Mapping urban night lights at a fine spatial resolution: downscaling VIIRS using geographically weighted area-to-point regression Kriging
Nikolaos Tziokas
Lancaster Environment Centre, Lancaster University, Lancaster LA1 4YQ, UK
Lancaster Environment Centre, Lancaster University, Lancaster LA1 4YQ, UK
Garyfallos Chrysovalantis Drolias
Lancaster Environment Centre, Lancaster University, Lancaster LA1 4YQ, UK
Peter M. Atkinson
Lancaster Environment Centre, Lancaster University, Lancaster LA1 4YQ, UK
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Zhige Wang, Ce Zhang, Kejian Shi, Yulin Shangguan, Bifeng Hu, Xueyao Chen, Danqing Wei, Songchao Chen, Peter M. Atkinson, and Qiang Zhang
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-315, https://doi.org/10.5194/essd-2024-315, 2024
Preprint under review for ESSD
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The irreversible trend in global warming underscores the necessity for accurate monitoring of atmospheric carbon dynamics on a global scale. This study generated a global dataset of column-averaged dry-air mole fraction of CO2 (XCO2) at 0.05° resolution with full coverage using carbon satellite data and a deep learning model. The dataset accurately depicts global and regional XCO2 patterns, advancing the monitoring of carbon emissions and understanding of global carbon dynamics.
C. Chen, C. Zhang, B. Tian, and Y. Zhou
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-3-2022, 375–381, https://doi.org/10.5194/isprs-annals-V-3-2022-375-2022, https://doi.org/10.5194/isprs-annals-V-3-2022-375-2022, 2022
Diarmuid Corr, Amber Leeson, Malcolm McMillan, Ce Zhang, and Thomas Barnes
Earth Syst. Sci. Data, 14, 209–228, https://doi.org/10.5194/essd-14-209-2022, https://doi.org/10.5194/essd-14-209-2022, 2022
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We identify 119 km2 of meltwater area over West Antarctica in January 2017. In combination with Stokes et al., 2019, this forms the first continent-wide assessment helping to quantify the mass balance of Antarctica and its contribution to global sea level rise. We apply thresholds for meltwater classification to satellite images, mapping the extent and manually post-processing to remove false positives. Our study provides a high-fidelity dataset to train and validate machine learning methods.
J. Murray, I. Sargent, D. Holland, A. Gardiner, K. Dionysopoulou, S. Coupland, J. Hare, C. Zhang, and P. M. Atkinson
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B5-2020, 185–189, https://doi.org/10.5194/isprs-archives-XLIII-B5-2020-185-2020, https://doi.org/10.5194/isprs-archives-XLIII-B5-2020-185-2020, 2020
Zhaofei Wen, Hong Yang, Changhong Ding, Ce Zhang, Guofan Shao, Jilong Chen, Mingquan Lv, Shengjun Wu, and Zhenfeng Shao
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2019-69, https://doi.org/10.5194/hess-2019-69, 2019
Preprint withdrawn
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The environmental effects of the world's largest Three Gorges Dam (TGD) have been received worldwide attentions. It is the first dynamics monitoring of mid-channel bars (MCBs) in the downstream of TGD at large spatiotemporal scale. The study shows most of the MCBs are located in the lower reach. Small MCBs become shorter and wider whereas the others became slimmer in post-TGD period. Impacts from the TGD operation on the MCB dynamics could decrease along with the increasing distance from TGD.
C. Zhang, X. Pan, S. Q. Zhang, H. P. Li, and P. M. Atkinson
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W7, 1451–1454, https://doi.org/10.5194/isprs-archives-XLII-2-W7-1451-2017, https://doi.org/10.5194/isprs-archives-XLII-2-W7-1451-2017, 2017