Shi Shen

Beijing Normal University | bnu · Faculty of Geography

Understanding the spatial distribution patterns (SDPs) of natural disasters plays an essential role in reducing and minimizing natural disaster risks. An integrated discussion on the SDPs of multiple global disasters is still lacking. In addition, due to their high quantity and complexity, natural disasters constitute high-dimensional data that rep...

Soil moisture (SM) is an essential Earth surface and climate system variable. Insights into its persistence and corresponding time scales can improve numerical modeling and climate system prediction. In this study, SM from 17 observation stations within the Babao River Basin, Northwest China, between 1 June and 31 August 2014 were used to investiga...

The streamflow from the headwater areas of the Tibetan Plateau (TP) provides critical support for downstream regions, yet understanding of the streamflow complexity on the TP, which is essential for hydrological modeling and water resource management, remains scarce. This study aims to measure streamflow complexity in the headwater areas of the TP...

Coronavirus disease 2019 (COVID-19) has spread around the world and requires effective control measures. Like the human-to-human transmission of the severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2), the distribution of COVID-19 was driven by population flow and required emergency response measures to slow down its spread and degrade the...

Natural disasters have caused substantial economic losses and numerous casualties. The demand analysis of relief supplies is the premise and basis for efficient relief operations after disasters. With the widespread use of social media, it has become a vital channel for people to report their demand for relief supplies and provides a way to obtain...

Evaluating prefecture-level health risks for hot extremes is the core of localized adaptation measures to mitigate negative heat-related impacts. Here, by applying the heat hazard-human exposure-social vulnerability framework, we assessed the prefecture-level health risk for summertime hot extremes in China, with multisource data from 329 prefectur...

Rapid urbanization and climate change have significantly altered urban hydrological processes. Previous research has highlighted their adverse effects on escalating risk of urban flood. Nevertheless, few assessments have quantified how future urban flood risk mitigation capacities evolve under various urban expansion and climate change scenarios. T...

Study region: The Zhengzhou City in China Study focus: Urban flood risk mitigation (UFRM) refers to the runoff retention capacity of land surface in urban regions. Previous studies have focused on assessing the UFRM change in central urban areas. Nevertheless, analysis of the UFRM change considering the heterogeneity of urban and rural gradient i...

The global public interest in a natural disaster event will help disaster-stricken areas obtain post-disaster international relief and assistance. However, knowledge gaps still exist in regard to global online social responses and their socioeconomic influencing factors. We used big social media data regarding the 2013 Super Typhoon Haiyan to explo...

Scholars have performed much research on reducing the redundancy of hyperspectral data. As a measure of the similarity between hyperspectral bands, structural similarity is used in band selection methods. However, existing structural similarity methods calculate all the structural similarity between bands, which leads to excessively long runtimes f...

Maize is a major crop that is particularly sensitive to climate change. In addition, the extreme shortage of water resources threatens crop production. Thus, improving the effective utilization rate of water is an important problem to discuss. In this regard, we quantified the combined effects of meteorological conditions and irrigation levels duri...

Outdoor thermal comfort (OTC) is critical for public health, labor productivity, and human life. Growing extreme heat events caused by climate change have a serious impact on OTCs, especially in urban areas. Quantitatively characterizing and evaluating the spatiotemporal changes in OTCs are essential, and more applications are needed in urban agglo...

Accurate land-use/-cover change (LUCC) simulation is of great significance to issues closely related to regional planning and policy-making. Many models have been committed to conducting LUCC simulations for better decision-making. However, LUCC is a nonlinear spatiotemporal process with complex links and feedback as well as latent dependencies in...

Detailed spatial distribution of soil organic matter (SOM) in arable land is essential for agricultural management and decision making. Based on digital soil mapping (DSM) theory, much attention has been focused on the selection of environmental covariates. However, the importance of human activity factors in SOM prediction has not received enough...

The population has a significant influence on economic growth, energy consumption, and climate change. Many scholars and organizations have published projections for China's future population due to its substantial population amounts. However, these projections have not been evaluated or analyzed, which may lead confusion to extensional studies bas...

