GIS, REMOTE SENSING, AND IMAGE PROCESSING IN STUDYING URBAN SYSTEMS

The Geographic Information System (GIS) is a computer-assisted system for acquisition, storage, analysis and display of geographic data. GIS allows for creating, maintaining and querying electronic databases of information normally displayed on maps. These databases are spatially oriented, the fundamental integrating element being their position on the earth’s surface. This system consists of a set of computerised tools and procedures that can be used to effectively encode, store, retrieve, overlay, correlate, manipulate, analyse, query, and display land-related information. They also facilitate the selection and transfer of data to application specific analytical models capable of assessing the impact of alternatives on the chosen environment. The underlying foundation of sound GIS is an effective digital map database, tied to an accurate horizontal control survey framework.
The spatial data generally is in the form of maps, which could be showing topography, geology, soil types, forest and vegetation, land use, water resource availability etc., stored as layers in a digital form. Integrating many layers of data in a computer can easily generate new thematic maps. Thus, a GIS has a database of multiple information layers that can be manipulated to evaluate relationships among the selected elements. GIS can create maps, integrate information, visualise scenarios, solve complicated problems, present powerful ideas, and develop effective solutions.
GIS works with two fundamentally different types of geographic models, the “vector” model and the “raster” model. Raster organises spatial features in regular spaced grid of pixels, while the vector data structure organises spatial feature by the set of vectors, which are specified by starting point co-ordinates. A single x, y co-ordinates, can describe the location of a point feature, such as a location of boreholes. Point features are represented as vectors without length and direction. Linear features such as roads and rivers can be stored as point co-ordinates. Polygon features, such as land parcels and river catchments, can be stored as a closed loop of co-ordinates. Compared to a line designated in a raster format, a vector line is 1-d and has no width associated with it. The vector model is extremely useful for describing discrete features, but less useful for describing continuously varying features such as soil top.
Advantages of vector type data
The Vector Storage type uses less storage space
It supports greater precision in the computation and processing of spatial features.
The smallest feature in a raster data structure is represented by a single pixel.
The raster model has evolved to model continuous features. A raster image comprises a collection of grid cells rather like a scanned map or a picture. Both the vector and raster models for storing geographic data have unique advantage and disadvantages.
Advantages of raster data type
provides better representation of continuous surfaces.
Map overlays are efficiently processed if thematic layers are coded in a simple raster structure.
Because the raster grid defines pixels that are constant in shape, spatial relationships among pixels are constant and easily traceable
GIS has been touted as a great boon to engineering, science, planning, and decision-making in every field. Some of the noteworthy applications of GIS are:
Map generation;
Calculation of land use;
Analysis of optimal land use allocations;
Determining changes over time – Temporal Analyses;
Route guidance and planning;
Targeted marketing;
Habitat prediction; and
Ecosystem simulation / Environmental modeling. Remote Sensing
Remote sensing refers to obtaining information about an object, area, or phenomenon through the analysis of data acquired by a device that is not in contact with the object, area, or phenomenon under investigation (Lillesand and Kiefer, 1996). The eyes are an excellent example of a remote sensing device. With this, it is possible to gather information about the surroundings or even reading the text as in this case. However, this simple definition of remote sensing is more commonly associated with the gauging of interactions between the earth surface and the electromagnetic energy. These days the data gathering of the earth surface is enabled with various sensors that are able to efficiently absorb reflected energy from the earth’s surface. The satellites with onboard sensors, play an important role in data capture.
Remote sensing systems are a very important source of information for GIS, as they provide access to spatio-temporal information on surface processes on scales ranging from regional to global. A wide range of environmental parameters can be measured including land use, vegetation types, surface temperatures, soil types, precipitation, phytoplankton, turbidity, surface elevation and geology. Remote sensing and GIS aid immensely in urban sprawl studies.
