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The number of studies on COVID-19 has rapidly grown in recent years. The pandemic has caused widespread disruption, including in renewable energy research. This study aims to examine the impact of the COVID-19 pandemic on renewable energy research by conducting a bibliometric analysis from the Scopus indexing database from 2020 to 2023. This study employs a bibliometric approach to analyze the authors, affiliation, publication source, keywords, thematic map, and trend topic. The analysis will focus on the comprehensive overview of the published research and identify areas where future research is needed. The results show that the number of research studies related to COVID-19’s effect on renewable energy will continue growing and a solid collaboration network exists. China has had a significant presence on the impact of COVID-19 on renewable energy studies, including organization and university affiliations, number of single and multiple country publications, funding sponsors, and most cited countries. The finding also shows niche themes, research trends, and thematic evolution shifting. This finding will contribute to a better understanding of the impact of the COVID19 pandemic on renewable energy research and a new direction for future research. [ABSTRACT FROM AUTHOR]

This article explores the concept of "immigrant consumption behavior (ICB)" in the context of its holistic surroundings. The study investigated the current dynamics and scientometrics of the research field regarding immigrant consumption behaviors. Using an integrative approach employing bibliometric and content analysis, it scrutinized a collection of 224 studies from the Web of Science and Scopus databases to detect the field evolution, disciplinary distribution thematic map, and emerging trends in the ICB literature, as well as to forecast research directions. The results showed that ICB is a multi- and inter-disciplinary research area that experienced three phases of growth between 1989 and 2023: initiation (1989–2006), development (2007–2012), and consolidation (2013–now). The thematic analysis revealed five current trends, i.e., (1) the immigrant consumption behavior domain, (2) the demographic sub-groups of immigrants and related consuming products, (3) country-, region-, and cultural-focused studies, (4) the effects of culture and the acculturation process, and (5) the impact of urbanization. Each theme contains a number of sub-themes. Based on the current thematic evolution and keyword burst analysis, this paper suggests a number of critical research directions, comprising (1) observatory studies including remittances, China, ethnic minorities, lifestyle, inequality, urbanization, and food consumption; (2) context-based studies focused on socioeconomic, cultural, legal, and environmental factors; (3) studies based on compensatory and compromissory consumption behavior; (4) studies focused on sustainable and green consumption behaviors; and (5) studies regarding the behavior of specific demographic co-ethnic communities. The results have great implications for developing interventions and programs that can support immigrant populations in making appropriate consumption patterns and adapting to new cultural environments. The paper pushes forward the ICB investigation from individual empirical studies to synthesis-based research, which (1) provides an ample overview of the ICB literature, (2) identifies research priorities, emerging trends, and gaps, (3) proposes new research avenues for investigation, and (4) outlines expected contributions. The research contributes to a variety of disciplines through the provision of new knowledge, since ICB studies are multidisciplinary in nature. It also has numerous implications for policymakers and practitioners. [ABSTRACT FROM AUTHOR]

This study employs bibliometric analysis to investigate the landscape of Environmental, Social, and Governance (ESG) factors and their relationship with performance. Drawing from a dataset of 634 papers retrieved from the Web of Science (WoS) database and analysed using Biblioshiny, the research explores academic interest trends, temporal dynamics, and citation impacts. Results indicate a surge in scholarly attention since 2010, peaking notably in 2022, reflecting the growing importance of ESG research. Prominent institutions such as Stanford and Bocconi emerge as collaborative hubs, with China leading in scientific production. Key themes include financial performance, governance, risk, responsibility, and management, reflecting comprehensive explorations of sustainable business practices and effective corporate governance. Thematic maps highlight essential elements in ESG and performance studies, with clusters like "impact" emphasizing critical factors such as "governance" and "financial performance." Future research directions could explore the integration of emerging technologies into ESG reporting procedures or sectorspecific discrepancies in ESG effects on performance. The study acknowledges limitations inherent in bibliometric analysis and underscores the importance of triangulating findings with additional data sources for a comprehensive understanding of the scholarly landscape. [ABSTRACT FROM AUTHOR]

Background: Since human papillomavirus (HPV) infection is known as one of the main causes of cervical cancer, medical researchers pay significant attention to this issue2. The current study applies the bibliometric method to identify the trends and advancements of research on HPV worldwide. Methods: This descriptive study was conducted using a bibliometric approach. All HPV-related scientific publications in the Web of Science database until 2022, August 30 were included in the statistical population. The Bibliometrix package of the R programming language was used to analyze the data. Results: In the field of HPV, a total of 45,657 scientific publications were retrieved, the majority of which were articles. The countries with the highest publications were the USA (45,954 document), China (9977), and UK (6652). The words "Infection," "Cancer," and "Women" are the most important keywords of scientific publications on HPV. "Cancer," "infection," and "women" are the more developed and essential in HPV subject area. "Protein," "gene-expression," and "human-keratinocytes" are in this quadrant. "DNA," "squamous-cell carcinoma," and "head" keywords are basic themes in the HPV subject area. "Human-papillomavirus vaccination," "knowledge," and "attitude" are in this quadrant. Conclusion: The study suggests the need to enhance the focus on global and public health aspects within HPV research to encourage greater participation from various countries in international research endeavors. [ABSTRACT FROM AUTHOR]

Purpose: This study aims to conduct a bibliometric analysis on knowledge management from journals in the Scopus database between 1988 and 2021. The paper covered the past three decades of publications and carried out performance analysis and science mapping analysis of articles. Design/methodology/approach: The study uses bibliometrics, performance analysis and science mapping analysis of 1,016 articles extracted from the Scopus database. The study examined the scientific productivity of articles, productive authors, citable documents, most relevant institutions, cited countries, co-occurrence of keywords, thematic mapping, co-citations and collaboration of authors and countries. The study used Biblioshiny as a tool to carry out the performance analysis and science mapping analysis. Findings: The results show that the number of publications has significantly increased in the past decade, 88.4% of authors contribute at least a single article, 8.3% of authors published two articles, 2% of the authors published three documents and 0.6% of the authors contribute four papers. The USA, China and Australia were the most productive countries in terms of the total number of citations and foreign collaborations. Journal of Knowledge Management, Knowledge Management Research and Practice, VINE Journal of Information and Knowledge Management and International Journal of Technology Management are the top outlets in the knowledge management literature. Originality/value: Over the past decade, the research on knowledge management construct has exploded because of the growing interest of researchers and practitioners in the field. Despite being a well-developed field, few studies have applied bibliometric analysis in the knowledge management literature. The study is more comprehensive in terms of the actors and methods involved in analyzing the scientific production of articles in the area of knowledge management. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) is being used in our daily lives, in all situations and in particular those concerning service systems. However, there is an absence of the ability of the conceptual structure, thematic structure, intellectual structure, and research trends of AI and disruptive technologies in service systems. The main purpose of this study was to carry out a bibliometric analysis of the scientific production of AI and disruptive technologies in service systems based on Elsevier's Scopus database. To do so, keywords were chosen and then data outputs such as the number of published documents, top authors and citations, top journals, countries, and affiliations with the highest number of productions, and network analysis using R-based "biblioshiny" software. The main results showed the growing interest in the subject in the last five years, pointed out current themes and research trends, and revealed the intellectual structure of the field, namely the importance of smart services, cloud computing, and smart sustainable cities. The number of articles for this study reached 1,323, the growth rate has increased in the last five years and the main sources have been reported. China, South Korea and the USA were the leading countries on the subject, and the top 10 authors of influence showed. The word cloud and word growth were presented, as well as the co-citation clusters and co-occurrence network revealed important aspects, and finally the thematic map and the thematic evolution of the subject showed the important concepts. It is hoped that this research will supply future directions for researchers in the area while highlighting the potential of quantitative methods. [ABSTRACT FROM AUTHOR]

