Towards better exploiting object-based image analysis paradigm for local climate zones mapping

[1]  M. Demuzere,et al.  A global map of local climate zones to support earth system modelling and urban-scale environmental science , 2022, Earth System Science Data.

[2]  Lei Ma,et al.  Comparing Object-Based and Pixel-Based Methods for Local Climate Zones Mapping with Multi-Source Data , 2022, Remote. Sens..

[3]  Liang Zhou,et al.  Patch-Based Local Climate Zones Mapping and Population Distribution Pattern in Provincial Capital Cities of China , 2022, ISPRS Int. J. Geo Inf..

[4]  Xiao Xiang Zhu,et al.  The urban morphology on our planet – Global perspectives from space , 2022, Remote sensing of environment.

[5]  Huanfeng Shen,et al.  Coupling Dual Graph Convolution Network and Residual Network for Local Climate Zone Mapping , 2022, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[6]  Minho Kim,et al.  Local climate zone classification using a multi-scale, multi-level attention network , 2021, ISPRS Journal of Photogrammetry and Remote Sensing.

[7]  Pingli An,et al.  Mapping local climate zones and their associated heat risk issues in Beijing: Based on open data , 2021 .

[8]  Thomas Blaschke,et al.  Advances of Local Climate Zone Mapping and Its Practice Using Object-Based Image Analysis , 2021, Atmosphere.

[9]  Xiuyuan Zhang,et al.  Mapping large-scale and fine-grained urban functional zones from VHR images using a multi-scale semantic segmentation network and object based approach , 2021 .

[10]  Steven Jige Quan,et al.  A systematic review of GIS-based local climate zone mapping studies , 2021, Building and Environment.

[11]  Qian Shi,et al.  Local climate zone mapping as remote sensing scene classification using deep learning: A case study of metropolitan China , 2020 .

[12]  Xiao Xiang Zhu,et al.  Multilevel Feature Fusion-Based CNN for Local Climate Zone Classification From Sentinel-2 Images: Benchmark Results on the So2Sat LCZ42 Dataset , 2020, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[13]  S. Sodoudi,et al.  Inter-local climate zone differentiation of land surface temperatures for Management of Urban Heat in Nairobi City, Kenya , 2020 .

[14]  Xingyuan He,et al.  Review of methods used to estimate the sky view factor in urban street canyons , 2020 .

[15]  Dongping Ming,et al.  SO–CNN based urban functional zone fine division with VHR remote sensing image , 2020 .

[16]  Xiao Xiang Zhu,et al.  So2Sat LCZ42: A Benchmark Dataset for Global Local Climate Zones Classification , 2019, ArXiv.

[17]  G. A. Pagani,et al.  Sky view factor calculations and its application in urban heat island studies , 2019, Urban Climate.

[18]  Cheolhee Yoo,et al.  Comparison between convolutional neural networks and random forest for local climate zone classification in mega urban areas using Landsat images , 2019, ISPRS Journal of Photogrammetry and Remote Sensing.

[19]  Iryna Dronova,et al.  Urban Landscape Change Analysis Using Local Climate Zones and Object-Based Classification in the Salt Lake Metro Region, Utah, USA , 2019, Remote. Sens..

[20]  Linda See,et al.  Using OpenStreetMap (OSM) to enhance the classification of local climate zones in the framework of WUDAPT , 2019, Urban Climate.

[21]  Monika Kuffer,et al.  Object-based image analysis to map local climate zones: The case of Bandung, Indonesia , 2019, Applied Geography.

[22]  Benjamin Bechtel,et al.  Mapping Europe into local climate zones , 2019, PloS one.

[23]  Linda See,et al.  Generating WUDAPT Level 0 data – Current status of production and evaluation , 2019, Urban Climate.

[24]  Xiao Xiang Zhu,et al.  Feature Importance Analysis for Local Climate Zone Classification Using a Residual Convolutional Neural Network with Multi-Source Datasets , 2018, Remote. Sens..

[25]  Xiao Xiang Zhu,et al.  Feature Extraction and Selection of Sentinel-1 Dual-Pol Data for Global-Scale Local Climate Zone Classification , 2018, ISPRS Int. J. Geo Inf..

[26]  Swades Pal,et al.  Analyzing control of respiratory particulate matter on Land Surface Temperature in local climatic zones of English Bazar Municipality and Surroundings , 2018, Urban Climate.

[27]  Jungho Im,et al.  Icing Detection over East Asia from Geostationary Satellite Data Using Machine Learning Approaches , 2018, Remote. Sens..

[28]  Naoto Yokoya,et al.  Open Data for Global Multimodal Land Use Classification: Outcome of the 2017 IEEE GRSS Data Fusion Contest , 2018, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[29]  Jungho Im,et al.  Classification and Mapping of Paddy Rice by Combining Landsat and SAR Time Series Data , 2018, Remote. Sens..

[30]  Edward Ng,et al.  GIS-based mapping of Local Climate Zone in the high-density city of Hong Kong , 2017, Urban Climate.

[31]  Frieke Van Coillie,et al.  Influence of neighbourhood information on 'Local Climate Zone' mapping in heterogeneous cities , 2017, Int. J. Appl. Earth Obs. Geoinformation.

[32]  Lei Ma,et al.  Training set size, scale, and features in Geographic Object-Based Image Analysis of very high resolution unmanned aerial vehicle imagery , 2015 .

[33]  Iain Stewart,et al.  Mapping Local Climate Zones for a Worldwide Database of the Form and Function of Cities , 2015, ISPRS Int. J. Geo Inf..

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

[35]  Julien Radoux,et al.  Accounting for the area of polygon sampling units for the prediction of primary accuracy assessment indices , 2014 .

[36]  T. Oke,et al.  Local Climate Zones for Urban Temperature Studies , 2012 .

[37]  P. Levelt,et al.  ESA's sentinel missions in support of Earth system science , 2012 .

[38]  Albert Rango,et al.  International Journal of Applied Earth Observation and Geoinformation a Comparison of Three Feature Selection Methods for Object-based Classification of Sub-decimeter Resolution Ultracam-l Imagery , 2022 .

[39]  Mario Chica-Olmo,et al.  An assessment of the effectiveness of a random forest classifier for land-cover classification , 2012 .

[40]  Christopher A. Barnes,et al.  Completion of the 2006 National Land Cover Database for the conterminous United States. , 2011 .

[41]  Austin Troy,et al.  Object-based land cover classification of shaded areas in high spatial resolution imagery of urban areas: A comparison study , 2009 .

[42]  S. Grimmond.  Urbanization and global environmental change: local effects of urban warming , 2007 .

[43]  Leo Breiman,et al.  Random Forests , 2001, Machine Learning.

[44]  U. Benz,et al.  Multi-resolution, object-oriented fuzzy analysis of remote sensing data for GIS-ready information , 2004 .

[45]  Arno Schäpe,et al.  Multiresolution Segmentation : an optimization approach for high quality multi-scale image segmentation , 2000 .