Part III-A Learning from Practice: GIS as a Tool in Planning Sustainable Development Urban Dynamics © 2006 by Taylor & Francis Group, LLC 313 18 Urban Multilevel Geographical Information Satellite Generation Sébastien Gadal CONTENTS 18.1 Introduction 313 18.2 Contribution of Data Satellites for Urban Geographic Information System (UGIS): Accuracies of Socioeconomic and Demographic Statistical Information 314 18.3 Interests of Remote Sensing Data for Geographical and Statistical Databases Generation 316 18.4 Space Imagery, Urban Dynamics, and UGIS 317 18.5 An Approach of Urban Dynamics by UGIS Satellite Data Generation 318 18.5.1 The Morocco Atlantic Metropolitan Area Example: The Available and Interoperable UGIS Question 318 18.5.2 A Multidimensional Approach 318 18.6 Technical and Operational Problems: The Information Paradigm Question 319 18.7 Conclusion 325 References 326 18.1 INTRODUCTION The exploitation of satellite data in urban land planning is sometimes unpredictable because of the specific needs of these practices compared to others. In common practice, morphological, environmental, and social aspects are needed to describe the characteristics of urban zones. However, remote sensing image processing meth- odologies, generating social and environmental information from satellite data as multispectral classification and textural filters, give a zone description of the urban environment mostly limited to the land use [1], the land cover, or the build densities zone’s description [2]. Furthermore, the socio-environmental level generated is dependent on the spatial resolution of satellite imagery. This inadequacy limits the use of remote sensing data for multilevel urban and socioeconomic database infor- mation systems development. New methodologies based on geometrical, logical set © 2006 by Taylor & Francis Group, LLC 314 GIS for Sustainable Development filters, and thermal imagery characteristics have been developed and utilized to generate and integrate socio-environmental and economical information databases at three different spatial levels [3]. The settlement level (the interface between imagery, society, and social characteristic of territories) deals with information on urban form, economical and social functions, levels of life, and equipment [4]. The meso-metropolitan level deals with demographic information (urban and human densities, human development indicators, the types of social or economical zone activities, and water pollution). The global level concerns the environmental infor- mation, global densities and localizations of populations [5], land cover and land use [6], spatial structures, and urban form dynamics [7,8]. The first method requires morphological operators and symbolic recognition (description of the geometrical properties such as the surface, the compactness, etc.). The objective of this method is to automatically generate a vectorial map of every build elements-settlements and a descriptive geometrical database for the geographical objects. From this descriptive geometrical database, a classification processing is then used to extract the different urban forms and built elements settlements typology. The second methodology uses logical set theory and textural filters to separate and identify functions of build elements at settlement level; it allows recognition of spatial structures and urban forms at a global level. Thirdly, a set of methodologies based on interpretation of urban thermal gradient permits characterization of social domains and production of demographical indicators. All these methodologies generate environmen- tal and social urban databases which may be useful in supporting territorial control and urban planning, as it will be shown with reference to a case study developed for the Morocco Atlantic Metropolitan (MAM) Area (Kenitra-Rabat-Casablanca). Production, update, and availability of multilevel urban geographic databases are some of the main problems many land-planning agencies and local governments from the Maghreb have to face in daily practice. While socio-demographic census data exist, like in Morocco, and can be used and implemented at two different spatial levels (prefectures and districts), the accuracy, pertinence, and efficiency are not properly exploited yet for the MAM’s territorial control and urban planning. For these reasons, the use of satellite data has been chosen and tested as the basis for the socio-environmental multilevel information system implementation. The use of satellite imagery for the socio-environmental and multilevel GIS implementation constitutes an advantage, because it makes it possible to produce, to associate, to merge, and to generate several types of socio-spatial information, as shown in the remainder of this chapter. 18.2 CONTRIBUTION OF DATA SATELLITES FOR URBAN GEOGRAPHIC INFORMATION SYSTEM (UGIS): ACCURACIES OF SOCIOECONOMIC AND DEMOGRAPHIC STATISTICAL INFORMATION The accuracy of socioeconomic and demographic statistical databases is dependent on the special context, which varies for different countries. In general, three sets can be distinguished. © 2006 by Taylor & Francis Group, LLC Urban Multilevel Geographical Information Satellite Generation 315 • The information collections based on exhaustive censuses are generally produced or updated every 8 to 10 years. They are usually based on administrative spatial units [9]. The spatial units generally serve as a base for annual samplings updating. This mode of information collection rep- resents the majority of the cases in the world. Generally, the studies on the urban processes based on the demographic and socioeconomic statis- tics show social