Human Socio-economic Activities Research Articles

Monitoring Water Area Dynamics in Kashgar (2003–2023) Using Multi-Source Remote Sensing Data

Understanding the dynamics of regional water area changes is crucial for effective water resource management and ecological conservation, particularly in arid regions. Located in northwestern China’s arid zone, changes in water area in Kashgar significantly impact local agricultural productivity, ecological integrity, and human socioeconomic activities. However, long-term trends in water area changes and their driving factors in Kashgar remain poorly understood. This study leverages Landsat and Sentinel-2 imagery from 2003 to 2023, employing a random forest algorithm to extract water body information. Key findings are as follows: (1) both total and seasonal water area exhibit a fluctuating downward trend, while permanent water area displays a fluctuating upward trend; (2) precipitation and temperature emerged as primary drivers of water area changes, with precipitation in the surrounding regions of Kashgar exerting a particularly significant influence, while evaporation exhibited a lesser impact; (3) the influence of climate change and anthropogenic activities in surrounding areas on water area changes in Kashgar cannot be overlooked.

Perspektif Antropolinguistik tentang Pancasudha: Praktik Budaya dalam Penentuan Waktu Bisnis di Tlogorejo

The Pancasudha tradition, a cultural practice preserved in Tlogorejo Village, Indonesia, remains notable for its integration with the business sector—a vital domain of human socioeconomic activity. This study aims to investigate the linguistic dimensions and sociocultural perspectives embedded within the Pancasudha tradition, focusing on its role in shaping communal beliefs and practices within the local business sphere. Employing a qualitative descriptive methodology, this research was conducted in Tlogorejo Village, with primary data derived from recorded interviews with key informants, including the village’s petungan shaman (ritual numerologist) and community members. Supplementary data included textual analysis of speech acts and ritual incantations associated with Pancasudha. Data were analyzed through an ethnographic lens, incorporating hermeneutic interpretation to decode symbolic meanings, while triangulation techniques ensured methodological rigor. Findings reveal that language functions as a pivotal conduit for transmitting and legitimizing Pancasudha’s spiritual and ethical frameworks, thereby reinforcing communal adherence to the tradition. Central to its preservation is the tradition’s emphasis on peace (rukun), a value that harmonizes individual aspirations with collective welfare, fostering social cohesion in business practices. This study underscores the significance of linguistic anthropology in elucidating how cultural traditions interface with economic activities, offering critical insights for policymakers and cultural custodians seeking to sustain indigenous practices. By foregrounding the interplay of language, belief, and communal values, the research contributes to broader discourses on cultural sustainability and the role of local wisdom in contemporary socioeconomic systems.

Influence mechanism of natural factors and human socio-economic activities on ecosystem health in arid regions of Central Asia: A case study of Fuyun area, northwest China

Influence mechanism of natural factors and human socio-economic activities on ecosystem health in arid regions of Central Asia: A case study of Fuyun area, northwest China

An evolution model for the mobility of urban societal classes based on complex networks

Abstract Cities serve as the main platform for human socio-economic activities, where large crowds, products and information converge, forming complex societal interactions and the space for human to interact with each other. Like traditional geographical space, in cities, cyberspace and societal space also offer diverse channels for human interactions. While urban mobility in geographical space has been extensively studied across disciplines such as geography, economics, transportation and human behavior, mobility within societal space in cities has rarely been examined in depth. This paper focuses on the self-organized consolidation of mobility within urban societal spaces. Based on the rational actor assumption and Dunbar’s number, we construct a simple model to explain why urban societal classes spontaneously emerge in the evolution of societal space. We also find that the mobility within urban societal space decreases spontaneously over time and eventually outstanding individuals potentially can be trapped in lower classes, resulting in an inefficient matching of urban resources.

