Integrating urban morphology and land surface temperature characteristics for urban functional area classification

References

• Amini, S., S. Homayouni, A. Safari, and A.A. Darvishsefat. 2018. “Object-based Classification of Hyperspectral Data Using Random Forest Algorithm.” Geo-spatial Information Science 21 (2): 127–138. doi:10.1080/10095020.2017.1399674.
   Web of Science ®Google Scholar
• Barnsley, M.J., and S.L. Barr. 1997. “Distinguishing Urban Land-use Categories in Fine Spatial Resolution Land-cover Data Using a Graph-based, Structural Pattern Recognition System.” Computers, Environment and Urban Systems 21: 209–225. doi:10.1016/S0198-9715(97)10001-1.
   Google Scholar
• Bian, X., C. Chen, L. Tian, and Q. Du. 2017. “Fusing Local and Global Features for High-Resolution Scene Classification.” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 10 (6): 2889–2901. doi:10.1109/JSTARS.2017.2683799.
   Web of Science ®Google Scholar
• Blaschke, T. 2010. “Object Based Image Analysis for Remote Sensing.” ISPRS Journal of Photogrammetry and Remote Sensing 65 (1): 2–16. doi:10.1016/j.isprsjprs.2009.06.004.
   Web of Science ®Google Scholar
• Blaschke, T., G.J. Hay, M. Kelly, S. Lang, P. Hofmann, E. Addink, R. Queiroz Feitosa, et al. 2014. “Geographic Object-Based Image Analysis - Towards a New Paradigm.” ISPRS Journal of Photogrammetry and Remote Sensing 87 (100): 180–191. doi:10.1016/j.isprsjprs.2013.09.014.
   PubMedGoogle Scholar
• Boulesteix, A.L., A. Bender, J. Lorenzo Bermejo, and C. Strobl. 2012. “Random Forest Gini Importance Favours SNPs with Large Minor Allele Frequency: Impact, Sources and Recommendations.” Briefings in Bioinformatics 13 (3): 292–304. doi:10.1093/bib/bbr053.
   PubMed Web of Science ®Google Scholar
• Callejas, I. J. A. 2011. “Relationship between Land Use/cover and Surface Temperatures in the Urban Agglomeration of Cuiabá-Várzea Grande, Central Brazil.” Journal of Applied Remote Sensing 5 (1): 053569. doi:10.1117/1.3666044.
   Google Scholar
• Chen, S., W. Lang, X. Li, C. Shen, and Q. Fan. 2018. “Determining the Influence of Building Density on Heat Island Effect Using Baidu Map and Remote Sensing.” Photogrammetric Engineering and Remote Sensing 84 (9): 549–558. doi:10.14358/PERS.84.9.549.
   Web of Science ®Google Scholar
• Chen, X.-L., H.-M. Zhao, P.-X. Li, and Z.-Y. Yin. 2006. “Remote Sensing Image-based Analysis of the Relationship between Urban Heat Island and Land Use/cover Changes.” Remote Sensing of Environment 104 (2): 133–146. doi:10.1016/j.rse.2005.11.016.
   Web of Science ®Google Scholar
• Chen, Z., B. Xu, and B. Devereux. 2014. “Urban Landscape Pattern Analysis Based on 3D Landscape Models.” Applied Geography 55: 82–91. doi:10.1016/j.apgeog.2014.09.006.
   Web of Science ®Google Scholar
• Farabet, C., C. Couprie, L. Najman, and Y. Lecun. 2013. “Learning Hierarchical Features for Scene Labeling.” IEEE Transactions on Pattern Analysis and Machine Intelligence 35 (8): 1915–1929. doi:10.1109/TPAMI.2012.231.
   PubMed Web of Science ®Google Scholar
• Feng, Y., C. Gao, X. Tong, S. Chen, Z. Lei, and J. Wang. 2019a. “Spatial Patterns of Land Surface Temperature and Their Influencing Factors: A Case Study in Suzhou, China.” Remote Sensing 11 (2): 182. doi:10.3390/rs11020182.
   Web of Science ®Google Scholar
• Feng, Y., S. Du, S.W. Myint, and M. Shu. 2019b. “Do Urban Functional Zones Affect Land Surface Temperature Differently? A Case Study of Beijing, China.” Remote Sensing 11 (15): 1802. doi:10.3390/rs11151802.
   Web of Science ®Google Scholar
• Gao, S., K. Janowicz, and H. Couclelis. 2017. “Extracting Urban Functional Regions from Points of Interest and Human Activities on Location-based Social Networks.” Transactions in GIS 21 (3): 446–467. doi:10.1111/tgis.12289.
