Spatial Data Sets PDF

8/10/2019 Spatial Data Sets PDF

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Geographical Data Sets

Geographic Data Types

Although the two terms, data and information, are often used indiscriminately, they both have a specificmeaning. Data can be described as different observations, which are collected and stored. Informationis that data, which is useful in answering queries or solving a problem. Digitizing a large number ofmaps provides a large amount of data after hours of painstaking works, but the data can only renderuseful information if it is used in analysis.

Spatial and Non-spatial dataGeographic data are organised in a geographic database. This database can be considered as acollection of spatially referenced data that acts as a model of reality. There are two importantcomponents of this geographic database: its geographic position and its attributes or properties. In otherwords, spatial data (where is it?) and attribute data (what is it?)

Attribute DataThe attributes refer to the properties of spatial entities. They are often referred to as non-spatial data

since they do not in themselves represent location information.

Spatial dataGeographic position refers to the fact that each feature has a location that must be specified in a uniqueway. To specify the position in an absolute way a coordinate system is used. For small areas, the

simplest coordinate system is the regular square grid. For larger areas, certain approved cartographicprojections are commonly used. Internationally there are many different coordinate systems in use.

Geographic object can be shown by FOUR type of representation viz., points, lines, areas, andcontinuous surfaces.

Point DataPoints are the simplest type of spatial data. They are-zero dimensional objects with only a position inspace but no length.

Line DataLines (also termed segments or arcs) are one-dimensional spatial objects. Besides having a position inspace, they also have a length.

Area DataAreas (also termed polygons) are two-dimensional spatial objects with not only a position in space anda length but also a width (in other words they have an area).

Continuous SurfaceContinuous surfaces are three-dimensional spatial objects with not only a position in space, a lengthand a width, but also a depth or height (in other words they have a volume). These spatial objects havenot been discussed further because most GIS do not include real volumetric spatial data.

Geographic Data -- Linkages and Matching

GISdevelopment.net ---> Tutorials Print

District Name Area Population

Noida 395 sq. Km. 6,75,341

Ghaziabad 385 sq. Km. 2,57,086

Mirzapur 119 sq. Km. 1,72,952

Page 1 of 14Geographical Data Sets

11/23/2006http://www.gisdevelopment.net/tutorials/tuman003pf.htm


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LinkagesA GIS typically links different sets. Suppose you want to know the mortality rate to cancer amongchildren under 10 years of age in each country. If you have one file that contains the number of childrenin this age group, and another that contains the mortality rate from cancer, you must first combine or linkthe two data files. Once this is done, you can divide one figure by the other to obtain the desiredanswer.

Exact MatchingExact matching occurs when you have information in one computer file about many geographic features(e.g., towns) and additional information in another file about the same set of features. The operation tobring them together is easily achieved by using a key common to both files -- in this case, the townname. Thus, the record in each file with the same town name is extracted, and the two are joined andstored in another file.

Name Populaiton

A 4038

B 7030

C 10777

D 5798

E 5606

Name Avg. housing Cost

A 30,500

B 22,000

C 100,000

D 24,000

E 24,000

Name Population Avg. Housing Cost

A 4038 30,500B 7030 22,000

C 10777 100,100

D 5798 24,000

E 5606 24,000




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Hierarchical MatchingSome types of information, however, are collected in more detail and less frequently than other types ofinformation. For example, financial and unemployment data covering a large area are collected quitefrequently. On the other hand, population data are collected in small areas but at less frequent intervals.If the smaller areas nest (i.e., fit exactly) within the larger ones, then the way to make the data match ofthe same area is to use hierarchical matching -- add the data for the small areas together until thegrouped areas match the bigger ones and then match them exactly.

The hierarchical structure illustrated in the chart shows that this city is composed of several tracts. Toobtain meaningful values for the city, the tract values must be added together.

Fuzzy MatchingOn many occasions, the boundaries of the smaller areas do not match those of the larger ones. Thisoccurs often while dealing with environmental data. For example, crop boundaries, usually defined byfield edges, rarely match the boundaries between the soil types. If you want to determine the mostproductive soil for a particular crop, you need to overlay the two sets and compute crop productivity foreach and every soil type. In principle, this is like laying one map over another and noting thecombinations of soil and productivity.

A GIS can carry out all these operations because it uses geography, as a common key between the

data sets. Information is linked only if it relates to the same geographical area.