Objective: To identify bibliometric parameters and research trends regarding to telerehabilitation of patients with stroke in the COVID-19 era. Methodology: This is an integrative review carried out in the Scopus database, from June to July 2021, through the Biblioshiny graphical interface, provided by the Bibliometrix program. The search terms used were “Stroke,” “COVID-19” and “Telerehabilitation.” Results were filtered by publication date from 2019 onwards. No language restrictions were imposed. Results: Twenty two articles were included in the study and the results were presented in the form of figures demonstrating that the journal Frontiers in Neurology was the one with the most relevant studies and the author with the highest number of citations. The Brazilian Academy of Neurology was the institution with the greatest number of studies and China ranked first as the country with the greatest scientific production. The authors used recent references in their work. A thematic map showed the centrality and density of the words presented and, finally, a three-field graph showed a strong intimacy between countries, keywords and authors. Conclusion: A greater interest in the subject was observed in China with greater relevance of journals and institutions focused on neurology. However, despite telerehabilitation being an effective alternative in the context of the pandemic, few studies have explored this modality. [ABSTRACT FROM AUTHOR]

Objectives: Radiomics is the high-throughput extraction of mineable and—possibly—reproducible quantitative imaging features from medical imaging. The aim of this work is to perform an unbiased bibliometric analysis on Radiomics 10 years after the first work became available, to highlight its status, pitfalls, and growing interest. Methods: Scopus database was used to investigate all the available English manuscripts about Radiomics. R Bibliometrix package was used for data analysis: a cumulative analysis of document categories, authors affiliations, country scientific collaborations, institution collaboration networks, keyword analysis, comprehensive of co-occurrence network, thematic map analysis, and 2021 sub-analysis of trend topics was performed. Results: A total of 5623 articles and 16,833 authors from 908 different sources have been identified. The first available document was published in March 2012, while the most recent included was released on the 31st of December 2021. China and USA were the most productive countries. Co-occurrence network analysis identified five words clusters based on top 50 authors' keywords: Radiomics, computed tomography, radiogenomics, deep learning, tomography. Trend topics analysis for 2021 showed an increased interest in artificial intelligence (n = 286), nomogram (n = 166), hepatocellular carcinoma (n = 125), COVID-19 (n = 63), and X-ray computed (n = 60). Conclusions: Our work demonstrates the importance of bibliometrics in aggregating information that otherwise would not be available in a granular analysis, detecting unknown patterns in Radiomics publications, while highlighting potential developments to ensure knowledge dissemination in the field and its future real-life applications in the clinical practice. Clinical relevance statement: This work aims to shed light on the state of the art in radiomics, which offers numerous tangible and intangible benefits, and to encourage its integration in the contemporary clinical practice for more precise imaging analysis. Key Points: • ML-based bibliometric analysis is fundamental to detect unknown pattern of data in Radiomics publications. • A raising interest in the field, the most relevant collaborations, keywords co-occurrence network, and trending topics have been investigated. • Some pitfalls still exist, including the scarce standardization and the relative lack of homogeneity across studies. [ABSTRACT FROM AUTHOR]

Allelopathy Journal is the official publication of 'Allelopathy Books' that promotes allelopathy research and publish researches related to plant sciences and health sciences. This study aimed to present an insight about the researches published in this journal, to help the Authors, Readers and Editorial team to understand the journal in depth. We analyzed the scholarly publications published in the Allelopathy Journal, their Citations, focussing on other aspects such as Publication output, Citation analysis, Co-authorship patterns, Collaboration networks, Research productivity, Research topics and International collaboration. This study is useful to identify emerging trends and evaluate research impact. The data for the study was extracted from the Scopus Database for the period from 1996 to 2022. The results showed that the journal has published 1209 papers during this period, which received 9826 citations with an average of 8.13 citations per paper. F.Z. Wu was the most prolific author with 22 papers receiving 127 citations and Prof. S.S. Narwal, with second highest papers in the journal, received the highest number of citations (242). China was the most productive country with 425 papers in the journal, followed by India (243 papers). The Chinese Academy of Sciences was the most productive institute in the journal and published 67 papers with 678 citations. A total of 4870 authors have appeared in 1209 papers with 0.91 degree of collaboration and a collaboration index of 4.03. Thematic maps indicated that the topics represented by keywords such as "Distribution", "Habitat", "Essential Oil", "Lettuce", "Morphology," have potential importance for future research. [ABSTRACT FROM AUTHOR]

This study examines mobile learning adoption and continuance in education literature through bibliometric methods. The metadata of 155 relevant publications was extracted from the Web of Science database and imported into "biblioshiny" for analysis. It was found that Education and Information Technologies has the highest publications, and Computers & Education is the most cited journal. Author analysis revealed that Shakeel Iqbal has the most articles fractionalized. Further, the most cited articles were published in the year 2012. The study revealed an exponential increase in research in the top producers, China and Turkey, since 2019. TAM was found to be the most popular theory among researchers. In addition, interest in self-determination theory has been growing recently. The studies examined limited subjects (language, mathematics, and science). The findings indicated several associated keywords, such as augmented reality, cyberloafing, and virtual reality. The thematic map revealed emerging (e.g., self-regulation), niche (e.g., literacy), motor (e.g., attitude), and basic (e.g., addiction) themes. Further, the conceptual structure map suggested the nuances of difference between the constructs of "intention" and "continuance intention". [ABSTRACT FROM AUTHOR]

Quantifying secondary forest age (SFA) is essential to evaluate the carbon processes of forest ecosystems at regional and global scales. However, the successional stages of secondary forests remain poorly understood due to low-frequency thematic maps. This study aimed to estimate SFA with higher frequency and more accuracy by using dense Landsat archives. The performances of four time-series change detection algorithms—moving average change detection (MACD), Continuous Change Detection and Classification (CCDC), LandTrendr (LT), and Vegetation Change Tracker (VCT)—for detecting forest regrowth were first evaluated. An ensemble model was then developed to determine more accurate timings for forest regrowth based on the evaluation results. Finally, after converting the forest regrowth year to the SFA, the spatiotemporal and topographical distributions of the SFA were analyzed. The proposed ensemble model was validated in Jiangxi province, China, which is located in a subtropical region and has experienced drastic forest disturbances, artificial afforestation, and natural regeneration. The results showed that: (1) the developed ensemble model effectively determined forest regrowth time with significantly decreased omission and commission rates compared to the direct use of the four single algorithms; (2) the optimal ensemble model combining the independent algorithms obtained the final SFA for Jiangxi province with the lowest omission and commission rates in the spatial domain (14.06% and 24.71%) and the highest accuracy in the temporal domain (R2 = 0.87 and root mean square error (RMSE) = 3.17 years); (3) the spatiotemporal and topographic distribution from 1 to 34 years in the 2021 SFA map was analyzed. This study demonstrated the feasibility of using change detection algorithms for estimating SFA at regional to national scales and provides a data foundation for forest ecosystem research. [ABSTRACT FROM AUTHOR]

In the face of the problems that have emerged along with the rapid industrialization and urbanization in China in recent years, the country proposes to compile the national main functional area plan, divides the national land space into four types of main functional areas: optimized development, key development, restricted development and prohibited development, and carries out the compilation of the national main functional area plan at two levels: national and provincial. The spatial evaluation indexes of the country and the results of the main functional area planning are expressed graphically in the form of thematic maps to make them visual, intuitive and easier to understand. In this paper, we study the topic selection of the National Atlas of Main Functional Area Planning, and mainly introduce the research results of the atlas in topic selection research, content structure design and layout design based on the comprehensive analysis of national and provincial information and following the principles of topic selection. [ABSTRACT FROM AUTHOR]

