: A local climate zone perspective" . | JOURNAL OF CLEANER PRODUCTION 478 (2024) . |
| APA | Chen, Ming , Ren, Zhuoyue , Bi, Shibo . Impact of green space patterns on PM 2.5 levels: A local climate zone perspective . | JOURNAL OF CLEANER PRODUCTION , 2024 , 478 . |
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Air pollution, particularly fine particulate matter (PM2.5), poses a significant health risk, especially in high-density urban areas. Urban green space (UGS) can effectively mitigate this pollution. Despite their potential, strategies for effectively leveraging Land Use/Land Cover (LULC) optimization to combat PM2.5 remain largely unexplored. Ordinary least squares (OLS), geographically weighted regression (GWR) and multiscale geographically weighted regression (MGWR) were employed to investigate the spatial heterogeneity relationship between UGS conversion and PM2.5 fluctuations across various scales and evolutionary stages, developing a multiscale practical framework for LULC synergy in combating air pollution. The areas of UGSs to/from other LULCs, PM2.5 concentrations and corresponding variation zones exhibited significant spatial clustering. These UGS conversions explained more than 65% of the PM2.5 changes in the study area, peaking at 76.4% explanatory power in the fourth stage. Compared to global spatial analysis (OLS: 0-0.48), local spatial regression analysis significantly improved the R-2 value (GWR: 0.32-0.75, MGWR: 0.48-0.90), but the fitting quality of local spatial regression analysis decreased with increasing scale, highlighting the importance of scale diagnosis. A 2 km scale was identified as optimal for assessing the spatial heterogeneity impact of UGS and other LULC conversions on PM2.5 changes. Conversion areas from water bodies and bare land to UGSs maintain stable local spatial properties at this scale (bandwidths: 44-99). Our research provides new insights into LULC management and planning, offering a coordinated approach to mitigating urban air pollution. Additionally, a practical framework was established for addressing spatially continuous variables such as PM2.5, revealing effective approaches for addressing urban environmental issues.
Keyword ：
land use and land cover land use and land cover PM2.5 PM2.5 spatial heterogeneity spatial heterogeneity spatiotemporal evolution spatiotemporal evolution synergy optimization synergy optimization urban green space urban green space
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| GB/T 7714 | Bi, Shibo , Chen, Ming , Tian, Zheng et al. Optimizing Urban Green Spaces for Air Quality Improvement: A Multiscale Land Use/Land Cover Synergy Practical Framework in Wuhan, China [J]. | LAND , 2024 , 13 (7) . |
| MLA | Bi, Shibo et al. "Optimizing Urban Green Spaces for Air Quality Improvement: A Multiscale Land Use/Land Cover Synergy Practical Framework in Wuhan, China" . | LAND 13 . 7 (2024) . |
| APA | Bi, Shibo , Chen, Ming , Tian, Zheng , Jiang, Peiyi , Dai, Fei , Wang, Guowei . Optimizing Urban Green Spaces for Air Quality Improvement: A Multiscale Land Use/Land Cover Synergy Practical Framework in Wuhan, China . | LAND , 2024 , 13 (7) . |
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不断深化的老龄化进程对城市建设提出了新的挑战。研究空间与非空间指标对于65岁以上老年人访问社区公园的影响机制，有助于完善中国社区生活圈规划并促进健康老龄化。手机信令数据(Mobile Signaling Data)与地理数据的应用，可为不同年龄组老年人的公园可达性进行社区层面的分析。基于MSD和地理数据，分析上海中心地区三个年龄段老年人访问社区公园的差异及其影响因素。通过多变量多元线性回归(Multivariate Multiple Linear Regression)模型，考察了空间与非空间指标的影响机制。结果显示，相比所有游客，老年游客使用社区公园时的实际服务范围减少了30%～50%。此外，本地老年人与其他年龄组游客访问社区公园的比例存在显著差异。空间指标中，旅行距离是限制75岁以上老年人访问公园的主要指标，而城市设施混合度对65～70岁老年人访问公园的负面影响最大。社会经济属性对70岁以上老年人访问公园具有显著的正面影响。旨在改善老年人友好的社区公园设计，支持健康老龄化社会的发展。
Keyword ：
上海 上海 健康城市 健康城市 手机信令数据 手机信令数据 社区公园 社区公园 适老化 适老化
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| GB/T 7714 | 姜佳怡 , 陈实 , 陈曦 et al. 老年健康促进视角下社区公园使用差异影响机制研究 [J]. | 园林 , 2024 , 41 (08) : 28-38 . |
| MLA | 姜佳怡 et al. "老年健康促进视角下社区公园使用差异影响机制研究" . | 园林 41 . 08 (2024) : 28-38 . |
| APA | 姜佳怡 , 陈实 , 陈曦 , 夏正伟 , 陈明 . 老年健康促进视角下社区公园使用差异影响机制研究 . | 园林 , 2024 , 41 (08) , 28-38 . |
