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The integration of socioeconomic and physical resource data for applied land management information systems
Abstract
Geographic information systems (GIS) have been seen as an important enabling technology in the integration of satellite remote sensing and more conventional forms of land use information. The development of GIS has closely followed perceived application needs in physical geography and led to the implementation of numerous digital databases for land resources management. However, data relating to the human population and its socioeconomic characteristics have been poorly integrated with these advances for a number of reasons. Geographic information processing in the social sciences has tended to lag behind the development of systems for physical applications and, at a more fundamental level, there are important differences in the way in which socioeconomic phenomena have been conceptualized and modelled. Nevertheless, an understanding of the distribution and characteristics of human activity has an increasingly important role to play in many questions relating to the management of the physical environment. This paper seeks to demonstrate the application of some developments in socioeconomic analysis using GIS to integrate conventional physical resource data with socioeconomic information in the context of land use planning. These involve the modelling and analysis of population information in a raster GIS environment, incorporating contemporary geodemographic techniques and providing valuable information on the analysis of settlement and neighbourhood patterns and the distribution of residential, commercial and industrial activities.
... Because of this map orientation, attention to physical resources has tended to overshadow human variables (Martin and Bracken, 1993). ...
... 48,Ibid). The interest in remote sensing has tended to reinforce this emphasis on the physical (Martin and Bracken, 1993). Marten credit D.J. Unwin (1981), andStan Openshaw (1984), among others with initially characterizing and treating the differences between socioeconomic and physical data. ...
... The needs of companies seeking to exploit the earth's mineral riches and of governments seeking to control these resources dominated the development of GIss after 1985. Data on human populations and on their social characteristics have been poorly integrated into GIS databases used by others (Martin & Bracken, 1993). Although GIs technology is still spreading at a furious pace,' it is not being aimed at the needs of the social sciences. ...
... Two types of drawing programs are used in modern Giss, the raster type and the vector type. The raster type can use remote sensing data more easily and has become very popular among analysts dealing with information on physical features of the earth (Martin & Bracken, 1993). The vector type precisely describes geometrical figures such as points, lines, circles, and three-dimensional surfaces. ...
Geographical information illuminates many features of culture that cannot be seen otherwise. Higher-resolution mapping of cultural traits, now possible with computer-ized techniques, can open a new window on human cultural adaptation. It can look at where people live on a scale that is small enough to reveal the features of the environ-ment to which their cultures respond. This article discusses the mapping of language in a rural area of Mexico. Much GIS technology has become so elaborate that it is not appropriate to cultural anthropology. The project described was successful because it developed and used techniques that were appropriate to the problem being studied and the situation in the field. The techniques can be used for other types of mapping projects.
... The general spatial distribution of the population is limited by the boundary (census regions), showing the same population density in an administrative area (Martin and Bracken 1993). However, the spatial distribution of flood hazards does not conform to administrative boundaries. ...
The intensity and frequency of extreme weather is increasing in major metropolitan areas around the world, which results in unprecedented urban floods. However, subway systems lack consideration of flood risk, and few studies have assessed risk during flood events from the view of subway travel. In this study, subway travel risk was evaluated by flood hazard, subway travel exposure and population vulnerability under three groups of rainfall scenarios. The degree of spatial exposure was calculated based on smart card data and a census, and the vulnerability of the population was assessed based on human stability in floodwaters. The results in the study area indicate that subway travel risk grows with an increase in the rainfall return period, and the highest subway travel risk occurs in the morning peak period. The return periods of rainfall, time-to-peak, and duration have an impact on the spatiotemporal trajectory of subway travel risk. Furthermore, the traditional census tends to underestimate subway transportation exposure due to subway travel. Subway travel risk increases significantly under the extreme rainfall scenario and requires further research. This study provides risk maps for making travel decisions before departures and support for subway operators to develop risk warnings.
... These results therefore highlight the value of incorporating a longer time period and the benefits of taking socio-demographic data into account during the calibration step, to exceed the linearity in the construction of change quantities prediction and to make them more realistic. This last approach is in line with the idea of "socializing" pixels, which appeared in the 1990s (Martin and Bracken 1993;National Research Council 1998). ...
Land use and land cover change (LUCC) models are increasingly being used to anticipate the future of territories, particularly through the prospective scenario method. In the case of so-called trend or Business-as-Usual (BAU) scenarios, the aim is to observe the current dynamics and to extend them into the future. However, as they are implemented as baseline simulation in most current software packages, BAU scenarios are calibrated from a training period built from only two dates. We argue that this limits the quantitative estimation of future change intensity, and we illustrate it from a simple model of deforestation in Northern Ecuadorian Amazon using the Land Change Modeler (LCM) software package. This paper proposes a contribution to improve BAU scenarios calibration by mainly two enhancements: taking into account a longer calibration period for estimating change quantities and the integration of thematic data in change probabilities matrices. We thus demonstrate the need to exceed the linear construction of BAU scenarios as well as the need to integrate thematic and particularly socio-demographic data into the estimation of future quantities of change. The spatial aspects of our quantitative adjustments are discussed and tend to show that improvements in the quantitative aspects should not be dissociated from an improvement in the spatial allocation of changes, which may lead to a decrease in the predictive accuracy of the simulations.