In the case of a combined application, an efficient, even though more complex, approach is the integration of remote sensing data processing, GIS analyses, database manipulation and models into a single analysis system (Michael and Gabriela, 1996). Such an integrated analysis, monitoring and forecasting system based on GIS and database management system technologies requires the analyst to understand not only the problem but also the available technologies yet without being a computer expert.
The integration of GIS and remote sensing with the aid of models and additional database management systems (DBMS) is the technically most advanced and applicable approach today.
The remote sensing applications are growing very rapidly with the availability of high-resolution data from the state of the art satellites like IRS-1C/1D/P4 and Landsat. The advancement in computer hardware and software in the area of remote sensing also enhances remote sensing applications. IRS-1C/1D/P4 provides data with 5.8 m resolution in panchromatic mode giving more information of the ground area covered. The remote sensing satellites with high-resolution sensors and wide coverage capabilities will provide the data with better resolution, coverage and revisit (once in 24 days for IRS 1C) to meet the growing applications needs. Many applications like crop acreage and yield estimation, drought monitoring and assessment, flood mapping, wasteland mapping, mineral prospects, forest resource survey etc., have become an integral part of the resources management system. These resource management systems need the data to be transferred in real time or near real time for processing.
The land use classification is primarily to understand the spatial distribution of various land features and plan accordingly for optimum utilisation of the land with least effects on the associated systems. The pattern and extent of land use is influenced mainly by two factors – physical and anthropogenic. Physical factors include topography, climate and soils, which set the broad limits upon the capabilities of the land, and the anthropogenic factors are, density, occupation of the people, socio-economic institutions, the technological level, and infrastructure facilities. GIS and remote sensing collectively help in understanding and undertaking these applications effectively.
Image Processing – Restoration, Enhancement, Classification, Transformation
The digital image processing is largely concerned with four basic operations: image restoration, image enhancement, image classification, and image transformation (Eastman, 1999). The image restoration is concerned with the correction and calibration of images in order to achieve as faithful representation of the earth surface as possible. Image enhancement is predominantly concerned with the modification of images to optimise their appearance to the visual system. Image classification refers to the computer-assisted interpretation of images that is vital to GIS. The image transformation refers to the derivation of new imagery as a result of some mathematical treatment of the raw image bands.
The operation of image restoration is to correct the distorted image data to create a more faithful representation of the original scene. This normally involves the initial processing of raw image data to correct for geometric distortions, to calibrate the data radiometrically, and to eliminate the noise present in the data. Image rectification and restoration are also termed as pre-processing operations.
Enhancement is concerned with the modification of images to make them more suited to the capabilities of human vision. Regardless of the extent of digital intervention, visual analysis invariably plays a very strong role in all aspects of remote sensing. Enhancement of the imagery can be done by the histogram equalisation method or linear saturation method before analysis.
Digital image classification is the process of assigning a pixel (or groups of pixels) of remote sensing image to a land cover or land use class. The objective of image classification is to classify each pixel into one class (crisp or hard classification) or to associate the pixel with many classes (fuzzy or soft classification). The classification techniques are categorised based on the training process – supervised and unsupervised classification.
Supervised classification has three distinct stages namely training, allocation and testing. Training is the identification of a sample of pixels of known class membership gathered from reference data such as ground truth, existing maps and aerial photographs. In the second stage, the training pixels are used to derive various statistics for each land cover class and so are correspondingly assigned as signature. In the third stage, the pixels are allocated to the same class with which they show greatest similarity based on the signature files.
