How GPS Works
The Global Positioning System (GPS) is a technical marvel made possible by a group of satellites in earth orbit that transmit precise signals, allowing GPS receivers to calculate and display accurate location, speed, and time information to the user.
By capturing the signals from three or more satellites (among a constellation of 31 satellites available), GPS receivers are able to use the mathematical principle of trilateration to pinpoint your location.
With the addition of computing power, and data stored in memory such as road maps, points of interest, topographic information, and much more, GPS receivers are able to convert location, speed, and time information into a useful display format.
GPS was originally created by the United States Department of Defense (DOD) as a military application. The system has been active since the early 1980s, but began to become useful to civilians in the late 1990s. Consumer GPS has since become a multi-billion dollar industry with a wide array of products, services, and Internet-based utilities.
GPS works accurately in all weather conditions, day or night, around the clock, and around the globe. There is no subscription fee for use of GPS signals. GPS signals may be blocked by dense forest, canyon walls, or skyscrapers, and they don’t penetrate indoor spaces well, so some locations may not permit accurate GPS navigation.
GPS receivers are generally accurate within 15 meters, and newer models that use Wide Area Augmentation System (WAAS) signals are accurate within three meters.
While the U.S. owned and operated GPS is currently the only active system, five other satellite-based global navigation systems are being developed by individual nations and by multi-nation consortiums.

Basics of GPS
GPS technology has found its way into a wide variety of consumer products that can help you in your travels for business or pleasure. Which type of GPS unit is right for you? What features are available? Once you know the class of product that will best suit your needs, and the features offered, you will be well-prepared to shop and compare.

Sales of aftermarket in-car GPS devices have more than doubled over the past two years, and automotive is the fastest-growing segment of the GPS market. Why? Better and brighter color screens, improved accuracy and usability of maps and directions, added features such as traffic alerts, the ability to wirelessly link a mobile phone to an in-car unit to get hands-free mobile speaker-phone use… all of these reasons and more.

You just got an in-car GPS navigator. Here are some tips for quick setup, safety, and getting the most from your GPS. Handheld GPS units have dramatically changed outdoors travel, replacing map and compass with moving digital maps, and precise location, elevation, topographic and other data. GPS products for cycling and running provide a great way to track and record your workouts. Marine GPS devices are a pleasure to use, and dramatically enhance all-weather, all-light-condition safety. Portable aviation units offer intuitive, moving-map views with navigation overlays, providing a great supplement to a plane's instrumentation.

Satellite Remote Sensing

Satellite remote sensing involves gathering information about features on the Earth's surface from orbiting satellites. These satellites carry two types of sensor systems known as "active" and "passive". A "passive" system generally consists of an array of small sensors or detectors, which record (as digital numbers), the amount of electro-magnetic radiation reflected and/or emitted from the Earth's surface. A multispectral scanner is an example of a passive system. An "active" system propagates its own electro-magnetic radiation, and measures (as digital numbers), the intensity of the return signal. Synthetic Aperture Radar (SAR) is an example of an active system.



The digital data acquired by the satellites is transmitted to ground stations and can be used to reconstitute an image of the Earth's surface not too dissimilar to an aerial photograph.







Bands Used in Remote Sensing

Emission of EMR (Electo-Magnetic Radiation) from gases is due to atoms and molecules in the gas. Atoms consist of a positively charged nucleus surrounded by orbiting electrons, which have discrete energy states. Transition of electrons from one energy state to the other leads to emission of radiation at discrete wavelengths. The resulting spectrum is called line spectrum. Molecules possess rotational and vibrational energy states. Transition between which leads to emission of radiation in a band spectrum. The wavelengths, which are emitted by atoms/molecules, are also the ones, which are absorbed by them. Emission from solids and liquids occurs when they are heated and results in a continuous spectrum. This is called thermal emission and it is an important source of EMR from the viewpoint of remote sensing.
The Electro-Magnetic Radiation (EMR), which is reflected or emitted from an object, is the usual source of Remote Sensing data. However, any medium, such as gravity or magnetic fields, can be used in remote sensing.