Evaluation of arable land ecosystem services capacity and arable land-use intensity (ALUI) is important for recognising key regional factors that impact arable land attributes changes, which is crucial for planning sustainable patterns of arable land use. The chronic lack of coordination between these two types of evaluation studies has made it har...

Understanding the spatiotemporal dynamics of global urbanization over a long time series is increasingly important for sustainable development goals. The harmonized nighttime light (NTL) time-series composites created by fusing multi-source NTL observations provide a long and consistent record of the nightscape for characterizing and understanding...

High spatial and temporal resolution NDVI time series are indispensable for monitoring land surfaces dynamics in spatiotemporally heterogeneous areas. Spatiotemporal fusion (STF) is one of the most common methods used for producing such data. These methods require the use of one or two pairs of fine images (with fine spatial but rough temporal reso...

Mobile phone signaling data reflect people's real-time geographic location and trajectory. Current research focuses on utilizing mobile phone signaling data to analyze urban residents' behaviors or identify urban land-use functions. The application of mobile phone signaling data in the disaster field is rare. This study uses a spatiotemporal co-clu...

Social media has been a vital channel for communicating and broadcasting disaster-related information. However, the global spatiotemporal patterns of social media users’ activities, interactions, and connections after a natural disaster remain unclear. Hence, we integrated geocoding, geovisualization, and complex network methods to illustrate and a...

Understanding the spatiotemporal dynamics of global urbanization over a long time series is increasingly important for sustainable development goals. The harmonized time-series nighttime light (NTL) composites by fusing multi-source NTL observations provide a long and consistent record of the nightscape for characterizing and understanding the glob...

Changes in the stress state of faults and their surroundings is a highly plausible mechanism explaining earthquake interaction. These stress changes can impact the seismicity rate and the size distribution of earthquakes. However, the effect of large earthquakes on the earthquake size distribution along the Longmenshan fault has not been quantified...

The coronavirus disease 2019 (COVID-19) pandemic continues to threaten lives and the economy around the world. Estimating the risk of COVID-19 can help in predicting spreading trends, identifying risk areas, and making public health decisions. In this study, we proposed a comparative risk assessment method to estimate comprehensive and dynamic COVI...

Sustainable development is the theme of the 21st century. To monitor the progress of sustainable development, the United Nations launched Sustainable Development Goals (SDGs) in 2015. Subsequently, nations of the world have drawn up a list of localized indicators regarding the United Nations SDGs as a paradigm. We established a database including S...

PM2.5 pollution influences the population health and people’s daily life. Because meteorological factors are main factor affecting the formation of PM2.5, the interaction between PM2.5 and meteorological factors needs to be better understood, both for air quality management and for PM2.5 projection. Here, we use a nonlinear state space method calle...

Changes in the stress state of faults and their surroundings is a highly plausible mechanism explaining earthquakes interaction. These stress changes can impact the seismicity rate and the size distribution of earthquakes. However, the effect of large earthquakes on the earthquake size distribution along the Longmenshan fault has not been quantifie...

Spatiotemporal fusion (STF) is considered a feasible and cost-effective way to deal with the trade-off between the spatial and temporal resolution of satellite sensors, and to generate satellite images with high spatial and high temporal resolutions. This is achieved by fusing two types of satellite images, i.e., images with fine temporal but rough...

Precipitation is an essential climate variable in the hydrologic cycle. Its abnormal change would have a serious impact on the social economy, ecological development and life safety. In recent decades, many studies about extreme precipitation have been performed on spatio-temporal variation patterns under global changes; little research has been co...

The vulnerability of vegetation ecosystems and hydrological systems in high-altitude areas makes their phenology more sensitive and their response to climate change more intense. The Qilian Mountains, an important geographic unit located in the northeastern Tibetan Plateau (TP), has experienced the more significant increases in temperature and prec...

