Assessing the Impact of Fractional Vegetation Cover on Urban Thermal Environment: A Case Study of Hangzhou, China

[1]  W. Mu,et al.  Impact assessment of urbanization on vegetation net primary productivity: A case study of the core development area in central plains urban agglomeration, China. , 2023, Environmental research.

[2]  Haimeng Liu,et al.  Conflict or Coordination? measuring the relationships between urbanization and vegetation cover in China , 2023, Ecological Indicators.

[3]  Yaochen Qin,et al.  Fostering deep learning approaches to evaluate the impact of urbanization on vegetation and future prospects , 2023, Ecological Indicators.

[4]  Maomao Zhang,et al.  Ventilation analysis of urban functional zoning based on circuit model in Guangzhou in winter, China , 2023, Urban Climate.

[5]  A. Kafy,et al.  Impact of urban expansion on land surface temperature and carbon emissions using machine learning algorithms in Wuhan, China , 2023, Urban Climate.

[6]  Mehmet Çetin,et al.  Using the Remote Sensing Method to Simulate the Land Change in the Year 2030 , 2022, Turkish Journal of Agriculture - Food Science and Technology.

[7]  Mehmet Çetin,et al.  Evaluation from Rural to Urban Scale for the Effect of NDVI-NDBI Indices on Land Surface Temperature, in Samsun, Türkiye , 2022, Turkish Journal of Agriculture - Food Science and Technology.

[8]  Yingbao Yang,et al.  A whale optimization algorithm-based cellular automata model for urban expansion simulation , 2022, Int. J. Appl. Earth Obs. Geoinformation.

[9]  Xiangming Xiao,et al.  Response characteristics and influencing factors of carbon emissions and land surface temperature in Guangdong Province, China , 2022, Urban Climate.

[10]  Likai Zhu,et al.  Assessing progress towards sustainable development goals for Chinese urban land use: A new cloud model approach. , 2022, Journal of environmental management.

[11]  Bin Tong,et al.  Predicting the impacts of urban land change on LST and carbon storage using InVEST, CA-ANN and WOA-LSTM models in Guangzhou, China , 2022, Earth Science Informatics.

[12]  Lei Zhang,et al.  Quantifying the direct effects of long-term dynamic land use intensity on vegetation change and its interacted effects with economic development and climate change in jiangsu, China. , 2022, Journal of environmental management.

[13]  N. Chan,et al.  Urban local surface temperature prediction using the urban gray-green space landscape and vegetation indices , 2022, Building and Environment.

[14]  C. Koo,et al.  Conceptual Sim-Heuristic Optimization Algorithm to Evaluate the Climate Impact on Reservoir Operations , 2022, Journal of Hydrology.

[15]  Jinxing Che,et al.  Unified whale optimization algorithm based multi-kernel SVR ensemble learning for wind speed forecasting , 2022, Appl. Soft Comput..

[16]  M. Khoshbakht,et al.  A clustering review of vegetation-indicating parameters in urban thermal environment studies towards various factors. , 2022, Journal of thermal biology.

[17]  Lei Shao,et al.  Short-Term Load Forecasting Based on EEMD-WOA-LSTM Combination Model , 2022, Applied bionics and biomechanics.

[18]  Ilknur Zeren Cetin,et al.  The effects of climate on land use/cover: a case study in Turkey by using remote sensing data , 2022, Environmental Science and Pollution Research.

[19]  Shukui Tan,et al.  The spatial spillover effect and nonlinear relationship analysis between land resource misallocation and environmental pollution: Evidence from China. , 2022, Journal of environmental management.

[20]  A. Kafy,et al.  Application of the Optimal Parameter Geographic Detector Model in the Identification of Influencing Factors of Ecological Quality in Guangzhou, China , 2022, Land.

[21]  M. Breitner,et al.  Mitigating urban heat with optimal distribution of vegetation and buildings , 2022, Urban Climate.

[22]  M. Cetin,et al.  The assessment of the thermal behavior of an urban park surface in a dense urban area for planning decisions , 2022, Environmental Monitoring and Assessment.

[23]  Ningbo Cui,et al.  Optimized empirical model based on whale optimization algorithm for simulate daily reference crop evapotranspiration in different climatic regions of China , 2022, Journal of Hydrology.

