Building a climate-adaptative city: A study on the optimization of thermal vulnerability

Journal of Cleaner Production, Год журнала: 2025, Номер unknown, С. 144768 - 144768

Опубликована: Янв. 1, 2025

Язык: Английский

---

Slum and urban deprivation in compacted and peri-urban neighborhoods in sub-Saharan Africa

Sustainable Cities and Society, Год журнала: 2023, Номер 99, С. 104863 - 104863

Опубликована: Авг. 15, 2023

Язык: Английский

---

A multimodal fusion framework for urban scene understanding and functional identification using geospatial data

International Journal of Applied Earth Observation and Geoinformation, Год журнала: 2024, Номер 127, С. 103696 - 103696

Опубликована: Фев. 2, 2024

Urban scene understanding and functional identification are essential for accurately characterizing the spatial structure optimizing city layouts during rapid urbanization. Multimodal data is important recognizing distribution patterns of urban functions revealing internal details. Previous studies have focused primarily on remote sensing imagery points interest (POIs) data, overlooking role building characteristics in determining scenes. These also limited terms mining fusing multimodal features. To address these challenges, this study proposes a fusion framework that integrates imagery, POIs, footprints mapping. The employs dual-branch model extracts visual semantic features from socioeconomic auxiliary such as POIs footprints. A branch attention module designed to assign weights Additionally, multiscale feature introduced extract combine through modal interaction. Experiments Beijing Chengdu validate effectiveness proposed with overall accuracy 90.04% 92.07%, kappa coefficient 0.881 0.895, respectively. This provides empirical evidence support accurate planning further promote sustainable development. source code at: https://github.com/sssuchen/MMFF.

Язык: Английский

---

Application and future of local climate zone system in urban climate assessment and planning—Bibliometrics and meta-analysis

Cities, Год журнала: 2024, Номер 150, С. 104999 - 104999

Опубликована: Апрель 14, 2024

Язык: Английский

---

Exploration of Influencing Factors of Land Surface Temperature in Cities Within the Beijing–Tianjin–Hebei Region Based on Local Climate Zone Scheme

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Год журнала: 2024, Номер 17, С. 9728 - 9744

Опубликована: Янв. 1, 2024

Clarifying the factors that influence land surface temperature (LST) is crucial for proposing specific LST mitigation strategies. This study focuses on Beijing-Tianjin-Hebei (BTH) Region and investigates influencing of various local climate zone (LCZ) built types from perspectives urban morphology, cover, human activity. The results suggest areas LCZ vary across cities within BTH Region, attributed to differences in city size Gross Domestic Product (GDP). area Beijing Tianjin, with significantly high sizes GDP, exceeds 2000 km2. In contrast, Qinhuangdao, Zhangjiakou Chengde, which have relatively low this less than 500 However, main same type are highly consistent. Building coverage ratio (BCR), average building height (ABH) pervious fraction (PSF) three most important factors. correlation between BCR mainly concentrated compact high-rise open types, Pearson coefficient (r) ranging 0.2 0.44; ABH high-rise, mid-rise, mid-rise r -0.2 -0.52; PSF almost all -0.56. By integrating these findings features each strategies were further proposed. can help develop context Coordinated Development thereby promoting healthy sustainable development region.

Язык: Английский

---

A transferable approach to assessing green infrastructure types (GITs) and their effects on surface urban heat islands with multi-source geospatial data

Remote Sensing of Environment, Год журнала: 2024, Номер 306, С. 114119 - 114119

Опубликована: Март 21, 2024

Язык: Английский

---

Mapping urban form into local climate zones for the continental US from 1986–2020

Scientific Data, Год журнала: 2024, Номер 11(1)

Опубликована: Фев. 13, 2024

Abstract Urbanization has altered land surface properties driving changes in micro-climates. Urban form influences people’s activities, environmental exposures, and health. Developing detailed unified longitudinal measures of urban is essential to quantify these relationships. Local Climate Zones [LCZ] are a culturally-neutral classification scheme. To date, LCZ maps at large scales (i.e., national, continental, or global) not available. We developed an approach map LCZs for the continental US from 1986 2020 100 m spatial resolution. lightweight contextual random forest models using hybrid model development pipeline that leveraged crowdsourced expert labeling cloud-enabled modeling – could be generalized other countries continents. Our achieved good performance: 0.76 overall accuracy (0.55–0.96 class-wise F1 scores). our knowledge, this first high-resolution, US. work may useful variety fields including earth system science, planning, public

Язык: Английский

---

Effective Factors for Reducing Land Surface Temperature in Each Local Climate Zone Built Type in Tokyo and Shanghai

Remote Sensing, Год журнала: 2023, Номер 15(15), С. 3840 - 3840

Опубликована: Авг. 1, 2023

Identifying the main factors influencing land surface temperature (LST) of each local climate zone (LCZ) built type is great significance for controlling LST. This study investigated LST LCZ in two Asian megacities: Tokyo and Shanghai. Each area both megacities was classified according to scheme. The diurnal LST, pervious fraction (PSF), albedo (SA), average building height (⟨BH⟩), gross coverage ratio (λp) were also calculated. Finally, influence properties on investigated. results demonstrated that different types differed ⟨BH⟩ factor compact mid-rise open high-rise Tokyo, Shanghai; PSF other types. Moreover, negatively correlated with Based above characteristics type, specific mitigation strategies proposed approach this can contribute perspectives urban planners policymakers develop highly feasible reasonable strategies.

Язык: Английский

---

Heat risk assessment and response to green infrastructure based on local climate zones

Building and Environment, Год журнала: 2023, Номер 248, С. 111040 - 111040

Опубликована: Ноя. 17, 2023

Язык: Английский

---

Local Climate Zone Mapping by Coupling Multilevel Features With Prior Knowledge Based on Remote Sensing Images

IEEE Transactions on Geoscience and Remote Sensing, Год журнала: 2024, Номер 62, С. 1 - 14

Опубликована: Янв. 1, 2024

Local climate zone (LCZ) mapping can explore the variability of impact urban form on thermal environment in different contexts, and large-scale LCZ help us to better understand spatial temporal dynamics areas around world. Studies have indicated that deep learning-based methods effectively perform classification. However, accuracy classification datasets is still unsatisfactory, mainly due fact traditional convolutional neural networks are not good at mining contextual information, which crucial for fully understanding remote sensing scenes. In this paper, solve problem, we propose an method based images by coupling multi-level features mined from global local ranges with prior knowledge, named LCZ-MFKNet. The extracted through Swin Transformer space-maintained ResNet (SM-ResNet) model branches, respectively, then fused improved squeeze-and-excitation (iSE) module. knowledge studied theoretical definition experimental tests two typical sets categories easily confounded multi-class but separable two-class Experiments conducted large publicly available So2Sat LCZ42 dataset, where proposed LCZ-MFKNet achieved highest accuracy. Moreover, six megacities were selected globally mapping, results verified general applicability mapping.

Язык: Английский

---