THE APPLICATION OF REMOTE SENSING AND GIS IN URBAN PLANNING MSc. Eng. Bahaa Eddin I. Al Haddad [email protected] I.S.U.F.I.– Universita’ delgi studi d...
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THE APPLICATION OF REMOTE SENSING AND GIS IN URBAN PLANNING MSc. Eng. Bahaa Eddin I. Al Haddad [email protected] I.S.U.F.I.– Universita’ delgi studi di Lecce- Via Monteroni s.n.- 73100 Lecce, tel. 0832 421 203 – fax 0832 421 221, http://isufi.unile SUMMARY Today, nearly half of the world's population lives in cities. In developing countries, people are deserting rural areas while population is rising rapidly. In less than 20 years from now, these two factors will combine to drive over two billion people into urban areas, which in some cases are already overcrowded. The conditions that many new city dwellers find on arrival simply compound the situation. Most urban growth falls outside formal planning controls, thus increasing economic and social pressures and exacerbating health and hygiene problems. The main advantages of Remote Sensing with GIS are to bring parties together, to spread and improve idea, to support the decision-making process, and to evaluate projects.

INTRODUCTION The future of Remote Sensing and GIS technologies will be interoperable. As such it offers opportunities to improve and to structure the information about the planning process and to make it accessible for all participants in the planning process and the general public. Remote Sensing with GIS can be of service to provide information, brings parties together, spread and improves idea, supports the decision-making process and to evaluate projects. The objectives of this paper is to confine it’s search for new techniques to deal with large Urban agglomeration and application of GIS and Remote Sensing technique at various stages of planning implementation and monitoring of the Urban projects.

1.0 REMOTE SENSING AND GIS TECHNOLOGIES Historically, Remote Sensing and GIS technologies developed as separated disciplines for both culture and information technology reasons. After over 20 years of essentially separated development, Remote Sensing application beginning to recognize the advantages of integrating GIS dataset in to image analysis. Very quick view let us know what is the meaning of Remote Sensing and GIS. Remote Sensing is: ”the measurement and analysis of electromagnetic radiation reflected from, transmitted through, or absorbed and scattered by the atmosphere, the hydrosphere and by material at or near the land


surface, for the purpose of understanding and managing the Earth’s resource and environment” (Larry Morley, Teledetection International). As to GIS :”is an integrated system of computer hardware, software, and trained personnel linking topographic, utility, facility, image and other resource data that is geographically referenced” (NASA, 2000) In all case, however, the linkage between Remote Sensing and GIS is clear and intelligent for preparation of base-map, formulation of planning proposal that acts as monitoring tool during implementation phase. A benefit from merging of GIS and Remote Sensing technologies are well recognized. On one side, GIS can be used for improving the information extraction potential of remotely sensed data. On other side, remotely sensed data can be used for updating GIS information.

2.0 URBAN PLANNING APPLICATION IN R.S. AND GIS Urban Planning can be defined variously as: “the formulation of alternative patterns of urban settlement, the rational use of resources to alleviate urban problems, and the provision of city’s physical and social infrastructure: transportation, utilities, housing, community facilities, and service”. The urban planning application using R.S. and GIS tools is one of the many areas where such utilities can be used for managing planning activities. The planner can look for different options and choose the best suited for the end result. The automated process is not only faster but also can be monitored effectively at any eventuality.

2.1 WHY REMOTE SENSING AND GIS? With multi-temporal analyses, Remote Sensing gives a unique perspective of how cities evolve. The key element for mapping rural to urban land use change is the ability to discriminate between rural uses (framing, pasture forest) and urban use (residential, commercial, and recreational). Remote Sensing method can be employed to classify types of land use over large areas in a practical, economical and repetitive fashion, over large areas. As an information management tool, GIS was originally a project-specific tool intended to deal with map-based physical application, such as tax mapping or surveying inventorying of utility networks running mainframes or minicomputers. Another important it is a fast moving and continuously developing technology. Future Remote Sensing and GIS software will be interoperable and web based. There will be no room left for specialist, standalone database system. And they are moving from ‘close’ to ‘open’ computing. This change has been set into motion because users want their corporate information system to handle any data regardless of the data’s complexity or sours, including spatial information.


3.0 PILOT PROJECT: We will discuss in this small example how Remote Sensing and GIS package can be managing rezoning exercise in a neighborhood property. If we know the problem Scenario zoning as the classification of an area into land use districts. Example of general land use districts and residential, industrial, commercial, and public open space. These can farther be classified into more detailed categories. Over a period of time, changing population and commercial needs often necessitate changes to zoning plan. With Remote Sensing and GIS we need to understand how cities will go to increase and protect what this city need to grow. 3.1 DATA REQUIREMENTS: In the beginning let us know what is the meaning of Image classification? The intent of the classification process is to categorize all pixels in a digital image into one of several land cover classes, or “themes”. This categorized data may then be used to produce thematic maps of the land cover present in an image. Normally, multispectral data are used to perform the classification indeed. The spectral pattern present within the data for ach pixel is used as the numerical basis for categorization. Requirements for rural/urban change detection and mapping applications are: - High resolution to obtain detailed information. - Multispectral optical data to make fine distinction among various land use classes. 3.2 THE STEPS: 1- classify old and new satellite images with R.S. tool (ER Mapper) for San Diego layout _ Landsat_TM_1985 & 1990 with scale 30 X 30 resolution, (note: I will use this satellite image from ER Mapper territorial with the aim of study with keeping all copyright for Earth Resource Mapping Pty Ltd). 2- Compared between both classified images with R.S. tools. 3- Building a sample data bas with GIS tool (I will use in this example