PM2.5 pollution influences the population health and people’s daily life. Because meteorological factors are main factor affecting the formation of PM2.5, the interaction between PM2.5 and meteorological factors needs to be better understood, both for air quality management and for PM2.5 projection. Here, we use a nonlinear state space method calle...

In recent years, the sustainable utilization of China’s arable land has been confronted with several challenges. The China government has been very strict in arable land protection, and a package of policies and measures have been promulgated. All these endeavors are of great significance for proposing an innovative policy system for sustainable la...

Over the last few decades, rapid urban expansion has spread over a great deal of arable and ecological land, leading to severe social and environmental issues. Although different urban growth scenarios cause varying types of urban forms to emerge, there is currently a lack of empirical studies and other research on these different forms. Therefore,...

This study aims to analyze the complex relationship between heat flow and seismicity in tectonically active zones worldwide. The problem was quantitatively analyzed by using a geographic detector method, which is well suited for analyzing nonlinear relationships in geography. Moreover, β-value that describes the frequency-magnitude distribution is...

Typhoons are an environmental threat that mainly affects coastal regions worldwide. The interactive effects of natural and socioeconomic factors on the losses caused by typhoon disasters need further examination. In this study, GeoDetector was used to quantify the determinant powers of natural and socioeconomic factors and their interactive effects...

The United States, Russia and China are militarily and economically among the most powerful countries in the post-Cold War period, and the interactions between the three powers heavily influence the international system. However, different conclusions about this question are generally made by researchers through qualitative analysis, and it is nece...

The development of trade research plays an important role in enhancing the understanding of the trade relationship structure, evolution and relevant driving factors. While there is little research on analyzing and visualizing bilateral trade patterns and the evolution of numerous kinds of commodities. In this paper, we respectively calculate reveal...

Product bilateral trade features can be organized and expressed in the Cartesian coordinate system by taking imports and exports as X and Y, which is similar to spatial visualization. Hence, geospatial expression and analysis methodologies can be applied in bilateral trade studies. In this paper, we propose a new digital trade feature map (DTFM) me...

Spatiotemporal fusion is considered a feasible and cost-effective way to solve the trade-off between the spatial and temporal resolution of satellite sensors. Recently proposed learning-based spatiotemporal fusion methods can address the prediction of both phenological and land-cover change. In this paper, we propose a novel deep learning-based spa...

Information content is an important criterion for many image processing algorithms such as band selection and image fusion. Usually, information content is quantified by using information entropy (i.e., Shannon entropy); however, this is not a suitable measure because information entropy is independent of the spatial distribution of image pixels. T...

The past several years have witnessed much progress in landscape ecology and fractal analysis. In landscape ecology, the gradient model of landscape patterns (i.e., landscape gradient) has emerged as a new operating paradigm, where most landscape metrics do not apply because they were developed for the patch mosaic model. In the fractal analysis, a...

The Babao River Basin is the “water tower” of the Heihe River Basin. The combination of vulnerable ecosystems and inhospitable natural environments substantially restricts the existence of humans and the sustainable development of society and environment in the Heihe River Basin. Soil temperature (ST) is a critical soil variable that could affect a...

Analyses of the soil moisture evolution trend and the influence of different types of radiation on soil moisture are of great significance to the simulation and prediction of soil moisture. In this paper, soil moisture (2–60 cm) and various radiation data from 2014–2015 at the A’rou superstation were selected. The radiation data include the net rad...

Complex natural disasters often cause people to suffer hardships, and they can cause a large number of casualties. A population that has been affected by a natural disaster is at high risk and desperately in need of help. Even with the timely assessment and knowledge of the degree that natural disasters affect populations, challenges arise during e...

Earthquakes exhibit clear clustering on the earth. It is important to explore the spatial-temporal characteristics of seismicity clusters and their spatial heterogeneity. We analyze effects of plate space, tectonic style, and their interaction on characteristic of cluster. Based on data of earthquakes not less than moment magnitude (MW) 5.6 from 19...