Remote Sensing Technology makes use of the wide range Electro-Magnetic Spectrum (EMS) from a very short wave "Gamma Ray" to a very long "Radio Wave". Wavelength regions of electro-magnetic radiation have different names ranging from Gamma ray, X-ray, Ultraviolet (UV), Visible light, Infrared (IR) to Radio Wave, in order from the shorter wavelengths.


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GIS and Remote Sensing

An Introduction: Remote Sensing is the science and art of acquiring information (spectral, spatial, temporal) about material objects, area, or phenomenon, without coming into physical contact with the objects, or area, or phenomenon under investigation. Without direct contact, some means of transferring information through space must be utilised. In remote sensing, information transfer is accomplished by use of electromagnetic radiation (EMR). EMR is a form of energy that reveals its presence by the observable effects it produces when it strikes the matter. EMR is considered to span the spectrum of wavelengths from 10-10 mm to cosmic rays up to 1010 mm, the broadcast wavelengths, which extend from 0.30-15 mm.

Geographic information and imaging systems visually portray layers of information in new ways to reveal relationships, patterns, and trends. Software from vendors such as ESRI and ERDAS provides the functions and tools needed to store, analyze, and display information about places. Indiana University has higher education license agreements with both ESRI and ERDAS that provide students, faculty, and research staff from all campuses with the use of software at reduced costs.

A geographic information system (GIS) is a computer-based tool for mapping and analyzing feature events on earth. GIS technology integrates common database operations, such as query and statistical analysis, with maps. GIS manages location-based information and provides tools for display and analysis of various statistics, including population characteristics, economic development opportunities, and vegetation types. GIS allows you to link databases and maps to create dynamic displays. Additionally, it provides tools to visualize, query, and overlay those databases in ways not possible with traditional spreadsheets. These abilities distinguish GIS from other information systems, and make it valuable to a wide range of public and private enterprises for explaining events, predicting outcomes, and planning strategies. For more information about GIS, see GIS.com.

Remote sensing is the art and science of making measurements of the earth using sensors on airplanes or satellites. These sensors collect data in the form of images and provide specialized capabilities for manipulating, analyzing, and visualizing those images. Remote sensed imagery is integrated within a GIS. For more information, see NASA's remote sensing tutorial.

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Soil Survey and GIS

A soil survey report is a record of occurrence of soil mapping units on the earth’s surface. In addition, a soil survey report contains information and data about the use and management of the soil. A soil survey report is an inventory of soils in a given area, usually a county, in which information about the uses, capabilities and limitations of the soils in the inventory are included.

Mapping units represent the boundaries between different soil series on a map of the surveyed area. These mapping units are represented as polygons on the soil survey. These mapping units are constructed from information gathered by soil scientists as they evaluate the landscape by digging or boring holes to determine the profile characteristics. The profile characteristics and the landscape location and position are evaluated to determine the best use of the soil and engineering properties. Soil surveys are developed to allow the user to predict the behavior of a soil without having first hand experience with the particular soil and it is a comprehensive source of information regarding the soils in a particular area. It must be stressed that the information contained in the report is based on a survey and is not a specific site survey. It is neither practical nor possible to evaluate every potential site included in the survey and since soils and landforms are highly variable, even over short distances, an onsite investigation must be conducted to verify the predicted soil properties.