... Les auteurs mettent toujours enévidence le problème de l'interpolation et de la représentation cartographique, que ces plans proviennent d'images : -SPOT (Weber et Hirsch, 1992), -Landsat TM (Iiasaka et Egedus, 1982 ;Langford et al., 1991 ;Yuan et al., 1997), -du système nocturne DMSP-OLS (Defense Meteorological Satellite Program -Optical Linescan System)à 1 km de résolution (Sutton, 1997(Sutton, et 2003Elvidge et al., 1997 ;Takashima et al., 2003), -d'images de nuit de NOAA-AVHRR (Streutker, 2003), pour dériver la température de l'UHI (Urban Heat Island ). Martin et Bracken (1993), comme Langford et Unwin (1994), rappellent le principe de la représentation dasymétrique (Wright, 1936) (2002). Les images produites par l'instrument ASAR sont regroupées selon trois niveaux de traitement successifs : -Niveau 0 : premier niveau de traitement des données brutes pour tous les modes de fonctionnement ; -Niveau 1B : regroupe l'essentiel des produits images standards (tab. ...
M.P. Stoll, ULP Strasbourg, Rapporteur interne C. Puech, CEMAGREF Montpellier, Rapporteur externe A. Musy, EPFL Lausanne, Rapporteur externe L. Hoffmann, CRPGL Luxembourg, Examinateur F. Becker, ULP Strasbourg, Examinateur (Président du Jury)
... The detailed spatial distribution of population is often obscured by the convention of displaying uniform densities in contiguous zones, such as census areas, that cover the entire surface (Martin and Bracken 1993). Similarly, the spatial distribution of natural hazards does not conform to administrative boundaries. ...
There is a growing need for high resolution spatio-temporal population estimates which allow accurate assessment of population exposure to natural hazards. Current approaches to population estimation are usually limited either by the use of arbitrary administrative boundaries or insufficient resolution in the temporal dimension. The innovative approach proposed here combines the use of a spatio-temporal gridded population model with flood inundation data to estimate time-specific variations in population exposed to natural hazards. The approach is exemplified through an application centred on Southampton (UK) using Environment Agency flood map inundation data. Results demonstrate that large fluctuations occur over time in the population distribution within flood risk zones. Variations in the spatio-temporal distribution of population subgroups are explored. Analysis using GIS indicates a diurnal shift in exposure between fluvial and tidal flooding, particularly attributable to the movement of the working age population. This illustrates the improvements achievable to flood risk management as well as potential application to other natural hazard scenarios both within the UK and globally.
... Socio-economic studies, for example, tend to be based on administrative units such as local authority districts, wards or primary care trusts (Martin 1996). The boundaries of such units are abstract creations with no particular relation to physical realities on the ground and may be subject to periodic change (Martin & Bracken 1993). In contrast, environmental data is mainly collected on the basis of units related to either physical attributes of the environment such as watersheds, or regular sampling grids related to the technology or methodology used to acquire or store the data. ...
Integrating socio-economic and ecological or environmental data spatially, for the purpose of planning processes, allows for more effective and targeted decision making. The integration of data from different sources is however an issue which is not easy to resolve. What makes the integration of data difficult is the widely differing scale and nature of analysis units. They are commonly dictated by academic discipline, nature of the study, survey methodology, administrative / service considerations or physiographic characteristics. This paper discusses the development of a disaggregation procedure for socio-economic data based on the principles of dasymetric mapping and areal interpolation in order to develop a flexible geo-data frame which allows the data to be assigned to different demarcations seamlessly. The geo-data frame is based on the spot building count points-dataset from ESKOM. The reason for selecting this point dataset is that it represents all formal and informal built up areas in South Africa. It is therefore a good stand-in indicator of human or socio-economic activity. The geo-data frame was used to determine the total population per census sub-places. The accuracy was tested against the recent population updates of eThekwini and City of Cape Town by calculating the intraclass correlation coefficient (ICC). The cities' data was used as control totals. The ICC for both cities shows a significant correlation (very strong) between the cities' vs. the geo-data frame's outputs.
... They help decision-makers integrate information to understand and address many resource management problems. There are numerous examples of database and GIS applications in rural resource management (eg., Aspinall et al., 1993;Martin and Bracken, 1993; and see the paper by Rhodora Gonzalez, this volume). ...