Why is data linkage so important? Consider a situation where you have two data sets for a given area,such as yearly income by county and average cost of housing for the same area. Each data might beanalysed and/or mapped individually. Alternatively, they may be combined. With two data sets, only onevalid combination exists. Even if your data sets may be meaningful for a single query you will still beable to answer many more questions than if the data sets were kept separate. By bringing themtogether, you add value to the database. To do this, you need GIS.

Tract Town Population

101 P 60,000

102 Q 45,000

103 R 35,000

104 S 36,000

105 T 57,000

106 Nakkhu 25,000

107 Kupondole 58,000

Tract 101

Tract 102

Tract 103

Tract 104

Tract 105

Tract 107Tract 106




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Figure 2

Principal Functions of GIS

Data Capture

Data used in GIS often come from many types, and are stored in different ways. A GIS provides toolsand a method for the integration of different data into a format to be compared and analysed. Datasources are mainly obtained from manual digitization and scanning of aerial photographs, paper maps,and existing digital data sets. Remote-sensing satellite imagery and GPS are promising data inputsources for GIS.

Database Management and Update

After data are collected and integrated, the GIS must provide facilities, which can store and maintaindata. Effective data management has many definitions but should include all of the following aspects:data security, data integrity, data storage and retrieval, and data maintenance abilities.

Geographic Analysis

Data integration and conversion are only a part of the input phase of GIS. What is required next is theability to interpret and to analyze the collected information quantitatively and qualitatively. For example,satellite image can assist an agricultural scientist to project crop yield per hectare for a particular region.For the same region, the scientist also has the rainfall data for the past six months collected throughweather station observations. The scientists also have a map of the soils for the region which showsfertility and suitability for agriculture. These point data can be interpolated and what you get is athematic map showing isohyets or contour lines of rainfall.

Presenting Results

One of the most exciting aspects of GIS technology is the variety of different ways in which theinformation can be presented once it has been processed by GIS. Traditional methods of tabulating andgraphing data can be supplemented by maps and three dimensional images. Visual communication isone of the most fascinating aspects of GIS technology and is available in a diverse range of outputoptions.

Data Capture an Introduction

The functionality of GIS relies on the quality of data available, which, in most developing countries, iseither redundant or inaccurate. Although GIS are being used widely, effective and efficient means of




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data collection have yet to be systematically established. The true value of GIS can only be realized ifthe proper tools to collect spatial data and integrate them with attribute data are available.

Manual Digitization

Manual Digitizing still is the most common method for entering maps into GIS. The map to be digitizedis affixed to a digitizing table, and a pointing device (called the digitizing cursor or mouse) is used totrace the features of the map. These features can be boundary lines between mapping units, otherlinear features (rivers, roads, etc.) or point features (sampling points, rainfall stations, etc.) The digitizingtable electronically encodes the position of the cursor with the precision of a fraction of a millimeter. Themost common digitizing table uses a fine grid of wires, embedded in the table. The vertical wires willrecord the Y-coordinates, and the horizontal ones, the X-coordinates.

The range of digitized coordinates depends upon the density of the wires (called digitizing resolution)and the settings of the digitizing software. A digitizing table is normally a rectangular area in the middle,

separated from the outer boundary of the table by a small rim. Outside of this so-called active area ofthe digitizing table, no coordinates are recorded. The lower left corner of the active area will have thecoordinates x = 0 and y = 0. Therefore, make sure that the (part of the) map that you want to digitize isalways fixed within the active area.

Scanning System

The second method of obtaining vector data is with the use of scanners. Scanning (or scan digitizing)provides a quicker means of data entry than manual digitizing. In scanning, a digital image of the map isproduced by moving an electronic detector across the map surface. The output of a scanner is a digitalraster image, consisting of a large number of individual cells ordered in rows and columns. For theConversion to vector format, two types of raster image can be used.

In the case of Chloropleth maps or thematic maps, such as geological maps, the individual mapping

units can be separated by the scanner according to their different colours or grey tones. The resultingimages will be in colours or grey tone images.

In the case of scanned line maps, such as topographic maps, the result is a black-and-white image.Black lines are converted to a value of 1, and the white areas in between lines will obtain a value of 0 inthe scanned image. These images, with only two possibilities (1 or 0) are also called binary images.

The raster image is processed by a computer to improve the image quality and is then edited andchecked by an operator. It is then converted into vector format by special computer programmes, whichare different for colour/grey tone images and binary images.

Scanning works best with maps that are very clean, simple, relate to one feature only, and do notcontain extraneous information, such as text or graphic symbols. For example, a contour map shouldonly contain the contour line, without height indication, drainage network, or infrastructure. In most

cases, such maps will not be available, and should be drawn especially for the purpose of scanning.Scanning and conversion to vector is therefore, only beneficial in large organizations, where a largenumber of complex maps are entered. In most cases, however, manual digitizing will be the only usefulmethod for entering spatial data in vector format.