Unsupervised classification techniques share a common intent to uncover the major land cover classes that exist in the image, without prior knowledge of what they might be. Such procedures often come under cluster analysis, since they search for clusters of pixels with similar reflectance values. Unlike the supervised classification, only major land classes are separated as clusters, while smaller classes may be ignored. The decision for the number of clusters can be based on the histogram analysis of the reflectance values. The most prominent number of classes as seen in the histogram can be considered as the number of clusters.
The Indian Remote Sensing (IRS) satellite’s Linear Imaging Self Scanning Sensor (LISS) imagery contains four bands. National Remote Sensing Agency (NRSA) distributes the satellite data for India. This will have image in Band Interleaved by Line (BIL) format i.e., this file contains first line from first band, first line from second band, first line from third band and first line from fourth band in one interleaved line and in second interleaved line it contains second line from first band, second line from second band, second line from third band, second line from fourth band and so on. Band extraction is implemented to separate these bands.
The 23.5 m ground resolution IRS-LISS3 multispectral image has the following bands
Green 0.52 – 0.59 micrometer
Red 0.62 – 0.68 micrometer
Near-Infrared 0.77 – 0.86 micrometer
Short-wave Infrared 1.55 – 1.7 micrometer
Imagery obtained from the satellites will have geometric errors due to the nature of motion of satellite and high altitude of sensing platform. Prominent Ground Control Points (GCPs) from toposheets (which is always correct) are taken to rectify geometric errors. This procedure is also called as geo-correction / geo-rectification.
Image processing, neural network and other techniques are used to analyse the satellite imagery. The decision rule based on geometric shapes, sizes, and patterns present in the data is termed as Spatial Pattern Recognition. Similarly, visual interpretation is done on satellite imagery by considering the elements of image interpretation such as, shape, size, tone, texture, pattern and size for pattern recognition. The pattern recognition of urban sprawl is identified after classification of the remote sensed images for the built-up area and is then further analysed.
Decision Support System
In recent years, considerable interest has been focused on the use of GIS as a decision support system. For some, this role consists of simply informing the decision making process. However, it is more likely in the realm of resource allocation that the greatest contribution can be made with the aid of GIS and remote sensing. The use of GIS as a direct extension of the human decision-making process, most particularly in the context of resource allocation decisions, is indeed a great challenge and an important milestone. With the incorporation of many software tools to GIS for multi-criteria and multi-objective decision-making, an area that can broadly be termed decision strategy analysis there seems to be no bounds for the application of GIS. Closely associated with the decision strategy analysis is the uncertainty management. Uncertainty is not considered as a problem with data, but it is an inherent characteristic of the decision making process. With the increasing pressures on the resource allocation process, the need to recognise uncertainty as a fact of the decision making process has to be understood and carefully assessed. Uncertainty management thus lies at the very heart of effective decision-making and constitutes a very special role for the software systems that support GIS (Eastman, 1999).
The decision support is based on a choice between alternatives arising under a given set of criterion for a given objective. A criterion is some basis for a decision that can be measured and evaluated. Criterion can be of two kinds: factors and constraints, and this can pertain either to attributes of the individual or to an entire decision set. In this case the objective being to urbanise; constraints include the already existing built-up area, road-rail network, water bodies, etc., where there is no scope for further sprawl; and factors include the components of population growth rate, population density and proximity to the highway and cities. The decision support system evaluates these sets of data using multi-criteria evaluation. This predicts the possibilities of sprawl in the subsequent years using the current and historical data giving the output images for the objective mentioned.