[24]  N. Xu,et al.  Gas Concentration Prediction Based on IWOA-LSTM-CEEMDAN Residual Correction Model , 2022, Sensors.

[25]  Ranae Dietzel,et al.  Estimate soil moisture of maize by combining support vector machine and chaotic whale optimization algorithm , 2022, Agricultural Water Management.

[26]  Heather A. Sander.  Closing four remaining gaps in deploying urban vegetation to enable sustainable cities , 2022, One Earth.

[27]  S. Rahaman,et al.  Identifying the effect of monsoon floods on vegetation and land surface temperature by using Google Earth Engine , 2022, Urban Climate.

[28]  Yongxian Su,et al.  Estimating the cooling effect magnitude of urban vegetation in different climate zones using multi-source remote sensing , 2022, Urban Climate.

[29]  Xiangming Xiao,et al.  Contribution of urban functional zones to the spatial distribution of urban thermal environment , 2022, Building and Environment.

[30]  Muhammad Tauhidur Rahman,et al.  Predicting the impacts of land use/land cover changes on seasonal urban thermal characteristics using machine learning algorithms , 2022, Building and Environment.

[31]  Zihan Liu,et al.  Seasonally disparate responses of surface thermal environment to 2D/3D urban morphology , 2022, Building and Environment.

[32]  Shukui Tan,et al.  Does land transfer promote the development of new-type urbanization? New evidence from urban agglomerations in the middle reaches of the Yangtze River , 2022, Ecological Indicators.

[33]  Fei Chen,et al.  Urbanization Impact on Regional Climate and Extreme Weather: Current Understanding, Uncertainties, and Future Research Directions , 2022, Advances in Atmospheric Sciences.

[34]  A. Kafy,et al.  Simulating the Relationship between Land Use/Cover Change and Urban Thermal Environment Using Machine Learning Algorithms in Wuhan City, China , 2021, Land.

[35]  Jing Zhong,et al.  Assessing the comprehensive impacts of different urbanization process on vegetation net primary productivity in Wuhan, China, from 1990 to 2020 , 2021 .

[36]  Ali Mohammadzadeh,et al.  Spatial and Temporal Analysis of Surface Urban Heat Island and Thermal Comfort Using Landsat Satellite Images between 1989 and 2019: A Case Study in Tehran , 2021, Remote. Sens..

[37]  L. Mentaschi,et al.  Urban heat island mitigation by green infrastructure in European Functional Urban Areas , 2021, Sustainable Cities and Society.

[38]  Ali Akbar Jamali,et al.  Modeling relationship between land surface temperature anomaly and environmental factors using GEE and Giovanni. , 2021, Journal of environmental management.

[39]  Xiangming Xiao,et al.  Influence of urban morphological characteristics on thermal environment , 2021 .

[40]  Yi Luo,et al.  China urbanization process induced vegetation degradation and improvement in recent 20 years , 2021, Cities.

[41]  Shahfahad,et al.  Modelling urban heat island (UHI) and thermal field variation and their relationship with land use indices over Delhi and Mumbai metro cities , 2021, Environment, Development and Sustainability.

[42]  W. Kou,et al.  Assessment of spatial–temporal changes of ecological environment quality based on RSEI and GEE: A case study in Erhai Lake Basin, Yunnan province, China , 2021, Ecological Indicators.

[43]  Peng Huang,et al.  Ecological vulnerability assessment based on AHP-PSR method and analysis of its single parameter sensitivity and spatial autocorrelation for ecological protection – A case of Weifang City, China , 2021 .

[44]  A. Hsu,et al.  Disproportionate exposure to urban heat island intensity across major US cities , 2021, Nature Communications.

[45]  H. Pourghasemi,et al.  Spatial and temporal analysis of urban heat island using Landsat satellite images , 2021, Environmental Science and Pollution Research.

[46]  Shukui Tan,et al.  How do varying socio-economic driving forces affect China’s carbon emissions? New evidence from a multiscale geographically weighted regression model , 2021, Environmental Science and Pollution Research.

[47]  S. Guha,et al.  Annual assessment on the relationship between land surface temperature and six remote sensing indices using landsat data from 1988 to 2019 , 2021, Geocarto International.