practices of the populations, their dynamics, and their distributions on the territory. They also allow approaching the economic dimension of the urban territory. They give a social, human, and economic representation of urban territories, describing them geographically by highlighting the territorial organizations. The plurality of the data, indi- cators, and statistical variables allows encircling the variety of the human facts and describing the urbanization dynamics. The statistical relation- ships of economical and human variables and the preparatory statistical methods verify the aptness of UGIS information. They examine the sig- nificance of the practices and the socioeconomic dynamics while charac- terizing them. They have descriptive and heuristic characters. As economic and socio-anthropological measure, the statistical data get at the same moment the driving elements and the actors of these geographic dynamics. Therefore, they offer the geographer a means to encircle the explanatory factors. However, they face difficulties so that it is often necessary to look for socio-anthropological and cultural factors. Hence, questions arise about the geographic scale aptness to report urban processes such as their choice in the studies concerning this geographic process. The interest in this descriptive statistical analytical method and this structuring informa- tion mode should take into account a very high number of variables. It allows refining the measure of the urban state process of the geographic space portion under study. The fitted multilevels method links the urban levels in various geographic scales and allows understanding of whether the urban process is at a stage of development that is only local or embraces the whole region or country. Thus, it can be defined as an indicator of geographic and urban spatial distribution. The normalization of the statistical measure extrapolated at the national or regional level reports, certainly, the urban level tendency and the average level of territory at that scale. It does not represent, however, the differential character of the urban process in its full character. Thus, issues arise about the administrative spatial unity choice and the most relevant geographic scale. • Other “conventional” data are produced from the administrative registers such as the registry office or statutory: building permission, cadastre, etc. While they often refer to the same concepts, these data often have different semantic meanings and refer to different spatial units [10]. • The data produced from the spatial remote sensing imageries. Remote sensing data give a physical description of the urban territory, from which it is possible to extract environmental and social indicators. © 2006 by Taylor & Francis Group, LLC 316 GIS for Sustainable Development 18.3 INTERESTS OF REMOTE SENSING DATA FOR GEOGRAPHICAL AND STATISTICAL DATABASES GENERATION Satellite imagery does not succeed in reporting all the above aspects per se. It describes, it measures the visible physical aspects — by remote sensing — of the consequences that result from geographic processes. Unlike studies made with socioeconomic data, urban studies using satellite data nevertheless show the influ- ence of the geographical context which relates the urban processes through the situation, the localization, the neighborhood, the spatial differentiation, etc. Indeed, the use of demographic and socioeconomic statistical data in the UGIS supplies an aspatial representation of the urban territory. They can be geo-referenced, but they are not necessarily spatial in essence. The cartographic transcription of urban pro- cesses, a posteriori, remains constrained by their membership in an area with boundaries that may be the result of a statistical sampling technique or an admin- istrative one: the municipality, the region, etc. Satellite data are not affected by this limit. In some other rare cases, on the other hand, the studies based on ground observations present the inconvenience to be too punctual to give a systematic description. A monograph is indeed often too local to allow more that a confirmation or a local analysis of an aspect of the urban processes. Nevertheless, if conceived as a separate element becoming integrated into the processing line, the field studies based and planned as sampling technique for statistical methods can be an indispensable aid to the expert to validate or invalidate his results or identify unrecognized geographic objects. These methods can help in understanding elements of social and cultural dynamics difficult to recognize by only image processing or data analysis [11,12]. Urban econometric and demographic analyses supply evident advantages, but they also present a certain number of deficiencies: failing to properly deal with the spatial dimension, and in the integration of physical, social, and human environment with cultural urban characteristics. Available statistical data are often inadequate when adapted to the problem at hand. Often, geographers or urban planners have to adapt the method and the geographic level of interest within the research focus or the urban planning project to the available statistical data, and not the opposite. The question is then how to construct geographies with information sources which are not made for the geographer or the urban planner? In the past, geographers and urban planners coped, like it or not, with this established limit, restricting the access to a part of the geographical reality. Paradoxically, the problem is less important for geographers or urban planners in developing countries, where information is poorest, ill assorted, or