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DESIGN AND IMPLEMENTATION OF A TEMPORAL GIS FOR MONITORING THE URBAN LAND USE CHANGE Ale Raza and Wolfgang Kainz Geoinformatics, Spatial Information Theory and Applied Computer Science International Institute for Aerospace Survey and Earth Sciences (ITC) PO Box 6, 7500 AA Enschede, The Netherlands. Tel: +31-53-4874374, Fax: +31-53-4874335, E-mail: {saraza, kainz}@itc.nl Richard Sliuzas Urban Survey, Planning and Management International Institute for Aerospace Survey and Earth Sciences (ITC) PO Box 6, 7500 AA Enschede, The Netherlands. Fax: +31-53-4874335, Tele: +31-53-4874374, E-mail:
[email protected] Abstract: Urban areas are the scene of considerable growth and transformation processes which result in the conversion of land from rural to urban use and in secondary transformations from one urban use to another. In the cities of developing the world such land use change processes can be both formal or informal and they are often also very rapid. Information systems, which can deal effectively with the spatial, temporal and contextual data pertaining to land use change are required. This paper is an attempt to provide a simple and easy to handle tool for urban planners to store and analyse spatio-temporal land use data more efficiently by implementing a Temporal GIS (TGIS). PC ArcInfo is one of the commonly used PC based GIS, which has been used to implement the space time composite model for TGIS, integrated with Object Oriented and Event and Evidence data type concepts. Database_time and World_time has been incorporated. System architecture, implementation, and user interface are discussed here; spatio-temporal data is covered by Raza and Kainz (1988). The user interface has been developed to create, edit and visualize spatio-temporal land use data. Distinction has been made between essential and non-essential changes in land use. Keywords: TGIS, Space-Time Composite, STAO, Land Use and Urban Planning. 1. INTRODUCTION Cities throughout the world are the scene of complex social and economic processes which result in land use changes. As urbanisation is occurring at hitherto unprecedented rates in many parts of the developing world large tracts of land are being converted from rural to urban use. In many cities, much of this initial land conversion process occurs informally (i.e. outside of the formal control and regulatory system for land development1). Urban growth continues in cities of the North too, although primarily driven by different combination of forces; e.g., environmental controls promoting the segregation of land uses, increasing
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In some cities land conversion due to autonomous development processes may even exceed planned land conversion. In Dar es Salaam, for example, 60-70 % of the population are housed in unplanned settlements which continue to expand in the absence of a an adequate supply of affordable, serviced and surveyed plots. The figure for Karachi is 50%.
Zhou, Q., Li, Z., Lin, H. and Shi, W. (eds.) Spatial Information Technology Towards 2000 and Beyond The Proceedings of Geoinformatics’98 Conference Beijing, 17-19 June, 1998, pp. 417-427
Copyright 1998 The Association of Chinese Professionals in GIS - Abroad 151 Hilgard Hall, University of California, Berkeley, CA 94720-3110, USA All rights reserved. ISBN 0-9651441-5-1 Printed in Beijing, P. R. CHINA
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affluence, the increasing use of private motorised transport and suburbanisation being amongst some of the leading causes of growth. Land use conversion is, however, not confined to the urban fringe areas. Within cities change processes also occur in response to changing patterns of demand for existing urban space. One can think of the effects of inner city decline and regeneration, the redevelopment of old harbour areas amongst other forms of land use transition. In whatever setting, land use changes can occur with or without accompanying changes in the structure of property or land use unit boundaries. Consolidation processes are also of great importance in autonomously developing areas. Such processes result in an increase in settlement densities (see for examples in Tanzania: De Bruijn, 1987, Sliuzas and van Vugt 1988) and at a micro level may also include land use changes at the level of individual houses/plots (i.e., commercial housing and informal industrial and commercial activities). Ideally, the urban planning process should be instrumental in defining the framework for such changes and establishing and implementing a co-ordinated approach to urban development. In cities with a high proportion of informal development planning may take place after the initial stages of development. Given that urban planning is most often undertaken as a government activity while most urban development is financed and executed by private or non-government sector agents it is hardly surprising that information on changes in the land and housing market is needed for policy making and the review and evaluation of action projects at regular intervals. A method for monitoring land and housing