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Apatite Fission-Track Thermochronology in the Tamusu Area,Bayingobi Basin,NW China,and its Geological Significance

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Acta Geologica Sinica(English Edition) 2024年第3期98卷 585-601页

作者： TONG Qinlong QIN Mingkuan YE Fawang CNNC Beijing Research institute of Uranium Geology National Key Laboratory of Remote Sensing Information and Image Analysis TechnologyBeijing 100029China

The Bayingobi basin is located in the middle of Central Asia Orogenic Belt,at the intersection of Paleo-Asian Ocean and Tethys Ocean,as well as the junction of multiple tectonic plates.This unique tectonic setting underpins the basin's intricate history of tectonic activity.To unravel the multifaceted tectono-thermal evolution within the southwestern region of the basin and to elucidate the implications of sandstone-hosted uranium mineralization,granitic and clastic rock samples were collected from the Zongnai Mts.uplift and Yingejing depression,and apatite fission track(AFT)dating and thermal history simulation analysis were performed.AFT dating findings reveal that the apparent ages of all samples fall within the range of 244 Ma to 112 Ma.In particular,the bedrock of the Zongnai Mts.and Jurassic detrital apatite fission tracks have undergone complete annealing,capturing the uplift-cooling age.Meanwhile,the AFT ages of Cretaceous detrital rocks are either equivalent to or notably exceed the age of sedimentary strata,signifying the cooling age of the provenance.A comprehensive examination of AFT ages and palaeocurrent direction analyses suggests that the Cretaceous source in the Tamusu area predominantly originated from the central and southern sectors of the Zongnai Mts.uplift.However,at a certain juncture during the Late Early Cretaceous,the Cretaceous provenance expanded to include the northern part of the Zongnai Mts.uplift.Based on the results of thermal history simulations and previous studies,it is considered that the Tamusu area has undergone four distinct tectonic uplift events since the Late Paleozoic.The first is the Late Permian to Early Triassic(260-240 Ma),which is associated with the closure of the Paleo-Asian Ocean and the accretionary orogeny within the Alxa region.The second uplift event took place in the Early Jurassic(190-175 Ma)and corresponded to intraplate orogeny following the closure of the Paleo-Asian Ocean.The third uplift event is the Late Jurassic to Early Cretaceous(160-120 Ma),which

关键词： apatite fission-track tectono-thermal history sandstone-hosted uranium deposit Bayingobi basin Central Asian Orogenic Belt

Monitoring Surface Deformation Using Distributed Scatterers InSAR

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Journal of Geodesy and Geoinformation Science 2024年第1期7卷 42-58页

作者： LI Haocheng DONG Jie WANG Yi’an LIAO Mingsheng State Key Laboratory of information Engineering in Surveying Mapping and Remote SensingWuhan UniversityWuhan 430079China School of remote sensing and information Engineering Wuhan UniversityWuhan 430079China

In the past two decades,extensive and in-depth research has been conducted on Time Series InSAR technology with the advancement of high-performance SAR satellites and the accumulation of big SAR data.The introduction of distributed scatterers in Distributed Scatterers InSAR(DS-InSAR)has significantly expanded the application scenarios of InSAR geodetic measurement by increasing the number of measurement points.This study traces the history of DS-InSAR,presents the definition and characteristics of distributed scatterers,and focuses on exploring the relationships and distinctions among proposed algorithms in two crucial steps:statistically homogeneous pixel selection and phase optimization.Additionally,the latest research progress in this field is tracked and the possible development direction in the future is discussed.Through simulation experiments and two real InSAR case studies,the proposed algorithms are compared and verified,and the advantages of DS-InSAR in deformation measurement practice are demonstrated.This work not only offers insights into current trends and focal points for theoretical research on DS-InSAR but also provides practical cases and guidance for applied research.