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Figure 3

Data Conversion

While manipulating and analyzing data, the same format should be used for all data. This ScanningSystem implies that, when different layers are to be used simultaneously, they should all be in vector orall in raster format. Usually the conversion is from vector to raster, because the biggest part of theanalysis is done in the raster domain. Vector data are transformed to raster data by overlaying a gridwith a user-defined cell size.

Sometimes the data in the raster format are converted into vector format. This is the case especially ifone wants to achieve data reduction because the data storage needed for raster data is much largerthan for vector data.

A digital data file with spatial and attribute data might already exist in some way or another. There mightbe a national database or specific databases from ministries, projects, or companies. In some cases aconversion is necessary before these data can be downloaded into the desired database.

The commonly used attribute databases are dBase and Oracle. Sometimes spreadsheet programmeslike Lotus, Quattro, or Excel are used, although these cannot be regarded as real database softwares.

Remote-sensing images are digital datasets recorded by satellite operating agencies and stored in theirown image database. They usually have to be converted into the format of the spatial (raster) databasebefore they can be downloaded.

Spatial Data Management




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Geo-Relational Data ModelAll spatial data files will be geo-referenced. Geo-referencing refers to the location of a layer or coveragein space defined by the coordinate referencing system. The geo relational approach involves abstractinggeographic information into a series of independent layers or coverages, each representing a selectedset of closely associated geographic features (e.g., roads, land use, river, settlement, etc). Each layerhas the theme of a geographic feature and the database is organized in the thematic layers.

With this approach users can combine simple feature sets representing complex relationships in the realworld. This approach borrows heavily on the concepts of relational DBMS, and it is typically closelyintegrated with such systems. This is fundamental to database organization in GIS.

Topological Data Structure.Topology is the spatial relationship between connecting and adjacent coverage features (e.g., arc,nodes, polygons, and points). For instance, the topology of an arc includes from and to nodes(beginning of the arc and ending of the arc representing direction) and its left and right polygon.Topological relationships are built from simple elements into complex elements: points (simplestelements), arcs (sets of connected points), and areas (sets of connected arcs). Topological datastructure, in fact, adds intelligence to the GIS database.

Attribute Data ManagementAll Data within a GIS (spatial data as well as attribute data) are stored within databases. A database is a

collection of information about things and their relationships to each other. For example, you can havean engineering geological database, containing information about soil and rock types, field observationsand measurements, and laboratory results. This is interesting data, but not very useful if the laboratorydata, for example, cannot be related to soil and rock types.

The objective of collecting and maintaining information in a database is to relate facts and situations thatwere previously separate.

The principle characteristics of a DBMS are: -

Centralized control over the database is possible, allowing for better quality management and operator-defined access to parts of the database;

Data can be shared effectively by different applications;

The access to the data is much easier, due to the use of a user-interface and the user-views (especiallydesigned formula for entering and consulting the database);

Data redundancy (storage of the same data in more than one place in the database) can be avoided asmuch as possible; redundancy or unnecessary duplication of data are an annoyance, since this makesupdating the database much more difficult; one can easily overlook changing redundant informationwhenever it occurs; and

The creation of new applications is much easier with DBMS.

The disadvantages relate to the higher cost of purchasing the software, the increased complexity ofmanagement, and the higher risk, as data are centrally managed.

Relational Database -- Concepts & ModelThe relational data model is conceived as a series of tables, with no hierarchy nor any predefinedrelations. The relation between the various tables should be made by the user. This is done byidentifying a common field in two tables, which is assigned as the flexibility than in the other two datamodels. However, accessing the database is slower than with the other two models. Due to its greaterflexibility, the relational data model is used by nearly all GIS systems

Choosing geographic dataThe main purpose of purchasing a geographic information system (GIS)* is to produce results for your




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organization. Choosing the right GIS/mapping data will help you produce those results effectively.

The role of base-map data in your GIS, The common characteristics of geographic data, The commonly available data sources Guidelines for evaluating the suitability of any data set for your project.

The world of GIS data is complex, by choosing the right data set, you can save significant amounts ofmoney and, even more importantly, quickly begin your GIS project.

Data: The Core of Your Mapping / GIS Project

When most people begin a GIS project, their immediate concern is with purchasing computer hardwareand software. They enter into lengthy discussions with vendors about the merits of various componentsand carefully budget for acquisitions. Yet they often give little thought to the core of the system, the datathat goes inside it. They fail to recognize that the choice of an initial data set has a tremendousinfluence on the ultimate success of their GIS project.