Geographic Information System:GIS

Geographic information system (GIS) technology can be used for scientific investigations, resource management, and development planning. For example, a GIS might allow emergency planners to easily calculate emergency response times in the event of a natural disaster, or a GIS might be used to find wetlands that need protection from pollution.
What is a GIS?
A GIS is a computer system capable of capturing, storing, analyzing, and displaying geographically referenced information; that is, data identified according to location. Practitioners also define a GIS as including the procedures, operating personnel, and spatial data that go into the system.
How does a GIS work?
The power of a GIS comes from the ability to relate different information in a spatial context and to reach a conclusion about this relationship. Most of the information we have about our world contains a location reference, placing that information at some point on the globe. When rainfall information is collected, it is important to know where the rainfall is located. This is done by using a location reference system, such as longitude and latitude, and perhaps elevation. Comparing the rainfall information with other information, such as the location of marshes across the landscape, may show that certain marshes receive little rainfall. This fact may indicate that these marshes are likely to dry up, and this inference can help us make the most appropriate decisions about how humans should interact with the marsh. A GIS, therefore, can reveal important new information that leads to better decisionmaking.
Many computer databases that can be directly entered into a GIS are being produced by Federal, State, tribal, and local governments, private companies, academia, and nonprofit organizations. Different kinds of data in map form can be entered into a GIS . A GIS can also convert existing digital information, which may not yet be in map form, into forms it can recognize and use. For example, digital satellite images can be analyzed to produce a map of digital information about land use and land cover . Likewise, census or hydrologic tabular data can be converted to a maplike form and serve as layers of thematic information in a GIS.
Data capture
How can a GIS use the information in a map? If the data to be used are not already in digital form, that is, in a form the computer can recognize, various techniques can capture the information. Maps can be digitized by hand-tracing with a computer mouse on the screen or on a digitizing tablet to collect the coordinates of features. Electronic scanners can also convert maps to digits. Cordinates from Global Positioning System (GPS) receivers can also be uploaded into a GIS.
A GIS can be used to emphasize the spatial relationships among the objects being mapped. While a computer-aided mapping system may represent a road simply as a line, a GIS may also recognize that road as the boundary between wetland and urban development between two census statistical areas.
Data capture—putting the information into the system—involves identifying the objects on the map, their absolute location on the Earth’s surface, and their spatial relationships. Software tools that automatically extract features from satellite images or aerial photographs are gradually replacing what has traditionally been a time-consuming capture process. Objects are identified in a series of attribute tables—the “information” part of a GIS. Spatial relationships, such as whether features intersect or whether they are adjacent, are the key to all GIS-based analysis.
Data integration
A GIS makes it possible to link, or integrate, information that is difficult to associate through any other means. Thus, a GIS can use combinations of mapped variables to build and analyze new variables.
Data integration is the linking of information in different forms through a GIS.
For example, using GIS technology, it is possible to combine agricultural records with hydrography data to determine which streams will carry certain levels of fertilizer runoff. Agricultural records can indicate how much pesticide has been applied to a parcel of land. By locating these parcels and intersecting them with streams, the GIS can be used to predict the amount of nutrient runoff in each stream. Then as streams converge, the total loads can be calculated downstream where the stream enters a lake.
Projection and registration
A property ownership map might be at a different scale than a soils map. Map information in a GIS must be manipulated so that it registers, or fits, with information gathered from other maps. Before the digital data can be analyzed, they may have to undergo other manipulations—projection conversions, for example—that integrate them into a GIS.
Projection is a fundamental component of mapmaking. A projection is a mathematical means of transferring information from the Earth’s three-dimensional, curved surface to a two-dimensional medium—paper or a computer screen. Different projections are used for different types of maps because each projection is particularly appropriate for certain uses. For example, a projection that accurately represents the shapes of the continents will distort their relative sizes.
Since much of the information in a GIS comes from existing maps, a GIS uses the processing power of the computer to transform digital information, gathered from sources with different projections, to a common projection .
An elevation image classified from a satellite image of Minnesota exists in a different scale and projection than the lines on the digital file of the State and province boundaries.The elevation image has been reprojected to match the projection and scale of the State and province boundaries.