still unavail- able. Hence, the geographer or the urban planner has to create his own information for its work. This fact gives place to the experimentation with a number of spa- tiotemporal information production methodologies in developing countries. The result of these research efforts is that these “African methods” are nowadays begin- ning to replace classical urban spatial sampling techniques even in Western countries [6,13]. “African” sampling technique methods have the advantage of being less expensive, easier to implement from an administrative point of view, and often more © 2006 by Taylor & Francis Group, LLC Urban Multilevel Geographical Information Satellite Generation 317 effective. Often in developing countries, data are rarely updated and many geogra- phers or planners hardly deal with the information production techniques with evident limit in the knowledge building process. Moreover, the statistical information production is often not tested, putting the expert in a face-to-face dependence on the statistical agencies for the exploitation of socioeconomic information. It is then difficult to estimate validity of the data used and, eventually, the suitability for their work, with evident limitation in interpreting the results. 18.4 SPACE IMAGERY, URBAN DYNAMICS, AND UGIS Satellite remote sensing data allow approaching the various aspects of the territorial dynamics along with the social and cultural, environmental, historic and physical aspects. Remote sensing techniques are able to supply a measure of the human and society impacts onto the environment. Indeed, it is this interaction between the human and physical geographies that made the territory. The remote sensing images and the aerial photographs describe the territory, its structures, it organization, its dynamics, its landscapes, its morphologies, the marks and signs of its history. Remote sensing techniques allow geographers and urban planners to study the territory in a “trans-disciplines” way or, if required by the study at hand, in a specific manner. Whatever logic of analysis geographers and planners are using, they need to analyze the themes by their spatial aspects. This is indeed peculiar in geographic and urban planning analyses made by means of remote sensing data. The multiplicity and the variety of the information offered by the satellite images, like the complexity of the physical and spatial mark structures of the urban dynamics, require the development of several information extraction and analysis methods by means of the image-processing techniques. Each method supplies a series of information, describing a state or a geographic process. These techniques can be effectively used when the objective is to detect, to recognize, to identify, to extract, to quantify, and to qualify urban structures and dynamics. They allow, for every geographic object describing urban growth and structures, implementation of one or several method- ologies to extract simple or complex information characterizing the urban territory, informing about the dynamics and the actual phenomena. However, the analysis of a part of the geographic space by remote sensing techniques, which search urban forms and spatial organizations, makes it necessary to know beforehand the phenomena, the objects, and the geographic places which structure it, in order to understand what satellite or airborne image may be useful to describe them. This approach is valid only if we limit ourselves to the detection and analysis of a given geographic phenomenon, which in this particular case is the urban dynamic. The analysis of the territory according to the geographic process theory using radiometric measures of the geographic space reality has the advantage of giving to the analyst reading, analysis, and interpretation grids which are made from quickly available sources at several levels of resolution and which supply multiple types of information. The deductive approach, which defines element rec- ognition by theorized heuristics, has, as the other advantage, to focus the image processing work on detection of the geographic objects and the spatial entities. © 2006 by Taylor & Francis Group, LLC 318 GIS for Sustainable Development 18.5 AN APPROACH OF URBAN DYNAMICS BY UGIS SATELLITE DATA GENERATION 18.5.1 T HE M OROCCO A TLANTIC M ETROPOLITAN A REA E XAMPLE : T HE A VAILABLE AND I NTEROPERABLE UGIS Q UESTION The levels of social indicators and geographic information and the pattern of the administrative boundaries are not suitable to properly represent urban dynamics and socioeconomic processes; information is aggregated too much, and it does not integrate the geographic and the environmental dimensions. This type of geographic multilevel information implemented in GIS is not efficient for urban planning pur- poses. In addition, discontinuities introduced by administrative boundaries do not give a suitable view of social and environmental processes. Administrative divisions made with population and territory controls in mind are not suitable for an integrated land management and a security control of the sprawling metropolitan area. Local urban databases in Rabat and Casablanca are available at planning agencies, but cannot be integrated to the same geographic information database system. However, the most urgent problem for GIS implementation, apart from the inadequacy of the socio-spatial information level of representation, is the obsolescence of databases supplied by census and land planning agencies, with their updating problems. The strong rates of urban growth and the fast transformation of society make data obsolete every three months [14]. The costs