Objectives: Provincial comprehensive atlas is a complex knowledge system. It uses thematic maps to comprehensively display the resource endowment and social development level of a province. We reconstruct the large, complex and unstructured contents of the atlas to establish the atlas content tupu, explore the basic content organization rules of provincial comprehensive atlas in China. Methods: First, we construct the vocabulary vectors of thematic subjects presented in atlas, calculate their semantic similarities, and extract the standard expressions of subject words. Second, following the compile order of “map group, map sheet, and cartographic index”, the semantic hierarchical clusters of subject words are figured out, and the content map of atlas are constructed in a tree-wised graph. Finally, the frequent subgraphs of content tupu among provincial atlases are examined to form an atlas fingerprint to identify the common features of subject expressions in the comprehensive atlas of China’s provinces. Results: It is shown that the thematic contents of provincial comprehensive atlas are organized hierarchically, and the fingerprint tupu can be used as a framework to guide the thematic selection and content organization during the comprehensive atlas compilation. With the benefit of content tupu and fingerprint tupu, it can be further revealed that the provincial comprehensive atlas in China has obvious clustering characteristics and diversity characteristics in content expression. Conclusions: The research results provide a basis for the design of provincial comprehensive atlas. In the future, we will explore the content tupus of different types of atlas to enrich the theory of atlas design and compilation. [ABSTRACT FROM AUTHOR]

Total nitrogen (TN), total phosphorus (TP), total potassium (TK), and soil organic matter (OM) can significantly affect forest growth. However, these soil properties are spatially heterogeneously distributed, complicating the prescription of forest management strategies. Thus, it is imperative to obtain an in-depth understanding of the spatial distribution of soil properties. In this study, soils were sampled at 181 locations in the Tropical Forest Research Center in the southwestern Guangxi Zhuang Autonomous Region in southern China. We investigated the spatial variability of soil OM, TN, TP, and TK using geostatistical analysis. The nugget to sill ratio indicated a strong spatial dependence of soil TN and a moderate spatial dependence of soil OM, TP, and TK, suggesting that TN was primarily controlled by intrinsic factors (e.g., soil texture, parent material, vegetation type, and topography), whereas soil OM, TP, and TK were controlled by intrinsic and extrinsic factors (e.g., cultivation practices, fertilization, and planting systems). Based on the spatial variability determined by the geostatistical analysis, we performed ordinary kriging to create thematic maps of soil TN, TP, TK, and OM. Model validation indicated that the thematic maps were reliable to inform forest management. [ABSTRACT FROM AUTHOR]

In recent years, bibliometric analysis as a field of study has captured researchers' interest worldwide. Bibliometric analysis enables one to have data about a particular field of research in one place. In this paper, the authors have attempted to capture insights on the study of bibliometric analysis of corporate governance in BRICS economies. For all companies, and most prominently the publicly traded companies, reliance to the ethos of good corporate governance helps enhance the value of the companies. Corporate governance is an umbrella term indicating all possible areas of best practice to elevate the performance of the companies. BRICS economies have their own set of similarities as well as differences. Bibliometric analysis of corporate governance research is elaborately studied in the context of European and other developed economies. As this kind of study has not been done with reference to the BRICS economies, we had the motivation to conduct this study. From the Scopus database, meta data has been collected for this study. In this study, we reviewed 3,596 research publications during the last three decades, between 1991 and 2020. The increasing trend of publications is observed in corporate governance in BRICS countries using the longitudinal data. Researchers from China rule the chart on the quantum of research done in the field of corporate governance among the BRICS economies. Meta data for ten years is analysed using Biblioshiny and Vosviewer. Using a thematic map, the study of 3,596 documents were divided into four time zones, i.e., 1991-2011 (976 documents), 2011-2014 (612 documents), 2014-2017 (792 documents), and 2017-2020 (1,296 documents). The key themes which emerged were governance and ownership structure (1991 to 2011); stakeholders, corporate social responsibility, and internationalisation (2011-2014); privatisation and investor protection (2014-2017); and audit committee, independent directors, and corporate governance (2017-2020).. [ABSTRACT FROM AUTHOR]

Southwest China has abundant grassland resources, but they are mainly scattered across fragmented mountainous terrain with frequently cloudy and rainy weather, making their accurate identification by remote sensing challenging. Therefore, the goal of this study was to generate prefecture-level city-scale mountainous grassland distribution data to support the development of sustainable grassland husbandry. Here, we proposed a sample selection method and comprehensively utilized multi-source data to obtain the quasi-10 m southwest grassland distribution data. The sample selection method was to first determine the sample selection range based on multi-source land use/cover database, and then to randomly select the samples under the constraint of secondary land use types, multiple factors of terrain and pure pixels. This method can deal with the difficulty in identifying the fragmented grassland distribution caused by steep mountains and hills. In addition, a multispectral time series dataset was constructed based on the fusion of Landsat 8 OLI and Sentinel-2A/B data due to cloudy and rainy weather and was used as one of the input features along with synthetic aperture radar Sentinel-1 time series data and the terrain multi-factor data. Finally, a remote sensing method to accurately identify grassland distribution in southwest China was constructed based on the Google Earth Engine (GEE) platform. Taking Zhaotong City, a prefecture-level city in Yunnan Province, as an example, a thematic map of grassland distribution with an overall accuracy of 88.21% was obtained using the above method. This map has been used by the local government of Zhaotong City in their planning of the development of sustainable grassland husbandry. [ABSTRACT FROM AUTHOR]

The contemporary innovations in financial technology (fintech) serve society with an environmentally friendly atmosphere. Fintech covers an enormous range of activities from data security to financial service deliverables that enable the companies to automate their existing business structure and introduce innovative products and services. Therefore, there is an increasing demand for scholars and professionals to identify the future trends and directions of the topic. This is why the present study conducted a bibliometric analysis in social, environmental, and computer sciences fields to analyse the implementation of environment-friendly computer applications to benefit societal growth and well-being. We have used the 'bibliometrix 3.0' package of the r-program to analyse the core aspects of fintech systematically. The study suggests that 'ACM International Conference Proceedings' is the core source of published fintech literature. China leads in both multiple and single country production of fintech publications. Bina Nusantara University is the most relevant affiliation. Arner and Buckley provide impactful fintech literature. In the conceptual framework, we analyse relationships between different topics of fintech and address dynamic research streams and themes. These research streams and themes highlight the future directions and core topics of fintech. The study deploys a co-occurrence network to differentiate the entire fintech literature into three research streams. These research streams are related to 'cryptocurrencies, smart contracts, financial technology', 'financial industry stability, service, innovation, regulatory technology (regtech)', and 'machine learning and deep learning innovations'. The study deploys a thematic map to identify basic, emerging, dropping, isolated, and motor themes based on centrality and density. These various themes and streams are designed to lead the researchers, academicians, policymakers, and practitioners to narrow, distinctive, and significant topics. [ABSTRACT FROM AUTHOR]

