Error processes in the integration of digital cartographic data in geographic information systems.

Errors within a Geographic Information System (GIS) arise from several factors. In the first instance receiving data from a variety of different sources results in a degree of incompatibility between such information. Secondly, the very processes used to acquire the information into the GIS may in fact degrade the quality of the data. If geometric overlay (the very raison d'etre of many GISs) is to be performed, such inconsistencies need to be carefully examined and dealt with. A variety of techniques exist for the user to eliminate such problems, but all of these tend to rely on the geometry of the information, rather than on its meaning or nature. This thesis explores the introduction of error into GISs and the consequences this has for any subsequent data analysis. Techniques for error removal at the overlay stage are also examined and improved solutions are offered. Furthermore, the thesis also looks at the role of the data model and the potential detrimental effects this can have, in forcing the data to be organised into a pre-defined structure

Investigation of techniques for inventorying forested regions. Volume 2: Forestry information system requirements and joint use of remotely sensed and ancillary data

The author has identified the following significant results. Effects of terrain topography in mountainous forested regions on LANDSAT signals and classifier training were found to be significant. The aspect of sloping terrain relative to the sun's azimuth was the major cause of variability. A relative insolation factor could be defined which, in a single variable, represents the joint effects of slope and aspect and solar geometry on irradiance. Forest canopy reflectances were bound, both through simulation, and empirically, to have nondiffuse reflectance characteristics. Training procedures could be improved by stratifying in the space of ancillary variables and training in each stratum. Application of the Tasselled-Cap transformation for LANDSAT data acquired over forested terrain could provide a viable technique for data compression and convenient physical interpretations

Geographic Information Science (GIScience) and Geospatial Approaches for the Analysis of Historical Visual Sources and Cartographic Material

This book focuses on the use of GIScience in conjunction with historical visual sources to resolve past scenarios. The themes, knowledge gained and methodologies conducted might be of interest to a variety of scholars from the social science and humanities disciplines

The total assessment profile, volume 2

Appendices are presented which include discussions of interest formulas, factors in regionalization, parametric modeling of discounted benefit-sacrifice streams, engineering economic calculations, and product innovation. For Volume 1, see

Exploring countrywide spatial systems: Spatio-structural correlates at the regional and national scales

In this paper we take a step towards extending space syntax analysis into the countrywide scale, through the study of three very-large spatial systems in the UK, namely the top-tier road network of the entire country (170,007 nodes), the complete road network (1,208,674 nodes) of three contiguous NUTS1 regions (the East of England, South East of England and Greater London) and the complete road network of UK's mainland (2,031,971 nodes). We compare the results of our analysis with several types of functional and socio-economic data, finding clear statistical associations at the scale of the entire country between network structure, vehicular movement flows and the spatial distribution of several socio-economic variables. We conclude by arguing that space syntax models and analysis hold their value at very-large territorial scales, being highly robust and producing coherent results between datasets of different sources, themes and dimensionalities

Analisis orientado a objetos de imágenes de teledetección para cartografia forestal : bases conceptuales y un metodo de segmentacion para obtener una particion inicial para la clasificacion = Object-oriented analysis of remote sensing images for land cover mapping : Conceptual foundations and a segmentation method to derive a baseline partition for classification

El enfoque comúnmente usado para analizar las imágenes de satélite con fines cartográficos da lugar a resultados insatisfactorios debido principalmente a que únicamente utiliza los patrones espectrales de los píxeles, ignorando casi por completo la estructura espacial de la imagen. Además, la equiparación de las clases de cubierta a tipos de materiales homogéneos permite que cualquier parte arbitrariamente delimitada dentro de una tesela del mapa siga siendo un referente del concepto definido por su etiqueta. Esta posibilidad es incongruente con el modelo jerárquico del paisaje cada vez más aceptado en Ecología del Paisaje, que asume que la homogeneidad depende de la escala de observación y en cualquier caso es más semántica que biofísica, y que por tanto los paisajes son intrínsecamente heterogéneos y están compuestos de unidades (patches) que funcionan simultáneamente como un todo diferente de lo que les rodea y como partes de un todo mayor. Por tanto se hace necesario un nuevo enfoque (orientado a objetos) que sea compatible con este modelo y en el que las unidades básicas del análisis sean delimitadas de acuerdo a la variación espacial del fenómeno estudiado. Esta tesis pretende contribuir a este cambio de paradigma en teledetección, y sus objetivos concretos son: 1.- Poner de relieve las deficiencias del enfoque tradicionalmente empleado en la clasificación de imágenes de satélite. 2.- Sentar las bases conceptuales de un enfoque alternativo basado en zonas básicas clasificables como objetos. 3.- Desarrollar e implementar una versión demostrativa de un método automático que convierte una imagen multiespectral en una capa vectorial formada por esas zonas. La estrategia que se propone es producir, basándose en la estructura espacial de las imágenes, una partición de estas en la que cada región puede considerarse relativamente homogénea y diferente de sus vecinas y que además supera (aunque no por mucho) el tamaño de la unidad mínima cartografiable. Cada región se asume corresponde a un rodal que tras la clasificación será agregado junto a otros rodales vecinos en una región mayor que en conjunto pueda verse como una instancia de un cierto tipo de objetos que más tarde son representados en el mapa mediante teselas de una clase particular