Data, the core of any GIS project, must be accurate - but accuracy is not enough. Having theappropriate level of accuracy is vital. Since an increase in data accuracy increases acquisition and

maintenance costs, data that is too detailed for your needs can hurt a project just as surely asinaccurate data can. All any GIS project needs is data accurate enough to accomplish its objectives andno more. For example, you would not purchase an engineering workstation to run a simple word-processing application. Similarly, you would not need third-order survey accuracy for a GIS-basedpopulation study whose smallest unit of measurement is a county. Purchasing such data would be toocostly and inappropriate for the project at hand. Even more critically, collecting overly complex datacould be so time-consuming that the GIS project might lose support within the organization.

Even so, many people argue that, since GIS data can far outlast the hardware and software on which itruns, no expense should be spared in its creation. Perfection, however, is relative. Projects and datarequirements evolve. Rather than overinvest in data, invest reasonably in a well-documented, well-understood data foundation that meets today's needs and provides a path for future enhancements.This approach is a key to successful GIS project implementation.

Are Your Data Needs Simple or Complex? Before you start your project, take some time to consider your objectives and your GIS data needs. Askyourself, "Are my data needs complex or simple?"

*Italicized words can be found in the Glossary at the end of this document except for words used foremphasis or words italicized for reasons of copyediting convention or layout.If you just need a map as a backdrop for other information, your data requirements are simple. You arebuilding a map for your specific project, and you are primarily interested in displaying the necessaryinformation, not in the map itself. You do not need highly accurate measurements of distances or areasor to combine maps from different sources. Nor do you want to edit or add to the map's basicgeographic information.

An example of simple data requirements is a map for a newspaper story that shows the location of afire. Good presentation is important; absolute accuracy is not.

If you have simple data needs, read this paper to get the overall picture of what GIS data is and how itfits into your project. A project with simple data requirements can be started with inexpensive maps.Your primary interests will be quality graphic- display characteristics and finding maps that are easy touse with your software. You need not be as concerned with technical mapping issues. However, basicknowledge of concepts such as coordinate systems, absolute accuracy, and file formats will help youunderstand your choices and help you make informed decisions when it's time to add to your system.

What issues suggest more complex GIS data needs?




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Building a GIS to be used by many people over a long period of time. Storing and maintaining database information about geographic features. Making accurate engineering measurements from the map. Editing or adding to the map.

Combining a variety of information from different sources.

An example of a system requiring complex data would be a GIS built to manage infrastructure for anelectric utility.

If your data requirements are complex, you ought to pay particular attention to the sections of this paperthat discuss data accuracy, coordinate systems, layering, file formats, and the issues involved incombining data from different sources.

Also keep in mind that projects evolve, and simple data needs expand into complex ones as yourproject moves beyond its original objectives. If you understand the basics of your data set, you willmake better decisions as your project grows.

Basics of Digital Mapping

Vector vs. Raster MapsThe most fundamental concept to grasp about any type of graphic data is making the distinctionbetween vector data and raster data. These two data types are as different as night and day, yet theycan look the same. For example, a question that commonly comes up is "How can I convert my TIFFfiles into DXF files?" The answer is "With difficulty," because TIFF is a raster data format and DXF(data interchange file) is a vector format. And converting from raster to vector is not simple. Rastermaps are best suited to some applications while vector maps are suited to others.

Figure 4

Raster data represents a graphic object as a pattern of dots, whereas vector data represents the objectas a set of lines drawn between specific points. Consider a line drawn diagonally on a piece of paper. Araster file would represent this image by subdividing the paper into a matrix of small rectangles-similarto a sheet of graph paper-called cells (figure 1). Each cell is assigned a position in the data file andgiven a value based on the color at that position. White cells could be given the value 0; black cells, thevalue 1; grays would fall in-between. This data representation allows the user to easily reconstruct orvisualize the original image.




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Figure 5

A vector representation of the same diagonal line would record the position of the line by simplyrecording the coordinates of its starting and ending points. Each point would be expressed as two orthree numbers (depending on whether the representation was 2D or 3D, often referred to as X,Y orX,Y,Z coordinates (figure 2). The first number, X, is the distance between the point and the left side ofthe paper; Y, the distance between the point and the bottom of the paper; Z, the point's elevation aboveor below the paper. The vector is formed by joining the measured points.

Some basic properties of raster and vector data are outlined below.

