1,720,971 research outputs found
Multi-index image differencing method for flood water detection
No full textThis study presents a remote sensing methodology to detect floods with a change detection approach based on image differencing of several water-related indexes. The proposed methodology is expected to integrate the strengths of each individual index and considers the agreement level among outputs obtained by different indexes as an indicator of overall uncertainty.
The analysis of data frequency distribution is used to obtain thresholds to implement data slicing and production of thematic maps. By considering different magnitudes of change, the proposed method is expected to be sensitive to detect different types of flood-related changes, including the detection of recent tracks of water presence. This is particularly interesting for those situations whenever it is impossible to obtain cloud-free satellite images immediately after a flood event, which is often the case given the limitations of optical sensors.
The methodology has been applied to a fluvial flood event occurred in the surrounding of a natural lagoon in the Aveiro region (Portugal). Landsat 7 ETM+ and Landsat 8 OLI surface reflectance products were used as inputs. Sentinel 1 GRD data was used for comparison purposes. Results indicate an overall consistency, which allows us to expect the proposed method is replicable for other events and areas
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe 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
Full text link“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
Full text linkWe 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
Full text linkWe 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
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
Continuous flood monitoring using on-demand SAR data acquired with different geometries: Methodology and test on COSMO-SkyMed images
No full textWhen large floods occur, satellite data are useful for providing emergency managers with frequent and synoptic
maps of affected areas, even on a daily basis. Only the use of on-demand SAR data enables the high-resolution
monitoring of flood events through acquisitions performed day and night, and regardless of cloud cover, over
different areas. However, continuous flood mapping generally requires combining images acquired with different
sensor parameters. In turn, this makes data interpretation and processing quite challenging and might require a
time-consuming visual analysis activity, which contrasts with the requirement of fast daily delivery of flood maps
to end-users.
This paper presents a new methodology designed to perform continuous flood monitoring in near real-time
using on-demand SAR data. It implements a complete workflow, ranging from satellite tasking and pre-flood
reference image collection to flood map generation. The core of the methodology is a new automated algorithm
based on change detection that can work with data captured with different imaging geometries. The algorithm
is designed to discriminate the change due to the change in the scenario from that due to possible
differences in the acquisition parameters of the images. It applies different image processing techniques, such as
clustering, histogram equalization, fuzzy logic, and region growing, and implements two electromagnetic
models. The algorithm is complemented by a post processing step whose objective is to make the daily flood
maps consistent with each other. The methodology was tested on a major flood that hit Italy (Emilia-Romagna
region) in May 2023, using COSMO-SkyMed data and benchmark flood maps derived from optical data and from
the Rapid Mapping component of the Copernicus Emergency Management Service (CEMS). Additionally, it was
applied to another flood event that occurred in Italy (Tuscany region) in November 2023, for which benchmark
CEMS products were also available, to further assess its reliability. Across these case studies, the algorithm
achieved F1-scores ranging from 76% to 90%, demonstrating that, even when using data acquired with geometries
that are non-optimal for flood mapping, the methodology produces reliable results. These results are
consistent with those reported in the literature for change detection methods applied to acquisitions from the
same orbit and for semi-automated supervised workflows such as those used by CEMS.
The pseudocode of the algorithm is available at: https://github.com/LucaP-CIMA/AUTOWADE2.0-pseu
docode
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
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