Data structures
Can a land use map be related to a satellite image, a timely indicator of land use? Yes, but because digital data are collected and stored in different ways, the two data sources may not be entirely compatible. Therefore, a GIS must be able to convert data from one structure to another.
Satellite image data that have been interpreted by a computer to produce a land use map can be “read into” the GIS in raster format. Raster data files consist of rows of uniform cells coded according to data values. An example is land cover classification.Raster files can be manipulated quickly by the computer, but they are often less detailed and may be less visually appealing than vector data files, which can approximate the appearance of more traditional hand-drafted maps. Vector digital data have been captured as points, lines (a series of point coordinates), or areas (shapes bounded by lines).An example of data typically held in a vector file would be the property boundaries for a particular housing subdivision.
Data restructuring can be performed by a GIS to convert data between different formats. For example, a GIS can be used to convert a satellite image map to a vector structure by generating lines around all cells with the same classification, while determining the spatial relationships of the cell, such as adjacency or inclusion.
Data modeling
It is impossible to collect data over every square meter of the Earth’s surface. Therefore, samples must be taken at discrete locations. A GIS can be used to depict two- and three-dimensional characteristics of the Earth’s surface, subsurface, and atmosphere from points where samples have been collected.
For example, a GIS can quickly generate a map with isolines that indicate the pH of soil from test points. Such a map can be thought of as a soil pH contour map. Many sophisticated methods can estimate the characteristics of surfaces from a limited number of point measurements. Two- and three-dimensional contour maps created from the surface modeling of sample points from pH measurements can be analyzed together with any other map in a GIS covering the area.
The way maps and other data have been stored or filed as layers of information in a GIS makes it possible to perform complex analyses.
A crosshair pointer (top) can be used to point at a location stored in a GIS. The bottom illustration depicts a computer screen containing the kind of information stored about the location—for example, the latitude, longitude, projection, coordinates, closeness to wells, sources of production, roads, and slopes of land.
Information retrieval
What do you know about the swampy area at the end of your street? With a GIS you can “point” at a location, object, or area on the screen and retrieve recorded information about it from offscreen files.Using scanned aerial photographs as a visual guide, you can ask a GIS about the geology or hydrology of the area or even about how close a swamp is to the end of a street. This type of analysis allows you to draw conclusions about the swamp’s environmental sensitivity.
Topological modeling
Have there ever been gas stations or factories that operated next to the swamp? Were any of these uphill from and within 2 miles of the swamp? A GIS can recognize and analyze the spatial relationships among mapped phenomena. Conditions of adjacency (what is next to what), containment (what is enclosed by what), and proximity (how close something is to something else) can be determined with a GIS .
Networks
When nutrients from farmland are running off into streams, it is important to know in which direction the streams flow and which streams empty into other streams. This is done by using a linear network. It allows the computer to determine how the nutrients are transported downstream. Additional information on water volume and speed throughout the spatial network can help the GIS determine how long it will take the nutrients to travel downstream. A GIS can simulate the movement of materials along a network of lines. These illustrations show the route of pollutants through a stream system. Flow directions are indicated by arrows.
Overlay
Using maps of wetlands, slopes, streams, land use, and soils (figs. 19a-f), the GIS might produce a new map layer or overlay that ranks the wetlands according to their relative sensitivity to damage from nutrient runoff.
Data output
A critical component of a GIS is its ability to produce graphics on the screen or on paper to convey the results of analyses to the people who make decisions about resources. Wall maps, Internet-ready maps, interactive maps, and other graphics can be generated, allowing the decisionmakers to visualize and thereby understand the results of analyses or simulations of potential events.
Framework for cooperation
The use of a GIS can encourage cooperation and communication among the organizations involved in environmental protection, planning, and resource management. The collection of data for a GIS is costly. Data collection can require very specialized computer equipment and technical expertise.
Standard data formats ease the exchange of digital information among users of different systems. Standardization helps to stretch data collection funds further by allowing data sharing, and, in many cases, gives users access to data that they could not otherwise collect for economic or technical reasons. Organizations such as the University Consortium for Geographic Information Science and the Federal Geographic Data Committee seek to encourage standardization efforts.
GIS through history