of updates by traditional survey techniques and of data production at a suitable spatial level make it impossible to implement the relevant geographic and social information levels in GIS. 18.5.2 A M ULTIDIMENSIONAL A PPROACH The study of the urban processes by remote sensing for urban and land planning purposes has been developed by integrating several methods, each of them relating to a set of semiological and semantic information testing one of its aspects or objects, such as the industrial parks, communication infrastructure, built elements, etc. In other words, the ways spatial information was produced depended on several char- acteristic objects: detection of the built elements and their economical and social functions, communication infrastructures, and social segregations; urban concentra- tions recognition at the infraterritorial and regional levels; and recognition of the morpho-landscape and geographic structures, hierarchies and spatial interrelations. The different information and analysis methods were based on several available spectral sources, such as panchromatic and thermal infrared imageries. Each of these two spectral data types supplies at different spectral and spatial resolutions an electromagnetic brilliance measure that is a radiometric biophysical radiation of the surface and of the urban fabric. Panchromatic and infrared thermal data imageries bring a series of information, often additional, sometimes redundant, of the same spatial reality, which is subdivided as imprints of a geographic, geologic, social, anthropological, historic, ecological, or political reality, etc. The deductive approach used in this method, as to say the recognition of geographical elements defined by a theorized heuristics, has the other advantage to focus the image processing work © 2006 by Taylor & Francis Group, LLC Urban Multilevel Geographical Information Satellite Generation 319 on the detection of the geographic objects and the spatial entities that show and explain urban dynamics. Descriptive elements can be classified in three categories: • The descriptive elements of selected objects (as built, urban concentra- tions, roads, etc.) •Regionalized descriptive elements (objects such as landscaped units, geo- graphic zones, etc.) • Spatial descriptive elements (reporting forms of organizations, structures, hierarchies of the physical environment) Besides putting in evidence a larger number of geographic descriptive elements, objects of urban dynamics, and structures (refining, in this way, the analysis and the heuristics), the multimethods approach has the potential for the methods to validate each other, in a complementary logic. For example, the combinatorial extraction and classification model of built objects recognizes townships, while the morpho-land- scaped recognition model recognizes all the types of built objects with the exception of townships. This last informative model, thanks to the types and the forms of landscapes recognition, allows replacing in the physical context built patterns rec- ognized with the extraction and classification of the built objects combinatorial model. The method has a double role: complementarity and validation of the other models used. The overall image processing method can be resumed in three phases as follows: •A phase of data optimization, which is a preprocessing step, intended “to improve” the satellite data for the needs of the following analysis processing • An image and analysis-processing phase based on NOAA [15,16] and LANDSAT [17] thermal infrared satellite images • An image and analysis processing phase using SPOT panchromatic sat- ellite images relying on three heuristic detection models, two morpho- landscape models, and a geometrical morphology model of the building and road objects The available data and the methods developed to analyze the urban dynamic allow extracting a certain amount of information, suitable to describe the phenom- enon with enough accuracy. This was experimented in Morocco along the Kenitra- Rabat-Casablanca’s urban axis, the MAM. few examples of Multilevel Geographical Urban Information produced by RS. 18.6 TECHNICAL AND OPERATIONAL PROBLEMS: THE INFORMATION PARADIGM QUESTION The singular and normative aspect of the urban form in emergence study for urban planning by remote sensing raises the technical operational problem of the “informative” © 2006 by Taylor & Francis Group, LLC Figure 18.1 and Figure 18.2 illustrate the methodologies of Urban Multilevel Geographical Information Satellite Generation, while Figure 18.2–18.5 illustrate a 320 GIS for Sustainable Development paradigm. The airborne and satellite data used as almost unique information bring geographers and planners to a situation of a new environment of expertise and a new way of working because of the few general experiences acquired in the devel- oping countries in the field of urban study, and in the absence of established and well-tested methodologies. FIGURE 18.1 AVHRR and LANDSAT 5 TM thermal data processing lines. (From Gadal, S., Recognition of Metropolization Spatial Forms by Remote Sensing, Eratosthenes, Lausanne, Switzerland, 2003. With permission.) Band 4 (10.5-11.3 µm) Band 5 (11.5-12.5 µm) NOAA 14 -AVHRR Band 6 (10.4-12.5 µm) LANDSAT 5 -TM Axis 1 of CPA Axis 2 of CPA Principal Component Analysis transformation (CPA) Transformation in real luminance Transformation in real luminance Transformation in temperature of surface (calibration from Atlantic Ocean surface temperatures) Transformation in temperature of surface (calculus of coefficients) Monodimensional classification (cluster classification) Thermal gradient Thermal gradient Land