This research article presents a novel approach to examining the utilization of artificial intelligence (AI) in sustainable supply chains (SSCs) by applying social network analysis (SNA). In contrast to previous literature that primarily relied on bibliometric analysis, this study investigates the intricate relationships among AI applications in SSCs using SNA. The primary objective is to promote collaborative research and offer valuable insights into influential authors, international co-authorship networks, collaborations among scientific institutions, and research categories identified through keyword analysis. Data were collected from the Web of Science (WOS) database to conduct this research, enabling a comprehensive co-authorship network analysis. This network revealed the collaboration patterns of 1400 authors and identified the most significant authors in this field using centrality measures and the TOPSIS technique. The study also explores institutional co-authorship networks, highlighting India's National Institute of Technology (NIT) as the most active institution. By considering geographical proximity and research specialization, the institutional network was divided into distinct clusters. A keyword analysis and thematic map also shed light on Sustainability and Supply Chain Management themes, revealing their connections with AI methodologies. Based on the thematic map, E-waste, Green supply chain management (GSCM), and Green innovation themes are potential future trends. The analysis of the country network showcased varying levels of development and scientific output, with China leading the field of AI applications in SSC research. Countries were further classified into clusters based on their investment in AI for sustainable supply chains, facilitating knowledge exchange and collaboration. The outcomes of this research contribute significantly to the field by utilizing social network analysis to explore co-authorship networks, leading to a comprehensive understanding of collaborative dynamics and knowledge dissemination. The insights gained from this study can inform decision-making, investments, and strategic collaborations in the domain of AI applications for sustainable supply chains, ultimately driving progress toward sustainability objectives. [ABSTRACT FROM AUTHOR]

Environmental engineering geological patterns (EEGPs) are used to express the trend and intensity of eco-geological environment caused by mining in underground coal mining areas, a complex process controlled by multiple factors. A new zoning method for EEGPs was developed based on the variable-weight theory (VWT), where the weights of factors vary with their value. The method was applied to the Yushenfu mining area, Shaanxi, China. First, the mechanism of the EEGPs caused by mining was elucidated, and four types of EEGPs were proposed. Subsequently, 13 key control factors were selected from mining conditions, lithosphere, hydrosphere, ecosphere, and climatic conditions; their thematic maps were constructed using ArcGIS software and remote-sensing technologies. Then, a stimulation-punishment variable-weight model derived from the partition of basic evaluation unit of study area, construction of partition state-variable-weight vector, and determination of variable-weight interval was built to calculate the variable weights of each factor. On this basis, a zoning mathematical model of EEGPs was established, and the zoning results were analyzed. For comparison, the traditional constant-weight theory (CWT) was also applied to divide the EEGPs. Finally, the zoning results obtained using VWT and CWT were compared. The verification of field investigation indicates that VWT is more accurate and reliable than CWT. The zoning results are consistent with the actual situations and the key of planning design for the rational development of coal resources and protection of eco-geological environment. [ABSTRACT FROM AUTHOR]

OBJECTIVE To investigate the geographic variation in diabetes prevalence and detection in China. RESEARCH DESIGN AND METHODS Self-report and biomedical data were collected from98,058 adults aged ≥18 years (90.5% response) from 162 areas spanning mainland China. Diabetes status was assessed using American Diabetes Association criteria. Among those with diabetes, detection was defined by prior diagnosis. Choropleth maps were used to visually assess geographical variation in each outcome at the provincial level. The odds of each outcome were assessed using multilevel logistic regression, with adjustment for person- and area-level characteristics. RESULTS Geographic visualization at the provincial level indicated widespread variation in diabetes prevalence and detection across China. Regional prevalence adjusted for age, sex, and urban/rural socioeconomic circumstances (SECs) ranged from 8.3% (95% CI 7.2%, 9.7%) in the northeast to 12.7% (11.1%, 14.6%) in the north. A clear negative gradient in diabetes prevalence was observed from13.1%(12.0%, 14.4%) in the urban high-SEC to 8.7% (7.8%, 9.6%) in rural low-SEC counties/districts. Adjusting for health literacy and other person-level characteristics only partially attenuated these geographic variations. Only one-third of participants living with diabetes had been previously diagnosed, but this also varied substantively by geography. Regional detection adjusted for age, sex, and urban/rural SEC, for example, spanned from 40.4% (34.9%, 46.3%) in the north to 15.6% (11.7%, 20.5%) in the southwest. Compared with detection of 40.8% (37.3%, 44.4%) in urban high-SEC counties, detection was poorest among rural low-SEC counties at just 20.5% (17.7%, 23.7%). Person-level characteristics did not fully account for these geographic variations in diabetes detection. CONCLUSIONS Strategies for addressing diabetes risk and improving detection require geographical targeting. [ABSTRACT FROM AUTHOR]

Research in urban ecology has recently focused on the field of ecological security. Ecological security should be assessed at different scales, from global (to understand some processes of global change) to regional (to understand processes in specific areas) to urban (to consider the processes of urban development). Remote sensing (RS) and geographical information systems (GISs) are widely utilized in ecological security evaluation, with remotely sensed images applied to determine the structure and quantitative indicators of urban ecological systems and GIS to manipulate, analyse, and visualize multisource information in urban ecology. This article focuses on urban ecological security assessment based on multitemporal RS information and GIS. As a case study, the changes in spatial patterns of urban ecological security in Xuzhou City are evaluated during its transformation from a coal mining industrial city to a modern one with decreasing mining production. The popular ‘pressure–state–response’ conceptual model is used to construct an evaluation framework according to geographical properties and data availability. A hierarchical weighted model is adopted to take different factors into account and determine the state of ecological security in the study area. Using Landsat Thematic Mapper/Enhanced Thematic Mapper Plus (TM/ETM+) images as the main RS data source, the derived parameters, such as vegetation index, urban thermal information, and landscape pattern, are integrated to depict the structure and properties of the urban ecological system. Other ancillary information, including mining pressure, water pollution pressure, population density, and ecological flexibility are collected and managed by ArcGIS. The GIS is then used to manage ecological factors derived from remotely sensed data, statistical reports, and geographical data, to evaluate and analyse urban ecological security, and to generate quantitative evaluation and spatial patterns of ecological security. The resulting maps of urban ecological security situations in 1987, 1994, 2000, 2005, and 2007 are analysed in both temporal and spatial dimensions. By analysing urban ecological security in both temporal and spatial dimensions, it is concluded that the ecological security of Xuzhou City is under increasing pressure. Influenced by the pressure of urbanization and mining industry development, the unsafe areas of Xuzhou City have greatly expanded, and with accelerating speed. Finally, suggestions for improving urban ecological security are provided. [ABSTRACT FROM PUBLISHER]

The aggravating urban thermal environment has considerable adverse effects on urban physical environment, energy consumption, and public health. Due to the complexity of factors contributing to the urban thermal environment, traditional statistical methods are insufficient for acquiring data and analyzing the impacts of human activities on the thermal environment, especially for identifying dominant factors. Based on thermal remote sensing imageries and Geographic Information System analysis, we assessed spatial pattern of urban thermal environment in Shanghai in 2008, and analyzed the factors contributing to the generation of urban heat island (UHI) using principal component analysis (PCA). We found that Shanghai had obvious UHI with uneven spatial pattern in 2008. Further, we identified three most important components leading to the variances of Shanghai's UHI: the gradient from man-made to natural land cover, landscape configuration, and anthropogenic heat release. A linear model has thus been successfully constructed, implying that PCA is helpful in identifying major contributors to UHI. The findings are of significance for policy implication to urban thermal environment mitigation. [ABSTRACT FROM AUTHOR]

Land use thematic maps are essential for the implementation of land use planning. China launched the third round of its land use planning in 2003, and the making of land use thematic maps series is one of the innovations for the new planning. The objective of this paper is to provide information about generating county-level land use thematic maps. The study area, Dachang Hui Autonomous County (178 km2), is located in Northern China and shares a boundary with Beijing. Methods for generating thematic land use maps are presented. These thematic maps include an existing land use map, zoning map for proposed land use, prime farmland protection map, zoning map for construction land expansion, planned land consolidation map, and planned major land use projects map. The scale for these maps is 1:50,000. All these maps are useful for researchers and local government, allowing them to be used as a reference for the study of land use mapping and support land resource management and planning. [ABSTRACT FROM AUTHOR]