Some 35,000 years ago, Cro-Magnon hunters drew pictures of the animals they hunted on the walls of caves near Lascaux, France. Associated with the animal drawings are track lines and tallies thought to depict migration routes. These early records followed the two-element structure of modern geographic information systems (GIS): a graphic file linked to an attribute database.
Today, biologists use collar transmitters and satellite receivers to track the migration routes of caribou and polar bears to help design programs to protect the animals. In a GIS, the migration routes were indicated by different colors for each month for 21 months.Researchers then used the GIS to superimpose the migration routes on maps of oil development plans to determine the potential for interference with the animals.
Mapmaking
Researchers are working to incorporate the mapmaking processes of traditional cartographers into GIS technology for the automated production of maps.
One of the most common products of a GIS is a map. Maps are generally easy to make using a GIS and they are often the most effective means of communicating the results of the GIS process. Therefore, the GIS is usually a prolific producer of maps. The users of a GIS must be concerned with the quality of the maps produced because the GIS normally does not regulate common cartographic principles. One of these principles is the concept of generalization, which deals with the content and detail of information at various scales. The GIS user can change scale at the push of a button, but controlling content and detail is often not so easy. Mapmakers have long recognized that content and detail need to change as the scale of the map changes. For example, the State of New Jersey can be mapped at various scales, from the small scale of 1:500,000 to the larger scale of 1:250,000 and the yet larger scale of 1:100,000 ,but each scale requires an appropriate level of generalization .
Site selection
The U.S. Geological Survey (USGS), in a cooperative project with the Connecticut Department of Natural Resources, digitized more than 40 map layers for the areas covered by the USGS Broad Brook and Ellington 7.5-minute topographic quadrangle maps . This information can be combined and manipulated in a GIS to address planning and natural resource issues. GIS information was used to locate a potential site for a new water well within half a mile of the Somers Water Company service area.
To prepare the analysis, cartographers stored digital maps of the water service areas in the GIS. They used the proximity function in the GIS to draw a half-mile buffer zone around the water company service area.This buffer zone was the “window” used to view and combine the various map coverages relevant to the well site selection.
The land use and land cover map for the two areas shows that the area is partly developed. A GIS was used to select undeveloped areas from the land use and land cover map as the first step in finding well sites. The developed areas were eliminated from further consideration.The quality of water in Connecticut streams is closely monitored. Some of the streams in the study area were known to be unusable as drinking water sources. To avoid pulling water from these streams into the wells, 100-meter buffer zones were created around the unsuitable streams using the GIS, and the zones were plotted on the map. The areas in blue have the characteristics desired for a water well site.
Point sources of pollution are recorded by the Connecticut Department of Natural Resources. These records consist of a location and a text description of the pollutant.To avoid these toxic areas, a buffer zone of 500 meters was established around each point.This information was combined with the previous two map layers to produce a new map of areas suitable for well sites. Points sources of pollution in the water service area are identified and entered into a GIS.
The map of surficial geology shows the earth materials that lie above bedrock. Since the area under consideration in Connecticut is covered by glacial deposits, the surface consists largely of sand and gravel, with some glacial till and fine-grained sediments. Of these materials, sand and gravel are the most likely to store water that could be tapped with wells. Areas underlain by sand and gravel were selected from the surficial geology map. They were combined with the results of the previous selections to produce a map consisting of: (1) sites in underdeveloped areas underlain by sand and gravel, (2) more than 500 meters from point sources of pollution, and (3) more than 100 meters from unsuitable streams .
A map that shows the thickness of saturated sediments was created by using the GIS to subtract the bedrock elevation from the surface elevation (fig. 17). For this analysis, areas having more than 40 feet of saturated sediments were selected and combined with the previous overlays.
The resulting site selection map shows areas that are undeveloped, are situated outside the buffered pollution areas, and are underlain by 40 feet or more of water-saturated sand and gravel. Because of map resolution and the limits of precision in digitizing, the very small polygons (areas) may not have all of the characteristics analyzed, so another GIS function was used to screen out areas smaller than 10 acres. The final six sites are displayed with the road and stream network and selected place names for use in the field .
Potential water well sites, roads, streams and place names.
The process illustrated by this site selection analysis has been used for many common applications, including transportation planning and waste disposal site location. The technique is particularly useful when several physical factors must be considered and integrated over a large area.