关键词： InSAR permanent scatterers distributed scatterers statistically homogeneous pixel selection phase optimization

Spatial identification and evaluation of rural vitality from a function-element-flow perspective: Evidence of Lin'an district in Hangzhou, China

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Journal of Geographical Sciences 2024年第6期34卷 1228-1250页

作者： ZHANG Jing GUAN Chenyue ZHANG Lin YU Zhoulu YE Chengxuan ZHU Congmou LI Sinan WANG Ke GAN Muye institute of applied remote sensing and information technology College of Environmental and Resource SciencesZhejiang UniversityHangzhou 310058China Zhejiang Key Research Laboratory of Agricultural remote sensing and information technology Hangzhou 310058China Shandong(Linyi)institute of Modern Agriculture Linyi 276000ShandongChina Huzhou Spatial Planning Preparation and Research Center Huzhou 313000ZhejiangChina Zhejiang Digital Governance Space Planning and Design Co. Ltd.Hangzhou 310000China Department of Land Resources Management Zhejiang Gongshang UniversityHangzhou 310018China

Rural vitality is the life force expressed by a combination of endogenous dynamics and external influences. Exploring the complex relationship between rural functions, elements and flows could achieve sustainable rural development. This study constructed a theoretical framework guided by the four functions of production, living, ecology and culture with the support of mobile big data. Furthermore, the network centrality of villages was estimated to reflect the intensity of urban-rural social mobility ties. The results indicated marked spatial disparities in rural vitality, and the coupling of ecological-cultural vitality has a high degree of coherence. Four rural vitality grades were identified: high level(38, 14.08%), medium-high level(66, 24.44%), medium-low level(110, 40.74%) and low level(56, 20.74%), covering 270 administrative village units. The flow intensity of social linkage elements is consistent with rural vitality and the socioeconomic spillover effect of urban centers on neighboring villages was noticeable. Topographic complexity negatively affected the living function, mainly in the T1 and T2 terrain gradients;the rural ecological function was not fully correlated with urban adjacency, and proximity could lead to adverse effects such as urban sprawl and resource destruction. The application of this study is to explore the importance of “flow” by utilizing mobile big data to refine the evaluation unit to the village scale. Accelerating the construction of network coverage and information interconnection and promoting the elemental flow of people, transportation and information between urban and rural areas are important ways to enhance rural vitality.

关键词： rural vitality rural multifunction elements urban-rural flows mobile big data

Thickness dependence of superconductivity in layered GeP_(5)

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Rare Metals 2024年第3期43卷 1323-1328页

作者： Lin Wu Ke-Meng Yang Wei Gan Rui-Chun Xiao Ya-Jie Dai Xi Tang Hong Lin Hui Han Hui Li information Materials and Intelligent sensing Laboratory of Anhui Province Institute of Physical Science and Information TechnologyAnhui UniversityHefei230601China

Understanding the relationship between dimensionality and superconductivity has attracted substantial research interest.In this work,we report the effective modulation of superconductivity in GeP_(5)through dimensionality.The superconducting phase transition temperature improves by~10%as the thickness of GeP_(5)decreases from bulk to~96 nm,behaving as a unique negative relationship between the superconducting phase transition temperatureand thickness.

关键词： superconductivity dimensionality

Improved simulation of winter wheat yield in North China Plain by using PRYM-Wheat integrated dry matter distribution coefficient

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Journal of Integrative Agriculture 2024年第4期23卷 1381-1392页

作者： Xuan Li Shaowen Wang Yifan Chen Danwen Zhang Shanshan Yang Jingwen Wang Jiahua Zhang Yun Bai Sha Zhang Research Center for remote sensing and Digital Earth College of Computer Science and TechnologyQingdao UniversityQingdao266071China Center for Geospatial information Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen 518055China School of Geographical Sciences Hebei Normal UniversityShijiazhuang 050024China

The accurate simulation of regional-scale winter wheat yield is important for national food security and the balance of grain supply and demand in China.Presently,most remote sensing process models use the“biomass×harvest index(HI)”method to simulate regional-scale winter wheat yield.However,spatiotemporal differences in HI contribute to inaccuracies in yield simulation at the regional scale.Time-series dry matter partition coefficients(Fr)can dynamically reflect the dry matter partition of winter wheat.In this study,Fr equations were fitted for each organ of winter wheat using site-scale data.These equations were then coupled into a process-based and remote sensingdriven crop yield model for wheat(PRYM-Wheat)to improve the regional simulation of winter wheat yield over the North China Plain(NCP).The improved PRYM-Wheat model integrated with the fitted Fr equations(PRYM-Wheat-Fr)was validated using data obtained from provincial yearbooks.A 3-year(2000-2002)averaged validation showed that PRYM-Wheat-Fr had a higher coefficient of determination(R^(2)=0.55)and lower root mean square error(RMSE=0.94 t ha^(-1))than PRYM-Wheat with a stable HI(abbreviated as PRYM-Wheat-HI),which had R^(2) and RMSE values of 0.30 and 1.62 t ha^(-1),respectively.The PRYM-Wheat-Fr model also performed better than PRYM-Wheat-HI for simulating yield in verification years(2013-2015).In conclusion,the PRYM-Wheat-Fr model exhibited a better accuracy than the original PRYM-Wheat model,making it a useful tool for the simulation of regional winter wheat yield.