Rectangular Survey System
To make it possible to match a parcel of land with the information about that parcel contained in a Soil Survey, the parcel must have an identification symbol or name. The basis for location of a particular tract of land is the Rectangular Survey System, sometimes called the township-range system. The starting point of the rectangular survey is determined by the intersection of a survey line running east and west called a base line and another line running north and south called a principle meridian. There are 34 surveyed principle meridians in the U.S. After the principle meridian and the base line were established, parallel lines to each of those lines were surveyed at six mile intervals, six miles north, 12 miles north, etc. (towns, T); then six miles east, 12 miles east, etc. (ranges, R) and then the south (T) and west (R) intervals were done until the entire area had been divided into a 6-square mile patchwork called townships. These townships are numbered in relationship to their distance from the starting point so a designation of T2N, R3W would indicate the parcel covers an area 6 to 12 miles north of the base line and 12 to 18 miles west of the principle meridian. See the following graph.

The highlighted township would be described as T4S, R4W and would represent 36 square miles as it is 6 miles on each side. This township is divided into 6 one-mile square parcels called sections. Each parcel with the section is numbered, beginning in the upper right hand corner, proceeding to the left and then counting in an S pattern until the bottom right hand corner is reached and labeled as section 36. See the following diagram. Each one-square mile section is then divided into quarters and then each quarter is divided into quarters, if needed.

The legal description of the highlighted township, section and quarter section, if this parcel was in Idaho is:

“The Northwest quarter of Section 15, Township 4 South, Range 4 West of the Boise Meridian or using the numerical notation the description would be NW ¼, Section 15, T2N, R3WBM”.

This rectangular survey system has a major drawback; it imposes a rectangular system on a curved earth. Because of the curvature, sections are not always exactly one square mile. On the average sections are about 50 feet shorter on the north edge than on the south. This makes the use of a correction line every 24 miles necessary and a corresponding adjustment in the size of sections 1-6 on the north side of the section and sections 6, 7, 18, 19, 30 and 31 on the west side of the abovementioned correction line.

Coordinate System

As mentioned above, when the spherical surface of the earth is projected onto a planer surface it is quickly recognized that the surface cannot be transformed without distortion. To overcome this problem hundreds of map projections have been developed, each with their own strengths and weaknesses. With the advent of the Geographical Information System (GIS) map projections with the least distortion were selected. Unfortunately, the distortion of the map projection is dependent upon the shape and orientation of the object, so each region chose a projection system with the least distortion for that area. Idaho uses the Universal Transverse Mercator (UTM) system which is recognized worldwide. This system divides the earth’s surface into 60 UTM zones and then establishes a false northing and false easting in the SW corner of the meridian so each coordinate pair (x and y axis) within the zone is a positive integer.

The rectangular survey system and the UTM system have been coordinated with each other to allow us to locate the parcel using the township-range system and then allowing us to establish the exact longitudinal and latitudinal coordinates with the UTM system. This interface is extremely important as the data is linked to the parcel using the UTM system. For additional information on GIS, please refer to “Introduction to Geographic Information System”, by Kang-tsung Chang, McGraw Hill, 2002.

Geo tagging in GIS

Definition: Geotagging a digital photo or other object on a Web site or in a document refers to the attachment of geographical identification data. For example, a geotagged digital image would include precise latitude and longitude coordinates, and may also include altitude and other information. This permits the image or other object to be easily and precisely positioned on a map, putting the geotagged image into context, and making it more easily searchable. A number of popular Web sites permit the upload of geotagged photos, and digital cameras may include geotagging capability, or may be fitted with accessories that automatically geotag photos.

Geotagging (also referred to as geocoding) essentially involves "tagging" something like an image or Web site with location data. It doesn't necessarily involve GPS, however it usually involves latitude/longitude coordinates so GPS is a logical tool for geotagging.

Most recently, geotagging has become a popular way for photographers to identify and record where they snap their photos. Whether it's a professional photographer or just an avid amateur who loves traveling or the outdoors, more and more people are discovering geotagging every day.

Geotagging can be a great way to organize images. When you combine geotagging with online mapping services, you can imagine how developers can come up with some creative options for using and publishing the data. For example, Flickr has some interesting tools for leveraging geotagging. Vacationers can now see a "map view" of all their images. Hikers can keep track of favorite routes for later use or to share with others.