Emergency response planning
The Wasatch Fault zone runs through Salt Lake City along the foot of the Wasatch Mountains in north-central Utah .

A GIS was used to combine road network and earth science information to analyze the effect of an earthquake on the response time of fire and rescue squads. The area covered by the USGS Sugar House 7.5-minute topographic quadrangle map was selected for the study because it includes both undeveloped areas in the mountains and a part of Salt Lake City. Detailed earth science information was available for the entire region.
The road network from a USGS digital line graph includes information on the types of roads, which range from rough trails to divided highways . The locations of fire stations were plotted on the road network. A GIS function called network analysis was used to calculate the time necessary for emergency vehicles to travel from the fire stations to different areas of the city. The network analysis function considers two elements: (1) distance from the fire station, and (2) speed of travel based on the type of road. The analysis shows that under normal conditions, most of the area within the city will be served in less than 7 minutes and 30 seconds because of the distribution and density of fire stations and the continuous network of roads.
The accompanying illustration depicts the blockage of the road network that would result from an earthquake, assuming that any road crossing the fault trace would become impassable. The primary effect on emergency response time would occur in neighborhoods west of the fault trace, where travel times from the fire stations would be noticeably lengthened.
Figure 21. Before faulting. Road network of area covered by the Sugar House quadrangle plotted from USGS digital line graph data, indicating the locations of fire stations and travel times of emergency vehicles. Areas in blue can receive service within 2½minutes, area in green within 5 minutes, areas in yellow within 7½ minutes, and areas in magenta within 10 minutes. Areas in white cannot receive service within 10 minutes.
After faulting, initial model. Network analysis in a GIS produces a map of travel times from the stations after faulting. The fault is in red. Emergency response times have increased for areas west of the fault.
The Salt Lake City area lies on lake sediments of varying thicknesses. These sediments range from clay to sand and gravel, and most are water-saturated. In an earthquake, these materials may momentarily lose their ability to support surface structures, including roads. The potential for this phenomenon, known as liquefaction, is shown in a composite map portraying the inferred relative stability of the land surface during an earthquake. Areas near the fault and underlain by thick, loosely consolidated, water-saturated sediments will suffer the most intense surface motion during an earthquake.Areas on the mountain front with thin surface sediments will experience less additional ground acceleration. The map of liquefaction potential was combined with the road network analysis to show the additional effect of liquefaction on response times.
The final map shows that areas near the fault, as well as those underlain by thick, water-saturated sediments, are subject to more road disruptions and slower emergency response than are other areas of the city.Map of potential ground l liquefaction during an earthquake. The least stable areas are shown by yellows and oranges, the most stable by grays and browns.
Figure 24. After faulting, final model. A map showing the effect of an earthquake on emergency travel times is reduced by combining the liquefaction potential information from figure 23 with the network analysis from .
Three-dimensional GIS
To more realistically analyze the effect of the Earth’s terrain, we use three-dimensional models within a GIS. A GIS can display the Earth in realistic, three-dimensional perspective views and animations that convey information more effectively and to wider audiences than traditional, two-dimensional, static maps. The U.S. Forest Service was offered a land swap by a mining company seeking development rights to a mineral deposit in Arizona’s Prescott National Forest. Using a GIS, the USGS and the U.S. Forest Service created perspective views of the area to depict the terrain as it would appear after mining .
Figure 25. Prescott National Forest, showing altered topography due to mine development.
To assess the potential hazard of landslides both on land and underwater, the USGS generated a three-dimensional image of the San Francisco Bay area .It created the image by mosaicking eight scenes of natural color composite Landsat 7 enhanced thematic mapper imagery on California fault data using approximately 700 digital elevation models at 1:24,000 scale.
Graphic display techniques
Traditional maps are abstractions of the real world; each map is a sampling of important elements portrayed on a sheet of paper with symbols to represent physical objects. People who use maps must interpret these symbols. Topographic maps show the shape of the land surface with contour lines. Graphic display techniques in GISs make relationships among map elements more visible, heightening one’s ability to extract and analyze information.
Two types of data were combined in a GIS to produce a perspective view of a part of San Mateo County, Calif. The digital elevation model, consisting of surface elevations recorded on a 30-meter horizontal grid, shows high elevations as white and low elevations as black (fig. 27). The accompanying Landsat thematic mapper image shows a false-color infrared image of the same area in 30-meter pixels, or picture elements and combine the two images to produce the three- dimentional image.
Visualization
Maps have traditionally been used to explore the Earth. GIS technology has enhanced the efficiency and analytical power of traditional cartography. As the scientific community recognizes the environmental consequences of human activity, GIS technology is becoming an essential tool in the effort to understand the process of global change. Map and satellite information sources can be combined in models that simulate the interactions of complex natural systems.
Through a process known as visualization, a GIS can be used to produce images— not just maps, but drawings, animations, and other cartographic products. These images allow researchers to view their subjects in ways that they never could before. The images often are helpful in conveying the technical concepts of a GIS to nonscientists.
Adding the element of time
The condition of the Earth’s surface, atmosphere, and subsurface can be examined by feeding satellite data into a GIS. GIS technology gives researchers the ability to examine the variations in Earth processes over days, months, and years. As an example, the changes in vegetation vigor through a growing season can be animated to determine when drought was most extensive in a particular region. The resulting normalized vegetation index represents a rough measure of plant health.Working with two variables over time will allow researchers to detect regional differences in the lag between a decline in rainfall and its effect on vegetation. The satellite sensor used in this analysis is the advanced very high resolution radiometer (AVHRR), which detects the amounts of energy reflected from the Earth’s surface at a 1-kilometer resolution twice a day. Other sensors provide spatial resolutions of less than 1 meter.
Serving GIS over the Internet
Through Internet map server technology, spatial data can be accessed and analyzed over the Internet. For example, current wildfire perimeters are displayed with a standard web browser, allowing fire managers to better respond to fires while in the field and helping homeowners to take precautionary measures.
The future of GIS
Environmental studies, geography, geology, planning, business marketing, and other disciplines have benefitted from GIS tools and methods. Together with cartography, remote sensing, global positioning systems, photogrammetry, and geography, the GIS has evolved into a discipline with its own research base known as geographic information sciences. An active GIS market has resulted in lower costs and continual improvements in GIS hardware, software, and data. These developments will lead to a much wider application of the technology throughout government, business, and industry.
GIS and related technology will help analyze large datasets, allowing a better understanding of terrestrial processes and human activities to improve economic vitality and environmental quality.
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I am Rashid Aziz Faridi ,Writer, Teacher and a Voracious Reader.
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12 Responses to GIS, REMOTE SENSING, AND IMAGE PROCESSING IN STUDYING URBAN SYSTEMS

