scholarly journals Exploring Semi-Automatic Map Labeling

2019 ◽  
Author(s):  
Fabian Klute ◽  
Guangping Li ◽  
Raphael Löffler ◽  
Martin Nöllenburg ◽  
Manuela Schmidt
Keyword(s):  
Map Labeling

scholarly journals First 1-M Resolution Land Cover Map Labeling the Overlap in the 3rd Dimension: The 2018 Map for Wallonia

Data ◽  
2020 ◽  
Vol 5 (4) ◽  
pp. 117
Author(s):  
Céline Bassine ◽  
Julien Radoux ◽  
Benjamin Beaumont ◽  
Taïs Grippa ◽  
Moritz Lennert ◽  
...  
Keyword(s):  
Land Cover ◽  
Land Use Planning ◽  
Climate Modeling ◽  
Decision Rules ◽  
Ancillary Data ◽  
Map Labeling ◽  
Small Water ◽  
Very High Spatial Resolution ◽  
Land Cover Map ◽  
Land Cover Maps

Land cover maps contribute to a large diversity of geospatial applications, including but not limited to land management, hydrology, land use planning, climate modeling and biodiversity monitoring. In densely populated and highly fragmented landscapes as observed in the Walloon region (Belgium), very high spatial resolution is required to depict all the infrastructures, buildings and most of the structural elements of the semi-natural landscapes (like hedges and small water bodies). Because of the resolution, the vertical dimension needs explicit handling to avoid discontinuities incompatible with many applications. For example, how to map a river flowing under a bridge? The particularity of our data is to provide a two-digit land cover code to label all the overlapping items. The identification of all the overlaps resulted from the combination of remote sensing image analysis and decision rules involving ancillary data. The final product is therefore semantically precise and accurate in terms of land cover description thanks to the addition of 24 classes on top of the 11 pure land cover classes. The quality of the map has been assessed using a state-of-the-art validation scheme. Its overall accuracy is as high as 91.5%, with an average producer’s accuracy of 86% and an average user’s accuracy of 91%.

New Bounds on Map Labeling with Circular Labels

2004 ◽  
pp. 606-617 ◽  
Author(s):  
Minghui Jiang ◽  
Sergey Bereg ◽  
Zhongping Qin ◽  
Binhai Zhu
Keyword(s):  
Map Labeling

Focus+context map labeling with optimized clutter reduction

2019 ◽  
Vol 5 (2-3) ◽  
pp. 158-177 ◽  
Author(s):  
Benjamin Niedermann ◽  
Jan-Henrik Haunert
Keyword(s):  
Map Labeling ◽  
Clutter Reduction

scholarly journals Folk Perception of African American English Regional Variation

2017 ◽  
Vol 5 (1) ◽  
pp. 1-16 ◽  
Author(s):  
David Mitchell ◽  
Marivic Lesho ◽  
Abby Walker
Keyword(s):  
African American ◽  
African Americans ◽  
American English ◽  
African American Vernacular English ◽  
Uniform Structure ◽  
Linguistic Features ◽  
Map Labeling ◽  
Perceptual Dialectology ◽  
Vernacular English ◽  
The Us

Contrary to previous “sociolinguistic folklore” that African American (Vernacular) English has a uniform structure across different parts of the US, recent studies have shown that it varies regionally, especially phonologically (Wolfram, 2007; Thomas & Wassink, 2010). However, there is little research on how Americans perceive AAE variation. Based on a map-labeling task, we investigate the folk perception of AAE variation by 55 participants, primarily African Americans in Columbus, Ohio. The analysis focuses on the dialect regions recognized by the participants, the linguistic features associated with different regions, and the attitudes associated with these beliefs. While the perceived regional boundaries mostly align with those identified by speakers in previous perceptual dialectology studies on American English, the participants consistently identified linguistic features that were specific to AAE. The participants recognized substantial phonological and lexical variation and identified “proper” dialects that do not necessarily sound “white”. This study demonstrates the value of considering African Americans’ perspectives in describing African American varieties of English.

scholarly journals A Unified Model and Algorithms for Temporal Map Labeling

Algorithmica ◽  
2020 ◽  
Vol 82 (10) ◽  
pp. 2709-2736
Author(s):  
Andreas Gemsa ◽  
Benjamin Niedermann ◽  
Martin Nöllenburg
Keyword(s):  
Approximation Algorithms ◽  
Traffic Control ◽  
Constant Factor ◽  
Maximization Problem ◽  
Fixed Position ◽  
Time Intervals ◽  
Map Labeling ◽  
Polynomial Time Algorithms ◽  
Dynamic Map ◽  
Flexible Model

