Jochen Schiewe

Bio: Jochen Schiewe is an academic researcher from HafenCity University Hamburg. The author has contributed to research in topics: Geovisualization & Visualization. The author has an hindex of 13, co-authored 60 publications receiving 673 citations. Previous affiliations of Jochen Schiewe include Leibniz University of Hanover & City University London.

Segmentation of high-resolution remotely sensed data - concepts, applications and problems

Abstract: Segmentation algorithms have already been recognized as a valuable and complementary approach that similar to human operators perform a region-based rather than a point-based evaluation of high-resolution and multi-source remotely sensed data. Goal of this paper is to summarize the state-of-the-art of respective segmentation methods by describing the underlying concepts which are rather complex in the case of processing remotely sensed data, demonstrating various applications (automatical object recognition, signalbased fusion as support for visual interpretation, and estimation of the terrain surface from Digital Surface Models), and identifying yet existing problems and further research and development needs.

How to assess visual communication of uncertainty? a systematic review of geospatial uncertainty visualisation user studies

Abstract: For decades, uncertainty visualisation has attracted attention in disciplines such as cartography and geographic visualisation, scientific visualisation and information visualisation. Most of this research deals with the development of new approaches to depict uncertainty visually; only a small part is concerned with empirical evaluation of such techniques. This systematic review aims to summarize past user studies and describe their characteristics and findings, focusing on the field of geographic visualisation and cartography and thus on displays containing geospatial uncertainty. From a discussion of the main findings, we derive lessons learned and recommendations for future evaluation in the field of uncertainty visualisation. We highlight the importance of user tasks for successful solutions and recommend moving towards task-centered typologies to support systematic evaluation in the field of uncertainty visualisation.

Evaluating the effect of visually represented geodata uncertainty on decision-making: systematic review, lessons learned, and recommendations

Abstract: For many years, uncertainty visualization has been a topic of research in several disparate fields, particularly in geographical visualization (geovisualization), information visualization, and sci...

Automated generation of an historic 4d city model of hamburg and its visualisation with the GE engine

Abstract: Current 3D city models are already available for many cities world-wide. However, the production of historical city models is still in its infancy. In this paper a procedure is presented that combines different data sources in order to derive individual 3D city models of different time periods using the example of the Free and Hanseatic City of Hamburg. A wooden model of the city from the year 1644 and an official map from 1859 have been used as a basis for the generation of the 4D city model. The physical model (~1:1000) was scanned by a fringe projection system for 3D modelling, while the digitized data from the map were combined with height information from different data sources. These two geo-referenced 3D city models were used to derive further epochs (1200, 1400, 1589 and 1700) using different historical bird's-eye views (isometric views) of the city. For interactive navigation and visualization of the 4D city model a program was developed using the Google Earth Application Programming Interface.

Empirical Studies on the Visual Perception of Spatial Patterns in Choropleth Maps

Abstract: An essential purpose of choropleth maps is the visual perception of spatial patterns (such as the detection of hot spots or extreme values). This requires an effective and as intuitive as possible comparison of color values between different regions. Accordingly, a number of design requirements must be considered. Due to the lack of empirical evidence regarding some elementary design aspects, an online study with 260 participants was conducted. Three closely related effects were examined: the “dark-is-more bias” (i.e., the intuitive ranking of color lightness), the “area-size bias” (i.e., the neglect of small areas, since these are less dominant in perception than larger ones) and the “data-classification effect” (i.e., attention to data classification when interpreting spatial patterns). For each hypothesis, one or more maps in connection with single or multiple choice questions were presented. Users should detect extreme values, central tendencies or homogeneities of values as well as comment on their task solving certainty. In general, the hypotheses regarding the mentioned effects could be confirmed by statistical analysis. The results are used to derive conclusions and topics for future research. In particular, further comparative empirical studies are recommended to determine the best possible map types for given applications, also considering alternatives to choropleth maps.

Using Multivariate Statistics

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Object based image analysis for remote sensing

Abstract: Remote sensing imagery needs to be converted into tangible information which can be utilised in conjunction with other data sets, often within widely used Geographic Information Systems (GIS). As long as pixel sizes remained typically coarser than, or at the best, similar in size to the objects of interest, emphasis was placed on per-pixel analysis, or even sub-pixel analysis for this conversion, but with increasing spatial resolutions alternative paths have been followed, aimed at deriving objects that are made up of several pixels. This paper gives an overview of the development of object based methods, which aim to delineate readily usable objects from imagery while at the same time combining image processing and GIS functionalities in order to utilize spectral and contextual information in an integrative way. The most common approach used for building objects is image segmentation, which dates back to the 1970s. Around the year 2000 GIS and image processing started to grow together rapidly through object based image analysis (OBIA - or GEOBIA for geospatial object based image analysis). In contrast to typical Landsat resolutions, high resolution images support several scales within their images. Through a comprehensive literature review several thousand abstracts have been screened, and more than 820 OBIA-related articles comprising 145 journal papers, 84 book chapters and nearly 600 conference papers, are analysed in detail. It becomes evident that the first years of the OBIA/GEOBIA developments were characterised by the dominance of ‘grey’ literature, but that the number of peer-reviewed journal articles has increased sharply over the last four to five years. The pixel paradigm is beginning to show cracks and the OBIA methods are making considerable progress towards a spatially explicit information extraction workflow, such as is required for spatial planning as well as for many monitoring programmes.

Smart and Digital City: A Systematic Literature Review

Abstract: The concept of Smart City embraces several definitions depending on the meanings of the word “smart”: intelligent city , knowledge city , ubiquitous city , sustainable city , digital city , etc. Many definitions of Smart City exist, but no one has been universally acknowledged yet. From literature analysis it emerges that Smart City and Digital City are the most used terminologies in literature to indicate the smartness of a city. This Chapter explores the literature about Smart City and Digital City from 1993 to the end of 2012 in order to investigate how these two concepts were born, how they have developed, which are the shared features and differences between them. To accomplish with these goals, three steps were followed: (1) to set up a search strategy for systematic literature review to collect a representative subset of papers about Smart City and Digital City using Google Scholar; (2) to store the selected subset in an ad-doc database to synthesize the literature review; (3) to organize the literature review subset to extract quantitative and qualitative data and information about Smart City and Digital City evolution. The author proposes a literature review taxonomy through five specific analysis: (1) time analysis, to explore the causes of the trend of Smart City and Digital City literature in the latest twenty years; (2) terminology analysis, to examine how and where these two ideas were born and what have been the main events influenced their development; (3) definitions analysis, to select and compare the most cited and validated definitions of Smart City and Digital City trying to identify similarities, differences or overlaps between these two concepts; (4) typology analysis, to investigate if Smart City and Digital City are included into a specific urban strategy pursued by government or if they face specific urban problems without a comprehensive framework; (5) geographic analysis, to understand where are the largest concentrations of Smart Cities and Digital Cities in the world and which are their main characteristics and best practices.