Patterns of land cover change in Kanyati communal land in Zimbabwe

Bibliography : pages 138-149.Expanding areas under cultivation and settlement are a global trend with significant effects on existing land cover types and ecosystems. High rates of human population growth in southern Africa and subsequent increased pressure on land has led to the extension of cultivation and settlement into marginal lands. This study investigates the spatial patterns ofland cover change in a communal land in Zimbabwe over the period 1973 to 1993, and their likely ecological effects. The study site is in the Zambezi Valley and has a well­ preserved area ofmiombo woodland and has the potential to become an important wildlife corridor between a national park, safari area and communal lands with local community based wildlife management projects. The area is divided into wildlife and settled areas by a game fence so provided an opportunity to compare patterns ofland cover change vvith and without extensive human impact within the same administrative area. The land cover types were derived from manually interpreted aerial photographs as multispectral satellite imagery is not available before the 1980's and is expensive. Geographical Information Systems were used to analyse the spatial patterns ofland covers identified, the sizes and shapes of spatial entities and the spatial distribution of land cover types in relation to slope and proximity to rivers. The likely ecological effects of land cover change were investigated by deriving habitat suitability maps using the habitat requirements of seven large herbivore species: buffalo, bushbuck, elephant, kudu, sable, waterbuck and zebra

An Evolutionary Approach to Adaptive Image Analysis for Retrieving and Long-term Monitoring Historical Land Use from Spatiotemporally Heterogeneous Map Sources

Land use changes have become a major contributor to the anthropogenic global change. The ongoing dispersion and concentration of the human species, being at their orders unprecedented, have indisputably altered Earth’s surface and atmosphere. The effects are so salient and irreversible that a new geological epoch, following the interglacial Holocene, has been announced: the Anthropocene. While its onset is by some scholars dated back to the Neolithic revolution, it is commonly referred to the late 18th century. The rapid development since the industrial revolution and its implications gave rise to an increasing awareness of the extensive anthropogenic land change and led to an urgent need for sustainable strategies for land use and land management. By preserving of landscape and settlement patterns at discrete points in time, archival geospatial data sources such as remote sensing imagery and historical geotopographic maps, in particular, could give evidence of the dynamic land use change during this crucial period. In this context, this thesis set out to explore the potentials of retrospective geoinformation for monitoring, communicating, modeling and eventually understanding the complex and gradually evolving processes of land cover and land use change. Currently, large amounts of geospatial data sources such as archival maps are being worldwide made online accessible by libraries and national mapping agencies. Despite their abundance and relevance, the usage of historical land use and land cover information in research is still often hindered by the laborious visual interpretation, limiting the temporal and spatial coverage of studies. Thus, the core of the thesis is dedicated to the computational acquisition of geoinformation from archival map sources by means of digital image analysis. Based on a comprehensive review of literature as well as the data and proposed algorithms, two major challenges for long-term retrospective information acquisition and change detection were identified: first, the diversity of geographical entity representations over space and time, and second, the uncertainty inherent to both the data source itself and its utilization for land change detection. To address the former challenge, image segmentation is considered a global non-linear optimization problem. The segmentation methods and parameters are adjusted using a metaheuristic, evolutionary approach. For preserving adaptability in high level image analysis, a hybrid model- and data-driven strategy, combining a knowledge-based and a neural net classifier, is recommended. To address the second challenge, a probabilistic object- and field-based change detection approach for modeling the positional, thematic, and temporal uncertainty adherent to both data and processing, is developed. Experimental results indicate the suitability of the methodology in support of land change monitoring. In conclusion, potentials of application and directions for further research are given

Spatial analysis, quantification and evaluation of developments in settlement structure based on topographic geodata