Analysis of aerosol climate effects under global warming

Global warming is a global environmental problem that has a profound impact on natural ecosystems, human socio-economic activities and the future fate of the planet. Aerosols, as tiny particles that are widespread in the atmosphere Its climate effects are complex and uncertain, and it is a key factor in global climate change research. This essay first introduces the definition and classification of aerosols, including natural source aerosols and anthropogenic source aerosols. Then it analyzed the interrelationship between global warming and aerosols. Then it explored the differences in aerosol impacts in various regions, using North China, Northeast China and the Qaidam Basin as examples. It was found that the differences in the spatial and temporal distribution of aerosols can be summarized from the seasonal and interannual variations of Aerosol Optical Depth (AOD) as well as the characteristics of the spatial distribution. The higher AOD values in spring and summer are mainly affected by sand and dust aerosols, localized pollution, and the EI Niño-Southern Oscillation (ENSO) phenomenon. The spatial distribution of AOD showed heterogeneity. The research provides an important scientific basis for the development of effective climate policy and response measures.

Spatiotemporal Patterns of Typhoon-Induced Extreme Precipitation in Hainan Island, China, 2000–2020, Using Satellite-Derived Precipitation Data

Extreme precipitation events induced by tropical cyclones have increased frequency and intensity, significantly impacting human socioeconomic activities and ecological environments. This study systematically examines the spatiotemporal characteristics of these events across Hainan Island and their influencing factors using GsMAP satellite precipitation data and tropical cyclone track data. The results indicate that while the frequency of typhoon events in Hainan decreased by 0.3 events decade−1 from 1949 to 2020, extreme precipitation events have increased significantly since 2000, especially in the eastern and central regions. Different typhoon tracks have distinct impacts on the island, with Track 1 (Northeastern track) and Track 2 (Central track) primarily affecting the western and central regions and Track 3 (Southern track) impacting the western region. The impact of typhoon precipitation on extreme events increased over time, being the greatest in the eastern region, followed by the central and western regions. Incorporating typhoon precipitation data shortened the recurrence interval of extreme precipitation in the central and eastern regions. Diurnal peaks occur in the early morning and late evening, primarily affecting coastal areas. Typhoon duration (CC_max = 0.850) and wind speed (CC_max = 0.369) positively correlated with extreme precipitation, while the pressure was negatively correlated. High sea surface temperature areas were closely associated with extreme precipitation events. The atmospheric circulation indices showed a significant negative correlation with extreme precipitation, particularly in the western and central regions. ENSO events, especially sea surface temperature changes in the Niño 1 + 2 region (−0.340 to −0.406), have significantly influenced typhoon precipitation characteristics. These findings can inform region-specific disaster prevention and mitigation strategies for Hainan Island.

A Comparative Study of Topic Modelling Approaches for User-generated Point of Interest Data

This study aims to enhance urban planning and management by harnessing the power of machine learning (ML) andbig data. We focus on Urban Functional Zones (UFZs), the fundamental units for human socio-economic activities. Ourmethodology involves compiling Point of Interest (POI) data from various sources for comprehensive analysis. Weemploy various topic modeling approaches such as Latent Dirichlet Allocation (LDA), Latent Semantic Index (LSI),Hierarchical Dirichlet Process (HDP), and Top2Vec. Our principal results reveal significant differences in theperformance and coherence of these models on short text documents. Consequently, our major conclusion isidentifying the better-performing topic model for classifying UFZs from POI data. We also explore four textpreprocessing steps to optimize the performance of the topic models. This study contributes to the field by providinga nuanced understanding of UFZs, paving the way for future data-driven urban planning and management.

Spatiotemporal Evolution and Transformation Regulation Strategies of Rural Residential Land on the Grand Canal (China)

