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Spatial modeling: On disaggregation of remotely sensed land surface temperature (DLST)
[1] Dong, P., Gao, L., Zhan, W.*, Liu, Z., Li, J., Lai, J., Li, H., Huang, F., Tamang, S. K., & Zhao, L. Global comparison of diverse scaling factors and regression models for downscaling Landsat-8 thermal data. ISPRS Journal of Photogrammetry and Remote Sensing, 2020, 169, 44-56.
[2] Gao, L., Zhan, W.*, Huang, F., Quan, J., Lu, X., Wang, F., Ju, W., Zhou, J. Localization or globalization? Determination of the optimal regression window for disaggregation of land surface temperature. IEEE Transactions on Geoscience and Remote Sensing, 2017, 55(1), 477-490.
[3] Tetralogy-IV: Gao, L., Zhan, W.*, Huang, F., Zhu, X., Zhou, J., Quan, J., Du, P., Li, M. Disaggregation of remotely sensed land surface temperature: A simple yet flexible index (SIFI) to assess method performances. Remote Sensing of Environment, 2017, 200, 206–219.
[4] Tetralogy-III: Zhan, W., Huang, F., Quan, J., Zhu, X., Gao, L., Zhou, J., Ju, W. Disaggregation of remotely sensed land surface temperature: A new dynamic methodology. Journal of Geophysical Research – Atmospheres, 2016, 121(18), 10391–11153. doi: 10.1002/2016JD024891.
[5] Tetralogy-II: Chen, Y., Zhan, W.*, Quan, J., Zhou, J., Zhu, X., Sun, H. Disaggregation of remotely sensed land surface temperature: A generalized paradigm. IEEE Transactions on Geoscience and Remote Sensing, 2014, 52(9), 5952-5965.
[6] Tetralogy-I: Zhan, W., Chen, Y., Zhou, J., Wang, J., Liu, W., Voogt, J., Zhu, X., Quan, J., Li, J. Disaggregation of remotely sensed land surface temperature: Literature survey, taxonomy, issues, and caveats. Remote Sensing of Environment, 2013, 131, 119-139.
[7] Prequel-III: Zhan, W., Chen, Y., Wang, J. F., Zhou, J., Quan, J., Liu, W., Li, J. Downscaling land surface temperatures through multi-spectral and multi-resolution bands. International Journal of Applied Earth Observation and Geo-information, 2012, 18, 23-36.
[8] Prequel-II: Zhan, W., Chen, Y., Zhou, J., Li, J., Liu, W. Sharpening thermal imageries: a generalized theoretical framework from an assimilation perspective. IEEE Transactions on Geoscience and Remote Sensing, 2011, 49(2), 773-789.
[9] Prequel-I: Zhan, W., Chen, Y., Zhou, J., Li, J. An algorithm for separating soil and vegetation temperatures with sensors featuring a single thermal channel. IEEE Transactions on Geoscience and Remote Sensing, 2011, 49(5), 1796-1809.
l Temporal modeling: On interpolation (or extrapolation) of temporally discrete surface or subsurface temperatures
[10] Hong, F., Zhan, W.*, Göttsche, F. M., Lai, J., Liu, Z., Hu, L., Fu, P., Huang, F., Li, J., Li, Hu., & Wu, H. A simple yet robust framework to estimate accurate daily mean land surface temperature from thermal observations of tandem polar orbiters. Remote Sensing of Environment, 2021, in press.
[11] Liu, Z., Zhan, W.*, Lai, J., Hong, F., Quan, J., Bechtel, B., Huang, F., Zou, Z. Balancing prediction accuracy and generalization ability: A hybrid framework for modelling the annual dynamics of satellite-derived land surface temperatures. ISPRS Journal of Photogrammetry and Remote Sensing, 2019, 151, 189-206.
[12] Hong, F., Zhan, W.*, Göttsche, F.-M., Liu, Z., Zhou, J., Huang, F., Lai, J., Li, M. Comprehensive assessment of four-parameter diurnal land surface temperature cycle models under clear-sky. ISPRS Journal of Photogrammetry and Remote Sensing, 2018, 142, 190–204.
[13] Zou, Z., Zhan, W.*, Liu, Z., Bechtel, B., Gao, L., Hong, F., Huang, F., Lai, J. Enhanced modeling of annual temperature cycle with temporally discrete remotely sensed thermal observations. Remote Sensing, 2018, 10(4), 650; https://doi.org/10.3390/rs10040650.