... From our results, it can be concluded that monitoring areas with changing demographic and urban dynamics could be important for comprehensive urban water planning. To achieve this objective, the application of GIS tools for monitoring past and present urban and demographic dynamics, for instance at the census track level, may be very useful, especially if integrated with other physical information relevant for urban water management at different scales (Martin & Bracken, 1993). In the Mediterranean region, the successful strategic planning of urban water must consider physical and socio-demographic aspects (Kent, Newnham, & Essex, 2002), acknowledging both negative (i.e., water as a criterion to limit the urban growth) and positive (i.e., urban entities as water producers after the mobilization of new resources) interactions. ...
This article examines how the socio-demographic characteristics of residents in low-density suburban developments are important factors in understanding and predicting the attitudes and behaviors of residents in relation to residential water use. This paper is based on information obtained from 230 surveyed residents in 9 municipalities of Girona (northeast Catalonia, Spain). First, we seek to define the socio-demographic profiles of the various population groups according to their members' birthplace. Subsequently, based on the existing literature, we analyze the relationships between social groups, their socio-demographic characteristics and their attitudes and behaviors regarding residential water use. Finally, after applying a Generalized Linear Mixed Model with panel data from 77 respondents, we examine whether the birthplace of the surveyed residents and their attitudes toward the conservation of water in homes are relevant factors in determining domestic water consumption. The results demonstrate the significance of birthplace (with its related socio-demographic and urban dynamics) and water conservation attitudes on residential water use and, therefore, the need to take these factors into account when managing this resource.
... They mainly focus on how to dis-aggregate population density data at a fine spatial resolution, such as the centroid-based surface model (Martin, 1989) and the dasymetric mapping approach (Langford, et al. 1991). Comprehensive comparisons between these two techniques are reviewed by Martin and Bracken (1993). They point out that the ability to re-model census data really offers an effective alternative to integrate socioeconomic data and physical environment data in a raster-based GIS environment. ...
With the increasingly available census data and remotely sensed data, to discuss their relationship is one of important issues in GIS data integration. This paper proposes a method to demonstrate the correlations between zonal census dwelling data and residential densities discriminated by RS classification. First, texture statistic (homogeneity) along with six TM bands (bands 1-5 and 7) is put together to classify residential density levels and it is shown that the homogeneity enhances classification accuracy. After classification, close correlations between residential densities and census dwelling data have been examined by using multiple linear regression. However, the accurate classification scenario does not methodically reveal higher correlations. It is concluded that data integration of zonal census data within the framework of RS-GIS is feasible, consequently the differentiation of residential densities could offer enormous opportunities to treat dwelling-related census data, such as identification of the scale and zonal effect of the modifiable area unit problem (MAUP), and topographical representation of zonal census data.
... Socio-economic studies, for example, tend to be based on administrative units such as local authority districts, wards or primary care trusts (Martin, 1996). The boundaries of such units are abstract creations with no particular relation to physical realities on the ground and may be subject to periodic change (Martin & Bracken, 1993). In contrast, environmental data are mainly collected on the basis of units related to either physical attributes of the environment such as watersheds, or regular sampling grids related to the technology or methodology used to acquire or store the data. ...
The study of sustainable development relies upon an understanding of the linkages and interactions between the physical, social and economic environments. One of the problems confronting investigations of sustainable development has been the apparent incompatibility of spatial data collected by different academic disciplines, due to the differing scale and nature of data collection. This paper discusses techniques for reconciling such data in the development of a spatial data set designed to characterise rural England in terms of what is there, what it is like, the living and working conditions, and the political and economic context. The methodological considerations of combining data from different sampling regimes, scales and themes to a consistent unit of analysis are described. They suggest that the origin of the data, be it social, economic or physical, need not in itself be a barrier to integration. While recognising certain constraints imposed by different disciplinary cultures, the paper argues that an understanding of data form and distribution is far more critical for the creation of a spatial dataset describing the variety of conditions prevailing in rural England.
We present a pilot implementation to identify and define slums spatially, using the integrated deprived area mapping system (IDEAMAPS)’ deprivation framework. This pilot allows the integration of diverse datasets toward using a data lake architecture developed by INEGI and a grid-based approach to build an ecosystem of interoperable information with an interactive user interface. The pipeline also offers spatial scalability, transferability, and flexibility to work with different data sources, while the grid-based design can facilitate the exploration of interactions among variables. The proposed methodology was tested on a hypothetical case of use in Mexico City, integrating more than 150 variables related to slum conditions in the IDEAMAPS’ framework. Additionally, we created a visualization tool to explore the integrated data.
