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Research Article

Impact of land transformation processes in Eastern China on the long-term development of land surface temperatures

, , ORCID Icon, , &
Article: 2322063 | Received 26 Dec 2023, Accepted 16 Feb 2024, Published online: 28 Feb 2024

References

  • An H, Cai H, Xu X, Qiao Z, Han D., 2022. Impacts of urban green space on land surface temperature from urban block perspectives. Rem Sens. 14(18):4580. doi:10.3390/rs14184580.
  • Asgarian A, Amiri BJ, Sakieh Y. 2015. Assessing the effect of green cover spatial patterns on urban LSTs using landscape metrics approach. Urban Ecosyst. 18(1):209–222. doi:10.1007/s11252-014-0387-7.
  • Barman S, Roy D, Chandra Sarkar B, Almohamad H, Abdo HG. 2024. Assessment of urban growth in relation to urban sprawl using landscape metrics and Shannon’s entropy model in Jalpaiguri urban agglomeration, West Bengal, India. Geocarto Int. 39(1):2306258. doi:10.1080/10106049.2024.2306258.
  • Chen Y, Yang J, Yu W, Ren J, Xiao X, Xia JC. 2023. Relationship between urban spatial form and seasonal land surface temperature under different grid scales. Sustainable Cities and Soc. 89:104374. doi:10.1016/j.scs.2022.104374.
  • Dash P, Göttsche F-M, Olesen F-S, Fischer H. 2002. Land surface temperature and emissivity estimation from passive sensor data: theory and practice-current trends. Int J Remote Sens. 23(13):2563–2594. doi:10.1080/01431160110115041.
  • Du C, Jia W, Chen M, Yan L, Wang K. 2022. How can urban parks be planned to maximize cooling effect in hot extremes? Linking maximum and accumulative perspectives. J Environ Management. 317:115346.
  • Fida GT, Baatuuwie BN, Issifu H. 2024. Potential impact of future land use/cover dynamics on the habitat quality of the Yayo Coffee Forest Biosphere Reserve, southwestern Ethiopia. Geocarto Int. 39(1):2278327. doi:10.1080/10106049.2023.2278327.
  • Friedl MA, McIver DK, Hodges JCF, Zhang XY, Muchoney D, Strahler AH, Woodcock CE, Gopal S, Schneider A, Cooper A, et al. 2002. Global land cover mapping from MODIS: algorithms and early results. Remote Sens Environ. 83(1–2):287–302. doi:10.1016/S0034-4257(02)00078-0.
  • Gillies RR, Carlson TN. 1995. Thermal remote sensing of surface soil water content with partial vegetation cover for incorporation into climate models. J Appl Meteor. 34(4):745–756. doi:10.1175/1520-0450(1995)034<0745:TRSOSS>2.0.CO;2.
  • Guo A, Yang J, Sun W, Xiao X, Xia Cecilia J, Jin C, Li X. 2020. Impact of urban morphology and landscape characteristics on spatiotemporal heterogeneity of land surface temperature. Sustainable Cities and Soc. 63:102443. doi:10.1016/j.scs.2020.
  • Han D, Xu X, Qiao Z, Wang F, Cai H, An H, Jia K, Liu Y, Sun Z, Wang S, et al. 2023. Roles of surrounding 2D/3D landscapes in park cooling effect: analysis from extreme hot and normal weather perspectives. Build Environ. 231:110053. doi:10.1016/j.buildenv.2023.
  • Hansen J, Ruedy R, Sato M, Lo K. 2010. Global surface temperature change. Rev Geophys. 48(4):RG4004. doi:10.1029/2010RG000345.
  • Huang GL, Cadenasso ML. 2016. People, landscape, and urban heat island: dynamics among neighborhood social conditions, land cover and surface temperatures. Landscape Ecol. 31(10):2507–2515. doi:10.1007/s10980-016-0437-z.