For a long time areas of Poyang Lake have been threatened by floods. It is therefore important to assess flood vulnerability in this area. A composite flood vulnerability index was developed using an indicator approach to detect spatial distribution and temporal variation of flood vulnerability in the Poyang Lake Ecological Economic Zone (abbreviated to PLEEZ). Thematic maps of flood vulnerability showed a spatially ring-shaped distribution. The flood vulnerability ranking of one unit negatively correlated with the distance between the unit and the lake. Although flood vulnerability in PLEEZ declined significantly, the spatial distribution hardly changed from 1997 to 2006. The degree of flood vulnerability is highly related to exposure; variations in flood vulnerability are influenced by sensitivity and adaptive capacity. Based on correlation analysis, three proxies were identified as determinants of flood vulnerability variation over the past 10 years. This approach could provide policymakers with important flood risk information and entry points for flood management. [ABSTRACT FROM AUTHOR]

Faults provide the path for geothermal natural convection and partially influence the ground surface thermal environment. The land surface temperatures (LSTs) near a fault are higher than in other areas and can indicate the strike trend of an underground fault. However, these anomalies of higher LSTs are not located accurately in the fault centre but near it with some offset, and these LST data may include other thermal information that needs to be eliminated prior to analysis. In this study, LSTs were retrieved from Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper Plus (ETM+) thermal infrared (TIR) images and enhanced with land cover classification and elimination. The spatial patterns of the enhanced images were compared with geophysical prospecting tectonic profiles and with regional geological tectonic maps, revealing the spatial correspondence between the thermal anomalies and the faults. The results indicated that the thermal anomalies are located near the faults and are consistent with the faults' dip planes. [ABSTRACT FROM AUTHOR]

This study focuses on the methodologies of winter wheat yield prediction based on Land Satellite Thematic Map (TM) and Earth Observation System Moderate Resolution Imaging Spectroradiometer (MODIS) imaging technologies in the North China Plain. Routine field measurements were initiated during the periods when the Landsat satellite passed over the study region. Five Landsat TM images were acquired. Wheat yields of the experimental sites were recorded after harvest. Spectral vegetation indices were calculated from TM and MODIS images. The correlation analysis among wheat yield and spectral parameters revealed that TM renormalized difference water index (RDWI) and MODIS near-infrared reflectance had the highest correlation with yield at grain-filling stages. The models from the best-fitting method were used to estimate wheat yield based on TM and MODIS data. The average relative error of the root mean square error (RMSE) of the predicted yield was smaller from TM than from MODIS. [ABSTRACT FROM AUTHOR]

In the work, a simple and reliable algorithm is presented to calculate the fractal dimension of single pixel for the remote sensing images, and the fractal dimension values obtained by the algorithm proposed in this work have positive correlation with the complexity of surface features. On the basis of a scene of Landsat7 ETM+ (i.e., Enhanced Thematic Mapper Plus) data and the proposed algorithm, expert classification models and fractal technique were introduced to identify the ground objects in a Chinese subtropical hilly region, where surface features are very diverse and complex. In the work, the different land use/land cover types, especially the different vegetation categories were successfully identified using the ETM+ image, and this classification has an overall accuracy of 80.25% and a Khat of 0.7738, which are higher than those of the traditional supervised classification. [ABSTRACT FROM AUTHOR]

Abstract: Three wetland distribution maps were drawn using Two Land-sat 5 Thematic Mapper (TM) images from 1991 and 1999, and a China–Brazil Earth Resources Satellite (CBERS)-02B image from 2006. A transition probability matrix was constructed using two wetland distribution maps, one from 1991 and one 1999 and GIS (Geographic Information System). The trends in changes in wetland types and the distribution area were predicted using a Markov model. The prediction model was then tested for relative accuracy and the feasibility of a test. The prediction model’s relative accuracy was 98.5%. The test results showed that both the simulated results and the actual wetland distribution area were in good agreement. Therefore, it is feasible to use the wetlands area transfer matrix to establish a transition probability matrix based on the Markov model and to predict the distribution pattern of the wetland in Yinchuan Plain. The results of this study may be helpful for local governments to develop wetland management policies. [Copyright &y& Elsevier]

Coastal wetland vegetation classification with remotely sensed data has attracted increased attention but remains a challenge. This paper explored a hybrid approach on a Landsat Thematic Mapper (TM) image for classifying coastal wetland vegetation classes. Linear spectral mixture analysis was used to unmix the TM image into four fraction images, which were used for classifying major land covers with a thresholding technique. The spectral signatures of each land cover were extracted separately and then classified into clusters with the unsupervised classification method. Expert rules were finally used to modify the classified image. This research indicates that the hybrid approach employing sub-pixel information, an analyst's knowledge and characteristics of coastal wetland vegetation distribution shows promise in successfully distinguishing coastal vegetation classes, which are difficult to separate with a maximum likelihood classifier (MLC). The hybrid method provides significantly better classification results than MLC. [ABSTRACT FROM AUTHOR]

The Moderate Resolution Imaging Spectroradiometer (MODIS)/Terra daily snow cover product MOD10A1 was compared with in situ climate station measurements and a snow map generated from Landsat Enhanced Thematic Mapper Plus (ETM+) data. Snow-covered area (SCA) dynamics were assessed using the MODIS 8-day snow cover composite product MOD10A2 for the 2001-2005 snow seasons in northern Xinjiang, China. The results indicate that the snow-mapping agreement between MODIS daily snow maps and surface observations is high at 94.6% over the four snow seasons under clear-sky conditions. The snow classification accuracy in a mountainous area was lower than that in a plain area and caused higher omission errors, probably resulting in an underestimation of the SCA. The omission errors were mainly determined by snow depth, land cover types, the terrain and mixed pixels. The cloud agreement was 95.9%, and approximately 4.1% of cloud was misclassified as snow when the sky view at the climate stations was covered by clouds. An improvement was found in suppressing clouds using the 8-day products, with MOD10A2 reducing about 88.4% of the average cloud cover compared with MOD10A1. SCA in northern Xinjiang retrieved using MOD10A2 shows a clear seasonal trend. The air temperature plays an important role in the fractional SCA, and the spatial distribution of the snow cover differs considerably in the various areas in the northern Xinjiang region. [ABSTRACT FROM AUTHOR]

Research into pixel unmixing in remote sensing imagery led to the development of soft classification methods. In this article, we propose a possibilistic c repulsive medoids (PCRMdd) clustering algorithm which attempts to find c repulsive medoids as a minimal solution of a particular objective function. The PCRMdd algorithm is applied to predict the proportion of each land use class within a single pixel, and generate a set of endmember fraction images. The clustering results obtained on multi-temporal Landsat Thematic Mapper (TM)/Enhanced Thematic Mapper plus (ETM+) images of Shanghai city in China reveal the spatio-temporal pattern of Shanghai land use evolvement and urban land spatial sprawl in course of urbanization from 1989 to 2002. The spatial pattern of land use transformation with urban renewal and expansion indicates the urban land use structure is gradually optimized during vigorous urban renewal and large-scale development of Pudong area, which will have an active influence on improving urban space landscape and enhancing the quality of the ecological environment. In addition, accuracy analysis demonstrates that PCRMdd represents a robust and effective tool for mixed-pixel classification on remote sensing imagery to obtain reliable soft classification results and endmember spectral information in a noisy environment. [ABSTRACT FROM AUTHOR]