[14] Lu, Y., Zhan, W.*, Hu, C. Detecting and quantifying oil slick thickness by thermal remote sensing: A ground-based experiment. Remote Sensing of Environment, 2016, 181, 207–217.
[15] Huang, F., Zhan, W.*, Ju, W., Wang, Z. Improved reconstruction of soil thermal field using two-depth measurements of soil temperature. Journal of Hydrology, 2014, 519, 711–719.
[16] Huang, F., Zhan, W.*, Duan, S.-B., Ju, W., Quan, J. A generic framework for modeling diurnal land surface temperatures with remotely sensed thermal observations under clear sky. Remote Sensing of Environment, 2014, 150, 140–151.
[17] Zhan, W., Zhou, J., Ju, W., Li, M., Sandholt, I., Voogt, J., & Yu, C. Remotely sensed soil temperatures beneath snow-free skin-surface using thermal observations from tandem polar-orbiting satellites: An analytical three-time-scale model. Remote Sensing of Environment, 2014, 143, 1-14.
[18] Zhan, W., Chen, Y., Voogt, J., Zhou, J., Wang, J., Liu, W., Ma, W. Interpolating diurnal surface temperatures of an urban facet using sporadic thermal observations. Building and Environment, 2012, 57, 239-252.
l Angular modeling: On urban thermal anisotropy
[19] Jiang, L., Zhan, W.*, Hu, L., Huang, F., Hong, F., Liu, Z., Lai, J., & Wang, C. Assessment of different kernel-driven models for daytime urban thermal radiation directionality simulation. Remote Sensing of Environment, 2021, 263, 112562.
[20] Jiang, L., Zhan, W.*, Voogt, J. A., Zhao, L., Gao, L., Huang, F., Cai, Z., & Ju, W. Remote estimation of complete urban surface temperature using only directional radiometric temperatures. Building and Environment, 2018, 135, 224–236.
[21] Zhan, W., Chen, Y., Voogt, J. A., Zhou, J., Wang, J., Ma, W., Liu, W. Assessment of thermal anisotropy on remote estimation of urban thermal inertia. Remote Sensing of Environment, 2012, 123, 12–24.
[22] Zhan, W., Chen, Y., Ma, W., Zhou, J., Li, J. FOV effect analysis in directional brightness temperature observations for urban targets. Journal of Remote Sensing, 2010, 14(2), 379-386. [占文凤, 陈云浩, 马伟, 周纪. 城市目标方向亮温观测的视场效应分析. 遥感学报, 2010, 14(2), 379-386.]
[23] Zhan, W., Zhou, J., Ma, W. Computer simulation of land surface thermal anisotropy based on realistic structure model: A review. Advances in Earth Science, 2009, 24(12), 1309-1317. [占文凤, 周纪, 马伟. 基于真实结构的地表热辐射方向性计算机模拟研究进展. 地球科学进展, 2009, 24(12), 1309-1317.]
l On urban heat island and related
[24] Li, J., Zhan, W.*, Hong, F., Lai, J., Dong, P., Liu, Z., Wang, C., Huang, F., Li, L., Wang, C., Fu, Y., & Miao, S. Similarities and disparities in urban local heat islands responsive to regular-, stable-, and counter-urbanization: A case study of Guangzhou, China. Building and Environment, 2021, 199, 107935.
[25] Lai, J., Zhan, W.*, Quan, J., Bechtel, B., Wang, K., Zhou, J., Huang, F., Chakraborty, T., Liu, Z., & Lee. Statistical estimation of next-day nighttime surface urban heat islands. ISPRS Journal of Photogrammetry and Remote Sensing, 2021, 176, 182-195.
[26] Lai, J., Zhan, W.*, Voogt, J. A., Quan, J., Huang, F., Zhou, J., Bechtel, B., Hu, L., Wang, K., Cao, C., & Lee, X. Meteorological controls on daily variations of nighttime surface urban heat islands. Remote Sensing of Environment, 2021, 253, 112198, https://doi.org/10.1016/j.rse.2020.112198.
[27] Jiang, S., Zhan, W.*, Yang, J., Liu, Z., Huang, F., Lai, J., Li, J., Hong, F., Huang, Y., Chen, J., & Lee, X. Urban heat island studies based on local climate zones: A systematic overview. Acta Geographica Sinica, 2020, 75(9), 1860-1878. [江斯达, 占文凤, 杨俊, 刘紫涵, 黄帆, 赖佳梦, 李久枫, 洪发路, 黄媛, 陈吉科, 李旭辉. 局地气候分区框架下城市热岛时空分异特征研究进展. 地理学报, 2020, 75(9), 1860-1878.]