In this article, the author addresses the spatial incompatibility between different types of data that is commonly faced in crime analysis research. Socioeconomic variables have been proved valuable in explaining crime behaviors and in predicting crime activities. However, socioeconomic data and crime statistics are usually collected and aggregated at different spatial zonations of geographical space, making the integration and analysis of these data difficult. Simple areal weighting interpolation technique, although frequently employed, often leads to unsatisfactory results due to the fact that most types of crime do not distributed evenly across space. Using 2007 burglary crime in Houston, Texas, as an example, the author illustrates a remote sensing approach to interpolating crime statistics from police beat enumeration district used by Houston Police Department to census tract defined by the U.S. Bureau of the Census.
Shelterbelt system plays an important role in improving environment, protecting farmland and enhancing crop yield. The previous researches about effect of shelterbelt on crop were mainly focused on crop yields by field measure. These methods restricted to study the protection effect of shelterbelt on regional scale and long time series. In this paper, by comparing with the previous researches, we tried to take the crop condition instead of crop yields as index, and chose Dehui, Nong'an, Yushu and Fuyu located in the mid-west of Jilin province of China as study area. Using the 16 days MODIS NDVI data with 250 m×250 m spatial resolution in the study area as data source, the NDVI curves of crop growth were extracted to indicate the crop condition. Then through comparing the crop condition in shelterbelt protected zone with unprotected zone, we analyzed the effect of shelterbelt on crop condition at different growth phase. And with the consideration of mean annual air temperature, precipitation and soil type, we divided the study area into nine sub-zones and analyzed the impact of air temperature, precipitation and soil type on the protection effect of shelterbelt. The results showed that, 1) The crop condition in the shelterbelt protected zone was better than unprotected zone as a whole, and it was the most obvious during the peak period of crop growth, where the accumulated value of NDVI in protected zone was increased by 0.05 than unprotected zone; 2) As the air temperature increase, the impact on protection effect tends to increase significantly, and as the air temperature increased by 0.5°C, the difference of accumulated value of NDVI between protected and unprotected zone was increased by 0.02; 3) With increase of precipitation, the impact on protection effect also tends to increase significantly at the beginning of crop growth, and with the precipitation increase of 100 mm, the difference of accumulated value of NDVI between protected and unprotected zones increased by 0.03 in this phase; 4) For different soil types, there was no significant impact on protection effect. In a word, the research can not only provide decision-making support for the shelterbelt management, promote the information technology level of management, but also enrich the monitoring method in shelterbelt field for remote sensing and improve the monitoring level of shelterbelt at regional scale.
The main purpose of this paper is to recognize the managing phase of shelterbelt by remote sensing, which can provide timely information for manager of shelterbelt. In this paper, by using multi-temporal remote sensing images, combined with the theory of management for shelterbelt, a method for monitoring the managing phase of the shelterbelt was established. Taking an area of 10 km × 10 km in northern Changchun as examples, we used the TM and ETM images to analyze the managing phase of the shelterbelt in the area, and compared the relative precision resulted from different monitoring period. The results showed that, compared with the results of the annual monitor, the whole precision of three years period was 84.8%, and that in the period of six years was 78.4%. Therefore, based on an overall consideration of computation efficiency, data availability and monitor precision, it is concluded that monitoring result of three years period can not only coincide with the growth and development law of shelterbelt, but also has an acceptable precision.
Awareness of spatial differences in disease incidence has existed for thousands of years. In biblical times before the Exodus, the Israelite refugees witnessed how the plagues that afflicted Egypt avoided the land of Goshen but selectively attacked the people living in the other areas (Exodus 9). Work relating to geographical dimensions of disease pre-dates the laboratory orientation of scientific and clinical medicine which was emerging around the time that Robert Koch discovered the cholera vibrio. Distributions of diseases, of which cholera serves as an excellent example, have been utilized to explain disease occurrence by elucidating causal mechanisms, describing its natural history, or providing guidance in the administration of health services.
Although GIS application integration system has not officially formed, the distributed GIS application integration is the main means to implement the seamless integration between GIS and applications. This paper studied on the current situation of enterprises GIS application integration, and proposed an Loose Model Application Integration (LMAI) strategy based on meta-driven, defined the concept model and algorithm of application integration in loose coupling mode, designed the system integration framework of meta-model and applications, established the common application integration interface employing the Application-Oriented Component (AOC), developed the application integration system in GIS loose coupling mode underlying the Metadata-driven. Focusing on the GIS actual needs in gas field area, the effective integration and transmission query between GIS and the gas field professional application were implemented.