Abstract: As more than 50% of the human population are situated in cities of the world, urbanization has become an important contributor to global warming due to remarkable urban heat island (UHI) effect. UHI effect has been linked to the regional climate, environment, and socio-economic development. In this study, Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper Plus (ETM+) imagery, respectively acquired in 1989 and 2001, were utilized to assess urban area thermal characteristics in Fuzhou, the capital city of Fujian province in south-eastern China. As a key indicator for the assessment of urban environments, sub-pixel impervious surface area (ISA) was mapped to quantitatively determine urban land-use extents and urban surface thermal patterns. In order to accurately estimate urban surface types, high-resolution imagery was utilized to generate the proportion of impervious surface areas. Urban thermal characteristics was further analysed by investigating the relationships between the land surface temperature (LST), percent impervious surface area, and two indices, the Normalized Difference Vegetation Index (NDVI) and Normalized Difference Built-up Index (NDBI). The results show that correlations between NDVI and LST are rather weak, but there is a strong positive correlation between percent ISA, NDBI and LST. This suggests that percent ISA, combined with LST, and NDBI, can quantitatively describe the spatial distribution and temporal variation of urban thermal patterns and associated land-use/land-cover (LULC) conditions. [Copyright &y& Elsevier]

Abstract: This paper analyzes the spatio-temporal dynamic patterns of farmland and rural settlements from 1990 to 2006 in Su–Xi–Chang region of coastal China experienced dramatic economic and spatial restructuring, using high-resolution Landsat TM (Thematic Mapper) data in 1990, 1995, 2000 and 2006, and socio-economic data from both research institutes and government departments. To examine the spatial patterns of farmland and rural settlements and their change over time, a set of pattern metrics that capture different dimensions of land fragmentation was identified. The outcomes indicated that, to a large extent, land-use change from 1990 to 2006 in Su–Xi–Chang region was characterized by a serious replacement of farmland with urban and rural settlements, construction land, and artificial ponds. Population growth, rapid industrialization and urbanization are the major driving forces of farmland change, and China''s economic reforms played an important role in the transformation of rural settlements. China''s “building a new countryside” is an epoch-making countryside planning policy. The focuses of building a new countryside in coastal China need to be concentrated on protecting the farmland, developing modern agriculture, and building “clean and tidy villages.” Rural construction land consolidation and cultivated land consolidation are two important ways to achieve the building objectives. The authors argue that it is fundamental to lay out a scientific urban–rural integrated development planning for building a new countryside, which needs to pay more attention to making the rural have certain functions serving for the urban. In addition, the cultural elements of idyll and the rural landscape need to be reserved and respected in the process of building a new countryside in coastal China, instead of building a new countryside, which looks more like a city. [Copyright &y& Elsevier]

Owing to the influence of global change, land cover and land use have changed significantly over the last decade in the cold and arid regions of China, such as Madoi County which is located in the source area of the Yellow River. In this paper, land-use/cover change and landscape dynamics are investigated using satellite remote sensing (RS) and a geographical information system (GIS). The objectives of this paper are to determine land-use/cover transition rates between different cover types in the Madoi County over 10 years e.g., from 1990 to 2000. Second, the changes of landscape metrics using various indices and models are quantified. The impact factors of LUCC (Land-Use land cover Change) are systematically identified by integrating remote sensing as well as statistical data, including climate, frozen soil, hydrological data and the socio-economic data. Using 30 m×30 m spatial resolution Landsat (Enhanced) Thematic Mapper (TM/ETM+) data in our study area, nine land cover classes can be discriminated. Our results show that Grassland, Marshes and Water Bodies decrease notably, while oppositely, Sands - Gobi and Barren land increase significantly. The number of lakes with an acreage larger than six hectares decreased from 405 in 1990 to 261 in 2000. Numerous small lakes dried out. The area of grassland with a high cover fraction decreased as well, while the surface area of grassland with a medium level of cover fraction increased. The medium cover fraction grassland mainly originates from high cover fraction grassland. The desertification of land is a serious issue. (ii) The inter-transformations between Grasslands, Barren Land, Sands, Gobi, Water Bodies and Marshes are remarkable. The Shannon-Weaver Diversity Index (SWDI), the Evenness Index (EI) and the extent of Landscape Heterogeneity (LH) has improved. Marshes have become more fragmented hence, with less connected patches. (iii) In the recent 30 years, average annual temperature, the power of evaporation and the index of dryness did increase significantly. Moreover, soil moisture content (SMC) decreased and the drought trend accelerated. The degradation of frozen soil has impacted on the decrease of surface water area and induced a drop in groundwater levels. Monitoring LUCC in sensitive regions would not only benefit from a study of vulnerable ecosystems in cold and high altitude regions, but would provide scientifically based decision-making tools for local governments as well. [ABSTRACT FROM AUTHOR]

Oilfield drilling sites are the potential dispersive pollution source of groundwater, especially to shallow groundwater. The pollution risk assessment in these areas is an important reference for effective groundwater management and protection. The vulnerability assessment alone is not sufficient for groundwater contamination risk assessment. In this study, we developed a comprehensive groundwater pollution risk assessment method for oilfield drilling sites that combine groundwater vulnerability, pollution source hazard, and groundwater value function to produce a more comprehensive result. Consider the oilfield drilling area in Yitong County of Jilin Province, China, as an example. Thematic maps of the three aspects (groundwater vulnerability, pollution source hazard, and groundwater value function) were generated in ArcGIS environment to assess the contamination risk of groundwater in quaternary pore unconfined aquifer. The results show that 9.92% of the study area is characterized as being at high risk. These areas are mainly distributed around the center position of the oil drilling site, floodplains, and the reservoir. The moderate risk area accounts for 21.04% of the total area. It is distributed in the first-level terrace, mainly because of the high function value of groundwater. The remaining 69.04% of the study area is characterized as none and mild risk, mainly distributed in the valleys and terraces. This integrated groundwater contamination risk assessment method is suited for comparative assessment of multiple-point sources of contamination at a regional scale. Finally, the groundwater contamination risk grade distributed in this area provides a reference for effective protection and sustainable supply of groundwater in the oilfield drilling area. [ABSTRACT FROM AUTHOR]

This research selected water soil erosion indicators (land cover, vegetation cover, slope) to assess the risk of soil erosion, ARCMAP GIS ver.9.0 environments and ERDAS ver.9.0 were used to manage and process satellite images and thematic tabular data. Landsat TM images in 2003 were used to produce land/cover maps of the study area based on visual interpreting method and derived vegetation cover maps, and the relief map at the scale of 1:50,000 to calculate the slope gradient maps. The area of water soil erosion was classified into six grades by an integration of slope gradients, land cover types, and vegetation cover fraction. All the data were integrated into a cross-tabular format to carry out the grid-based analysis of soil erosion risk. Results showed that the upper basin of Miyun Reservoir, in general, is exposed to a moderate risk of soil erosion, there is 715,848 ha of land suffered from water soil erosion in 2003, occupied 46.62% of total area, and most of the soil erosion area is on the slight and moderate risk, occupied 45.60 and 47.58% of soil erosion area, respectively. [ABSTRACT FROM AUTHOR]

Due to the existence of fragile karst geo-ecological environments, such as environments with extremely poor soil cover, low soil-forming velocity, and fragmentized terrain and physiognomy, as well as inappropriate and intensive land use, soil erosion is a serious problem in Guizhou Province, which is located in the centre of the karst areas of southwestern China; evaluation of soil loss and spatial distribution for conservation planning is urgently needed. This study integrated the revised universal soil loss equation (RUSLE) with a GIS to assess soil loss and identify risk erosion areas in the Maotiao River watershed of Guizhou. Current land use/cover and management practices were evaluated to determine their effects on average annual soil loss and future soil conservation practices were discussed. Data used to generate the RUSLE factors included a Landsat Thematic Mapper image (land cover), digitized topographic and soil maps, and precipitation data. The results of the study compare well with the other studies and local data, and provide useful information for decision makers and planners to take appropriate land management measures in the area. It thus indicates the RUSLE–GIS model is a useful tool for evaluating and mapping soil erosion quantitatively and spatially at a larger watershed scale in Guizhou. [ABSTRACT FROM AUTHOR]