GeoMedia Prof. 4). 4- Analysis and result. In our case study we will use supervised classification features to transform multispectural image data into user-defined thematic information classes. We are using a scale 30X30 for the general information investigation like regional land use, ecological analysis, soil, water, vegetation and built area..etc. required by regional planning and resource management, this resolution can meet the needs of the professional which is demonstrated by many case studies and practical projects, including the one done by other.


3.2.1 Regions choice In the first way to choose which area can we use to make a supervised classification depend on which data we need from this satellite image, usually taking a sample from ground to analyze and determine the position of these samples with GPS after determining these points on satellite image in such a way will give more accurate to classify. In our example we before which kind that we need, (Figure 1 & 2): 1- Deep Water 2- Urban Area

3- Residential Area 4- Green Grass

Fig. 1: Landsat year 1985, region choice process.

5- Sand 6- Shallow Water

Fig. 2: Landsat year 1991, region choice process.

3.2.2 Supervised Classification After choosing a regions area we will made a supervised classification with ER Mapper R.S. tool, the results can be seen in figure (3 & 4): From this result we get a lot of information that haven’t been reached before, such as table (1) is presenting the area in hectare for each region in each band, also a diagram (2) are presenting a percentage of each area from the total area


Fig. 3: Super classification satellite image, San Diego, year 1985

Regions choice Residential Area Urban Areas Sand Green Grass Deep Water Shallow Water

Fig. 4: Super classification satellite image, San Diego, year 1985

Area in hectare, San Diego 1985 Band1 to Band 7 8445.87 5191.47 2981.61 696.6 2095.74 3088.71

Area in hectare, San Diego 1990 Band1 to Band 7 9467.82 4885.74 3062.34 392.85 1762.29 2928.87

Table 1: Statistic for Dataset, Area in Hectare for each region in each band, San Diego 1985, 1985

Diagram 2: a percentage for each region area, San Diego 1985 & 1990

Of satellite image. Now we can compare between both satellite images through tables and diagrams or with R.S tool. (Figure 5).


1985 & 1991

New Image

Old Image



Compared between two supervised classification and True color Satellite images, San Diego, year 1985 & 1991.


3.2.3 WORK UNDER GIS TOOLS With our example, San Diego satellite image we wanted to develop is a country –wide interdepartmental GIS. There for monitoring and managing future growth, such as a new school to accommodate the growing number of school children in the area and developing streets to accommodate the growing number of population or increase a residential area. Under GIS tool such as GeoMedia Pro.4 we will import last supervised classification image to make a digitizing (figure 6) and build a simple database


presenting how we can determine a new school, for example, through understanding which are in density populated (figure 7).

Fig. 6: Supervised classification image after digitizing in GeoMedia GIS, San Diego, year 1985.

Fig. 7: Buffer zones for new school, GeoMedia GIS, San Diego, year 1985.


4.0 CONCLUSION This paper illustrates the importance of computer aided tools for day-to-day activities. With this introduction for Remote Sensing and GIS should never be standalone operation. The Remote Sensing and GIS are being developed to support the urban planning process and will be part of a larger system. The new technology is a component based that makes possible to deliver scalable, continuously available, timely, and useful information from a limitless variety of sources for analysis and update. ACKNOWLEDGMENTS I have to thank ISUFI and GeoMap s.r.l., and in particular Eng. Paglialunga, Prof. Roberto Cingolani, Prof. Luciano Guerriero, and Prof. Lorenzo Vasanelli, who allowed me to perform this stage. A cordial farewell also to Dr. Emanuela Chiriacò, Dr. Ivana Bianco, Eng. Marco Palazzo, Dr. Letizia Sabetta, Mr. Gianfranco and Mr. Giuri Fabio. REFERENCES •

Wiliam L. Stefanov, Michael S. Ramsy, Philip R. Christensen Monitoring Urban Land Cover Change: An Expert System Approach to Land Cover Classification of Semiarid to Urban Centres Department of Geological Sciences, Centre for Environmental Study and Department of Geology and Planetary, Arizona State University and University of Pittsburgh, USA P.S.Uttarwar, Join Director (Planning) Application of GIS and Remote Sensing in Urban Planning, Implementation and Monitoring of Urban Projects – case study of Rohini and Dwarka project, New Delhi Delhi Development Authority, New Delhi, India Prof. Binyi Liu Toward The 21ST Century: GIS and Remote Sensing Application on Architecture, Urban and Landscape Panning. College of Architecture and Urban Planning, Tongji University, China Jerry C. Coiner Enterprise GIS in Urban Planning and Management Ph.D., Principal Remote Sensing and Information Systems Co., Kailua-Kona, HI USA

WWW Geographic Information System: ƒ ƒ ƒ ƒ Remote Sensing ƒ ƒ ƒ Urban Planning & Remote Sensing ƒ ƒ


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