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The Lenglongling Fault Zone (LLLFZ) is an important left‐lateral strike‐slip tectonic belt in the northeastern Tibetan Plateau (NETP), and the tectonic deformation and seismic activity of the LLLFZ reflect tectonic adjustments of the Qilian‐Haiyuan tectonic zone to the NETP. Although historical records of large earthquakes along the LLLFZ are not available, offset landforms reveal that large earthquakes have occurred. Therefore, offset landforms are used to study the seismic slip distribution to determine a fault slip model and earthquake recurrence behaviour based on an analysis of high‐resolution remote sensing images. Geomorphic markers associated with 316 systematically sinistrally deflected landforms were measured and analysed. The cumulative offset probability densities were analysed according to slip distributions measured along two segments of the fault. Offset density peaks in the eastern section of the fault decay exponentially with increasing offset size, suggesting that approximately seven palaeoearthquakes with an average slip of approximately 8 m occurred during the Holocene. The cumulative slips in the western segment increase gradually from west to east, with single‐event slips of approximately 2–3 m in the western part of the western segment and approximately 5–7 m in the eastern part. The seismic slip distributions of the LLLFZ indicate that the fault conforms to a quasi‐characteristic slip model. Both the eastern and western segments present typical left‐lateral strike‐slip movement. A magnitude of 8.0 was estimated for the LLLFZ palaeoearthquakes that occurred during the Holocene according to empirical relations. This study is helpful for understanding the tectonic deformation of the NETP. [ABSTRACT FROM AUTHOR]

For prediction of urban remote sensing surface temperature, cloud, cloud shadow and snow contamination lead to the failure of surface temperature inversion and vegetation‐related index calculation. A time series prediction framework of urban surface temperature under cloud interference is proposed in this paper. This is helpful to solve the problem of the impact of data loss on surface temperature prediction. Spatial and temporal variation trends of surface temperature and vegetation index are analyzed using Landsat 7/8 remote sensing data of 2010 to 2019 from Beijing. The geographically weighed regression (GWR) method is used to realize the simulation of surface temperature based on the current date. The deep learning prediction network based on convolution and long short‐term memory (LSTM) networks was constructed to predict the spatial distribution of surface temperature on the next observation date. The time series analysis shows that the NDBI is less than −0.2, which indicates that there may be cloud contamination. The land surface temperature (LST) modeling results show that the precision of estimation using GWR method on impervious surface and water bodies is superior compared to the vegetation area. For LST prediction using deep learning methods, the result of the prediction on surface temperature space distribution was relatively good. The purpose of this study is to make up for the missing data affected by cloud, snow, and other interference factors, and to be applied to the prediction of the spatial and temporal distributions of LST. This article is categorized under:Technologies > Machine Learning [ABSTRACT FROM AUTHOR]

Areas with sharp spatial changes in crustal structure are usually considered prone to strong earthquakes, especially late Cenozoic structural zones. However, quantitative relationships have not been established between the occurrence of earthquakes and the extent to which the crustal structure changes. The crustal structure can be reflected by gravity anomalies. In this study, we investigate the crustal structure variation in the eastern Tibetan Plateau based on the gravity data acquired by the Gravity field and steady‐state Ocean Circulation Explorer satellite. The multiscales wavelet decomposition and power spectrum methods are used to analyze the spatial variation of crustal structure at different depths. Based on a fourth‐order wavelet map, four variable factors are constructed to represent the spatial variations of the crustal structure, and their statistical relationship with earthquakes is studied. The results show that the changing rate of the gravity anomalies is significantly positively correlated with the occurrence of earthquakes. Areas of high earthquake hazards are places where the gravity field changes dramatically, usually with a value of 11°–18° for the SLP (slope) index. The assessment efficiency of the SLP increases with the earthquake magnitude. According to the SLP index, several regions are assessed to have a high level of risk for strong earthquakes in the eastern Tibetan Plateau, including the Longmenshan Fault belt, where a Ms8.0 earthquake occurred in 2008, thus demonstrating the promising implications of our method in the earthquake susceptibility assessment. Plain Language Summary: The distribution of earthquake epicenters is uneven in space. At present, it is generally believed that locations with crustal material changes are prone to earthquakes. However, not all earthquakes are distributed in these locations. To answer the questions of how many earthquakes are distributed in these locations and whether these characteristics can be used to predict the locations of earthquakes, we construct some factors based on gravity data and active faults and conduct statistical analyses in this paper. The results show that the greater is the variation in the gravity field, the higher is the frequency of earthquakes. The assessment efficiency of these characteristics increases with the earthquake magnitude. Key Points: Based on the fourth‐order wavelet detail map of gravity, we constructed four quantitative indexes to express the spatial changes in the crustEarthquakes are concentrated in the high‐value region of the slope (SLP) factor, approximately 11°‐18°The earthquake risk assessment efficiency of the SLP increases with the earthquake magnitude [ABSTRACT FROM AUTHOR]