   Web of Science ®Google Scholar
• Getz, W.M., and D. Saltz. 2008. “A Framework for Generating and Analyzing Movement Paths on Ecological Landscapes.” Proceedings of the National Academy of Sciences 105 (49): 19066–19071. doi:10.1073/pnas.0801732105.
   PubMed Web of Science ®Google Scholar
• Guo, A., J. Yang, X. Xiao, J. Xia, C. Jin, and X. Li. 2020. “Influences of Urban Spatial Form on Urban Heat Island Effects at the Community Level in China.” Sustainable Cities and Society 53: 101972. doi:10.1016/j.scs.2019.101972.
   Web of Science ®Google Scholar
• Guo, G., X. Zhou, Z. Wu, R. Xiao, and Y. Chen. 2016. “Characterizing the Impact of Urban Morphology Heterogeneity on Land Surface Temperature in Guangzhou, China.” Environmental Modelling and Software 84: 427–439. doi:10.1016/j.envsoft.2016.06.021.
   Web of Science ®Google Scholar
• Haashemi, S., Q. Weng, A. Darvishi, and S. Alavipanah. 2016. “Seasonal Variations of the Surface Urban Heat Island in a Semi-Arid City.” Remote Sensing 8 (4): 352. doi:10.3390/rs8040352.
   Web of Science ®Google Scholar
• Hu, T., J. Yang, X. Li, and P. Gong. 2016. “Mapping Urban Land Use by Using Landsat Images and Open Social Data.” Remote Sensing 8 (2): 151. doi:10.3390/rs8020151.
   Web of Science ®Google Scholar
• Huang, X., J. Yang, J. Li, and D. Wen. 2021. “Urban Functional Zone Mapping by Integrating High Spatial Resolution Nighttime Light and Daytime Multi-view Imagery.” ISPRS Journal of Photogrammetry and Remote Sensing 175: 403–415. doi:10.1016/j.isprsjprs.2021.03.019.
   Web of Science ®Google Scholar
• Huang, Xin, Anling Liu, and Jiayi Li. 2021. ”Mapping and analyzing the local climate zones in China’s 32 major cities using Landsat imagery based on a novel convolutional neural network.” Geo-spatial Information Science 24 (4):528–557. doi: 10.1080/10095020.2021.1892459
   Web of Science ®Google Scholar
• Li, T., Y. Xu, and L. Yao. 2021. “Detecting Urban Landscape Factors Controlling Seasonal Land Surface Temperature: From the Perspective of Urban Function Zones.” Environmental Science and Pollution Research 1–16. doi:10.1007/s11356-020-11060-z.
   Web of Science ®Google Scholar
• Liu, W., J. Feddema, L. Hu, A. Zung, and N. Brunsell. 2017a. “Seasonal and Diurnal Characteristics of Land Surface Temperature and Major Explanatory Factors in Harris County, Texas.” Sustainability 9 (12): 2324. doi:10.3390/su9122324.
   Web of Science ®Google Scholar
• Liu, Xiaoping, Jialv He, Yao Yao, Jinbao Zhang, Haolin Liang, Huan Wang, and Ye Hong. 2017. ”Classifying urban land use by integrating remote sensing and social media data.” International Journal of Geographical Information Science 31 (8):1675–1696. doi: 10.1080/13658816.2017.1324976.
   Web of Science ®Google Scholar
• Liu, Y., F. Wang, Y. Xiao, and S. Gao. 2012. “Urban Land Uses and Traffic ‘Source-sink Areas’: Evidence from GPS-enabled Taxi Data in Shanghai.” Landscape and Urban Planning 106 (1): 73–87. doi:10.1016/j.landurbplan.2012.02.012.
   Web of Science ®Google Scholar
• Mangai, U., S. Samanta, S. Das, and P. Chowdhury. 2010. “A Survey of Decision Fusion and Feature Fusion Strategies for Pattern Classification.” IETE Technical Review 27 (4): 293–307. doi:10.4103/0256-4602.64604.
   Web of Science ®Google Scholar
• Menze, B.H., B.M. Kelm, R. Masuch, U. Himmelreich, P. Bachert, W. Petrich, and F.A. Hamprecht. 2009. “A Comparison of Random Forest and Its Gini Importance with Standard Chemometric Methods for the Feature Selection and Classification of Spectral Data.” BMC Bioinformatics 10: 213. doi:10.1186/1471-2105-10-213.
   PubMed Web of Science ®Google Scholar
• Patz, J.A., D. Campbell-Lendrum, T. Holloway, and J.A. Foley. 2005. “Impact of Regional Climate Change on Human Health.” Nature 438 (7066): 310–317. doi:10.1038/nature04188.
   PubMed Web of Science ®Google Scholar
• Portela, C.I., K.G. Massi, T. Rodrigues, and E. Alcântara. 2020. “Impact of Urban and Industrial Features on Land Surface Temperature: Evidences from Satellite Thermal Indices.” Sustainable Cities and Society 56: 102100. doi:10.1016/j.scs.2020.102100.