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    It is nice to have body like this, that provide information like the one above and other once too. I came across this site as a result of searching for literature material for my PGD student on urban growth.

    I’m looking forward to see, if you can build an electronic internet querying base with data and software variaties for the researchers to do their research and proccess the data and analysis the findings so these will be at the end a benifit for both of us.

    this will add a recoginition to your institution for researchers in Africa and other part of the world. becouse of the diffculties in accessing data of gis remote sensing

    thanks

    Like this

  4. karwani abel says:

    sounding research work,keep it up.

    Like this

  5. Anthony says:

    Hi,
    This is such valuable information that summarises GIS in its basic forms. They are easy to read and digest.
    Thanks for the good work

    Like this

  6. Thank you for writing this! I found it very helpful.

    Like this

  7. Apryll says:

    This is very valuable information for anyone in the industry. We will share this through our social media outlets. We are a new start up company called Fuze Go – we have the best pan sharpening software that we have finally decided to commercially license. Would be interested in hearing your thoughts (as you have a lot of knowledge in this area) about the software if you pan sharpen satellite images yourself….we have a free trial version :)

    Like this

  8. Austin says:

    I have read some good stuff here. Definitely price bookmarking for revisiting.
    I wonder how much effort you set to create any such wonderful informative website.

    Like this

  9. Jefferey says:

    Wow that was odd. I just wrote an incredibly long comment
    but after I clicked submit my comment didn’t appear. Grrrr… well I’m not writing all
    that over again. Anyways, just wanted to say superb blog!

    Like this

  10. garden grow says:

    Very nice article. I certainly love this site. Stick with it!

    Like this

  11. Nripendra Kumar Sarma, Guwahati, Assam, India says:

    Thanks for this informative article. However I would like to request you to highlight on it’s use on Monitoring & Evaluation and Data analysis on the field interventions / achievement etc.
    Regards.

    Like this

  12. Excellent post but I was wanting to know if you could write a litte more
    on this subject? I’d be very thankful if you could elaborate a little bit more. Appreciate it!

    Like this

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