The purpose of this study is to investigate the oasis landscape fragmentation in northwestern China’s arid regions. Landscape maps of Jinta oasis were compiled by using GIS based on Landsat TM data of 1990 and 2000. Landscape indexes for evaluating fragmentation are patch area, patch density, corridor density and split index. Results indicated many difference. First, between the years 1990 and 2000, the landscape fragmentation in Jinta oasis decreased slightly. Second, the area of the matrix decreased at the class level. The landscape fragmentation of the matrix (bare soil) increased as a result of increased influence of human activities on matrix and was opposite to the irrigated farmland whose area is larger and more aggregated in 2000 than in 1990. Third, dense corridor system is one of the most prominent characteristics of the arid regions. It is one of the key factors resulting in the landscape fragmentation; especially the fragmentation within the same patch types. The corridor density of irrigated farmland, residential area and forestland were quite large in Jinta oasis both in 1990 and 2000. The pattern of Jinta oasis is characterized by agricultural oasis embedded in Gobi and in the desert, where the ecosystem was disturbed strongly by the intense human activities. [ABSTRACT FROM AUTHOR]

Through interpreting Landsat TM images, this study analyzes the spatial distribution of rural settlements in China in 2000. It calculates rural residential land percentage for every 1-km2 cell. The entire country is divided into 33 regions to investigate the spatio-temporal dynamic patterns of rural residential land during the 1990s. According to the remote sensing survey, the rural residential land increased by 7.88 × 105 ha in the 1990s. The increment of rural residential land was 0.55 million ha in 1990–1995 and 0.23 million ha in 1995–2000. In 1990–1995, rural residential land increased dramatically in the eastern regions such as the Yangtze River Delta, Pearl River Delta, and North China Plain, accounting for 80.80% of the national growth; the expansion in the western regions was much more moderate. In 1995–2000, the expansion of rural residential land in eastern regions slowed, accounting for only 58.54% of the increase at the national level, whereas the expansion in the western regions accelerated. Rapid rural residential development resulted from increasing home construction and the limited control on rural land. The great regional disparity reflected the regional economic development and land-use policy change. Our finding shows that nearly 60% of the rural residential area came from cropland. [ABSTRACT FROM AUTHOR]

Abstract: Satellite images have been used extensively to study temporal changes in land use and land cover (LULC) in China. However, few studies have been conducted in the karst areas despite the large area and population involved and the fragile ecosystem. In this study, LULC changes were examined in part of Guizhou Province of southern China from 1991 to 2001 based on Landsat Thematic Mapper (TM) images of November 7, 1991, December 5, 1994, and December 19, 2001. Land surface temperature (LST) and normalized difference vegetation index (NDVI) were computed based on LULC types. The results show that agricultural land decreased, while urban areas expanded dramatically, and forest land increased slightly. Barren land increased from 1991 to 1994, and then decreased from 1994 to 2001. These changes in LULC widened the temperature difference between the urban and the rural areas. The change in LST was mainly associated with changes in construction materials in the urban area and in vegetation abundance both in the urban and rural areas. Vegetation had a dual function in the temperatures of different LULC types. While it could ease the warming trend in the urban or built-up areas, it helped to keep other lands warmer in the cold weather. The study also reveals that due to the government''s efforts on reforestation, rural ecosystems in some of the study area were being restored. The time required for the karst ecosystem to recover was shorter than previously thought. [Copyright &y& Elsevier]

Detecting the morphologic change of intertidal shoals from satellite images is severely hampered by the requirement that they be acquired at the same tidal height. This limitation is circumvented with a new detection method proposed in this paper. It is based on the median line of tidal channels from which the stability of adjoining intertidal shoals is inferred. This method was applied to detect the changes of intertidal shoals in the vicinity of Jiangang Town in Jiangsu Province of East China from seven Thematic Mapper images recorded between 1988 and 2003. The delineated median lines of three tidal channels from the seven images were overlaid with each other in MapInfo. It is found that the net positional change of a channel varies with its section. The closer a section is to the shore, the larger change it underwent. On average, the magnitude of change in a section ranges from 25 to 134 m per annum. Temporarily, all three channels experienced more changes in early than in recent years of the study. The intertidal shoals have shifted their boundaries at a rate of about 110-150 m per annum, which would decrease further offshore. It is concluded that the intertidal shoals have shown some degree of stability over the study period. [ABSTRACT FROM AUTHOR]

The Chinese Loess Plateau is suffering from severe soil erosion. The eco-environmental changes of the plateau are believed to have an important influence on global eco-environmental sustainability; hence, this problem has attracted considerable attention from scientists around the world. This study has two purposes; application of remote sensing (RS) and geographic information system (GIS) techniques in the dynamic analysis of eco-environmental changes in the semiarid zone; and using the Longdong region of the Chinese Loess Plateau as an example, to make dynamic analysis of the eco-environmental changes of the region during the 1986–2004 period and identify controlling factors. Landsat Thematic Mapper (TM) data at a spatial resolution of 30 m were used for analysis. Two training areas were selected in Jingning and Qingcheng counties for analysis using 10-m resolution SPOT and Landsat TM data. The satellite RS images were obtained from the Institute of Remote Sensing Application (IRSA), Chinese Academy of Sciences (CAS). Each images was rectified by Albers Equal Area Conic projection based on 1:50,000 scale topographic maps after spectrum preparation of the images. To make the precision within 1 or 2 pixels, the accurate coordinative control points of the two systems were identified. Then the interpretation key was established based on the land use/cover survey in the study area. The images were classified into six primary environmental types (farmland, forest, grassland, water, construction area, and desert) and 25 sub-types using a visual image interactive interpretation method to obtain vector and attribute data. The resultant accuracy of the land use/cover classification reached 95%. Finally, the transformation areas and ratios of various eco-environmental types in the region were calculated to obtain the transition matrixes of eco-environmental types in the two training areas, Jingning and Qingcheng. This study demonstrates that satellite RS and GIS techniques are effective tools to monitor and analyze the eco-environmental changes in the semiarid region. Visual image interactive interpretation based on GIS technique provides comprehensive information on the direction, rate, and location of eco-environmental changes. The transition matrix model can be used to precisely analyze the variation and rates of the eco-environmental types and their spatial distribution. Great land use changes have taken place Longdong during the 1986–2004 period. These eco-environmental changes were driven by natural and human factors. Natural factors influencing the Longdong region of the Chinese Loess Plateau mainly include temperature, water condition, terrain, soil, and erosion; while human activities include over-cultivation, overgrazing, and fuelwood cutting. As viewed from the extent and severity of the influences, human activities play a very important role in altering the eco-environment of the semiarid region. The study results indicate a need for future research and observation in the semiarid region. [ABSTRACT FROM AUTHOR]