This paper evaluates and maps the quality of life in the Atlanta, Georgia metropolitan area in 2000. Three environmental variables from Landsat TM data, four socioeconomic variables from census data, and a hazard-related variable from toxic release inventory (TRI) database were integrated into a geographic information system (GIS) environment for the quality of life assessment. To solve the incompatibility problem in areal units among different data, the four socioeconomic variables aggregated by zonal units were spatially disaggregated into individual pixels. Principal components analysis (PCA) was employed to integrate and transform environmental, socioeconomic, and hazard-related variables into a resultant quality of life score for each pixel. Results indicate that the highest quality of life score was found around Sandy Springs, Roswell, Alphretta, and the northern parts of Fulton County along Georgia 400 whereas the lowest quality of life score was clustered around Smyma of Cobb County, the inner city of Atlanta, and Hartsfield-Jackson International Airport. The results also reveals that normalized difference vegetation index (NDVI) and relative risk from TRI facilities are two versatile indicators of environmental and socioeconomic quality of an urban area in the United States.
Urban sprawl is gaining increasing attention in developing countries of the world, With a population of some 1,027 million people, India has more than 10 cities that have one million population. This population is bound to grow and is a major concern of urban sprawl in most of the cities. In this study, we analyze the trends in vegetation greenness patterns in six different cities of India. An attempt has also been made to relate these vegetation changes to population densities. Temporal changes in vegetation vigor from 1984 till 2000 have been analyzed using vegetation greenness index and change detection methodology using NOAA AVHRR remote sensing data. Results from this analysis suggested different patterns of vegetation changes over a period of time. Of the six cities, Hyderabad and Mumbai had similar patterns of vegetation change, where the "vegetation loss" has considerably decreased from 1984 till 2000. Calcutta showed increasing vegetation loss from 1996 to 2000. To infer the patterns of vegetation dispersion resulting from urban sprawl and land development, entropy index has been used. Results from this index suggested that the city of Bangalore had much less dispersion in vegetation compared to Hyderabad and New Delhi. Further, results for Calcutta and Hyderabad suggested that the vegetation has been changing toward concentrated pattern. Results from correlation analysis suggested that as population density increased, the entropy of vegetation greenness decreased in the cities of Calcutta, Bangalore, and Mumbai and Hyderabad compared to Chennai and Delhi. These results suggest that as the density of population increased, the vegetation greenness became more concentrated in these cities. These results on vegetation changes will be useful for urban planners and researchers in addressing some urban climate issues in the rapidly growing cities of India.
A computerised aid to the land use planning process is demonstrated on the urban edge of Cape Town, South Africa. Multi-criteria analysis is performed in the IDRISI GIS package to evaluate development suitability for four land use categories according to appropriately measured and weighted criteria. The four suitability images are then subjected to multi-objective land allocation to demarcate optimum locations for each land use type. The decision-making process entails execution of seven consecutive steps which are discussed in detail and applied in the case study. Technical decisions are rationalised and results displayed. The paper concludes with a call for the development of applications which can incorporate public participation in this type of decision-making process to ensure the wider acceptance of advanced GIS technology as appropriate technology.
Development of the Spatial Information System(SIS) consists of the Remote Sensing and the Geographical Information System and Global Navigation Satellite System, that etc provides the vast road into the fast and accurate inquisition of the resources, also provides the brand-new means to the obtain quickly and management and applications of the medium relevant information in sustainable development of the City and Countryside Orchestrate to Experiment the Area research and practice. Aim in text, the Spatial Information System(SIS) support bottom, establishment the concept frame and index sign systems of the evaluation for Sustainable Development of the City and Countryside Orchestrate to Experiment the Area. For example, the Chengdu and Countryside Orchestrate to Experiment the Area for evaluate the unit, make use of the data of RS and GNSS to carry on the dynamic state analysis and evaluations for the ecosystem environment of the Chengdu and Countryside Orchestrate to Experiment the Area.
In geographic information systems (GIS) studies there has been some difficulty integrating socioeconomic and physiogeographic data. One important type of socioeconomic data, census data, offers a wide range of socioeconomic information, but is aggregated within arbitrary enumeration districts (EDs). Values reflect either raw counts or, when standardized, the mean densities in the EDs. On the other hand, remote sensing imagery, an important type of physiogeographic data, provides large quantities of information with more spatial details than census data. Based on the dasymetric mapping principle, this study applies multivariable regression to examine the correlation between population counts from census and land cover types. The land cover map is classified from LandSat TM imagery. The correlation is high. Census population counts are remodeled to a GIS raster layer based on the discovered correlations coupled with scaling techniques, which offset influences from other than land cover types. The GIS raster layer depicts the population distribution with much more spatial detail than census data offer. The resulting GIS raster layer is ready to be analyzed or integrated with other GIS data.
