remote sensing Article An Improved Cloud Gap-Filling Method for Longwave Infrared Land Surface Temperatures through Introducing Passive Microwave Techniques Thomas P. F. Dowling 1 , Peilin Song 2,* , Mark C. De Jong 1, Lutz Merbold 3,† , Martin J. Wooster 1 , Jingfeng Huang 4 and Yongqiang Zhang 2 1 National Centre for Earth Observation (NCEO), Department of Geography, King’s College London, London WC2B 4BG, UK;
[email protected] (T.P.F.D.);
[email protected] (M.C.D.J.);
[email protected] (M.J.W.) 2 Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, The Chinese Academy of Sciences, Beijing 100101, China;
[email protected] 3 Mazingira Centre, International Livestock Research Institute (ILRI), Nairobi P.O. Box 30709, Kenya;
[email protected] 4 Institute of Applied Remote Sensing and Information Technology, Zhejiang University, Hangzhou 310058, China;
[email protected] * Correspondence:
[email protected] † Now at Agroscope, Research Division Agroecology & Environment, Reckenholzstrasse 191, 8046 Zurich, Switzerland. Abstract: Satellite-derived land surface temperature (LST) data are most commonly observed in the longwave infrared (LWIR) spectral region. However, such data suffer frequent gaps in coverage Citation: Dowling, T.P.F.; Song, P.; caused by cloud cover. Filling these ‘cloud gaps’ usually relies on statistical re-constructions using Jong, M.C.D.; Merbold, L.; Wooster, proximal clear sky LST pixels, whilst this is often a poor surrogate for shadowed LSTs insulated under M.J.; Huang, J.; Zhang, Y. An cloud. Another solution is to rely on passive microwave (PM) LST data that are largely unimpeded Improved Cloud Gap-Filling Method by cloud cover impacts, the quality of which, however, is limited by the very coarse spatial resolution for Longwave Infrared Land Surface typical of PM signals.