[48]  A. Sekertekin,et al.  Simulation of future land surface temperature distribution and evaluating surface urban heat island based on impervious surface area , 2021 .

[49]  Jianqiao Han,et al.  Quantifying the contributions of human activities and climate change to vegetation net primary productivity dynamics in China from 2001 to 2016. , 2021, The Science of the total environment.

[50]  M. Cetin,et al.  Effect of the surface temperature of surface materials on thermal comfort: a case study of Iskenderun (Hatay, Turkey) , 2021, Theoretical and Applied Climatology.

[51]  M. Masoudi,et al.  The effects of land use on spatial pattern of urban green spaces and their cooling ability , 2021 .

[52]  Md. Shahinoor Rahman,et al.  Prediction of seasonal urban thermal field variance index using machine learning algorithms in Cumilla, Bangladesh , 2021 .

[53]  Willyan Ronaldo Becker,et al.  Statistical features for land use and land cover classification in Google Earth Engine , 2020 .

[54]  Wang Xin.  Forecast of photovoltaic generated power based on WOA-LSTM , 2020, 2020 5th International Conference on Mechanical, Control and Computer Engineering (ICMCCE).

[55]  Yichun Xie,et al.  Modeling urban growth sustainability in the cloud by augmenting Google Earth Engine (GEE) , 2020, Comput. Environ. Urban Syst..

[56]  Asaduzzaman,et al.  Low impact development techniques to mitigate the impacts of climate-change-induced urban floods: Current trends, issues and challenges , 2020, Sustainable Cities and Society.

[57]  Lukumon O. Oyedele,et al.  Comparative study of machine learning-based multi-objective prediction framework for multiple building energy loads , 2020 .

[58]  M. Kalubarme,et al.  Monitoring land use changes and its future prospects using cellular automata simulation and artificial neural network for Ahmedabad city, India , 2020, GeoJournal.

[59]  Zhile Yang,et al.  A novel competitive swarm optimized RBF neural network model for short-term solar power generation forecasting , 2020, Neurocomputing.

[60]  D. Rybski,et al.  On the influence of density and morphology on the Urban Heat Island intensity , 2020, Nature Communications.

[61]  Md. Shahinoor Rahman,et al.  Modelling future land use land cover changes and their impacts on land surface temperatures in Rajshahi, Bangladesh , 2020 .

[62]  Dong Liu,et al.  Random forest regression evaluation model of regional flood disaster resilience based on the whale optimization algorithm , 2020 .

[63]  Yi Luo,et al.  Spatial-temporal process simulation and prediction of chlorophyll-a concentration in Dianchi Lake based on wavelet analysis and long-short term memory network , 2020 .

[64]  Xueming Li,et al.  Influences of urban spatial form on urban heat island effects at the community level in China , 2020 .

[65]  Yu Wang,et al.  Remote sensing algorithms for estimation of fractional vegetation cover using pure vegetation index values: A review. , 2020, ISPRS journal of photogrammetry and remote sensing : official publication of the International Society for Photogrammetry and Remote Sensing.

[66]  A. Lin,et al.  Distinguishing the impacts of climate change and anthropogenic factors on vegetation dynamics in the Yangtze River Basin, China , 2020 .

[67]  Deren Li,et al.  Remote sensing monitoring of multi-scale watersheds impermeability for urban hydrological evaluation , 2019, Remote Sensing of Environment.

[68]  Bao-jie He.  Towards the next generation of green building for urban heat island mitigation: Zero UHI impact building , 2019, Sustainable Cities and Society.

[69]  J. Xia,et al.  Local climate zone ventilation and urban land surface temperatures: Towards a performance-based and wind-sensitive planning proposal in megacities , 2019, Sustainable Cities and Society.

[70]  Feng-Min Li,et al.  Impacts of climate change and human activities on grassland vegetation variation in the Chinese Loess Plateau. , 2019, The Science of the total environment.

[71]  S. Malyshev,et al.  Urban heat island: Aerodynamics or imperviousness? , 2019, Science Advances.

[72]  Yutao Wang,et al.  Cities: The core of climate change mitigation , 2019, Journal of Cleaner Production.