This paper analysed the evolution of landslide research and research foci in different countries. The data comprise 3105 landslide SCI articles published between January 1977 and June 2015 from the Web of Science. The data are extracted under interaction constraints of the journal title, category, and keywords. The complex network method is used fo...

Poyang Lake basin is one of the most biodiversity areas in China. Fluctuation of water level is an important factor of hydrological process which is a guarantee of ecosystem health and biodiversity conservation. To measure its spatial-temporal variation, classical statistical methods and permutation entropy were employed: 1) Variation of water leve...

Studying the tendency of soil temperature and moisture can provide scientific support for setting soil parameters for land surface hydrological model. Previous research has shown that there is long-range correlation of soil temperature or moisture; however, driving factors of long-range correlation variations and the cross correlation between tempe...

In recent years, remote sensing (RS) research on crop growth status monitoring has gradually turned from static spectrum information retrieval in large-scale to meso-scale or micro-scale, timely multi-source data cooperative analysis; this change has presented higher requirements for RS data acquisition and analysis efficiency. How to implement rap...

Big Data analysis was applied in this study to visualize and analyze the developing trends and emerging topics in agricultural drought research. In total, 10,048 agricultural drought-related articles (From Jan 1900 to Dec 2015) were indexed from the Web of Science. First, a co-citation network of these articles was generated and a semantic cluster...

This study visualized and analyzed the developing trends and hot topics in natural disaster research. 19694 natural disaster-related articles (January 1900 to June 2015) are indexed in the Web of Science database. The first step in this study is using complex networks to visualize and analyze these articles. CiteSpace and Gephi were employed to gen...

Invasive alien plants (IAPs) are an important reason for biodiversity crisis and changes of local ecosystem and landscape. The key content of IAPs investigating research is about how to timely and efficiently monitor the growth and occurrence of IAPs. Timely gathering IAPs’ occurrence is helpful for governments to prevent and control them in time....

Big natural disasters attract great international response in social media and can be used to analyze how information about the disaster is distributed around the world. On example of typhoon Haiyan (Philippines, 2013) we analyze structure of the social graph extracted from Twitter and information propagation in the English-speaking world. Clusteri...

Purpose The purpose of this study is to propose a method to retrieve data on an event based on a preliminary collection of event-specific hashtags. Design/methodology/approach Extra knowledge, or a list of events with recorded features that can be used to characterize an event and separate it from other simultaneously occurring social phenomena,...

This study proposes a method for improving customer satisfaction evaluation of power supply enterprises using sentiment analysis. First, a corpus of comments and posts about power supply enterprise is generated. Second, several machine learning algorithms are used to extract features from the corpus. Finally, the best classifier is used to evaluate...

How to process massive historic natural disasters events is a great challenge to recognize patterns. And more and more scientific research data provides a new source of nature disasters. In this study, the biclustering method is used to categorize the scientists concerned natural disasters and historic events. Cartograms, one kind of transformed ma...

This paper addresses a special zone design problem for economic census investigators that is motivated by a real-world application. This paper presented a heuristic multikernel growth approach via Constrained Delaunay Triangulation (CDT). This approach not only solved the barriers problem but also dealt with the polygon data in zoning procedure. In...

Recent advances in wireless sensor networks (WSNs) technologies and their incorporation with geographic information system (GIS) technologies offer vast opportunities for development and application of agriculture fields. This paper describes the design and implementation of jujube real-time monitoring and management system based on the WSN and GIS...

Aiming at the problems of narrow investigation ranges, inconsistent standards, slow update speed and lacking of continuous monitoring information about monitored samples, an online survey system for alien invasive plant based on Google Maps was designed and developed. This system is able to monitor online through combining field survey with real-ti...

Landsat TM5 images are used to calculate and retrieve normalized difference vegetation index (NDVI) and land surface temperature (LST). Combining with two index mentioned, vegetation temperature condition index (VTCI) can be retrieved for drought monitoring indicator applied in Junchuan farm of Heilongjiang Province in Northeast China. With well pe...