The Yishu fault zone (YSFZ) is the most active fault in eastern China, and it is the location of an M 8.5 earthquake that occurred in 1668. However, topography and landforms in this area have been greatly altered by human activity during the previous three to four decades, which makes assessment of past earthquakes difficult. We therefore used a set of remote sensing images captured in the 1960s to evaluate the single-event and multievent cumulative offsets of streams along the fault. The local landforms have preserved the Holocene seismic offsets well despite the moderately humid climate in which the local landforms have evolved rapidly. Geomorphic markers associated with 401 systematically dextrally offset streams were analyzed and measured. These offset markers are considered to record seismic rupture processes. Cumulative offset probability densities were analyzed according to slip distributions along various subsections of the YSFZ. Four strong paleoearthquakes in addition to the 1668 earthquake were revealed by offset density peaks within the YSFZ, a finding that differs from those of previous studies. The average offset of the 1668 event is approximately 9 m. The cumulative offsets of the other four paleoseismic events are essentially multiples of the latest event. A single event ruptured more than 200 km of discontinuous fault traces. The similarity of the previous five earthquakes implies that rupturing of the YSFZ has followed a characteristic slip model during the Holocene, with a right-lateral slip rate of 2.2-2.6 mm/yr. We expect that the YSFZ is not due for another large earthquake for several thousand years. [ABSTRACT FROM AUTHOR]

The Damxung-Yangbajain rift is one of the most active north-south trending rifts in the south Tibetan Plateau, and it has been playing an important role in accommodating the east-west extension of the Tibetan Plateau. Both stream profiles on the Nyainqentanglha Range adjacent to the northwest part of the Damxung-Yangbajain rift and tectonic geomorphology in the north of the rift are analyzed to assess the spatial pattern and intensity of rock uplift which is related to neotectonic activity. A total of 85 stream profiles across the Nyainqentanglha Range are analyzed, and 111 knickpoints are interpreted. Most of these stream profiles are characterized by prominent convexities with two or more knickpoints, many of which are formed due to the strong rock uplift evidenced by abnormal concavity and extremely high steepness indices during the Quaternary. Neotectonic activity in this region is well replicated in the stream profile indices and offset landforms. Tectono-geomorphic analysis shows that the concavity and steepness indices correlate with the fault movements at many places. The Damxung-Yangbajain rift is characterized by left-lateral strike-slip in the north of Damxung and by normal movement in middle and southern parts. The middle and southern parts have been undergoing higher uplift than has the northern area. It is most likely that the strong uplift is related to the heat flow under the crust. Earthquakes occurring in the Damxung-Yangbajain rift, including a M8 in 1411 and M6.6 in 2008, are thought to be related to heat flow activity. All of the stream profile indices and tectonic geomorphology show that the Damxung-Yangbajain rift is not in a stable state. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]