Land use is an embodiment of human socio-economic activities and represents a bridge between these activities and natural systems. Rural residential land represents a space for rural residents to reside in and exhibits spatial characteristics that evolve over time, which is proof of rural socio-economic development. As one of the most developed regions in China, cities along the Beijing–Hangzhou Canal experienced significant changes in rural residential land use from 1990 to 2020. This paper analyses the spatial differentiation of rural residential land in 21 cities on the Grand Canal. Then, it explores the driving factors of this land using spatial grid analysis and the geographic detector model. According to the spatial differentiation characteristics and the driving factors of rural residential land, the study proposed an improved potential model for rural residential land improvement. Lastly, it proposes three different forms of rural residential land based on the results. The study found that (1) the change in rural residential land in the northern part of the Grand Canal was more volatile than that in the southern part. The change in rural residential land from 1990 to 2020 conformed to the pattern of cultivated land–rural residential land–urban construction land. (2) Based on the driving factors of rural residential land, the land is divided into one-dimensional cities, two-dimensional cities, and three-dimensional cities. Circular, linear, and scattered cities of different sizes were affected by socio-economic factors, transportation accessibility, and the natural environment, respectively. (3) Based on the potential scale of rural residential land consolidation, different types of development strategies were proposed through research, including constructing large-scale villages, relocating and reconstructing new villages, and constructing high-quality villages, respectively. Enhancing the scientific planning of rural residential land and its efficiency and tapping into the potential of land consolidation can offer the protection of agricultural land and the integration of urban and rural areas in the new era.

Spatio-Temporal Dynamics of Economic Density and Vegetation Cover in the Yellow River Basin: Unraveling Interconnections

Vegetation, serving as the primary constituent of terrestrial ecosystems, plays a crucial role in regulating energy flow and material cycles and providing vital resources for human socio-economic activities. This study analyzes the spatio-temporal patterns of economic density and vegetation coverage in the Yellow River Basin (YRB) based on forest resource inventory and socio-economic data from 448 counties in 2008, 2013, and 2018. A three-tiered criterion layer is constructed using economic density as the core explanatory variable, encompassing social development factors, land use factors, and natural factors. A two-way fixed effects model is then utilized to analyze the impact of economic density on vegetation coverage. Results reveal that: (1) Spatially, economic density demonstrates a “low in the west and high in the east” pattern, with an overall upward trend in the YRB. Conversely, vegetation cover exhibits a “high in the west and low in the east” pattern, displaying a downward trend. (2) Over the 2008–2018 period, a significant negative correlation between economic density and vegetation cover is observed in each county of the YRB, with vegetation cover decreasing by 1.108% for every 1 unit increase in economic density. Notably, the upstream areas of the YRB experience a significant increase in vegetation coverage, while the middle and lower reaches witness a decrease. (3) Considering control variables, the proportion of the primary industry, urbanization rate, forest protection level, and cultivated land area exert a significant influence on vegetation coverage across the entire basin. Policymakers should formulate relevant policies to achieve sustainable development in the YRB, as discussed in the proposed countermeasures. This study delineates a practical pathway for high-quality economic development and high-level ecological protection in the YRB, offering a valuable reference for analogous research in other regions.

Integrating landscape ecological risk with ecosystem services in the Republic of Tatarstan, Russia

It is a novel approach to linking landscape ecological risk (LER) and ecosystem services (ESs) for environmental management and sustainable development, since it enables real-time decision-making. This study used 12 natural factors relevant to LER and 11 ESs factors to analyze spatiotemporal changes and establish a relationship between them in Tatarstan, Russia, for the years 2010, 2015, and 2020. The statistical tests (Global Moran's I, Getis-Ord Gi*), analysis of habitat vulnerability, and ecological loss in the ArcGIS platform reveal a consistent variance in factor clustering and pattern as well as the impact of governmental policies in the studied area. According to analysis findings, 2015 had the best ecological conditions of the three years because 44.79 % of the research area had decreased landscape ecological risk, which increased ecosystem services. Additionally, the results show that both maps have significant spatial disparities and that LER and ESs are negatively impacted by high human-socioeconomic activity. The integration of LER and ESs through the overlap of both maps provides a significant amount of spatial information for mapping, monitoring, management, and the protection of the fragile environment for sustainable landscape development and management.

High performance computing to support land, climate, and user‐oriented services: The HIGHLANDER Data Portal

AbstractThe Italian territory is located at the heart of one of the global hot spots of climate change, where the implementation of climate‐smart land management practices is imperative to guarantee the present and future maintenance of ecosystem functions as well as the sustainability of human socioeconomic activities. The project HIGHLANDER (HIGH performance computing to support smart LAND sERvices) led by Cineca aims at building a comprehensive and multi‐sector framework for land‐management decision‐making in Italy. The project relies on high quality information on different components of the landscape, with a focus on climate‐driven processes, and state‐of‐the‐art computing infrastructures. The HIGHLANDER Data Portal maximizes the impact of HIGHLANDER results by providing access to data products and services. In this article, we describe the architectural features of the platform, as well as the available HIGHLANDER datasets and downstream applications.