As the global population continues to grow, urbanization is one of the most significant anthropogenic processes linked to ecological change. But even in countries where the overall population is stagnating, migratory movements toward urban centres will continue to place pressure on the finite resource of land. Therefore, it is particularly important to determine and describe the development of settlement areas as precisely as possible in order to inform spatial planning decisions. For this reason, this dissertation presents vector-based methods to analyse, quantify and evaluate small-scale changes in settlement area. In this work, which constitutes a cumulative dissertation, novel methods are described that can be used to determine not only areal change in settlement and traffic areas (SuV), but also the type of building change and urban densification. This is of particular interest for the spatial planning of expanding metropolitan areas, where the question arises: Where, how and to which extent can built-up areas be further densified in order to reduce the consumption of land for new settlement areas? The methods presented here can facilitate spatially detailed analyses and already form the basis for a nationwide monitoring of settlement and open space development. This work shows how geometric deviations and changes in the underlying data model can be taken into account when determining SuV growth from data of the Authoritative Topographic-Cartographic Information System (ATKIS). In this context, positional inaccuracies of linearly and arealy modelled geometries are each treated in a special way so that minor positional offsets no longer affect the SuV increase. In addition, changes in the data model are accommodated by disregarding specific object reallocations when determining the SuV increase. To test these methods, the SuV increase was determined and analysed for Germany using national ATKIS data sets that feature geometric positional inaccuracies and data model changes. It could be shown that a considerable share of the calculated SuV increase is not due to real-world changes but to modelling issues. Furthermore, a novel method for the detection of building changes is presented, which focuses on the differentiation between modified and replaced buildings. It could be shown that this new approach is more accurate than other investigated methods. Furthermore, an algorithm was developed in this work to generate defined location deviations. This could be used to show how position deviations affect the accuracy of the examined procedures. The threshold values determined in this work can form the basis for similar investigations. In addition, an indicator was developed to track changes in building density. This indicator not only reflects the extent of building change but also the size of the existing building stock. Moreover, the indicator was designed in such a way as to allow comparison of the densification of developed and undeveloped areas, and thus also inner and outer urban areas. Furthermore, the indicator can be used to symmetrically calculate a decrease in the building stock, enabling a comparison of densification and de-densification processes.:1. Introduction 1.1 Motivation 1.2 Problem description 1.3 Aims 1.4 Structure 2. Dissertation main articles 2.1 Measuring land take in Germany 2.2 Detecting building change 2.3 Indicator for building densification 3. Methods for measuring settlement changes 3.1 Measuring changes through land use data 3.2 Detection of building changes 3.3 Measuring changes in building density 4. Main findings 4.1 Effects of non-real changes on land take 4.2 Distinguishing building modification and replacement 4.3 Impact of building changes on building density 4.4 How the articles are connected 4.5 Additional relevant publications 5. Conclusion and Outlook References Abbreviations List of figures List of author’s publications Articles Conference Papers Acknowledgments Appendix with publication

A methodology for landscape characterisation based on GIS and spatially constrained multivariate analysis

Landscape is about the relationship between people and place and in 2000 was defined by the European Landscape Commission (ELC) as "an area as perceived by people whose character is the result of natural and human actions and interactions”. In the 70s the reason for studying the landscape was because of the necessity of attributing a value to it. Nowadays the motivations behind managing, conserving and enhancing the landscape is because the landscape is the place where people belong to and, consciously or not, recognise themselves. In addition, people identify different landscapes on the basis of the particular combinations of the elements in the landscape. As a consequence a landscape can be distinguished from another on the basis of its character which, according to the Landscape Character Assessment (LCA) guidance for England and Scotland (C. Swanwick and Land Use Consultant, 2002), is defined as “a distinct, recognisable and consistent pattern of elements in the landscape that makes one landscape different from the other rather than better or worse”. This definition was the starting point of a PhD research project aimed at developing and implementing a methodology able to identify and quantify the character of the Scottish landscape through the application of GIS and statistics. The reason for doing this research was to provide the landscape architects and practitioners with a tool that could help them to define the landscape character types in a more consistent, objective, and scientifically robust way. One of the objectives of the research was to identify the spatial patterns formed by the landscape elements by taking into account the influence of the spatial location. The first law of geography, which states that "everything is related to everything else but near things are more related than distant ones" (W Tobler, 1970), was transposed in the assumption of the presence of spatial autocorrelation amongst the data which contributes to form spatial patterns within the data. Since landscape comprises of many elements, data were also multivariate, thus the analysis required a method of calculation able to deal simultaneously with multivariate and spatial autocorrelation issues. MULTISPATI-PCA, a spatially constrained Principal Component Analysis, was the statistical technique applied for the analysis of the data whose results showed that it was possible to detect the spatial structure of the data and that each spatial pattern corresponded to a distinct landscape. Despite their importance in forming the character of the landscape, aesthetic and perceptual aspects were not inlcuded in MULTISPATI-PCA analysis. It was preferred to test the technique only on data that were quantifiable in a more objective way. Perhaps taking into account the human perception of the landscape can be the starting point for future investigation