[28] Wang, C., Zhan, W.*, Liu, Z., Li, J., Li, L., Fu, P., Huang, F., Lai, J., Chen, J., Hong, F., & Jiang, S. Satellite-based mapping of the universal thermal climate index over the Yangtze River Delta Urban Agglomeration. Journal of Cleaner Production, 2020, 277, 123830, https://doi.org/10.1016/j.jclepro.2020.123830.
[29] Huang, F., Zhan, W. F.*, Wang, Z.-H., Voogt, J. A., Hu, L. Q., Quan, J. L., Liu, C., Zhang, N., & Lai, J. Satellite identification of atmospheric-surface-subsurface urban heat islands under clear sky. Remote Sensing of Environment, 2020, 250, 112039, https://doi.org/10.1016/j.rse.2020.112039.
[30] Lai, J., Zhan, W.*, Huang, F., Voogt, J., Bechtel, B., Allen, M., Peng, S., Hong, F., Liu, Y., & Du, P.* Identification of typical diurnal patterns for clear-sky climatology of surface urban heat islands. Remote Sensing of Environment, 2018, 217, 203-220.
[31] Zou, Z., Huang, F., Lai, J., Liu, Z., Zhan, W.* Impacts of temporal upscaling methods on calculation of surface urban heat island intensity. Geography and Geographical Information Science, 2018, 34(3), 26-31. [邹照旭, 黄帆, 赖佳梦, 刘紫涵, 占文凤*. 时间升尺度方法对城市地表热岛强度计算的影响研究. 地理与地理信息科学, 2018, 34(3), 26-31.]
[32] Lai, J., Zhan, W.*, Huang, F., Quan, J., Hu, L., Gao, L., Ju, W. Does quality control matter? Surface urban heat island intensity variations estimated by satellite-derived land surface temperature products. ISPRS Journal of Photogrammetry and Remote Sensing, 2018, 139, 212–227.
[33] Huang, F., Zhan, W.*, Wang, Z., Wang, K., Chen, J. M., Liu, Y., Lai, J., Ju, W. Positive or negative? urbanization-induced variations in diurnal skin-surface temperature range detected using satellite data. Journal of Geophysical Research – Atmospheres, 2017, 122(24), 13229–13244. doi:10.1002/2017JD027021.
[34] Fang, M., Ju, W.*, Zhan, W.*, Cheng, T., Qiu, F., & Wang, J. A new spectral similarity water index for the estimation of leaf water content from hyperspectral data of leaves. Remote Sensing of Environment, 2017, 196, 13–27.
[35] Zhou, Y., Jiang, L., Lu, Y.*, Zhan, W.*, Mao, Z., Qian, W., & Liu, Y. Thermal infrared contrast between different types of oil slicks on top of water bodies. IEEE Geoscience and Remote Sensing Letters, 2017, 14(7), 1042-1045.
[36] Fang, Y., Zhan, W.*, Huang, F., Gao, L., Quan, J., & Zou, Z. Hourly variation of surface urban heat island over the Yangtze River Delta urban agglomeration. Advances in Earth Science, 2017, 32(2), 187-198, doi:10.11867/j.issn.1001-8166.2017.02.0187. [方迎波, 占文凤, 黄帆, 高伦, 全金玲, 邹照旭. 长三角城市群表面城市热岛日内逐时变化规律. 地球科学进展, 2017, 32(2), 187-198.]
[37] Huang, F., Zhan, W.*, Voogt, J. A., Hu, L., Wang, Z., Quan, J., Ju, W., & Guo, Z. Temporal upscaling of surface urban heat island by incorporating an annual temperature cycle model: A tale of two cities. Remote Sensing of Environment, 2016, 186, 1−12, doi: 10.1016/j.rse.2016.08.009.
[38] Zhan, W., Ju, W., Hai, S., Ferguson, G., Quan, J., Tang, C., Guo, Z., Kong, F. Satellite-derived subsurface urban heat island. Environmental Science & Technology, 2014, 48, 12134−12140.
[39] Zhan, W., Chen, Y., Zhou, J., Li, J. Spatial simulation of urban heat island intensity based on the support vector machine technique: A case study in Beijing. Acta Geodaetica et Cartographica Sinica, 2011, 40(1), 96-103. [占文凤, 陈云浩, 周纪, 李京. 基于支持向量机的北京城市热岛模拟—热岛强度空间格局曲面模拟及其应用. 测绘学报, 2011, 40(1), 96-103.]
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