Construction and Application of a Seasonal River Health Evaluation System in Arid and Semi-Arid Areas

Addressing the inadequacy of theoretical frameworks and evaluation indicators for assessing the health of seasonal rivers in arid and semi-arid regions, this study aims to enrich the theoretical foundation for the management and ecological restoration of seasonal river systems. By selecting seven indicators from three aspects: hydrology, habitat, and social services, a seasonal river health assessment indicator system was constructed for the Tabu River basin. The weights of the indicators were determined using the analytic hierarchy process and entropy weight method, and a classification standard for seasonal river health was established. The health status of the Tabu River in 2021 was evaluated accordingly. The results revealed that the upstream, midstream, and downstream reaches of the Tabu River were categorized as healthy, sub-healthy, and diseased, respectively, with poor hydrological conditions being the primary concern. The satisfaction level of ecological flow within the basin was low, accompanied by deep groundwater levels and water scarcity issues, aligning with the actual situation. This indicator system effectively reflects the true state of seasonal river ecosystems. Based on the evaluation results, measures such as establishing ecological water storage projects and adjusting agricultural planting structures were proposed to alleviate the impacts caused by water scarcity. Additionally, implementing river and lake management systems, water resource protection measures, and water-saving technologies can directly regulate the pressures imposed on rivers by human socio-economic activities, thus alleviating regional water resource shortages and promoting the health of rivers and regional water resources. These findings provide scientific decision-making support for the management of seasonal river basins and the maintenance of river health.

Adapting subseasonal-to-seasonal (S2S) precipitation forecast at watersheds for hydrologic ensemble streamflow forecasting with a machine learning-based post-processing approach

Adapting subseasonal-to-seasonal (S2S) precipitation forecast at watersheds for hydrologic ensemble streamflow forecasting with a machine learning-based post-processing approach

Rethinking industrial land-use in American rust cities towards sustainability based on a block-level model

Rethinking industrial land-use in American rust cities towards sustainability based on a block-level model

Evolution and zoning of spatial ecosystem functional stability in the southern hilly region of China: a “structure–function” perspective

IntroductionA series of significant ecological construction projects in the southern hilly region have brought about substantial changes to the ecological status and comprehensive zoning of the region. Hunan Province, with its strategic significance, was chosen as a representative research subject in the southern hilly region.MethodsWe conducted a dynamic evaluation of the ecological status change and comprehensive zoning of Hunan Province from a structure–function perspective by applying the transfer matrix, Theil-Sen, Mann-Kendall, and ecosystem service trade-offs or synergies methods. The research goal was to integrate and harmonize structural complexity and functional diversification, providing valuable insights for optimizing both ecological background and territorial background.ResultsThe main results are as follows: (1) The structural changes of ecosystems were mainly concentrated in settlement and Cropland ecosystems. While the area of bulti-up ecosystems has increased significantly, from 1.34% in 2000 to 2.72% in 2020. Cropland ecosystems marking a decrease of 1.39%, with a continued conversion of Cropland into construction land ecosystems. (2) Ecosystem function changes have introduced instability. Over time, NPP exhibited an oscillating trend of increase followed by a decrease. Spatially, there was a sharp decline in peripheral building land, and the regions of declining NPP displayed a lateral U-shaped distribution. (3) The overall trend in ecosystem service changes was positive. Quantitatively, GP and CS experienced an ascending-then-decreasing pattern, while HQ showed a weak decline and WY increased annually. At the county scale, there was noticeable spatial heterogeneity. Human socio-economic activities and environmental protection policies exert a significant impact on the ecological conditions within the study area. (4) Regarding the national territory space function partition, urban functional zones have primarily catered to residential functions and were mainly distributed in the Changsha-Zhuzhou-Xiangtan area.DiscussionEcological functional zones were mainly centered on ecological functions, and most were located in the mountainous areas of western and southern Hunan Province. The agricultural function areas were mainly to serve production functions and were mainly located in the Dongting Lake Plain, the nearshore plain of the mainstream and tributary systems of the rivers of Xiang, Zi, Yuan, and Li. In general, the changes in ecosystem structure and function in the study area reflect changes in ecological conditions. In the future, ecosystem diversity, stability, and sustainability should be improved from an integrated structure–function perspective.