In this article, the author addresses the spatial incompatibility between different types of data that is commonly faced in crime analysis research. Socioeconomic variables have been proved valuable in explaining crime behaviors and in predicting crime activities. However, socioeconomic data and crime statistics are usually collected and aggregated at different spatial zonations of geographical space, making the integration and analysis of these data difficult. Simple areal weighting interpolation technique, although frequently employed, often leads to unsatisfactory results due to the fact that most types of crime do not distributed evenly across space. Using 2007 burglary crime in Houston, Texas, as an example, the author illustrates a remote sensing approach to interpolating crime statistics from police beat enumeration district used by Houston Police Department to census tract defined by the U.S. Bureau of the Census.
The sustainability of rural development depends on the distribution of the social and environmental resources needed to maintain and improve the vitality of rural areas. Here we examine the complexity of measuring patterns of distribution using examples of socioeconomic data on rural poverty and affluence as well as data on environmental quality and species richness. We demonstrate how changes in the base spatial units used for analysis have different effects on different measures of inequality. The effects of such changes in spatial resolution also depend on the underlying processes that generate the data. The results of our investigations into the effects of scale on the assessment of inequality suggest that, where data come from both the social and natural science sources, the most appropriate level for analysis is that of the finest common resolution. This may result in redundancy of effort for some types of data but any such disadvantage is offset by the benefits of identifying inequalities that are masked at coarser resolutions.
The main objective of the present research is to develop a methodology for the generation of trips using Geographic Information Systems and Remote Sensoring. According to the new developments in this technology, it is now possible to sectorise an urban structure, through the analysis of the data obtained from aerial photographs. Furthermore, this sectorization allows the systematic identification of sectors with similar characteristics. These characteristics allow the definition of the geometric and photographic patterns in the urban structure, which can be grouped up to form "Homogeneous Aggregated Sectors" (HAS). Based on the fundamentals from Geographic Information Systems (GIS) and Remote Sensing (RS), using the treatment of aerial photographs, a methodology was developed for the analysis and classification of the data from these images that results in of "Photo-Interpreted Classes" (PIC), which are grouped up to form "Homogeneous Aggregated Sedors" (HAS). With respect to the case study of the town of Sobradinho, 16 PlCs and 15 HASs were identified. Furthermore, based on the relationship of these classes with the census data obtained from IBGE (Instituto Brasileiro de Geografia e Estatistica), the formulation of a model for the generation of trips was developed. This model of trip generation factors for each class, in Sobradinho town was obtained. This results shows the relation between land use pattern and trip generation. In this study, the highest value was obtained in residential sectors with buildings with many floors while, mixed occupation patterns, such as residences and workshops or residences and comercial area, presented low value comparing with residencial patterns. It was also verified that the factor values of a class are influenced by the age of the area.
Local area spatial analysis, using census-type data and derived indicators, has an important role in the allocation of public resources. The Government places a growing emphasis upon the evaluation of such allocation decisions and the need for them to be substantively justified. Traditional zone-based analysis, using administrative areas such as districts or wards, have long been recognised as suffering both geographical and inferential limitations in this role. Here, a surface model approach to population-based data representation is described which offers important advantages for inferential work over traditional methods. Local area indicators can be uniquely generated with great spatial flexibility. This article has demonstrated the versatility of surface model concepts applied to areas of public policy. The methods outlined address a central requirement in the use of social and economic data derived from a variety of sources in informing public policy making to ensure that the form of representation accords closely with the nature of the phenomenon. More generally the approach has important properties of data integration and analysis that are likely to have wider application for information handling in geography and planning. -from Author
Some reuslts of a study to develop the potential of LANDSAT imagery for monitoring urban growth are described. Automated digital extraction of urban areas from single screens is not yet sufficiently accurate for such monitoring. Two additional measures are suggested to overcome some of the problems. These are the use of a base-line survey to limit the area of search and use of successive scenes to confirm the growth.
The authors are concerned with cross-estimation, or the estimation of data values for one set of reporting zones based on known values for another set. In essence this is the applied perspective on the modifiable areal unit problem, as cross-estimation is vitally important to people working with demographic or socioeconomic data in health, political redistricting, regional economic modeling and a number of other practically significant areas. It is also an information-limited problem - the more one knows about the area, the better the estimates. Information on some underlying factor might be used to improve the target zone estimates over the results of more naive techniques. -from Editors
Addresses the use of GIS within planning. It examines the tasks typically performed by planners which involve spatial data handling and the consequences in terms of data sets and GIS functionality. An objective of the chapter is to assess, in a critical way, the GIS resources currently available and the needs for a spatial decision support system. The final part of the chapter utilizes a case study of a major GIS project in the US to demonstrate how Digital Line Graphs, TIGER files and remotely sensed data can be integrated into a single system that successfully addresses many of the obstacles normally associated with the use of GIS in planning. -Authors
This paper provides an overview of developments and applications of geographical information systems(GIS) in North America over the past 20 years, together with some indications of lessons learned and prospects for the future. Most developments in this field have been confined to a small number of sectors, including forestry, land registry, transport and facility planning, civil engineering, agriculture and environment, although progress has been variable. The wider use of GIS has been (and will probably continue to be) inhibited by a number of factors, such as lack of digital base mapping, limited digital data, unawareness among potential users and resistance to new technology, coverage of data, assessment of costs and benefits, technological developments affecting GIS and sources of funds for research to political structures, availability of skilled staff, lack of proper advice, the un wisdom of going it alone' and management problems (which are as important as technical problems, if not more so). A successful programme of GIS depends on a coordination of effort relating to applications, trained personnel, governmental involvement in R.&D. and development of a source of independent advice.