   Web of Science ®Google Scholar
• Rodriguez-Galiano, V.F., M. Chica-Olmo, F. Abarca-Hernandez, P.M. Atkinson, and C. Jeganathan. 2012a. “Random Forest Classification of Mediterranean Land Cover Using Multi-seasonal Imagery and Multi-seasonal Texture.” Remote Sensing of Environment 121: 93–107. doi:10.1016/j.rse.2011.12.003.
   Web of Science ®Google Scholar
• Rodriguez-Galiano, V.F., B. Ghimire, J. Rogan, M. Chica-Olmo, and J.P. Rigol-Sanchez. 2012b. “An Assessment of the Effectiveness of a Random Forest Classifier for Land-cover Classification.” ISPRS Journal of Photogrammetry and Remote Sensing 67: 93–104. doi:10.1016/j.isprsjprs.2011.11.002.
   Web of Science ®Google Scholar
• Sekertekin, A., and S. Bonafoni. 2020. “Land Surface Temperature Retrieval from Landsat 5, 7, and 8 over Rural Areas: Assessment of Different Retrieval Algorithms and Emissivity Models and Toolbox Implementation.” Remote Sensing 12 (2): 294. doi:10.3390/rs12020294.
   Web of Science ®Google Scholar
• Shahmohamadi, P., A.I. Che-Ani, K.N.A. Maulud, N.M. Tawil, and N.A.G. Abdullah. 2011. “The Impact of Anthropogenic Heat on Formation of Urban Heat Island and Energy Consumption Balance.” Urban Studies Research 2011: 1–9. doi:10.1155/2011/497524.
   Google Scholar
• Shao, Z., P. Tang, Z. Wang, N. Saleem, S. Yam, and C. Sommai. 2020. “BRRNet: A Fully Convolutional Neural Network for Automatic Building Extraction from High-Resolution Remote Sensing Images.” Remote Sensing 12 (6): 1050. doi:10.3390/rs12061050.
   Web of Science ®Google Scholar
• Song, J., S. Du, X. Feng, and L. Guo. 2014. “The Relationships between Landscape Compositions and Land Surface Temperature: Quantifying Their Resolution Sensitivity with Spatial Regression Models.” Landscape and Urban Planning 123: 145–157. doi:10.1016/j.landurbplan.2013.11.014.
   Web of Science ®Google Scholar
• Song, X.P., M.C. Hansen, S.V. Stehman, P.V. Potapov, A. Tyukavina, E.F. Vermote, and J.R. Townshend. 2018. “Global Land Change from 1982 to 2016.” Nature 560 (7720): 639–643. doi:10.1038/s41586-018-0411-9.
   PubMed Web of Science ®Google Scholar
• Strobl, C., A.L. Boulesteix, A. Zeileis, and T. Hothorn. 2007. “Bias in Random Forest Variable Importance Measures: Illustrations, Sources and a Solution.” BMC Bioinformatics 8: 25. doi:10.1186/1471-2105-8-25.
   PubMed Web of Science ®Google Scholar
• Sun, R., Y. Lü, L. Chen, L. Yang, and A. Chen. 2013. “Assessing the Stability of Annual Temperatures for Different Urban Functional Zones.” Building and Environment 65: 90–98. doi:10.1016/j.buildenv.2013.04.001.
   Web of Science ®Google Scholar
• Tu, W., Z. Hu, L. Li, J. Cao, J. Jiang, L. Qiuping, and Q. Li. 2018. “Portraying Urban Functional Zones by Coupling Remote Sensing Imagery and Human Sensing Data.” Remote Sensing 10 (1): 141. doi:10.3390/rs10010141.
   Web of Science ®Google Scholar
• Vanderhaegen, S., and F. Canters. 2017. “Mapping Urban Form and Function at City Block Level Using Spatial Metrics.” Landscape and Urban Planning 167: 399–409. doi:10.1016/j.landurbplan.2017.05.023.
   Web of Science ®Google Scholar
• Vargo, J., B. Stone, D. Habeeb, P. Liu, and A. Russell. 2016. “The Social and Spatial Distribution of Temperature-related Health Impacts from Urban Heat Island Reduction Policies.” Environmental Science & Policy 66: 366–374. doi:10.1016/j.envsci.2016.08.012.
   Web of Science ®Google Scholar
• Wu, H., A. Lin, K.C. Clarke, W. Shi, A. Cardenas-Tristan, and Z. Tu. 2020. “A Comprehensive Quality Assessment Framework for Linear Features from Volunteered Geographic Information.” International Journal of Geographical Information Science 35 (9): 1826–1847. doi:10.1080/13658816.2020.1832228.