Spatial Identification and Change Analysis of Production-Living-Ecological Space Using Multi-Source Geospatial Data: A Case Study in Jiaodong Peninsula, China

The significant heterogeneity in the spatial distribution of point of interest (POI) data, the absence of human socio-economic activity information in remote sensing images (RSI), and the high cost of land use (LU) data acquisition restrict their application in PLES spatial identification. Utilizing easily accessible data for detailed spatial identification of PLES remains an urgent challenge, especially when selecting a study area that encompasses both urban built-up areas (UBUA) and non-urban built-up areas (NUBUA). To address this issue, we proposed a PLES spatial identification method that combines POI data and land cover (LC) data in this paper. The proposed method first classified spatial analysis units (SAUs) into agricultural production space (APS), ecological space (ES), and ambiguous space (AS) based on the rich surface physical information from LC data. Subsequently, the AS was further classified into living space (LS) and non-agricultural production space (NAPS) based on the rich human socioeconomic information from POI data. For the AS that contains no POI, a simple rule was established to differentiate it into LS or NAPS. The effectiveness of the method was verified by accuracy evaluation and visual comparison. Applying the method to the Jiaodong Peninsula, we identified the PLES of the Jiaodong Peninsula for 2018 and 2022, further explored their spatial distribution characteristics, and analyzed their changes. Finally, we conducted a discussion on the real-world situations and driving mechanisms of the PLES changes and proposed several policy insights. The results indicated that both the spatial distribution characteristics of PLES and PLES change in the Jiaodong Peninsula were obvious and showed significant differentiation between UBUA and NUBUA. Climatic and natural resource conditions, geographic location, macro-policies, and governmental behaviors drove the PLES changes.

A Study of Sandy Land Changes in the Chifeng Region from 1990 to 2020 Based on Dynamic Convolution

Desertification is the process of land degradation and the reduction or destruction of biological potential in arid, semi-arid, and semi-humid areas, and its impact on agricultural development and the ecological environment cannot be ignored. Therefore, many researchers have aimed to achieve the acquisition of large-scale sandy land areas using sandy land extraction algorithms based on remote sensing images. However, the sandy land extraction accuracy needs to be improved because of the variable contour features in the remote sensing images and the easy confusion with targets such as the Gobi and bare ground areas. In this study, we combine the dynamic convolution with a U-Net model and propose the DU-Net sandy land extraction model. The method is based on dynamic convolution, which can adaptively learn the complex features of the target and build a dynamic convolutional neural network to achieve high-accuracy extraction of complex targets. DU-Net achieved 86.32% in IoU, 93.22% in precision, 94.5% in recall, and 92.66% in F1-score in sandy land extraction accuracy, which are 4.68%, 2.33%, 3.09%, and 2.76% improvements, respectively, compared with the U-Net static neural network. Based on this, we obtained the spatial and temporal evolution trends of sandy land areas based on Landsat images in the Chifeng region in the Inner Mongolia Autonomous Region, China. Meanwhile, in order to investigate the mechanism of spatial and temporal changes in the sandy land area in the study region over the past 30 years, the direct and indirect effects of seven climatic and human socioeconomic activity factors on the changes in the sandy land area in the study region were evaluated based on a structural equation model. The results show that the sandy area in the Chifeng region tended to first increase and then decrease over the study period, with the sandy land area reaching its maximum around the year 2000. In addition, the main driving factor for the change in the sandy land area in the Chifeng region has been human socioeconomic activities, with climatic conditions as the secondary driving factor. The method proposed in this paper realizes the rapid extraction of sandy land areas with high accuracy at a large scale and with a long time series and provides a basis for assessing the effectiveness of ecosystem restoration projects.