surface temperatures Land surface temperatures Map of urban concentrations (>100 hab/km 2 ) Map of urban concentrations (>40 hab/km 2 ) © 2006 by Taylor & Francis Group, LLC Urban Multilevel Geographical Information Satellite Generation 321 FIGURE 18.2 SPOT panchromatic data processing lines. (From Gadal, S., Recognition of Metropolization Spatial Forms by Remote Sensing, Eratosthenes, Lausanne, Switzerland, 2003. With permission.) Enhanced data by -1 -1 -1 -1 16 -1 -1 -1 -1 Convolution filtering (geometric enhancement) Enhanced data by 0 -1 0 -1 16 -1 0 -1 0 Enhanced data by -1 0 -1 0 16 0 -1 0 -1 Local linear regressions Morphological filtering Symbolic recognition Unsupervised classification Data fusion Vectorial database and vectorial map of built elements Geometrical classification of built elements Map of classified built elements Geometrical databases of built elements Enhanced image Panchromatic band SPOT 3 © 2006 by Taylor & Francis Group, LLC [...]... dimensions of the urbanity for the surveillance of the urban territories or for the control of the settlement future form Ikonos 2, Orbview 2-3 , Eros 1A, Spot 5 or future Pleiades satellite images have a greater geometrical and spectral resolution [24,25] that shows © 2006 by Taylor & Francis Group, LLC 326 GIS for Sustainable Development certain anthropo-socio-cultural aspects of interest for the geographers... corridors, and extended regions The aim of MOLAND is to 329 © 2006 by Taylor & Francis Group, LLC 330 GIS for Sustainable Development assess, monitor, and model past, present, and future urban and regional development from the viewpoint of sustainable development and natural hazards, by setting up GIS databases for cities and regions MOLAND has defined and validated a methodology in support of assessing the... “Change,” “Understand,” and “Forecast.” In the “Change” phase of MOLAND, detailed GIS databases of land-use and transport networks are produced for each study area The databases are typically for four dates (early 1950s, late 1960s, 1980s, late 1990s) for urban areas, or (in the case of larger areas) for two dates (mid-1980s, early 2000s), at a mapping scale of 1:25,000 The MOLAND land-use legend, which is... (19.1) 334 GIS for Sustainable Development t PK,x,y CA transition potential of the cell (x, y) for land use at time t Ar,K,x,y Accessibility of the cell (x, y) to infrastructure element r for land use K at time t SK,x,y Intrinsic suitability of the cell (x, y) for land use K tZ K,x,y Zoning status of the cell (x, y) for land use K at time t tN K,x,y Neighborhood space effect on the cell (x, y) for land... terms urban land-use © 2006 by Taylor & Francis Group, LLC Urban Scenario Modeling and Forecast 337 FIGURE 19.1 Udine, built-up and land-use maps for 1980, 2000, and the simulation from 1980 to 2000 © 2006 by Taylor & Francis Group, LLC 338 GIS for Sustainable Development FIGURE 19.2 Zoning regulation data sets for Udine provided from local authorities: (a) residential areas; (b) industrial areas;... scenario for planning purposes The inclusion of extensive detailed land-use classes, such as several types of residential classes, together with the fine detail of the data sets, increases the experimental potential of the model, given that it can be used by planners like a simulation © 2006 by Taylor & Francis Group, LLC 342 GIS for Sustainable Development FIGURE 19.3 Udine, built-up and land-use maps for. .. European Commission’s Joint Research Centre, is to provide up-to-date, standardized, and comparable information on the past, current, and likely future land-use development in Europe As part of MOLAND, an urban growth model has been developed This model is used to assess the likely impact of current spatial planning and policies on future land-use development To date, the MOLAND database has covered more... general form of the current city due to the initial conditions of transport network and land-use The foreseen urban pattern appears to be realistic However, the form of the city has clearly developed and shows increased built-up nuclei in peripheral areas Furthermore, it is remarkable that the model has produced iteratively long-term predictions based on several hypotheses for several urban land-use classes,...322 GIS for Sustainable Development Copyright Sébastien GADAL 2001 0 Legend: Low thermal emittance Coast line 100 km High thermal emittance Source: NOAA -AVHRR (bands 4 and 5), 1995 FIGURE 18.3 Urban and socio-demographic concentration recognition (From Gadal, S., Recognition of Metropolization Spatial Forms by Remote Sensing, Eratosthenes, Lausanne, Switzerland, 2003 With permission.) However, image-processing... 19.1.3 SPATIAL DYNAMIC SYSTEMS FOR URBAN SCENARIO SIMULATION The estimation of future impacts on land-use development of existing spatial plans and policies and the consideration of alternative planning and policy scenarios for impact minimization are of particular interest for urban and regional planners In the last decade CA have gained popularity as a modeling tool for the simulation of spatially . permission.) Enhanced data by -1 -1 -1 -1 16 -1 -1 -1 -1 Convolution filtering (geometric enhancement) Enhanced data by 0 -1 0 -1 16 -1 0 -1 0 Enhanced data by -1 0 -1 0 16 0 -1 0 -1 Local linear regressions. socioeconomic database infor- mation systems development. New methodologies based on geometrical, logical set © 2006 by Taylor & Francis Group, LLC 314 GIS for Sustainable Development filters,. that shows © 2006 by Taylor & Francis Group, LLC 326 GIS for Sustainable Development certain anthropo-socio-cultural aspects of interest for the geographers or urban planners. The difficulty recognizing