   Web of Science ®Google Scholar
• Wu, H., L.-P. Ye, W.-Z. Shi, and K.C. Clarke. 2014. “Assessing the Effects of Land Use Spatial Structure on Urban Heat Islands Using HJ-1B Remote Sensing Imagery in Wuhan, China.” International Journal of Applied Earth Observation and Geoinformation 32: 67–78. doi:10.1016/j.jag.2014.03.019.
   Web of Science ®Google Scholar
• Wu, H., Z. Gui, and Z. Yang. 2020. “Geospatial Big Data for Urban Planning and Urban Management.” Geo-spatial Information Science 23 (4): 273–274. doi:10.1080/10095020.2020.1854981.
   Web of Science ®Google Scholar
• Xing, H., and Y. Meng. 2018. “Integrating Landscape Metrics and Socioeconomic Features for Urban Functional Region Classification.” Computers, Environment and Urban Systems 72: 134–145. doi:10.1016/j.compenvurbsys.2018.06.005.
   Web of Science ®Google Scholar
• Xing, H., and Y. Meng. 2020. “Measuring Urban Landscapes for Urban Function Classification Using Spatial Metrics.” Ecological Indicators 108: 105722. doi:10.1016/j.ecolind.2019.105722.
   Web of Science ®Google Scholar
• Yang, C., Q. Zhan, S. Gao, and H. Liu. 2020. “Characterizing the Spatial and Temporal Variation of the Land Surface Temperature Hotspots in Wuhan from a Local Scale.” Geo-spatial Information Science 23 (4): 327–340. doi:10.1080/10095020.2020.1834882.
   Web of Science ®Google Scholar
• Yao, L., Y. Xu, and B. Zhang. 2019. “Effect of Urban Function and Landscape Structure on the Urban Heat Island Phenomenon in Beijing, China.” Landscape and Ecological Engineering 15 (4): 379–390. doi:10.1007/s11355-019-00388-5.
   Web of Science ®Google Scholar
• Yu, X., X. Guo, and Z. Wu. 2014. “Land Surface Temperature Retrieval from Landsat 8 TIRS—Comparison between Radiative Transfer Equation-Based Method, Split Window Algorithm and Single Channel Method.” Remote Sensing 6 (10): 9829–9852. doi:10.3390/rs6109829.
   Web of Science ®Google Scholar
• Yuan, N.J., Y. Zheng, X. Xie, Y. Wang, K. Zheng, and H. Xiong. 2015. “Discovering Urban Functional Zones Using Latent Activity Trajectories.” IEEE Transactions on Knowledge and Data Engineering 27 (3): 712–725. doi:10.1109/TKDE.2014.2345405.
   Web of Science ®Google Scholar
• Zhang, X., and S. Du. 2015. “A Linear Dirichlet Mixture Model for Decomposing Scenes: Application to Analyzing Urban Functional Zonings.” Remote Sensing of Environment 169: 37–49. doi:10.1016/j.rse.2015.07.017.
   Web of Science ®Google Scholar
• Zhang, X., S. Du, and Q. Wang. 2017. “Hierarchical Semantic Cognition for Urban Functional Zones with VHR Satellite Images and POI Data.” ISPRS Journal of Photogrammetry and Remote Sensing 132: 170–184. doi:10.1016/j.isprsjprs.2017.09.007.
   Web of Science ®Google Scholar
• Zhang, X., P. Xiao, X. Feng, and M. Yuan. 2017. “Separate Segmentation of Multi-temporal High-resolution Remote Sensing Images for Object-based Change Detection in Urban Area.” Remote Sensing of Environment 201: 243–255. doi:10.1016/j.rse.2017.09.022.
   Web of Science ®Google Scholar
• Zhou, S., K. Wang, S. Yang, W. Li, Y. Zhang, B. Zhang, Y. Fu, et al. 2020. “Warming Effort and Energy Budget Difference of Various Human Land Use Intensity: Case Study of Beijing, China.” Land 9 (9): 280. doi:10.3390/land9090280.
   Web of Science ®Google Scholar
• Zhou, W., G. Huang, and M.L. Cadenasso. 2011. “Does Spatial Configuration Matter? Understanding the Effects of Land Cover Pattern on Land Surface Temperature in Urban Landscapes.” Landscape and Urban Planning 102 (1): 54–63. doi:10.1016/j.landurbplan.2011.03.009.
   Web of Science ®Google Scholar
• Wu, Hao, Anqi Lin, Xudong Xing, Danxia Song, and Yan Li. 2021. ”Identifying core driving factors of urban land use change from global land cover products and POI data using the random forest method.” International Journal of Applied Earth Observation and Geoinformation 103:102475. doi: https://doi.org/10.1016/j.jag.2021.102475
   Web of Science ®Google Scholar