121,404 research outputs found
Government Information and Open Content Licensing: An Access and
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143593.pdf (publisher's version ) (Open Access)Radboud Universiteit Nijmegen, 13 oktober 2015Promotor : Verhoeven, L.T.W. Co-promotor : Segers, P.C.J.167 p
Entropy, complexity, and spatial information
We pose the central problem of defining a measure of complexity, specifically for spatial systems in general, city systems in particular. The measures we adopt are based on Shannon's (in Bell Syst Tech J 27:379-423, 623-656, 1948) definition of information. We introduce this measure and argue that increasing information is equivalent to increasing complexity, and we show that for spatial distributions, this involves a trade-off between the density of the distribution and the number of events that characterize it; as cities get bigger and are characterized by more events-more places or locations, information increases, all other things being equal. But sometimes the distribution changes at a faster rate than the number of events and thus information can decrease even if a city grows. We develop these ideas using various information measures. We first demonstrate their applicability to various distributions of population in London over the last 100 years, then to a wider region of London which is divided into bands of zones at increasing distances from the core, and finally to the evolution of the street system that characterizes the built-up area of London from 1786 to the present day. We conclude by arguing that we need to relate these measures to other measures of complexity, to choose a wider array of examples, and to extend the analysis to two-dimensional spatial systems
Is spatial information in ICT data reliable?
An increasing number of human activities are studied using data produced by
individuals' ICT devices. In particular, when ICT data contain spatial
information, they represent an invaluable source for analyzing urban dynamics.
However, there have been relatively few contributions investigating the
robustness of this type of results against fluctuations of data
characteristics. Here, we present a stability analysis of higher-level
information extracted from mobile phone data passively produced during an
entire year by 9 million individuals in Senegal. We focus on two
information-retrieval tasks: (a) the identification of land use in the region
of Dakar from the temporal rhythms of the communication activity; (b) the
identification of home and work locations of anonymized individuals, which
enable to construct Origin-Destination (OD) matrices of commuting flows. Our
analysis reveal that the uncertainty of results highly depends on the sample
size, the scale and the period of the year at which the data were gathered.
Nevertheless, the spatial distributions of land use computed for different
samples are remarkably robust: on average, we observe more than 75% of shared
surface area between the different spatial partitions when considering activity
of at least 100,000 users whatever the scale. The OD matrix is less stable and
depends on the scale with a share of at least 75% of commuters in common when
considering all types of flows constructed from the home-work locations of
100,000 users. For both tasks, better results can be obtained at larger levels
of aggregation or by considering more users. These results confirm that ICT
data are very useful sources for the spatial analysis of urban systems, but
that their reliability should in general be tested more thoroughly.Comment: 11 pages, 9 figures + Appendix, Extended version of the conference
paper published in the proceedings of the 2016 Spatial Accuracy Conference, p
9-17, Montpellier, Franc
Improving Bag-of-Words model with spatial information
Bag-of-Words (BOW) models have recently become popular for the task of object recognition, owing to their good performance and simplicity. Much work has been proposed over the years to improve the BOW model, where the Spatial Pyramid Matching technique is the most notable. In this work, we propose three novel techniques to capture more re_ned spatial information between image features than that provided by the Spatial Pyramids. Our techniques demonstrate a performance gain over the Spatial Pyramid representation of the BOW model
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Image segmentation using fuzzy clustering incorporating spatial information
Effective image segmentation cannot be achieved for a fuzzy clustering algorithm based on using only pixel intensity, pixel locations or a combination of the two. Often if both pixel intensity and pixel location are combined, one feature tends to minimize the effect of other, thus degrading the resulting segmentation. This paper directly addresses this problem by introducing a new algorithm called image segmentation using fuzzy clustering incorporating spatial information (FCSI), which merges the segmented results independently generated by fuzzy clustering-based on pixel intensity and the location of pixels. Qualitative results show the superiority of the FCSI algorithm compared with the fuzzy c-means (FCM) algorithm for all three alternatives, clustering using only pixel intensity, pixel locations and a combination of the two
Extracting spatial information : grounding, classifying and linking spatial expressions
This paper is concerned with the tagging of spatial expressions in German newspaper articles, assigning a meaning to the expression and classifying the usages of the spatial expression and linking the derived referent to an event description. In our system, we implemented the activation of concepts in a very simple fashion, a concept is activated once (with a cost depending on the item that activated it) and is left activated thereafter. As an example, a city also activates the nodes for the region and the country it is part of, so that cities from one country are chosen over cities from different countries. A test corpus of 12 German newspaper articles was tested regarding several disambiguation strategies. Disambiguation was carried out via a beam search to find an approximately cost-optimal solution for the conflict set of potential grounding candidates for the tagged spatial expression. Test showed that the disambiguation strategies improved accuracy significantly
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