A brief summary is presented of a study on Geographic Information Systems; a full report on the study is being published elsewhere. At present, the benefits of satellite remote sensing within the U.K. are largely potential rather than established. A continuing need exists to explore ways of widening the topics to which remote sensing can be applied and to demonstrate the values of remote sensing in enabling existing tasks to be undertaken even more efficiently and cost effectively. Planning, managing and monitoring natural and cultural resources require timely information, the capability to update this information regularly-if not frequently, and the need to interrelate different sets of information for wise and objective decision making. All are prime areas for testing the utility of remote sensing within the operating environment of a geographic information system (GIS).
A discussion of the benefits of satellite remote sensing to urban studies is followed by a consideration of resolution requirements and associated problems. Problems include loss of contextual clues for interpretation, heterogeneity of cover surfaces, temporal differences in atmospheric effects and registration of different scenes. A number of solutions to these problems are considered, such as the use of reference surfaces for atmospheric corrections and the use of targetted control points for temporal change monitoring. The specific advantages of high-resolution satellite data are particularly considered
Remotely-sensed data constitute a major potential source of input to geographical information systems (GIS)However, these data often have a relatively poor classification accuracy compared with that of the cartographic data from maps with which they may be combined in the course of GIS analysis. The possibility exists of using data sets (in the form of digital maps) resident within a GIS in order to improve this accuracy, before the classified image is incorporated into the GIS. Results are discussed from a British Alvey Information Technology project to develop a system for the knowledge-based segmentation and classification of remotely-sensed terrain images, in which the knowledge contained in digital map
This paper describes a framework for the role of geographical information systems (GIS) in the monitoring and management of hazardous waste sites. Compilation of required information, incorporation of existing strategies for waste monitoring, analysis of these data in a GIS environment and the integration of computerized models for transport processes are discussed. Examples for the analysis of spatial data using techniques of cartographic overlay and the implementation of geo-statistical methods on monitoring data are provided from work in progress by the authors. These examples are set in the context of developing a fully integrated monitoring and management system utilizing GIS technology.
The role of GIS in the official counting of population numbers has expanded substantially in recent years, even if the procedures are rarely described officially in GIS terms. Counting the people and ascertaining their characteristics is a non-trivial operation. This chapter sets out to describe the fundamental tasks involved in counting population, the alternative ways in which this is achieved in different social, economic and political circumstances, and how GIS can underpin both the preplanning phase and the subsequent data compilation, analysis, dissemination and display. It uses case studies of censuses in Britain and the United States and population registers in Scandinavia to demonstrate the international variations. -from Author
Considers the nature of the modifiable areal unit problem. A survey is made of the prevailing ambivalent attitudes that geographers display and the general absence of any sense of verisimilitude is emphasized. A critical review is made of several alternative approaches to handling the problem.-from Authors
The paper introduces a method of population estimation using the Landsat MSS data. The radiance in the four spectral bands, detected by the multi spectral scanner (MSS) depends upon the ground covering materials, albeit the land use of the area. A mathematical model is set up to express the relation between the reflected electromagnetic energy of sample areas and their population distribution. Landsat 1 and Landsat 3 data of the Kanto area (including Tokyo Metropolitan), acquired in 1972 and 1979, are used along with ground-based census data of 1970 and 1975 to monitor the population distribution and its temporal changes. The method provided a reliable assessment of the population density in residential zones, however land-use classification using MSS imagery previous to the modeling is expected to improve the results.
In an effort to automate the time-consuming procedure of the dwelling unit count method of population estimation using aerial photographs, a raster approach was adopted to extract residential building density data on a grid cell by grid cell basis from high-altitude aerial and space photographs. The maximum possible occurrence of dwelling units in each grid cell was determined with reference to the dwelling unit sizes and existing housing data from the census. The actual percentage of occurrence of residential buildings in each grid cell was then estimated from the photographs and translated into a population estimate. This approach was applied to the Providence area, Rhode Island, using both black-and-white National High Altitude Photography (NHAP) at 1:80,000 scale and Large Format Camera (LFC) photography enlarged to 1: 50,000 scale. It was found that the number of dwelling units so obtained from NHAP had to be corrected with the application of a double logarithmic model and that tone was the sole element used in dwelling unit estimation in the case of LFC photography. At census tract level, population estimates exhibited mean relative errors between +2.50 and +6.94% in NHAP and between −8.24 and −13.64% in LFC photography, depending on whether regional or overall household size values respectively were employed in computing the population size from the number of dwelling units. The raster approach permitted the application of a microcomputer-based GIS package to model and update the population estimation from high altitude aerial and space photographs.