Using geotagging technology, you can also "geoblog" by attaching a blog post to a specific location through a geotag. In the latter example, blog posts could be organized (and selected) by location vs. by topic or date. This is great for people who already like to blog about their vacations, for example, and want to share images this way as well.

There are various pieces of equipment that you can attach to your camera to record GPS coordinates and begin geotagging. One such product is the "Kato" from Geotate. According to Geotate, the Kato requires "zero integration" with the camera- recording the information for each picture, but not requiring a transfer of the information until the pictures are downloaded on to your computer.

However, iPhone users are in luck. The 3G iPhone with GPS also has geotagging capabilities. GPS-enabled camera phones with geotagging software will eventually lead to a real surge in geotagging. Many people have not yet discovered geotagging but it's only a matter of time. Combined with phone GPS navigation, it will open up a whole new range of possibilities within online and mobile social networking.

What is Geotagging a photo?
Geotagging is the act of associating geographical / GPS co-ordinates with a photo, normally by embedding the data in the EXIF information stored in several image formats - for example, alongside the ISO, shutter speed and aperture settings.

There are two ways geotagging is performed: with a suitable camera (such as the Nikon D200) and an adapter for a GPS unit, you can record it straight to EXIF at shooting time. Alternatively, you can replay the the track and align the timestamps to see the nearest point to the time at which you took each photo. Latter one is preferred, because not only is it cheaper, but it looks a whole lot easier than carrying around huge adapter cables.

And Why?
Adding location data to photos at source saves me the hassle of browsing around on multimap trying to find exactly where you were at the time; the data is there, accurate to maybe 5s and a few metres.

A glossary of terms commonly used in GIS

following are terms used to describe data in the format used with ESRI products :

Arcs - Lines that begin and end with a node. Intersections of arcs are always connected with a node. Arcs also make up part of a polygon. An example of data that would use this form would be roads.

Node - Beginning, connecting and ending points of an arc. An example of data that would be represented by this form would be manholes or inlets in a stormwater system.

Point - A single "dot" location. A point is also called a "label point". A label point is the element that holds information in the polygon. An example of data that would be stored in the system using this form would be fire hydrants, or a set of individual address locations.

Polygon - An arc that closes on itself to make a circle or a closed shape. An example of a set of data that would be stored in the GIS in this format would be parks or lakes.

ArcView - Desktop GIS software developed by ESRI used to do some basic GIS operations and print maps.

Shapefile - A set of files that contain a set of points, arcs, or polygons (or features) that hold tabular data and a spatial location. This file format is used in ArcView software. - A set of files that contain a set of points, arcs, or polygons (or features) that hold tabular data and a spatial location. This file format is used in ArcView software.

Arc/INFO - The GIS software developed by ESRI that is used to do more robust GIS operations

Coverage - A file format used in Arc/INFO software developed by ESRI that contain a set of points, arcs, or polygons (or features) that hold tabular data and a spatial location.

Common GIS Terms
Area - A description of the dimension or content of a polygon.

Coordinate System - A fixed reference framework superimposed onto the surface of an area to designate the position of a point within it by using x and y coordinates. The State Plane Coordinate System and the system of latitude and longitude used on the Earth's surface are common examples.

Data - A collection of facts, concepts or instructions in a formalized manner suitable for communication or processing by human or automatic means. Generally used in the GIS field as a reference to all spatial information.

Feature - A spatial element which represent a real-world entity by having specific characteristics. Often used synonymously with the term object. A generalized description of a point, line or polygon.

Field - A location in a data record in which a unit of information is stored. For example, in a database of addresses, one field would be 'city'.

Geocoding - The process by which the geographic coordinates of a location are determined by its address, postal code, or other explicitly non-geographic descriptor.

Legend - The description of the symbology representing features on a map.

Map - A graphic representation of geographically distributed phenomena. The information displayed may be in the form of symbols or signs.

North Arrow - The graphical representation of which direction north is on the map.

