Enhancing Urban Land Use Identification Using Urban Morphology

Land, Год журнала: 2024, Номер 13(6), С. 761 - 761

Опубликована: Май 28, 2024

Urban land use provides essential information about how is utilized within cities, which critical for planning, urban renewal, and early warnings natural disasters. Although existing studies have multi-source perception data to acquire quickly at low cost, some integrated morphological indicators aid in identification, there still a lack of systematic discussion the literature regarding potential three-dimensional morphology enhance identification effectiveness. Therefore, this paper aims explore can be used improve types. This study presents an innovative approach called UMH–LUC model accuracy identification. The first conducts preliminary classification using points interest (POI) data. It then improves results with dynamic reclassification based on floor area ratio (FAR) measurements variance perimeter metrics. These methodologies leverage key features distinguish types more precisely. was validated Pearl River Delta agglomeration random sampling, comparative analysis case studies. Results demonstrate that achieved 81.7% Kappa coefficient 77.6%, representing 11.9% improvement over non-morphology-based approach. Moreover, overall disagreement 0.183, reduction 0.099 compared LUC without 0.19 EULUC-China. performed particularly well identifying residential land, mixed-use areas marginal lands. confirms morphology’s value supporting low-cost, efficient mapping applications sustainable planning management.

Язык: Английский

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Innovative hybrid algorithm for simultaneous land surface temperature and emissivity retrieval: Case study with SDGSAT-1 data

Remote Sensing of Environment, Год журнала: 2024, Номер 315, С. 114449 - 114449

Опубликована: Окт. 14, 2024

Язык: Английский

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Classification of urban underlying surfaces in Beijing and its impact on summer high temperature and heat wave event

Atmospheric Science Letters, Год журнала: 2025, Номер 26(1)

Опубликована: Янв. 1, 2025

Abstract With analysis of local climate zone (LCZ) classification, approximately 52.0% underlying surfaces in Beijing are covered by buildings with LCZ 5 (open midrise) accounting for the highest proportion, and D (low plants) is most distributed among natural surface types. Compared to surfaces, building have higher values high temperature (HT) heat wave (HW) days, HW intensity, maximum duration. In recent decades, HT days on start earlier end later than those surfaces. Building make greater contribution urban island intensity apparent that temperature, yet it opposite

Язык: Английский

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Unlocking the Ecological Blueprint: Strategic Zoning and Policy Guidelines for Ecosystem Services in Guangdong Province, China

Journal of Urban Planning and Development, Год журнала: 2025, Номер 151(2)

Опубликована: Янв. 28, 2025

Язык: Английский

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Diurnal and seasonal variation of surface heat island of local climate zones using FengYun-4A land surface temperature data

Urban Climate, Год журнала: 2025, Номер 59, С. 102317 - 102317

Опубликована: Янв. 29, 2025

Язык: Английский

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Research on the Nonlinear Relationship Between Carbon Emissions from Residential Land and the Built Environment: A Case Study of Susong County, Anhui Province Using the XGBoost-SHAP Model

Land, Год журнала: 2025, Номер 14(3), С. 440 - 440

Опубликована: Фев. 20, 2025

Residential land is the basic unit of urban-scale carbon emissions (CEs). Quantifying and predicting CEs from residential are conducive to achieving urban neutrality. This study took 84 communities in Susong County, Anhui Province as its research object, exploring nonlinear relationship between built environment land. By identifying through building electricity consumption, 14 indicators, including area (LA), floor ratio (FAR), greening (GA), density (BD), gross (GFA), use mix rate (Phh), permanent population (PPD), were selected establish an interpretable machine learning (ML) model based on XGBoost-SHAP attribution analysis framework. The results show that, first, goodness fit XGBoost reached 91.9%, prediction accuracy was better than that gradient boosting decision tree (GBDT), random forest (RF), Adaboost model, traditional logistic model. Second, compared with other ML models, explained influencing factors more clearly. SHAP indicate BD, FAR, Phh most important affecting CEs. Third, there a significant threshold effect characteristic variables Fourth, interaction different dimensions environmental factors, played dominant role interaction. Reducing FAR considered be effective CE reduction strategy. provides practical suggestions for planners reducing land, which has policy implications significance.

Язык: Английский

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Asymmetry in the intensity and frequency of extreme high temperature during daytime and nighttime in China in the summer 2022

The Science of The Total Environment, Год журнала: 2025, Номер 976, С. 179332 - 179332

Опубликована: Апрель 9, 2025

Язык: Английский

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Satellite Data Revealed That the Expansion of China’s Lakes Is Accompanied by Rising Temperatures and Wider Temperature Differences

Remote Sensing, Год журнала: 2025, Номер 17(9), С. 1546 - 1546

Опубликована: Апрель 26, 2025

Lake surface water area (LSWA) and lake temperature (LSWT) are critical indicators of climate change, responding rapidly to global warming. However, studies on the synergistic variations LSWA LSWT scarce, coupling relationships among lakes with different environmental characteristics remain unclear. In this study, relative growth rate (RKLSWA); absolute rates annual maximum, mean, minimum LSWTs (i.e., KLSWT_max, KLSWT_mean, KLSWT_min); difference between maximum (LSWT_mmd) (KLSWT_mmd) were investigated across more than 4000 in China using long-term Landsat data, their types permafrost non-permafrost recharge, endorheic or exorheic lakes, natural artificial lakes) comprehensively analyzed. Results indicate significant differences trends LSWT, as well interrelationships various regions types. Qinghai–Tibet Plateau (QTP), 57.8% showed an increasing trend LSWA, 2.4% showing moderate expansion (RKLSWA values 0.1–0.2), while over 27.5% South (SC) region displayed shrinkage −0.1~0%/year). Regarding LSWTs, 49.8% QTP exhibited a KLSWT_max greater 0, 47.9% KLSWT_mean 0. contrast, 48.1% Middle Lower Yangtze River Plain (MLYP) had less 48.5% Additionally, supplied by permanent demonstrated both those non-permanent permafrost. Further analysis revealed that approximately 20.2% experienced concurrent increase mean whereas around 18.9% simultaneous rise LSWT_mmd LSWA. This suggests is correlated rising temperatures differences. study provides deeper insights into response Chinese change offers important references for resource management ecological conservation.

Язык: Английский

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How Urban Characteristics Impact Surface Urban Heat Island in Subtropical High-Density Cities Based on Lczs: A Case Study of Macau

Опубликована: Янв. 1, 2024

Although numerous studies have explored the influence of urban spatial characteristics (USC) on surface heat island intensity (SUHII) from perspective local climate zone (LCZ), spatio-temporal heterogeneity within and between LCZs has not been demonstrated. In this study, a total 1540 grid units in Macau across 7 years were screened as research samples. USC, SUHII LCZ calculated derived multi-source data. GWR GTWR models applied to detect non-stationarity USC SUHII, Geodetector was used for ranking interpretation strength driving factors each class. Results show that 8 is highest. Besides, model had best fitting degree accounting thermal variations due form changes, regression performance generally different among classes, especially compact-types open-types. Furthermore, strategies related optimization finally proposed class based contribution factors. This study sheds new light "USC-SUHII-LCZ" linkage provides specific planning recommendations environment improvement, subtropical highdensity cities.

Язык: Английский

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Evaluating urban–rural gradients and urban forms in metropolitan areas: a local climate zone approach with future spatial simulation

Sustainable Cities and Society, Год журнала: 2024, Номер 112, С. 105636 - 105636

Опубликована: Июль 2, 2024

Язык: Английский

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