1,721,173 research outputs found

    Instability of remote sensing based ecological index (RSEI) and its improvement for time series analysis

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    With the rapid development of remote sensing technology, the monitoring of land surface ecological status (LSES) based on remote sensing has made remarkable progress, which has a positive contribution on improving the regional ecological environment and promoting the realization of Sustainable Development Goals (SDGs). Among them, the proposed Remote Sensing-based Ecological Index (RSEI) becomes the most widely used model in the current application of remote sensing-based LSES monitoring due to its complete derived from remote sensing images and no subjective intervention. RSEI is not flawless either, and it still suffers from some uncertainties in its application in multiple scenarios. However, compared to the extensive applied research, work on the instability assessment and improvement of RSEI is particularly scarce and urgently needed. Therefore, in this paper, we analyzed the possible instabilities in the RSEI calculation process and proposed various inversion models to evaluate their accuracy and stability in time-series LSES monitoring. The results indicated that the existing normalized RSEI is relatively stable for the characterization of single-phase LSES, however, there is a high risk in the time-series analysis or cross-regional comparison due to the interference of component extremes. The standard deviation discretized DRSEIs proposed in this paper perform better in both single-phase and long-term dynamics LSES assessments and are more consistent with the real land cover changes. Also, compared with the approach that measures LSES dynamics using time-series regional RSEI mean values, the DRSEIs change detection results can reveal the spatial heterogeneity of regional LSES dynamics more effectively and provide a finer reference for the formulation and implementation of ecological protection policies

    Going Beyond Counting First Authors in Author Co-citation Analysis

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    The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed

    Variations on the Author

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    “Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship

    Appropriate Similarity Measures for Author Cocitation Analysis

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    We provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis

    Dispelling the Myths Behind First-author Citation Counts

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    We conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more sophisticated methods

    Author Index

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