关键词： dry matter partition remote sensing model winter wheat yield North China Plain

Data error propagation in stacked bioclimatic envelope models

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Integrative Zoology 2024年第2期19卷 262-276页

作者： Xueyan LI Babak NAIMI Peng GONG Miguel B.ARAÚJO Guangdong Provincial Key Laboratory of remote sensing and Geographical information System Guangdong Open Laboratory of Geospatial Information Technology and ApplicationGuangzhou Institute of GeographyGuangdong Academy of ScienceGuangzhouChina ‘Rui Nabeiro’Biodiversity Chair CHANGE-MED InstituteUniversity ofÉvoraÉvoraPortugal Department of Geography and Department of Earth Sciences University of Hong KongHong KongChina Department of Biogeography and Global Change National Museum of Natural SciencesCSICMadridSpain

Stacking is the process of overlaying inferred species potential distributions for multiple species based on outputs of bioclimatic envelope models(BEMs).The approach can be used to investigate patterns and processes of species richness.If data limitations on individual species distributions are inevitable,but how do they affect inferences of patterns and processes of species richness?We investigate the influence of different data sources on estimated species richness gradients in China.We fitted BEMs using species distributions data for 334 bird species obtained from(1)global range maps,(2)regional checklists,(3)museum records and surveys,and(4)citizen science data using presence-only(Mahalanobis distance),presence-background(MAXENT),and presence–absence(GAM and BRT)BEMs.Individual species predictions were stacked to generate species richness gradients.Here,we show that different data sources and BEMs can generate spatially varying gradients of species richness.The environmental predictors that best explained species distributions also differed between data sources.Models using citizen-based data had the highest accuracy,whereas those using range data had the lowest accuracy.Potential richness patterns estimated by GAM and BRT models were robust to data uncertainty.When multiple data sets exist for the same region and taxa,we advise that explicit treatments of uncertainty,such as sensitivity analyses of the input data,should be conducted during the process of modeling.

关键词： richness patterns species distribution stacked bioclimatic envelope models uncertainty

Spatiotemporal changes of gross primary productivity and its response to drought in the Mongolian Plateau under climate change

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Journal of Arid Land 2024年第1期16卷 46-70页

作者： ZHAO Xuqin LUO Min MENG Fanhao SA Chula BAO Shanhu BAO Yuhai College of Geographical Science Inner Mongolia Normal UniversityHohhot 010022China Inner Mongolia Key Laboratory of remote sensing and Geographic information Systems Hohhot 010022China

Gross primary productivity(GPP)of vegetation is an important constituent of the terrestrial carbon sinks and is significantly influenced by drought.Understanding the impact of droughts on different types of vegetation GPP provides insight into the spatiotemporal variation of terrestrial carbon sinks,aiding efforts to mitigate the detrimental effects of climate change.In this study,we utilized the precipitation and temperature data from the Climatic Research Unit,the standardized precipitation evapotranspiration index(SPEI),the standardized precipitation index(SPI),and the simulated vegetation GPP using the eddy covariance-light use efficiency(EC-LUE)model to analyze the spatiotemporal change of GPP and its response to different drought indices in the Mongolian Plateau during 1982-2018.The main findings indicated that vegetation GPP decreased in 50.53% of the plateau,mainly in its northern and northeastern parts,while it increased in the remaining 49.47%area.Specifically,meadow steppe(78.92%)and deciduous forest(79.46%)witnessed a significant decrease in vegetation GPP,while alpine steppe(75.08%),cropland(76.27%),and sandy vegetation(87.88%)recovered well.Warming aridification areas accounted for 71.39% of the affected areas,while 28.53% of the areas underwent severe aridification,mainly located in the south and central regions.Notably,the warming aridification areas of desert steppe(92.68%)and sandy vegetation(90.24%)were significant.Climate warming was found to amplify the sensitivity of coniferous forest,deciduous forest,meadow steppe,and alpine steppe GPP to drought.Additionally,the drought sensitivity of vegetation GPP in the Mongolian Plateau gradually decreased as altitude increased.The cumulative effect of drought on vegetation GPP persisted for 3.00-8.00 months.The findings of this study will improve the understanding of how drought influences vegetation in arid and semi-arid areas.