market activity which is being promoted by the Urban Management Program (Dowall 1992 and 1995) includes the need for regular data on the expansion of land used for residential, industrial and commercial purposes. The availability of such data, together with a range of other key indicators is recommended as being essential for the better understanding and ultimately control or guidance of the land market. Land market assessment data including data on land use change can serve a variety of interests: a) formulation and evaluation of government urban development policies b) enable monitoring and evaluation of land development projects c) enable the monitoring and assessment of autonomous development processes d) assist in reducing the risks to the private sector inherent in land and property development e) assist in the preparation of integrated urban infrastructure development projects In accordance with the above the provision of information to decision makers on urban land use change should provide a flexible means for the generation of visual displays of spatial-temporal change supplemented with corresponding statistical descriptions of the extent and nature of change. The ability to store, retrieve and analyse change data according to formal or informal development processes is of additional significance. The development of systems which support flexible spatial-temporal queries combined with change-context information should allow for improved insights into development trends and the agents of change. 2 LAND USE DATA IN GIS Conventional GIS (non-temporal) assume a world that exists only in the present. The sense of change or dynamic through time is not maintained while updating the spatial database. Conventional methods such as snapshots have many disadvantages in terms of management, analysis, consistency, and visualisation, especially in case of monitoring the land use change. A TGIS, which explicitly incorporate time as one of its structural element, may be more appropriate for monitoring land use change.
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To validate the utility of a TGIS approach a model is implemented on top of the relational data model, which is still a useful and accepted standard. Tuple-level versioning method is used to implement the model, which provides lower storage costs than other implementations in relational data model. The system is developed in PC Arc/Info and ArcView. A graphic use interface (GUI) has been developed to facilitate the users by integrating two modules - Object Create/Edit and View/Query module. Edit module create/edit object, atom, and other information and view module visualize, explore and analyse (limited capability) temporal land use data. The digital land use database was created at ITC, using 1992 aerial photographs (1:12,500) and supplemented by 1982 land use map (digital data). 1982 and 1992 data has been tested on the comparatively small area of Dar-es-Salaam urban area. This model provides a simple and consistent approach to updating urban land use data. The model is application oriented and a first step in designing a TGIS for monitoring land use change. No generic commercial or operational TGIS exist. 3. OBJECT ORIENTED MODELING FOR LAND USE CHANGE A good model is one, which provides an acceptable approximation of reality. Three fundamental components of real world objects, i.e., location (spatial), attribute (aspatial), and time (temporal) have been identified by Raza and Kainz (1998). We called this spatiotemporal-attribute object STAO (Figure 1). The spatial component can further be divided into two parts, i.e. geometry and topology. No further subdivision is considered in the temporal component. To simplify the model, only geometric and attribute changes are considered. A change in land use can be caused by a change in spatial, attribute or spatial and attribute component simultaneously. These STAO can further be decomposed into STO (spatiotemporal object) and ATO (attribute-temporal object). Users may refer to (Raza 1996) for a detailed description of STAOs. Each application is defined by its properties (Roshannejad 1996 and Raafat et al. 1994). Therefore, we shall first identify the properties of land use which cause the change in land use. Urban land use is defined by a number of properties such as land use, area, perimeter, spatial and temporal neighbours, number of floors, etc. These properties can be classified as essential and non-essential properties based on the application context (Raza and Kainz 1998). In a land use change application, land use (attribute) is a vital concept, therefore it is an essential property; while other properties are considered to be nonessential. The essence of any application is the object. In land use change, the object is represented by STAO. The properties of land use are associated with STO and ATO; land use is associated with ATO and area, perimeter, spatial neighbours are associated with STO. Based on OO concepts, a change in an essential property (land use) means birth of a new STAO or death of a existing STAO. While a change in non-essential property triggers a new version of same STAO.
