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Imported risk in global financial markets: Evidence from cross-market connectedness

NORTH AMERICAN JOURNAL OF ECONOMICS AND FINANCE 2025年 76卷

作者： Ouyang, Zisheng Chen, Zhen Zhou, Xuewei Ouyang, Zhongzhe Hunan Normal Univ Business Sch Changsha 410081 Hunan Peoples R China Hunan Normal Univ Sch Business Hunan Key Lab Macroecon Big Data Min & Its Applica Changsha 410081 Hunan Peoples R China Hunan Normal Univ Sch Math & Stat Changsha 410081 Hunan Peoples R China Shanghai Univ Finance & Econ Sch Finance Shanghai 200433 Peoples R China Shanghai Inst Int Finance & Econ Shanghai 200433 Peoples R China Guangzhou Univ Sch Econ & Stat Guangzhou 510006 Guangdong Peoples R China

We propose a cross-market connectedness network, including stock market layer and foreign exchange market layer in the spillover index method for investigating imported risk in global financial markets. In addition, we explore the topology of the cross-market connectedness network at the system and market layers. We also identify the key drivers of global risk spillovers by constructing the systemic importance indicator. Meanwhile, we examine the impact of global economic policy uncertainty, geopolitical risks, and external financial conditions on imported risk of international financial markets. Our results show that risk contagion in the stock market is more pronounced than in the foreign exchange market. Furthermore, we note that advanced markets are the main recipients of global imported risk, with the Netherlands, the EU and France being the most strongly shocked to external risks. Finally, the determinants analysis suggests that geopolitical risks significantly increase imported risk in global stock markets, while external financial conditions have a driving effect on risk spillovers in foreign exchange markets.

关键词： Spillover index method Imported risk Risk measurement Influencing factors

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integrating NTL intensity and Building Volume to Improve the Built-Up Areas' Extraction from SDGSAT-1 GLI data

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REMOTE SENSING 2024年第13期16卷 2278页

作者： Liu, Shaoyang Wang, Congxiao Wu, Bin Chen, Zuoqi Zhang, Jiarui Huang, Yan Wu, Jianping Yu, Bailang East China Normal Univ Key Lab Geog Informat Sci Minist Educ Shanghai 200241 Peoples R China East China Normal Univ Sch Geog Sci Shanghai 200241 Peoples R China Minist Nat Resources Key Lab Spatial Temporal Big Data Anal & Applicat Shanghai 200241 Peoples R China Sun Yat Sen Univ Sch Geospatial Engn & Sci Zhuhai 519082 Peoples R China Minist Nat Resources Key Lab Urban Land Resources Monitoring & Simulat Shenzhen 518060 Peoples R China Fuzhou Univ Natl & Local Joint Engn Res Ctr Satellite Geospati Key Lab Spatial Data Min & Informat Sharing Minist Educ Fuzhou 350108 Peoples R China Fuzhou Univ Acad Digital China Fuzhou 350108 Peoples R China

Urban built-up areas are the main space carrier of population and urban activities. It is of great significance to accurately identify urban built-up area for monitoring urbanization dynamics and their impact on Sustainable Development Goals. Using only nighttime light (NTL) remote sensing data will lead to omission phenomena in urban built-up area extraction, especially for SDGSAT-1 glimmer imager (GLI) data with high spatial resolution. Therefore, this study proposed a novel nighttime Lights integrate Building Volume (LitBV) index by integrating NTL intensity information from SDGSAT-1 GLI data and building volume information from Digital Surface Model (DSM) data to extract built-up areas more accurately. The results indicated that the LitBV index achieved remarkable results in the extraction of built-up areas, with the overall accuracy of 81.25%. The accuracy of the built-up area extraction based on the LitBV index is better than the results based on only NTL data and only building volume. Moreover, experiments at different spatial resolutions (10 m, 100 m, and 500 m) and different types of NTL data (SDGSAT-1 GLI data, Luojia-1 data, and NASA's Black Marble data) showed that the LitBV index can significantly improve the extraction accuracy of built-up areas. The LitBV index has a good application ability and prospect for extracting built-up areas with high-resolution SDGSAT-1 GLI data.