  • Kotharkar R, Surawar M. 2016. Land use, land cover, and population density impact on the formation of canopy urban heat islands through traverse survey in the Nagpur urban area, India. J Urban Plann Dev. 142:1. doi:10.1061/(ASCE)UP.1943-5444.0000277.
  • Li JX, Song CH, Cao L, Zhu FG, Meng XL, Wu JG. 2011. Impacts of landscape structure on surface urban heat islands: a case study of Shanghai, China. Remote Sens Environ. 115(12):3249–3263. doi:10.1016/j.rse.2011.07.008.
  • Liu YX, Wu CY, Peng DL, Xu SG, Gonsamo A, Jassal RS, Arain MA, Lu LL, Fang B, Chen JM. 2016. Improved modeling of land surface phenology using MODIS land surface reflectance and temperature at evergreen needleleaf forests of central North America. Remote Sens Environ. 176:152–162. doi:10.1016/j.rse.2016.01.021.
  • Luintel N, Ma W, Ma Y, Wang B, Subba S., 2019. Spatial and temporal variation of daytime and nighttime MODIS land surface temperature across Nepal. Atmos Oceanic Sci Lett. 12(5):305–312. doi:10.1080/16742834.2019.1625701.
  • Neteler M. 2010. Estimating daily LSTs in mountainous environments by reconstructed MODIS LST data. Remote Sens. 2(1):333–351. doi:10.3390/rs1020333.
  • Peng J, Jia J, Liu Y, Li H, Wu J. 2018. Seasonal contrast of the dominate factors for spatial distribution of land surface temperature in urban areas. Remote Sens Environ. 215:255–267. doi:10.1016/j.rse.2018.06.010.
  • Prata AJ, Caselles V, Coll C, Sobrino JA, Ottlé C. 1995. Thermal remote sensing of land surface temperature from satellites: current status and future prospects. Remote Sens Rev. 12(3–4):175–224. doi:10.1080/02757259509532285.
  • Qiao Z, Tian GJ, Xiao L. 2013. Diurnal and seasonal impacts of urbanization on the urban thermal environment: a case study of Beijing using MODIS data. ISPRS, J Photogrammetr Remote Sens. 85:93–101. doi:10.1016/j.isprsjprs.2013.08.010.
  • Tuholske C, Caylor K, Funk C, Verdin A, Sweeney S, Grace K, Peterson P, Evans T. 2021. Global urban population exposure to extreme heat. Proc Natl Acad Sci U S A. 118(41):e2024792118. doi:10.1073/pnas.2024792118.
  • Wan Z, Zhang Y, Zhang Q, Li ZL. 2004. Quality assessment and validation of the MODIS global land surface temperature. Int J Remote Sens. 25(1):261–274. doi:10.1080/0143116031000116417.
  • Yang J, Yang Y, Sun D, Jin C, Xiao X., 2021. Influence of urban morphological characteristics on thermal environment. Sustainable Cities and Soc. 72:103045. doi:10.1016/j.scs.2021.103045.
  • Ye X, Ren H, Liu R, Qin Q, Liu Y, Dong J. 2017. Land surface temperature estimate from Chinese Gaofen-5 satellite data using split-window algorithm. Transac Geosci Remote Sens. 55(10):5877–5888. doi:10.1016/j.rse.2003.11.005.
  • Zhang R, Yang J, Ma X, Xiao X, Xia J. 2023. Optimal allocation of local climate zones based on heat vulnerability perspective. Sustainable Cities and Soc. 99:104981. doi:10.1016/j.scs.2023.104981.
  • Zhou WQ, Wang J, Cadenasso ML. 2017. Effects of the spatial configuration of trees on urban heat mitigation: a comparative study. Remote Sens Environ. 195:1–12. doi:10.1016/j.rse.2017.03.043.
  • Zhou ZG. 2018. Analysis of evolution characteristics of Nanchang’s ecological spatial landscape pattern based on RS and GIS. China: Jiangxi Normal University; p. 1–55.