Cross-Load Fault Diagnosis Via Time-Frequency Multi-Scale Network
In: COGROB-D-24-00015
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In: COGROB-D-24-00015
SSRN
In: Remote Sensing ; Volume 7 ; Issue 11 ; Pages 15224-15243
During the 2014 Asia-Pacific Economic Cooperation (APEC) Economic Leaders' Meetings in Beijing, the Chinese government made significant efforts to clear Beijing's sky. The emission control measures were very effective and the improved air quality during the APEC Meetings was called the "APEC Blue". To monitor and estimate how these emission control measures affected air quality in Beijing and its five neighboring large cities (Tianjin, Shijiazhuang, Tangshan, Jinan, and Qingdao), we compared and analyzed the satellite-retrieved Aerosol Optical Thickness (AOT) products of the pre-APEC (18–31 October), APEC (1–11 November), and post-APEC periods (11–31 November) in 2002–2014 and daily PM2.5 measurements of the three periods in 2014 on the ground. Compared with the pre- and post-APEC periods, both ground and satellite observations indicated significantly reduced aerosol loading during the 2014 APEC period in Beijing and its surroundings, but with apparent spatial heterogeneity. For example, the peak value of PM2.5 in Beijing were around 100 µg∙m−3 during the APEC period, however, during the pre- and post-APEC periods, the peak values were up to 290 µg∙m−3. The following temporal correlation analysis of mean AOT values between Beijing and other five cities for the past thirteen years (2002–2014) indicated that the potential emission source regions strongly impacting air quality of Beijing were confined within central and southern Hebei as well as northern and southwestern Shandong, in correspondence with the spatial pattern of Digital Earth Model (DEM) of the study region. In addition to stringent emission control measures, back trajectory analysis indicated that the relatively favorable regional transport pattern might also have contributed to the "APEC Blue" in Beijing. These results suggest that the "APEC Blue" is a temporarily regional phenomenon ; a long-term improvement of air quality in Beijing is still challenging and joint efforts of the whole region are needed.
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In: COGROB-D-24-00032
SSRN
In: TAL-D-22-03275
SSRN
In: Computers and electronics in agriculture: COMPAG online ; an international journal, Band 224, S. 109232
ISSN: 1872-7107
Satellite observations of Amazon forests show seasonal and interannual variations, but the underlying biological processes remain debated. Here we combined radiative transfer models (RTMs) with field observations of Amazon forest leaf and canopy characteristics to test three hypotheses for satellite-observed canopy reflectance seasonality: seasonal changes in leaf area index, in canopy-surface leafless crown fraction and/or in leaf demography. Canopy RTMs (PROSAIL and FLiES), driven by these three factors combined, simulated satellite-observed seasonal patterns well, explaining c. 70% of the variability in a key reflectance-based vegetation index (MAIAC EVI, which removes artifacts that would otherwise arise from clouds/aerosols and sun–sensor geometry). Leaf area index, leafless crown fraction and leaf demography independently accounted for 1, 33 and 66% of FLiES-simulated EVI seasonality, respectively. These factors also strongly influenced modeled near-infrared (NIR) reflectance, explaining why both modeled and observed EVI, which is especially sensitive to NIR, captures canopy seasonal dynamics well. Our improved analysis of canopy-scale biophysics rules out satellite artifacts as significant causes of satellite-observed seasonal patterns at this site, implying that aggregated phenology explains the larger scale remotely observed patterns. This work significantly reconciles current controversies about satellite-detected Amazon phenology, and improves our use of satellite observations to study climate–phenology relationships in the tropics. No claim to original US Government works New Phytologist © 2017 New Phytologist Trust
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