Scale - The ratio or fraction between the distance on a map, chart or photograph and the corresponding distance in the real world.

Scale Bar - A map element which shows the scale of a map graphically.

Set - A group of features and their data.

Spatial - (pro. Spay-shawl) An adjective. Of, relating to, or occurring in space.

Table - A means of organizing data in rows and columns in which each row represents an individual entity, record, or feature and each column represents a single field or attribute value.

Query - A way of selecting features based on a set of common characteristics. For example, the act of selecting all the buildings that have an area greater than 2000 sq. ft. out of a database.

Spatial Data Management

Geo-Relational Data Model: All spatial data files will be geo-referenced. Geo-referencing refers to the location of a layer or coverage in space defined by the coordinate referencing system. The geo relational approach involves abstracting geographic information into a series of independent layers or coverages, each representing a selected set of closely associated geographic features (e.g., roads, land use, river, settlement, etc). Each layer has 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 real world. This approach borrows heavily on the concepts of relational DBMS, and it is typically closely integrated 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 (simplest elements), arcs (sets of connected points), and areas (sets of connected arcs). Topological data structure, in fact, adds intelligence to the GIS database.

Attribute Data Management: All 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 have an engineering geological database, containing information about soil and rock types, field observations and measurements, and laboratory results. This is interesting data, but not very useful if the laboratory data, 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 that were 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 (especially designed 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 as much as possible; redundancy or unnecessary duplication of data are an annoyance, since this makes updating the database much more difficult; one can easily overlook changing redundant information whenever 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 of management, and the higher risk, as data are centrally managed.

The Core of Your Mapping / GIS Project: When most people begin a GIS project, their immediate concern is with purchasing computer hardware and software. They enter into lengthy discussions with vendors about the merits of various components and carefully budget for acquisitions. Yet they often give little thought to the core of the system, the data that goes inside it. They fail to recognize that the choice of an initial data set has a tremendous influence on the ultimate success of their GIS project.



Data, the core of any GIS project, must be accurate - but accuracy is not enough. Having the appropriate 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 as inaccurate data can. All any GIS project needs is data accurate enough to accomplish its objectives and no 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-based population study whose smallest unit of measurement is a county. Purchasing such data would be too costly and inappropriate for the project at hand. Even more critically, collecting overly complex data could 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 it runs, no expense should be spared in its creation. Perfection, however, is relative. Projects and data requirements 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.


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Why do Windows servers hang?

Troubleshooting a hung or nonresponsive Windows server can be a challenging endeavor. Simply hitting the reset button is no longer a tolerated option as more companies use these servers for business-critical operations. This three-part series will explore the reasons why a Windows server may hang and provide a cookbook approach to diagnosing the underlying issues with the Windows Kernel Debugger (Windbg).

When Microsoft released the early versions of its server operating system (Windows NT 3.5x and NT4), there was no easy way to troubleshoot a hung server. Other mainstream operating systems, such as Digital Equipment Corp.'s VAX/VMS, offered ways to manually intervene by forcing a crash dump whereby the server's state could be captured at the time of the hang. This dump could then be analyzed to determine why the server hung. The only option for early Windows platforms, however, was to reset the box.

As Windows servers became more predominant in the business world, hitting the reset button became unacceptable. As a result, in Windows 2000 Server and later versions, it became possible to force a crash dump to assist with determining why the server hung. Microsoft introduced this feature in Knowledge Base article 244139. It allows a keystroke combination (right CTRL+SCROLL LOCK twice) to generate a crash dump on PS/2-type keyboards. Microsoft extended this feature in Windows Server 2003 with a hotfix to the Kbdhid.sys driver to accommodate USB-type keyboards.