关键词： SDGSAT-1 built-up area nighttime light remote sensing building volume sustainable development goals

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Vegetation descriptors from Sentinel-1 SAR data for crop growth monitoring

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ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING 2023年第1期203卷 86-114页

作者： Bao, Xin Zhang, Rui Lv, Jichao Wu, Renzhe Zhang, Hongsheng Chen, Jie Zhang, Bo Ouyang, Xiaoying Liu, Guoxiang Southwest Jiaotong Univ Fac Geosci & Environm Engn Chengdu 610031 Peoples R China Southwest Jiaotong Univ State Prov Joint Engn Lab Spatial Informat Technol Chengdu 61003 Peoples R China Univ Hong Kong Dept Geog Hong Kong 999077 Peoples R China Chinese Acad Sci Northwest Inst Ecoenvironm & Resources State Key Lab Cryospher Sci Cryosphere Res Stn Qinghai Tibet Plateau Lanzhou 730000 Gansu Peoples R China Chinese Acad Sci Inst Mt Hazards & Environm IMHE Chengdu 610299 Peoples R China Int Res Ctr Big Data Sustainable Dev Goals CBAS Beijing 100094 Peoples R China Chinese Acad Sci Aerosp Informat Res Inst AIR Key Lab Digital Earth Sci Beijing 100094 Peoples R China

Synthetic aperture radar (SAR) remote sensing technology has the advantage of all-weather observation and can acquire time-series images with crop growth period, which has great potential for applications such as crop phenology analysis. However, available studies primarily focus on conducting statistical and crop growth analyses based on the polarization or backscatter intensities of SAR images, and the exploration of polarization scattering information in SAR images is not sufficient. To comprehensively reflect the polarization characteristics and scattering mechanisms of crop at different growth stages, we propose a new method for extracting vegetation descriptors from Sentinel-1 dual-polarimetric SAR data. The method combines the backscattering intensity and polarization decomposition information to construct a normalized index q, which is used to generate three vegetation descriptors: the co-pol purity parameter (mcp), the pseudo-scattering angle (t9cp), and the pseudoscattering entropy (Hcp). Further, a novel unsupervised clustering framework, founded on Hcp and t9cp, has been proposed. This framework establishes six zones (named as Z1 to Z6) representing distinct physical scattering mechanisms, and by statistically sampling point data, it can determine the growth stage of the crops For validating the performance of the proposed vegetation descriptors and clustering framework, we conducted a three-year experiment using four crops from two publicly available datasets, namely wheat and canola from the Carman in Canada (Test site-1), corn and soybeans from Iowa in the United States (Test site-2). The experimental results indicate that mcp,t9cp, and Hcp exhibit regular changes at different growth stages of crops from planting to maturity, with mcp and t9cp gradually decreasing while Hcp gradually increasing. Within the entire phenology window, t9cp changes by approximately 42 degrees, while both mcp and t9cp varies by about 0.9, and the sampling points shift from

关键词： Sentinel-1 Vegetation descriptors Dual-polarization Unsupervised classification Crop growth

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Deephullnet: a deep learning approach for solving the convex hull and concave hull problems with transformer

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intERNATIONAL JOURNAL OF DIGITAL EARTH 2024年第1期17卷

作者： Liang, Haojian Wang, Shaohua Gao, Song Li, Huilai Su, Cheng Lu, Hao Zhang, Xueyan Chen, Xi Chen, Yinan Chinese Acad Sci Aerosp Informat Res Inst Key Lab Remote Sensing & Digital Earth Beijing Peoples R China Jilin Univ Sch Artificial Intelligence Changchun Peoples R China Chinese Acad Sci Int Res Ctr Big Data Sustainable Dev Goals Beijing Peoples R China Univ Wisconsin Dept Geog Madison WI USA Jilin Univ Sch Math Changchun Peoples R China SuperMap Software Co Ltd Beijing Peoples R China Univ Southern Calif Viterbi Sch Engn Los Angeles CA USA UCL Bartlett Ctr Adv Spatial Anal London England South China Univ Technol Sch Business Adm Guangzhou Peoples R China 9 Dengzhuang South Rd Beijing 100094 Peoples R China

Convex and concave hulls originating from computational geometry are widely applied in practice. For instance, to determine the boundaries of a geographical area within a group of cities, convex hulls can represent the approximate boundaries of the areas. Concave hulls can accurately describe the shape of the area. The traditional methods for solving two-dimensional convex hull problems include the Jarvis March algorithm and the Graham scanning algorithm. The K-nearest neighbours and alpha-shape methods are designed for solving the concave hull problem. Other than traditional algorithms, we consider using deep neural networks to handle the convex and concave hull problems. General neural networks cannot deal with the problem whose output is a variable-length sequence. Our study provides a machine-learning approach for solving the convex hull and concave hull problems. We combine the Pointer network (Ptr-Net) with the Transformer model and propose the DeepHullNet. The trained DeepHullNet can provide a feasible solution in the majority of cases. The experimental results show that DeepHullNet outperforms the original Ptr-Net regarding accuracy. Compared with traditional methods, DeepHullNet can generate a good solution quickly, and the running time is shortened by nearly 100 times based on GPU.