The overall goal of this study is to use medium-resolution satellite imagery to determine recent changes in the landscape of the coastal zone near Sanya in the Province of Hainan, China. A search for suitable satellite imagery revealed that the only way to identify the changes was to use data from three different sensors acquired over a 12-year time period: a 1987 Landsat 5 Thematic Mapper (TM) image, a 1999 Landsat 7 Enhanced Thematic Mapper Plus (ETM+) image, and two SPOT 2 High Resolution Visible (HRV) images acquired in 1991 and 1997. Given that the Landsat and SPOT images have different spatial resolutions and that the spectral bands cover somewhat different spectral ranges, the challenge was how to combine the images in digital format to be able to detect subtle changes in the landscape. Measures of brightness, greenness, and the normalized difference vegetation index (NDVI) were explored using standardized principal components analysis (PCA). Approximately 38 percent of the scene was occupied by water, so tests were performed with the water included and also with the water masked out to remove these low-variance pixels. Factor loadings and input-band contributions were used to interpret component images. Results show that PCA of the visible bands, representing brightness, is the superior approach for identifying new urban features in the landscape. For identification of changes to vegetation, the near-infrared (Nm) bands outperformed NDVI. Selected standardized PCA images with visible and NIB bands are recommended for identifying general changes to an urban landscape using a time-series of imagery acquired by different satellite sensors. Benefits of using a mask are believed to be dependent upon study-site characteristics. [ABSTRACT FROM AUTHOR]

Using remote-sensing data and ground-based data, we constructed an integrated algorithm for estimating regional surface latent heat flux ( LE ) and daily evapotranspiration ( ET d ). In the algorithm, we first used trapezoidal diagrams relating the surface temperature and fractional vegetation cover ( f c ) to calculate the surface temperature–vegetation cover index, a land surface moisture index with a range from 0.0 to 1.0. We then revised a sine function to assess ET d from LE estimated for the satellite's overpass time. The algorithm was applied to farmland in the North China Plain using Landsat Thematic Mapper (TM)/Enhanced Thematic Mapper Plus (ETM + ) data and synchronous surface-observed data as inputs. The estimated LE and ET d were tested against measured data from a Bowen Ratio Energy Balance (BREB) system and a large-scale weighing lysimeter, respectively. The algorithm estimated LE with a root mean square error (RMSE) of 50.1 W m -2 as compared to measurements with the BREB System, and ET d with an RMSE of 0.93 mm d -1 as compared with the measurement by the lysimeter. Sensitivity analysis showed that changing meteorological variables have some influence on LE , while variation of f c has little effect on LE . The test of the model in the study indicated that the improved algorithm provides an accurate and easy-to-handle approach for assessing regional surface LE and ET d . Further improvement can be achieved in the assessments if we increase the accuracy of some key parameters on a large regional scale, such as the minimum stomatal conductance and the atmospheric vapour pressure deficit. [ABSTRACT FROM AUTHOR]

In this paper, we will study the temporal-spatial landscape change from 1978 to 2001 in Daqing City, based on the multi spectral scanner (MSS) and thematic mapper (TM) images of remote sensing (RS) of 1978, 1988, 1992, 1996 and 2001. In order to explain the effects of the component change on the whole landscape, we make a statistic analysis about the transfer probability matrix of the component types of the landscape by using the ARCGIS platform through the overlay analysis of different landscape components. Based on the transfer probability matrix, we calculate the in-transfer ratio, the out-transfer ratio and the contributor ratio of the special transfer process of the main landscape components. The results illustrate that the cultivated-land, grassland, swamp, and alkaline land are the main contributors resulting in the landscape change: the out-transfer ratios of grassland and swamp are much higher than the in-transfer ones; the in-transfer ratio of alkaline land is much higher than the out-transfer one; the in-transfer ratio of the land-lot is always higher than its out-transfer with the highest rate per year, although there is a small difference among the in-transfers and the out-transfers per year. The main landscape changing processes are the salination of cultivated-land, salination or desertification of grassland, salination and degeneration of swamp. Results in this paper can provide scientific basis for investigating the landscape change mechanism of resources-based city. [ABSTRACT FROM AUTHOR]

We introduce a flexible method for creating stereoscopic pairs of images from any interesting sub-area of the same scene of Landsat Thematic Mapper (TM)/Enhanced Thematic Mapper (ETM) and Indian Remote Sensing (IRS)-1C Pan remote sensing data by setting the Z scale. As a test of this method, stereoscopic images were used to study Quaternary deformation along the Tian Shan Orogenic Belt, north-west China. The new stereoscopic images can then provide detailed information of Quaternary deformation structures, including spatial distribution and arrangement pattern of fold structures, fault scarps and displacement of alluvial fans, terraces and drainage systems along active faults, in three dimensions. The strike-slip partitioning has been revealed by interpretation of stereoscopic images within Chinese Tian Shan. Structural interpretations derived from stereoscopic analysis were confirmed to a high degree of accuracy during a subsequent field study. The satellite remote sensing stereoscopic technique is an effective method of analysing Quaternary tectonic deformation in remote arid to semi-arid regions such as the Tian Shan. [ABSTRACT FROM AUTHOR]

The Ms 8.1 Central Kunlun earthquake occurred on 14 November 2001 in northern Tibet, China. Landsat Enhanced Thematic Mapper (ETM) and Thematic Mapper (TM), Système Probatoire de l'Observation de la Terre (SPOT) High Resolution Visible (HRV) panchromatic, and Advanced Space-borne Thermal Emission and Reflection Radiometer (ASTER) visible and near-infrared (VNIR) images before and after the earthquake are compared to detect the spatial distribution of the surface rupture zone. A surface rupture zone at least 400 km long produced by this event can be accurately identified from satellite sensor images. It is the longest surface rupture zone among the co-seismic rupture zones ever reported worldwide. In spatial terms, the surface rupture zone consists of two segments. The eastern segment extends about 350 km striking N75°-85°W (between 91° 07′E and 94° 55′E), and the western segment bends south-west extending more than 70 km to west of Sun Lake with a strike of N50°E-N70°W (west of 91° 07′E). Analyses of satellite sensor images are well consistent with ground data obtained from the field survey. High spatial resolution satellite remote sensing techniques, therefore, provide a rapid and powerful tool to detect the co-seismic surface rupture in the remote and high mountainous Tibet area. [ABSTRACT FROM AUTHOR]

A remote sensing yield estimation of aboveground phytomass in Hulunbeiermeng Leymus chinensis grassland, Inner Mongolia, China was made using Landsat Thematic Mapper data. Starting with the ecological principles of plant population, and based on observed data in fixed positions of the experimental region, a synchronous revision of the practical measurement of grass yield was made by using a logistic equation for the case that the measurement time and the satellite pass time are not synchronous. Statistical analysis results show that the interrelation between the revised grass yield and Ratio Vegetation Index (RVI) has been considerably enhanced. The correlation coefficient, r =0.856-0.944, shows a remarkable positive correlation, while the correlation coefficient of the unrevised grass yield is only 0.679-0.817, which does not pass the notability test of the α[sub 0.01] level. The forecasting result of the grass yield of the Leymus chinensis grassland, in Ewenk Banner of Hulunbeiermeng, Inner Mongolia, China, also shows that the forecast value agrees well with the measured value. [ABSTRACT FROM AUTHOR]

In order to accelerate the reconnaissance of mineral resources in Xingjiang Uygur Autonomous Region of China, multispectral Thematic Mapper (TM) data were used to delineate hydrothermal alteration related to polymetallic mineralization. In addition to the use of commercial image processing packages, new image processing software based on geological environment and spectral information have been developed. The Gram-Schmidt Orthogonal Projection (GSOP) method used in linear algebra for signal processing was adopted for our study. The kernel part of the algorithm is that the GSOP uses least mean square deviation of mathematical expectation in linear vector space (Hilbert space). In a vector space, one base axis is established and other transitional vectors are inputted to evaluate the effectiveness of GSOP. Satisfactory results have been achieved by applying this method to differentiate hydrothermal alterations in the Kangxiwa area of the Kunlun mountains, western China. The red colour in the image shows Pb-Zn-Cu-Au-Ag polymetallic mineralization zones, which were confirmed by field investigations and sample analyses in 1998. [ABSTRACT FROM AUTHOR]