Each entity in a vector file appears as an individual data object. It is easy to record informationabout an object or to compute characteristics such as its exact length or surface area. It is muchharder to derive this kind of information from a raster file because raster files contain little (andsometimes no) geometric information.

Some applications can be handled much more easily with raster techniques than with vectortechniques. Raster works best for surface modeling and for applications where individual featuresare not important. For example, a raster surface model can be very useful for performing cut-and-fill analyses for road-building applications, but it doesn't tell you much about the characteristics ofthe road itself. Terrain elevations can be recorded in a raster format and used to construct digitalelevation models (DEMs) (figure 3). Some land-use information comes in raster format.

Figure 6

Raster files are often larger than vector files. The raster representation of the line in the exampleabove required a data value for each cell on the page, whereas the vector representation onlyrequired the positions of two points.

The size of the cells in a raster file is an important factor. Smaller cells improve image quality becausethey increase detail. As cell size increases, image definition decreases or blurs. In the example, theposition of the line's edge is defined most clearly if the cells are very small. However, there is a trade-off: Dividing the cell size in half increases file size by a factor of four.

Cell size in a raster file is referred to as resolution. For a given resolution value, the raster cost does notincrease with image complexity. That is, any scanner can quickly make a raster file. It takes no moreeffort to scan a map of a dense urban area than to scan a sparse rural one. On the other hand, a vectorfile requires careful measuring and recording of each point, so an urban map will be much more time-




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consuming to draw than a rural map. The process of making vector maps is not easily automated, andcost increases with map complexity.

Because raster data is often more repetitive and predictable, it can be compressed more easily thanvector data. Many raster formats, such as TIFF, have compression options that drastically reduce imagesizes, depending upon image complexity and variability.

Raster files are most often used:

For digital representations of aerial photographs, satellite images, scanned paper maps, andother applications with very detailed images.

When costs need to be kept down. When the map does not require analysis of individual map features. When "backdrop" maps are required.

In contrast, vector maps are appropriate for:

Highly precise applications. When file sizes are important. When individual map features require analysis.

When descriptive information must be stored.

Raster and vector maps can also be combined visually. For example, a vector street map could beoverlaid on a raster aerial photograph. The vector map would provide discrete information aboutindividual street segments, the raster image, a backdrop of the surrounding environment.

Digital Map Formats- How Data Is StoredThe term file format refers to the logical structure used to store information in a GIS file. File formats areimportant in part because not every GIS software package supports all formats. If you want to use adata set, but it isn't available in a format that your GIS supports, you will have to find a way to transformit, find another data set, or find another GIS.

Almost every GIS has its own internal file format. These formats are designed for optimal use inside thesoftware and are often proprietary. They are not designed for use outside their native systems. Mostsystems also support transfer file formats. Transfer formats are designed to bring data in and out of theGIS software, so they are usually standardized and well documented.

If your data needs are simple, your main concern will be with the internal format that your GIS softwaresupports. If you have complex data needs, you will want to learn about a wider range of transferformats, especially if you want to mix data from different sources. Transfer formats will be required toimport some data sets into your software.

Vector FormatsMany GIS applications are based on vector technology, so vector formats are the most common. Theyare also the most complex because there are many ways to store coordinates, attributes, attributelinkages, database structures, and display information. Some of the most common formats are briefly

described below

Common Vector File Formats

Format NameSoftwarePlatform

Internal orTransfer

Developer Comments

Arc Export ARC/INFO* TransferEnvironmentalSystems ResearchInstitute, Inc. (ESRI)

Transfers dataacross ARC/INFO*platforms.

ARC/INFO* Coverages ARC/INFO* Internal ESRI




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An Example of Raster and Vector Integration

Figure 7: An Example of Raster and Vector Integration

Vectors & Raster Data Models - Merits & Demerits.

PC PaintbrushExchange (PCX)

PC Paintbrush Both Zsoft Widely used raster format.

Spatial DataTransferStandard (SDTS)

Many (in thefuture)

TransferUS FederalGovernment

New US standard for both rasterand vector geographic data;raster version still underdevelopment.

Tagged ImageFile Format(TIFF)

PageMaker Both Aldus Widely used raster format.

RASTER MODEL VECTOR MODEL

Advantages

Simple data structure Easy and efficient overlaying Compatible with RS imagery High spatial variability is efficiently

represented Simple for own programming Same grid cells for several attributes

Disadvantages

Advantages

Compact data structure Efficient for network analysis Efficient projection transformation Accurate map output.

Disadvantages

Complex data structure Difficult overlay operations




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