关键词： Convex hull problem concave hull problem deep learning transformer GeoAI

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Research on the Application of User Recommendation Based on the Fusion Method of spatially Complex Location Similarity

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COMPLEXITY 2021年第1期2021卷

作者： Wang, Lili Shi, Ting Li, Shijin Chongqing Finance & Econ Coll Big Data Integrat Ecol & Environm Chongqing Key Lab Spatial Data Min Chongqing 401320 Peoples R China Yunnan Business Informat Engn Sch Kunming 677000 Yunnan Peoples R China Yunnan Univ Finance & Econ Acad Affairs Off Kunming 650221 Yunnan Peoples R China

Since the user recommendation complex matrix is characterized by strong sparsity, it is difficult to correctly recommend relevant services for users by using the recommendation method based on location and collaborative filtering. The similarity measure between users is low. This paper proposes a fusion method based on KL divergence and cosine similarity. KL divergence and cosine similarity have advantages by comparing three similar metrics at different K values. Using the fusion method of the two, the user's similarity with the preference is reused. By comparing the location-based collaborative filtering (LCF) algorithm, user-based collaborative filtering (UCF) algorithm, and user recommendation algorithm (F2F), the proposed method has the preparation rate, recall rate, and experimental effect advantage. In different median values, the proposed method also has an advantage in experimental results.

关键词： Location

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Study on the prediction method of grasshopper occurrence risk in Inner Mongolia based on the maximum entropy model during the growing period

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JOURNAL OF ECONOMIC ENTOMOLOGY 2024年第3期117卷 843-857页

作者： Wen, Fu Liu, Ronghao Garcia y Garcia, Axel Ye, Huichun Lu, Longhui Qimuge, Eerdeng Sun, Zhongxiang Nie, Chaojia Han, Xuemei Zhang, Yue Int Res Ctr Big Data Sustainable Dev Goals Beijing 100094 Peoples R China Taiyuan Univ Technol Coll Water Resources Sci & Engn Taiyuan 030024 Peoples R China Univ Minnesota Dept Agron & Plant Genet St Paul MN 55108 USA Univ Minnesota Southwest Res & Outreach Ctr Lamberton MN 56152 USA Aerosp Informat Res Inst Chinese Acad Sci Key Lab Digital Earth Sci Beijing 100094 Peoples R China Hainan Aerosp Informat Res Inst Key Lab Earth Observat Hainan Prov Sanya 572029 Peoples R China Grassland Workstat Xilingol League Xilinhot 026000 Peoples R China China Agr Museum Beijing 100125 Peoples R China Xinjiang Univ Sch Geol & Min Engn Urumqi 830046 Peoples R China

Grasshoppers represent a significant biological challenge in Inner Mongolia's grasslands, severely affecting the region's animal husbandry. Thus, dynamic monitoring of grasshopper infestation risk is crucial for sustainable livestock farming. This study employed the Maxent model, along with remote sensing data, to forecast Oedaleus decorus asiaticus occurrence during the growing season, using grasshopper suitability habitats as a base. The Maxent model's predictive accuracy was high, with an AUC of 0.966. The most influential environmental variables for grasshopper distribution were suitable habitat data (34.27%), the temperature-vegetation dryness index during the spawning period (18.81%), and various other meteorological and vegetation factors. The risk index model was applied to calculate the grasshopper distribution across different risk levels for the years 2019-2022. The data indicated that the level 1 risk area primarily spans central, eastern, and southwestern Inner Mongolia. By examining the variable weights, the primary drivers of risk level fluctuation from 2019 to 2022 were identified as accumulated precipitation and land surface temperature anomalies during the overwintering period. This study offers valuable insights for future O. decorus asiaticus monitoring in Inner Mongolia.