A Study on Spatiotemporal Changes of Ecological Vulnerability in Yunnan Province Based on Interpretation of Remote Sensing Images

The inherent ecological environment of mountainous regions is highly fragile, and the degree of sustainable development is low. There has not yet been a multi-phase ecological vulnerability evaluation (EVE) study based on remote sensing (RS) and GIS for mountainous provinces, for which there is an urgent need to establish a system that is appropriate, practicable and easily operated and applied. In this study, an integrated “RS and GIS + multi-phase land use/cover change (LUCC) + practically quantitative theory and methods of EVE” approach was adopted for analysis based on the interpretation results of five phases of the land use/land cover (LULC) RS images of Yunnan, with 129 counties being considered as the evaluation units. The organic combination of quantitative multi-index comprehensive evaluation (QMCE) and qualitative comprehensive analysis (QCA) methods was adopted to perform quantitative calculations of a system of county-level evaluation indicators which includes “innate” natural ecological vulnerability (INEV), land use ecological vulnerability (LUEV) and land cover ecological vulnerability (LCEV); the degree of ecological vulnerability (DEV) was assessed for the 129 counties within the province during the five study phases (1980, 1990, 2000, 2010 and 2020). The spatiotemporal variation characteristics and laws of DEV from 1980 to 2020 in the whole province and 129 counties were revealed, aiming to provide a basis for meeting the SDGs for mountainous provinces. The results are as follows: (1) Overall, INEV is high because of the high mountains and steep slopes, and the entire province is classified as “highly vulnerable” on average. In terms of counties, more than 79.07% are classified as “moderately vulnerable”, “highly vulnerable” and “very highly vulnerable”. (2) The degree of LUEV and LCEV caused by acquired human socioeconomic activities was higher in 1980. However, after a series of ecological measures in the past 40 years, the values of DEVLU and DEVLC in the whole province and counties in 2020 have decreased to different degrees. Accordingly, the degree of overall ecological vulnerability of Yunnan province and counties decreased significantly from 1980 to 2020. The basic law of change is that the number of counties with high DEV decreases significantly, while the number of counties with low DEV increases significantly. (3) The regional difference in the DEV of Yunnan province is large. In general, the degree of ecological vulnerability is lower in the southern, southwestern, western and central areas of Yunnan and higher in the northwest high mountain canyon, northeast mountain areas and east and southeast karst areas. (4) Overall, the DEV in Yunnan province is currently still high. There is an urgent need to enhance the construction of ecological civilization across the whole province and take effective measures to protect the ecological environment according to local conditions, so as to steadily reduce the DEV.

Digitalization and Smartification of Urban Services to Enhance Urban Resilience in the Post-Pandemic Era: The Case of the Pilgrimage City of Makkah

The COVID-19 pandemic has significantly disrupted human socioeconomic activities, leaving an everlasting impact on urban systems. As a result, there is a growing scholarly focus on exploring how urban planning strategies and tools can help create resilient cities. In Saudi Arabia, the pilgrimage city of Makkah, which has always faced the challenge of managing crowds during the annual pilgrimage, was left deserted due to lockdowns and social distancing measures. To quickly revive socioeconomic and pilgrimage activities in the city, a set of digital tools and communication technologies were deployed to manage crowds and enforce social distancing to minimize the spread of the COVID-19 virus. This study examines the role of digitalization and smartification in reviving the city and the importance of context in building urban resilience. This study used desktop research and case study analysis to highlight the transformation to the new normal and the development of future smart technologies for the city. Smart solutions provided valuable support in reducing the impacts of the pandemic and restarting Makkah’s economy. Although most activities have been restored, some facilities and services are still operating below capacity. Digitalization and smartification of urban services could play a major role in improving service delivery and urban resilience.

Urban planning schemes for developing low-carbon cities in the Gulf Cooperation Council region

Urban planning schemes for developing low-carbon cities in the Gulf Cooperation Council region