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Extensive farmland loss and fragmentation due to urbanization pose a significant challenge to sustainable urban development and food security. However, existing research often separately examines the drivers of area or fragmentation-related metrics of built-up land and farmland, potentially undermining effectiveness of policy since the same factors influence the two land types differently. This study addresses the gap by exploring the spatiotemporal dynamics of and the combined effects of various factors on both farmland and built-up land. By utilizing the Multiscale Geographically Weighted Regression model (MGWR), this study investigates the dynamics and combined effects of two socioeconomic factors and three location factors on the landscape patterns of built-up land and farmland in Chengdu from 2000 to 2015. To examine the performance of MGWR, the results are compared with Ordinary Least Squares (OLS) and Geographically Weighted Regression (GWR). The results indicate that MGWR exhibits stronger explanatory power than OLS and GWR. All five factors showed influence at the county scale on the area of both farmland and built-up land, with only the distance to rural settlements and population density affecting landscape metrics at the city scale. The five selected factors showed opposite effects on the aggregation index and the area of built-up land and farmland. Specifically, gross domestic product and population density were similarly associated with the landscape patterns of both land types, but these relationships shifted to contradictions with urban development. Distance to urban and rural settlements inversely affected the size of built-up land and farmland yet had consistent effects on their fragmentation. This study presents an integrated perspective and novel methodology for analyzing landscape pattern evolution, providing policymakers with insights for balancing urban expansion and farmland protection by considering area and landscape patterns of two land types. The findings advance the application of ecological indicators in sustainable land-use strategies and provide a novel perspective for exploring sustainable urbanization-associated farmland evolution.
Keyword ：
Farmland preservation Farmland preservation Landscape metrics Landscape metrics Multiscale Geographically Weighted Multiscale Geographically Weighted Regression (MGWR) Regression (MGWR) Sustainability Sustainability Urbanization Urbanization
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| GB/T 7714 | Li, Wenpei , Diehl, Jessica Ann , Chen, Ming et al. The combined effects of multiple factors on farmland and built-up land landscape patterns-A case study of Chengdu, China [J]. | ECOLOGICAL INDICATORS , 2024 , 167 . |
| MLA | Li, Wenpei et al. "The combined effects of multiple factors on farmland and built-up land landscape patterns-A case study of Chengdu, China" . | ECOLOGICAL INDICATORS 167 (2024) . |
| APA | Li, Wenpei , Diehl, Jessica Ann , Chen, Ming , Herr, Christiane M. , Stouffs, Rudi . The combined effects of multiple factors on farmland and built-up land landscape patterns-A case study of Chengdu, China . | ECOLOGICAL INDICATORS , 2024 , 167 . |
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绿色空间是碳汇最有效的要素之一，但绿色空间格局与碳汇之间的关系鲜有研究涉及，尤其基于地理空间的视角。针对长三角地区县域单元，从5个维度各选取1个景观格局指标衡量绿色空间的形态特征，采用地理加权回归模型揭示绿色空间格局对碳汇影响的空间分异特征。结果表明，长三角县域单元的碳汇量存在显著的空间自相关，地理加权回归模型相比传统回归模型能更好地呈现影响机制。绿色空间的景观形状指数对碳汇的贡献最大，并在所有县域单元中对碳汇均起到促进作用；其次为最大斑块指数，以促进作用为主导；边缘密度对碳汇的作用呈双面性，促进与抑制作用的县域单元数量相当；香农均匀性指数和斑块密度的贡献相对最小。此外，5个指标对碳汇影响的强弱程度与促进、抑制作用也表现出空间上的差异。研究结果从助力碳中和的角度为县域层面的绿色空间优化提供了一些参考。
Keyword ：
景观格局 景观格局 碳汇 碳汇 空间回归 空间回归 绿色空间 绿色空间 风景园林 风景园林
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| GB/T 7714 | 陈明 , 李若雯 . 县域绿色空间景观格局对碳汇的影响——以长三角为例 [J]. | 中国园林 , 2024 , 40 (08) : 111-117 . |
| MLA | 陈明 et al. "县域绿色空间景观格局对碳汇的影响——以长三角为例" . | 中国园林 40 . 08 (2024) : 111-117 . |
| APA | 陈明 , 李若雯 . 县域绿色空间景观格局对碳汇的影响——以长三角为例 . | 中国园林 , 2024 , 40 (08) , 111-117 . |
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