关键词： Maxent insect dynamics predictive modeling remote sensing influencing factor

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Impact of urbanization factors on mortality due to unintentional injuries using panel data regression model and spatial-temporal analysis

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ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH 2020年第3期27卷 2945-2954页

作者： Pu, Haixia Li, Bin Luo, Dongqi Wang, Shaobin Wang, Zhaolin Zhao, Wei Zheng, Lingyu Duan, Ping Chongqing Technol & Business Univ Res Ctr Econ Upper Reaches Yangtze River Minist Educ Chongqing 400067 Peoples R China Chongqing Technol & Business Univ Key Res Base Humanities Minist Educ Chongqing 400067 Peoples R China Chongqing Technol & Business Univ Coll Tourism & Land Resources Chongqing 400067 Peoples R China Chongqing Key Lab Spatial Data Min & Big Data Int Chongqing Peoples R China Chinese Acad Sci Inst Geog Sci & Nat Resources Res Beijing 100101 Peoples R China Yunnan Normal Univ Coll Tourism & Geog Sci Kunming 650500 Yunnan Peoples R China

Unintentional injuries pose a great risk for human health in China. Few studies have focused on unintentional injuries at national level from urbanization perspective. The panel data of mortality rate of transportation accidents (TA), fall and drowning and sinking (DS) is investigated, and urbanization development index is collected. Global Moran's I and linear regression of panel data are applied to determine the spatial distribution and spatial influencing factors of unintentional injuries. The results are the following: (1) The unintentional injury such as TA, fall, and DS shows clear non-uniformity of spatial distribution and relative immobility through time. (2) A 10,000 tons increase in SO2 emission amount (SO2 EA) and emission of smoke and dust (ESD) can result in 15.7 and 12.5 increases in TA death in eastern region, respectively. Meanwhile, A 10,000 tons increase in NOx emission amount can cause 15.1 increase in TA death in western region. For every 100 billion yuan increase in GDP, the fall death can reduce by 8.4 in central region. One bed increase in number of hospital beds per 10,000 population (NHBP) is favorable for decreasing in fall death by 16.7 in eastern region. However, increase in number of workers enjoying industrial injury (NEWII) does not reduce the fall death in eastern region. (3) For every 1 ten thousand people increase in number of students in ordinary high schools (NSOHS) is conductive to reducing DS death by 7.8 in the western region. Our findings show that there exist spatial differences for urbanization influencing TA, fall, and DS death in eastern, western, and central regions. This study is expected to provide a reference for unintentional injuries control in those three regions.

关键词： Unintentional injuries Spatio-temporal distribution Urbanization Global Moran's I Linear regression of panel data

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A Forest Leaf Area Index Inversion Scheme Using Polarimetric SAR

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IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 2023年 61卷 1页

作者： Fu, Wenxue Wang, Jian Guo, Huadong Chinese Acad Sci Int Res Ctr Big Data Sustainable Dev Goals Beijing 210094 Peoples R China Chinese Acad Sci Aerosp Informat Res Inst Key Lab Digital Earth Sci Beijing 210094 Peoples R China Anhui Univ Sci & Technol Sch Spatial Informat & Geomat Engn Huainan 232000 Peoples R China

A novel forest leaf area index (LAI) inversion scheme using polarimetric synthetic aperture radar (PolSAR) images is proposed. The advantage of inversion using synthetic aperture radar (SAR) images over conventional optical methods is the ability to perform all-weather and all-time forest observation, especially in the tropical rainforest area. In this article, leaves were assumed to be isotropic media, while branches were assumed to be anisotropic with a certain orientation. We first investigated the specific extinction coefficients of propagation through leaves and branches, respectively. Then, a method was employed to separate the attenuation of leaves and branches. Subsequently, an inversion scheme model for LAI inversion using PolSAR images was designed based on the linear relationship between the LAI, and the products of forest height and extinction coefficient. Finally, an experiment was performed using L-band Satelite Argentino de Observacion COn Microondas (SAOCOM) spaceborne SAR image pairs. The forest height and extinction coefficients according to H and V polarizations were retrieved using the oriented volume over ground (OVoG) model. The linear relation between the LAI, and the products of forest height and extinction coefficient were verified using the data measured in situ, and the coefficient of determination (R-2) was 0.64. Finally, the temporal decorrelation and the extinction component caused by the oriented elements were analyzed.