关键词： gross primary productivity(GPP) climate change warming aridification areas drought sensitivity cumulative effect duration(CED) Mongolian Plateau

Improving model performance in mapping cropland soil organic matter using time-series remote sensing data

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Journal of Integrative Agriculture 2024年第8期 2820-2841页

作者： Xianglin Zhang Jie Xue Songchao Chen Zhiqing Zhuo Zheng Wang Xueyao Chen Yi Xiao Zhou Shi institute of applied remote sensing and information technology College of Environmental and Resource Sciences Zhejiang University Department of Land Management Zhejiang University ZJU-Hangzhou Global Scientific and Technological Innovation Center Zhejiang University institute of Digital Agriculture Zhejiang Academy of Agricultural Sciences Key Laboratory of Spectroscopy sensing Ministry of Agriculture and Rural Affairs

Faced with increasing global soil degradation, spatially explicit data on cropland soil organic matter（SOM）provides crucial data for soil carbon pool accounting, cropland quality assessment and the formulation of effective management policies. As a spatial information prediction technique, digital soil mapping（DSM） has been widely used to spatially map soil information at different scales. However, the accuracy of digital SOM maps for cropland is typically lower than for other land cover types due to the inherent difficulty in precisely quantifying human disturbance. To overcome this limitation, this study systematically assessed a framework of “information extractionfeature selection-model averaging” for improving model performance in mapping cropland SOM using 462 cropland soil samples collected in Guangzhou, China in 2021. The results showed that using the framework of dynamic information extraction, feature selection and model averaging could efficiently improve the accuracy of the final predictions（R2: 0.48 to 0.53） without having obviously negative impacts on uncertainty. Quantifying the dynamic information of the environment was an efficient way to generate covariates that are linearly and nonlinearly related to SOM, which improved the R2of random forest from 0.44 to 0.48 and the R2of extreme gradient boosting from 0.37to 0.43. Forward recursive feature selection（FRFS） is recommended when there are relatively few environmental covariates（500）. The Granger-Ramanathan model averaging approach could improve the prediction accuracy and average uncertainty.When the structures of initial prediction models are similar, increasing in the number of averaging models did not have significantly positive effects on the final predictions. Given the advantages of these selected strategies over information extraction, feature selection and model averaging have a great potential for high-accuracy soil mapping at any scales, so this approach

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Unraveling adaptive changes in electric vehicle charging behavior toward the postpandemic era by federated meta-learning

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The Innovation 2024年第2期5卷 21-23页

作者： Linlin You Rui Zhu Mei-Po Kwan Min Chen Fan Zhang Bisheng Yang Man Sing Wong Zheng Qin School of Intelligent Systems Engineering Sun Yat-Sen UniversityShenzhen 518107China institute of High Performance Computing(IHPC) Agency for ScienceTechnology and Research(A*STAR)1 Fusionopolis WaySingapore 138632Republic of Singapore institute of Space and Earth information Science Chinese University of Hong KongHong KongChina Key Laboratory of Virtual Geographic Environment(Ministry of Education) Nanjing Normal UniversityNanjing 210023China institute of remote sensing and Geographical information System School of Earth and Space SciencesPeking UniversityBeijing 100871China State Key Laboratory of information Engineering in Surveying Mappingand Remote SensingWuhan UniversityWuhan 430079China Department of Land Surveying and Geo-Informatics The Hong Kong Polytechnic UniversityHong KongChina

Dear Editor,Electric vehicle(EV)sales have significantly grown over the years to fulfill growing demands for economic travel and greenhouse gas mitigation.1 However,the surge in the number of EVs has led to charging anxiety as users struggle to find an available charging station before running out of electricity,resulting in longer reserve and waiting times.2 Moreover,severe mobility restrictions caused by infectious diseases,such as coronavirus disease 2019(COVID-19),have greatly affected people’s travel behavior3,4 and hindered their willingness to use EVs,given that charging in public spaces consumes time and increases the risk of contracting the virus.5 This implies that in the postpandemic era,in which individuals coexist with the virus,the interplay between the two important trends,namely vehicle electrification and mobility restrictions,can extensively affect people’s daily commuting by using EVs.

关键词： travel behavior charging