[73]  S. Smith,et al.  Influence of evaporative cooling by urban forests on cooling demand in cities , 2019, Urban Forestry & Urban Greening.

[74]  Kevin J. Gaston,et al.  The impact of urbanisation on nature dose and the implications for human health , 2018, Landscape and Urban Planning.

[75]  C. Havas,et al.  Combining machine-learning topic models and spatiotemporal analysis of social media data for disaster footprint and damage assessment , 2018 .

[76]  Bao-Jie He,et al.  Potentials of meteorological characteristics and synoptic conditions to mitigate urban heat island effects , 2018 .

[77]  Edzer Pebesma,et al.  Using Google Earth Engine to detect land cover change: Singapore as a use case , 2018 .

[78]  Gregory Duveiller,et al.  The mark of vegetation change on Earth’s surface energy balance , 2018, Nature Communications.

[79]  Mike Hutchins,et al.  The impacts of urbanisation and climate change on urban flooding and urban water quality: A review of the evidence concerning the United Kingdom , 2017 .

[80]  Ranga B. Myneni,et al.  Climate mitigation from vegetation biophysical feedbacks during the past three decades , 2017 .

[81]  V. C. Broto.  Urban Governance and the Politics of Climate change , 2017 .

[82]  T. Kershaw,et al.  Utilising green and bluespace to mitigate urban heat island intensity. , 2017, The Science of the total environment.

[83]  Alan T. Murray,et al.  Tree shade coverage optimization in an urban residential environment , 2017 .

[84]  H. Akbari,et al.  Three decades of urban heat islands and mitigation technologies research , 2016 .

[85]  Ali Hosseini,et al.  Assessment of Urban Heat Island based on the relationship between land surface temperature and Land Use/ Land Cover in Tehran , 2016 .

[86]  X. Lee,et al.  Urban heat islands in China enhanced by haze pollution , 2015, Nature Communications.

[87]  H. Akbari,et al.  Local climate change and urban heat island mitigation techniques – the state of the art , 2015 .

[88]  Neil Debbage,et al.  The urban heat island effect and city contiguity , 2015, Comput. Environ. Urban Syst..

[89]  Fei Wang,et al.  Spatiotemporal vegetation cover variations associated with climate change and ecological restoration in the Loess Plateau , 2015 .

[90]  W. Klemm,et al.  Street greenery and its physical and psychological impact on outdoor thermal comfort , 2015 .

[91]  Weifeng Li,et al.  Comparing Machine Learning Classifiers for Object-Based Land Cover Classification Using Very High Resolution Imagery , 2014, Remote. Sens..

[92]  N. Mittal,et al.  Mitigating and adapting to climate change: multi-functional and multi-scale assessment of green urban infrastructure. , 2014, Journal of environmental management.

[93]  Xiaolei Yu,et al.  Land Surface Temperature Retrieval from Landsat 8 TIRS - Comparison between Radiative Transfer Equation-Based Method, Split Window Algorithm and Single Channel Method , 2014, Remote. Sens..

[94]  J. Guldmann,et al.  Spatial statistical analysis and simulation of the urban heat island in high-density central cities , 2014 .

[95]  S. Myint,et al.  A comparison of spatial autocorrelation indices and landscape metrics in measuring urban landscape fragmentation , 2014 .

[96]  Elie Bou-Zeid,et al.  Synergistic Interactions between Urban Heat Islands and Heat Waves: The Impact in Cities Is Larger than the Sum of Its Parts* , 2013 .

[97]  P. Gong,et al.  MODIS detected surface urban heat islands and sinks: Global locations and controls , 2013 .

[98]  Steven J. Phillips,et al.  Shifts in Arctic vegetation and associated feedbacks under climate change , 2013 .

[99]  M. Betsill,et al.  Revisiting the urban politics of climate change , 2013 .

[100]  Jinfeng Wang,et al.  Optimal discretization for geographical detectors-based risk assessment , 2013 .

[101]  H. Bulkeley,et al.  A survey of urban climate change experiments in 100 cities , 2013, Global environmental change : human and policy dimensions.

[102]  E. Kalnay,et al.  Impact of urbanization and land-use change on climate , 2003, Nature.