This paper examines the common methods for converting spatial data sets between vector and raster formats and presents the results of extensive benchmark testing of these procedures. The tests performed are unique in this field since: (1) they used both synthetic and real test data sets; (2) they measured conversion quality, accuracy and efficiency, not just how fast the procedure operated; and (3) they were conducted in a generic geographic information system (GIS) environment without the aid of specialized computer hardware. The results show that the best overall techniques are the ones which take advantage of spatial relationships inherent in the data sets. These were the Scan Line algorithm for vector to raster conversions and the Boundary Linking algorithm for raster to vector conversions.
Remotely-sensed image data have long served as a primary source of information for. geographical information systems (GIS), with the transformation of data to information provided by visual image interpretation. Digital image data, in combination with recent advances in computer technology, currently allow visual image interpretation to be realised in a completely digital processing environment. However, it remains desirable to capitalize even further on the potential of digital image data for GIS, through the use of schemes involving automated data processing. The opportunities for, and impediments to, such schemes are considered here with particular reference to the provision of information for natural resource management. It is concluded that further—although foreseeable—developments in both research and technology will be required before fully operational procedures for the automated acquisition of GIS information from image data can be established.
A text detailing critical aspects of geographic information systems for land resources assessment. Nine chapters cover themes on: 1. Overview of GIS components - computer mapping, data bases, future directions. 2. Data structures for thematic maps, including files, spatial data definitions, vector and raster structures, database facilities. 3. Digital elevation models. 4. Data input, verification, storage and output. 5. Methods of spatial data analysis and modelling, ranging from basic map overlay, to natural language processing. 6. Data quality, errors, and the nature of spatial data on maps. 7. Classification techniques - multivariate, and using expert systems. 8. Spatial interpolation methods. 9. Selecting a GIS. Each chapter has a list of references, and two appendices give a glossary of terms, and a list of selected information sources.-after Author
The integration of CAD/CAM/mapping with image processing using geographic information systems (GISs) as the interface is examined. Particular emphasis is given to the development of software interfaces between JPL's Video Image Communication and Retrieval (VICAR)/Imaged Based Information System (IBIS) raster-based GIS and the CAD/CAM/mapping system. The design and functions of the VICAR and IBIS are described. Vector data capture and editing are studied. Various software programs for interfacing between the VICAR/IBIS and CAD/CAM/mapping are presented and analyzed.
Geographers are familiar with the difficulties encountered in the use of choropleth maps to represent census-type data, especially those associated with the modifiable areal unit problem. Here, an alternative, raster representation is suggested which seeks to recover some of the underlying distribution from population weighted centroids. These issues are considered, and found to be of great importance to any attempt to build a geographic information system for population-based data. -from Author
The development is explained of a technique to generate 'modeled' surfaces of census-type socioeconomic survey data that offer the potential to overcome many of the problems inherent in the analysis and presentation of such data in conventional area-based form. Potential benefits of the modeled surfaces include a level of resolution that arguably can provide a more finely focused spatial basis for the generation of a wide range of spatial indicators that can aid public policy making. This type of application requires that the method is set within a flexibly managed information framework and includes suitable tests for the reliability of the generated surfaces.
Object oriented GIS improving environmental compatibility in Italian rural landscape planning
- Besio
Besio, M. and Roccataglianta, E. (1991) Object oriented GIS improving environmental compatibility in Italian rural landscape planning. In Proceedings of the Second European Conference on Geographical Information Systems, Vol. 1, pp. 95-105.
The role of GIS in rural land use monitoring-current UK issues The generation of socioeconomic surfaces for public policy making
- A C Bird
Bird, A. C. (1991) The role of GIS in rural land use monitoring-current UK issues. In Proceedings of the Second European Conference on Geographical Information Systems, Vol. 1, pp. 121-127. Utrecht: EGIS Foundation. Bracken, I. (1989) The generation of socioeconomic surfaces for public policy making. Environment and Planning B, 16, 307-325.
Contextual classification of urban areas using population data
- Drayton
The role of GIS in rural land use monitoring—current UK issues
- Bird
Land division survey of the Netherlands 1990: a geographical information system for land-use management
- Linthorst
Information extraction from remotely sensed images for urban land analysis
- Sadler
Integration of GIS-derived spatial data with satellite imagery for improved land cover mapping using an expert system
- Wilkinson