1,720,970 research outputs found
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
Using spectral and textural information to detect and map Parthenium hysterophorus L. in Mtubatuba, South Africa.
Full text linkMasters Degree. University of KwaZulu-Natal, Pietermaritzburg.Parthenium hysterophorus L. (parthenium) is an alien invasive species that has had severe environmental and human impacts in three continents. Sustainable management and control of the invasive species requires an understanding of its distribution and rate of spread. Our first study focuses on the use of spectral information of commercial sensor RapidEye and freely available Sentinel-2 imagery to detect parthenium and other land cover classes. Sentinel-2 outperformed RapidEye to classify most land cover classes, with an overall classification accuracy of 82% and 71%, respectively. This was likely due to the superior spectral resolution of Sentinel-2. However, RapidEye performed better when classifying parthenium, potentially due to the fact that there were some patches that were smaller than the Sentinel-2 spatial resolution. Nonetheless, Sentinel-2 represents a good opportunity to map larger parthenium stands and other land cover types. The second study focused on mapping parthenium using texture analysis and SPOT-6 imagery. It compared the mapping ability between the panchromatic and multispectral bands using the PLS-DA algorithm. The panchromatic band achieved a higher overall classification accuracy than the multispectral bands (77% and 73%, respectively). Furthermore, the panchromatic band achieved superior performance compared to multispectral bands for parthenium. This may be attributed to the higher spatial resolution of the panchromatic band as it has been shown that finer spatial resolution is beneficial in texture analysis. Overall texture analysis using SPOT 6 imagery was the most successful combination which allowed us to accurately map parthenium distribution
Predicting inter-seasonal aboveground grass biomass using Sentinel-2 MSI and machine learning in the Umngeni catchment, KwaZulu-Natal, South Africa.
Full text linkMasters Degree. University of KwaZulu-Natal, Pietermaritzburg.Abstract available in PDF
Commercial forest species discrimination and mapping using image texture computed from WorldView-2 pan sharpened imagery in KwaZulu-Natal, South Africa.
Full text linkMasters Degree. University of KwaZulu-Natal, Pietermaritzburg.Forest species discrimination is vital for precise and dependable information, essential for
commercial forest management and monitoring. Recently, the adoption of remote sensing
approaches has become an important source of information in commercial forest management.
However, previous studies have utilized spectral data or vegetation indices to detect and map
commercial forest species, with less focus on the spatial elements. Therefore, this study using
image texture aims to discriminate commercial forest plantations (i.e. A. mearnsii, E. dunnii, E.
grandis and P. patula) computed from a 0.5m WorldView-2 pan-sharpened image in
KwaZuluNatal, South Africa. The first objective of the study was to discriminate commercial
forest species using image texture computed from a 0.5m WorldView-2 pan-sharpened image and
the Partial Least Squares Discriminate Analysis (PLS-DA) algorithm. The results indicated that
the image texture model (overall accuracy (OA) = 77%, kappa = 0.69) outperformed both the
vegetation indices model (OA = 69%, kappa = 0.59) and raw spectral bands model (OA = 64%,
kappa = 0.52). The most successful texture parameters selected by PLS-DA were mean,
correlation, and homogeneity, which were primarily computed from the red-edge, NIR1 and NIR2
bands. Lastly, the 7x7 moving window was commonly selected by the PLS-DA model when
compared to the 3x3 and 5x5 moving windows. The second objective of the study was to explore
the utility of texture combinations computed from a fused 0.5m WorldView-2 image in
discriminating commercial forest species in conjunction with the PLS-DA and Sparse Partial Least
Squares Discriminate Analysis (SPLS-DA) algorithm. The accuracies achieved using SPLS-DA
model, which performed variable selection and dimension reduction simultaneously yielded an
overall accuracy of 86%. In contrast, the PLS-DA and variable importance in the projection (VIP)
produced an overall classification accuracy of 81%. Generally, the finding of this study
demonstrated the ability of image texture to precisely provide adequate information that is
essential for tree species mapping and monitoring
Examining the socio-economic impacts of water service delivery in the Rookdale rural community of KwaZulu-Natal, South Africa.
No full textMasters Degree. University of KwaZulu-Natal, Pietermaritzburg.Two abstracts available in PDF.Supervisor on WMS appears as: Shenelle Janalyn Sewell
Informing reforestation practices : quantifying live forest above ground biomass of a randomly mixed natural forest plantation using GIS and remote sensing models.
Full text linkMaster of Science in Geography. University of KwaZulu-Natal, Pietermaritzburg, 2017.Restoration of natural forests is viewed as one of the effective and viable approaches for mitigating and adapting to climate change. However, maximising the carbon capture and storage of naturally mixed forest plantations is currently a challenge for forest managers, due to the complex nature of species interaction and environmental controls that inhibit the distribution and growth rates of certain species. Monitoring the amount of carbon captured and stored in natural forest ecosystem is vital in verifying their productivity and detecting areas of concern that could be unproductive. In this study the productivity of the Buffelsdraai reforestation site was monitored using above ground biomass (AGB) of planted trees. While there are traditional approaches for monitoring forest AGB with high accuracy, these approaches are unfavourable because they are timeous and spatially restricted. Fortunately, the inception of remote sensing has provided viable approaches for estimating forest AGB at a synoptic scale and with low cost. The purpose of this study was to apply remote sensing and GIS models to quantify the ecological benefits of the Buffelsdraai reforestation project on AGB productivity. The study investigated the potential of the spatially optimised three band texture combinations in predicting and mapping forest AGB and structural diversity. This research study has potential to contribute to the importance of spatial planning and design of naturally mixed forest plantations to improve their diversity and AGB productivity. The first part of the study focused on mapping the temporal and spatial distribution of forest AGB using spatially optimised three band texture combinations computed from SPOT-6 imagery and random forest regression algorithm. The results indicated that the three band texture combinations were superior in predicting forest AGB compared to raw texture bands and two band texture combinations. The second part of the thesis focussed on assessing the effects of forest structural diversity and topographic variables on forest AGB productivity using GIS and remotely sensed data. The forest structural diversity measures were predicted using three band texture combinations modelled using random forest and stochastic gradient boosting algorithms. The topographic variables were derived using the digital elevation model in ArcMap 10.3. Results indicated that random forest yielded overall higher accuracies in predicting the forest structural diversity measures compared to stochastic gradient boosting. More importantly, the study showed that forest diversity and topographic variables have significant influences on forest AGB variability. Overall the study provided insight into the management of natural forests and to the importance of spatial planning and design of these mixed forests
Remote sensing applications for monitoring the spatial distribution of Bracken fern (Pteridium) in the Cathedral Peak : Drakensberg, South Africa.
Full text linkAbstract available in PDF file
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