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Figure 1: Three Components of TGIS
Figure 2 is a change model, consisting of three layers, i.e., a) object, b) properties and c) change. Each layer is classified into two components. Object layer has object and version, properties layer has essential and non-essential properties and change layer consists of essential and non-essential change. Incorporating the changes in STO is more complex than incorporating the changes in ATO. Moreover, the graphic display of a STO is one of the fundamental requirements of any generic GIS. Incorporating changes in STO and then displaying them is a complicated process. Object Version
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Figure-2: Essential and Non-Essential Change Model
To visualise and model the changes, four types of conceptual models have been proposed by researchers: a) Sequential Snapshot, b) Base-State with Overlays, c) Space-Time Composite and d) Space-Time Cube (Langran 1992b). The choice of any one is the trade-off between system performance (from TGIS point of view), simplicity of data structure, data volume, output, error detection/control, and integrity of system etc. Due to implementation constraints we have chosen a ‘space time composite’ technique. In space-time composite, each change causes the changed portion of the coverage to break from its parent object to become a discrete object with its own distinct history. The next step is to apply the STAO model to the land use change application. Worboys, (1992a and 1992b) proposed that spatio-temporal objects have spatio-temporal (ST-) and non-spatio-temporal components. He assumes that the
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temporality of attribute component is constant throughout the spatio-temporal extent. However, in land use change the temporality of ATO is indispensable. Therefore, based on Worboys’ approach, we consider temporality in both components, i.e., STO and ATO and model land use change using a space-time composite model. Linear time has been considered and measured as a discrete variable due to the nature of land use change. Two time dimensions, i.e., World-Time (WT) and Database-Time (DT) are attached to objects (STAO), atom (STO and ATO), event and evidence data types.
Figure 3: Change in Land Use from 1980 to 1995 (adapted from Raza and Kainz 1998)
Figure 4: Decomposition of STA-Object into STA-Atoms creation of new versions of an object (adapted from Raza and Kainz 1998)
To illustrate the modelling of land use change, four land uses (Residential, Recreational, Commercial and Industrial) are considered from 1980 to 1995 (Figure 3). The space-time composite is constructed by overlaying four states of land use (from 1988 to 1995). Until 1995, three spatial units (polygons) are generated as a result of the overlay process. These polygons are the greatest common spatial unit of four land uses. Four objects (STAO), i.e., O1, O2, O3 and O4 correspond to four land uses. a) At time T1, there were two land uses residential and recreational. They are represented by object O1 and O2, respectively. b) At time T2, all recreational (O2) converted to commercial and are represented by object O3. c) At time T3, commercial (O3) land use extended in area causing residential to reduce in size. These two states of commercial and residential are represented by O3' and O1', respectively. d) At time T4, all residential converted to industrial land represented by object O4. We can summarise Figure 3 as: a) Feature: Residential, recreational, commercial and industrial. b) Time: 1980, 1985, 1990 and 1995. c) Polygon-1: 1980 -> Residential (O1,1)/ 1995 -> Industrial (O4,1) // d) Polygon-2: 1980 -> Recreational (O2,1)/ 1985 -> Commercial (O3,1) // e) Polygon-3: 1980 -> Residential (O1,2)/ 1990 -> Commercial (O3,2) // To identify the various versions of STAO, we can decompose the four land use (STAOs) into atoms or versions (Figure 4). An STAO is encapsulated with unplanned residential = and WT_From = 1982. c) Simple spatio-Temporal Query: What is the state of a region at time t? This query would be helpful for obtaining LU defined within the window (region) at a specified time. d) Spatio-Temporal Range Query: What happens to a region over a period? Space and time is bounded. Space defined by window or region and time by WT_From and WT_Until. The following is the example of a query which a user can make through GUI. In case of WT_From, WT_Until, and DT the values 9999 represents the current date/time. The user can formulate the query either through menu or Query Builder Window (QBW) of Arc/View. We shall follow the QBW to demonstrate the principle. Query-1: Action: Result: Query-2: Action: Result: Query-3: Action: Result:
Display all LU ‘unplanned residential’ [high density (81)] in 1982. From QWB type ( [Land_Use] = “81” ) and ( [WT_From] = 1982 ) Figure 8 Display all LU ‘unplanned residential’ [high density (81)] in 1992. From QWB type ( [Land_Use] = “81” ) and ( [WT_From]