关键词： Extinction coefficient forest leaf area index (LAI) oriented volume over ground (OVoG) model polarimetric synthetic aperture radar (PolSAR)

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Frequency Bias Causes Overestimation of Climate Change Impacts on Global Flood Occurrence

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GEOPHYSICAL RESEARCH LETTERS 2024年第16期51卷 e2024GL108855-e2024GL108855页

作者： Zhao, Fang Lange, Stefan Goswami, Bedartha Frieler, Katja East China Normal Univ Sch Geog Sci Minist Educ Key Lab Geog Informat Sci Shanghai Peoples R China Minist Nat Resources Key Lab Spatial temporal Big Data Anal & Applicat Shanghai Peoples R China Leibniz Assoc Potsdam Inst Climate Impact Res PIK Potsdam Germany Int Inst Appl Syst Anal IIASA Biodivers & Nat Resources Program Water Secur Res Grp Laxenburg Austria Univ Tubingen Machine Learning Climate Sci Tubingen Germany

The frequency change of 100-year flood events is often determined by fitting extreme value distributions to annual maximum discharge from a historical base period. This study demonstrates that this approach may significantly bias the computed flood frequency change. An idealized experiment shows frequency bias exceeding 100% for a 50-year base period. Further analyses using Monte Carlo simulations, mathematical derivations, and hydrological model outputs reveal that bias magnitude inversely relates to base period length and is weakly influenced by the generalized extreme value distribution's shape parameter. The bias, persisting across different estimation methods, implies floods may exceed local defenses designed based on short historical records more often than expected, even without climate change. We introduce a frequency bias adjustment method, which significantly reduces the projected rise in global flood occurrence. This suggests a substantial part of the earlier projected increase in flood occurrence and impacts is not attributable to climate change. We report a previously overlooked bias in a common method for projecting the frequency of extreme floods, like 100-year events. This method typically uses a short period of historical data for two primary purposes: first, to define local thresholds for extreme floods, such as 100-year events, and second, to serve as a base for projecting future changes in flood occurrences. Our study, utilizing random data, demonstrates that this method can lead to inaccurate projections, increasing the number of expected extreme floods in future years and decreasing them in historical baseline years, even when no change is indicated by the data. Additionally, we find that the longer the historical period used, the smaller the bias. By simulating the characteristics of real hydrological model projections with artificial data, we are able to estimate a bias similar to that observed in these projections, and thus propose a simple

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Matching end-of-life household vehicle generation and recycling capacity in Chinese cities: A spatio-temporal analysis for 2022-2050

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SCIENCE OF THE TOTAL ENVIRONMENT 2023年第1期899卷 165498页

作者： Ren, Shuliang Huang, Zhou Bao, Yi Yin, Ganmin Yang, Jingfan Shan, Xv Peking Univ Inst Remote Sensing & Geog Informat Syst Sch Earth & Space Sci Beijing 100871 Peoples R China Peking Univ Beijing Key Lab Spatial Informat Integrat & Its Ap Beijing 100871 Peoples R China Int Res Ctr Big Data Sustainable Dev Goals Beijing 100094 Peoples R China State Key Lab Media Convergence Prod Technol & Sys Beijing Peoples R China

End-of-life vehicles (ELVs) present both opportunities and challenges for the environment and the economy, where effective recycling management plays a decisive role. Recently, the primary focus of recycling manage-ment has shifted from simply meeting demand to refining and optimizing processes at the city-scale. However, the mismatch in recycling capacity has become a significant obstacle to maximizing environmental and economic benefits. To reveal this issue and propose improvements in the context of China, this study simulates end-of-life internal combustion engine vehicles (ICEVs) and new energy vehicles (NEVs) at the city-scale from 2021 to 2050, and analyzes their spatio-temporal pattern and recycling capacity matching. The results indicate that the number of ELVs in China will continue to increase, peaking between 3.5 and 3.7 million. This growth will be mainly driven by third-to fifth-tier cities, as well as central and southwestern cities. Regarding recycling capacity matching, most cities possess excess dismantling capacity, while first-tier cities face coordination problems in battery collection. spatial coordination across cities or provinces is a viable approach for dismantling enterprises and should be prioritized over indiscriminate deregistration or establishing new facilities. The absence of initiative within the recycling system results in uncoordinated battery collection. Implementing a recycling -sharing mechanism and establishing a reuse market can effectively tackle this problem by leveraging market incentives. These analyses provide practical suggestions to maximize the environmental and economic benefits of resource recycling, thereby contributing to the UN's 2030 Sustainable Development Goals (SDGs).

关键词： End-of-life vehicles Material flow analysis spatial-temporal patterns Over capacity City scale

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