Abstract We consider map labeling for the case that a map undergoes a sequence of operations such as rotation, zoom and translation over a specified time span. We unify and generalize several previous models for dynamic map labeling into one versatile and flexible model. In contrast to previous research, we completely abstract from the particular operations and express the labeling problem as a set of time intervals representing the labels’ presences, activities and conflicts. One of the model’s strength is manifested in its simplicity and broad range of applications. In particular, it supports label selection both for map features with fixed position as well as for moving entities (e.g., for tracking vehicles in logistics or air traffic control). We study the active range maximization problem in this model. We prove that the problem is -complete and [1]-hard, and present constant-factor approximation algorithms. In the restricted, yet practically relevant case that no more than k labels can be active at any time, we give polynomial-time algorithms as well as constant-factor approximation algorithms.

A New Technology for Interactive Online Mapping with Vector Markup and XML

2000 ◽  
pp. 65-77 ◽  
Author(s):  
Ilya Zavlavsky
Keyword(s):  
New Technology ◽  
Multiple Point ◽  
Markup Language ◽  
Map Labeling ◽  
Scalable Vector Graphics ◽  
Geographic Data ◽  
Online Mapping ◽  
Extensible Markup ◽  
Point Line ◽  
Client Side

As Internet cartography matures from static map images to interactive and animated maps, and embraces extensive GIS functionality, the limitations of presenting Web maps as image files become obvious. In this paper, a new technology for Internet cartography is demonstrated that uses direct vector rendering in a browser to create highly interactive virtual maps from distributed sources of geographic data. This technology is made possible by the advent of XML (eXtensible Markup Language) and XML applications for 2D vector rendering such as VML (Vector Markup Language) and SVG (Scalable Vector Graphics). AXIOMAP – Application of XML for Interactive Online Mapping – is a Web map publishing kit and a customizable virtual map interface that allows for the display and manipulation of multiple point, line and area layers, database query, choropleth mapping, hyperlinking, map labeling and annotation. To render maps in a Web browser (Internet Explorer 5, in the current version), AXIOMAP generates VML shapes “on the fly” from XML-encoded geographic data that can physically reside on different servers. A thin client-side solution, AXIOMAP provides for better interactivity than traditional map serverbased approaches. The paper explains the functionality of AXIOMAP, the technology behind it, and presents several applications. A free version of the software can be downloaded from www.elzaresearch.com/landv/.

scholarly journals Optimizing active ranges for consistent dynamic map labeling

2010 ◽  
Vol 43 (3) ◽  
pp. 312-328 ◽  
Author(s):  
Ken Been ◽  
Martin Nöllenburg ◽  
Sheung-Hung Poon ◽  
Alexander Wolff
Keyword(s):  
Map Labeling ◽  
Dynamic Map

scholarly journals BEYOND MAXIMUM INDEPENDENT SET: AN EXTENDED MODEL FOR POINT-FEATURE LABEL PLACEMENT

2016 ◽  
Vol XLI-B2 ◽  
pp. 109-114
Author(s):  
Jan-Henrik Haunert ◽  
Alexander Wolff
Keyword(s):  
Classical Problem ◽  
Independent Set ◽  
Exact Algorithm ◽  
Maximum Independent Set ◽  
Extended Model ◽  
Optimal Solutions ◽  
Maximum Weight ◽  
Map Labeling ◽  
Label Placement ◽  
Point Feature

Map labeling is a classical problem of cartography that has frequently been approached by combinatorial optimization. Given a set of features in the map and for each feature a set of label candidates, a common problem is to select an independent set of labels (that is, a labeling without label–label overlaps) that contains as many labels as possible and at most one label for each feature. To obtain solutions of high cartographic quality, the labels can be weighted and one can maximize the total weight (rather than the number) of the selected labels. We argue, however, that when maximizing the weight of the labeling, interdependences between labels are insufficiently addressed. Furthermore, in a maximum-weight labeling, the labels tend to be densely packed and thus the map background can be occluded too much. We propose extensions of an existing model to overcome these limitations. Since even without our extensions the problem is NP-hard, we cannot hope for an efficient exact algorithm for the problem. Therefore, we present a formalization of our model as an integer linear program (ILP). This allows us to compute optimal solutions in reasonable time, which we demonstrate for randomly generated instances.

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