Several other options now exist to force a crash dump. Microsoft provides the Windows Special Administrative Console (SAC) Crashdump command as part of Windows Emergency Management Services (EMS), which allows for "headless" servers with no local graphical console. Vendor-specific options also exist to force a crash dump including the HP Integrity server's Management Processor TC (transfer of control) command, an NMI (non-maskable interrupt) button on some Integrity models, or the Integrated Lights Out (iLO) virtual NMI button. We'll take a closer look at each of these options later in the series.

Why a server hangs
There are a variety of reasons why a server may hang, including both hardware and software issues. The most common hardware reason for a server hang is spurious interrupts by a failing device. For example, a network interface controller (NIC) may have a bad component or be attached to a bad cable causing false interrupts to occur. These interrupts occur at an elevated interrupt request level (IRQL) dominating the attention of the processor(s), leaving lower priority requests (user level) unanswered. As a result, the server appears to be hung.

Another example of a hardware-induced hang involves storage requests going unanswered. For example, consider a case where a disk drive fails, causing outstanding I/O requests to be queued up. Eventually, these pending requests trigger a cascading effect of user and system threads to hang, leading to a system-wide outage.

More often, however, server hangs are a result of software issues. These issues come in several flavors, including:

• System resource depletion (e.g., out of memory pool) -- The most common type of software hang, this typically is the result of a memory leak by a driver or kernel mode thread. Resource depletion can also result from exceeding architectural limits of paged and nonpaged memory pools (typically experienced on an x86 32-bit operating system).

• Deadlock conditions -- A deadlock occurs when contention exists for common resources between two or more threads. For example, a deadlock exists when one thread owns an exclusive lock on a resource that another thread wants, and that thread exclusively owns a resource that the initial thread wants.

• Spinlock conditions -- Spinlock hangs are similar to deadlocks, but involve contention for a spinlock that is used to synchronize access to data structures in a multi-processor environment. Other permutations of these conditions include a driver holding a lock while performing other activities for an extended period of time. Actual examples of deadlock and spinlock hangs will be provided later.

• High-priority, compute-bound threads -- A software hang can also occur if high-priority, compute-bound thread(s) are dominating the processors. Since the Windows operating system permits varying levels of thread priority, one or more threads may execute at a higher priority than typical user threads. The result is that applications and users at normal priority are starved for CPU time, causing a perceived software hang.

The big picture
So, as you can see, there are numerous reasons why a server may hang. To give you a better idea of what happens when you force a crash to generate a memory dump, and subsequently analyze the crash to determine what caused the hang, see Figure 1 below.

Starting on the left-hand side, you can see the server crashes or hangs. In the event of a crash, the server would generate a memory dump if the dumpfile and pagefile are properly configured (see Microsoft Knowledge Base articles 254649, 197379 and 889654).

In the event of a hang, manual intervention would be required to force a crash dump as previously described. In either case, the content of memory is written to the pagefile.sys before the server is rebooted. During the reboot, the pagefile.sys is written to the memory.dmp file. Finally, once the server has rebooted, you can use the Windows Kernel Debugger (Windbg) to analyze the memory dump using a symbol server (as documented in KB article 311503) to translate memory references to meaningful functions and variables.

Figure 1: Overview of memory dump process and analysis

Now that you have a better idea of why server hangs occur.

ArcGIS Supports Microsoft SQL Server 2008

ArcGIS users now have access to SQL Server 2008. SQL Server 2008, combined with ESRI's powerful geodata management capabilities, will provide users with the tools they need to seamlessly consume, use, and extend location-based analysis for enterprise-scale computing and Web collaboration. The support is the result of a close, multiyear working relationship between ESRI and Microsoft Corp. in the development of the spatial extensions to SQL Server 2008.

A geographic information system (GIS) integrates hardware, software, and data for capturing, managing, and analyzing geographically referenced information. ESRI's ArcGIS is an integrated collection of GIS software products, providing a standards-based platform for spatial analysis, data management, and mapping. ArcGIS can be used via the Web, mobile devices, and desktop applications and can also be integrated with other enterprise systems such as work order management systems, financial systems, supply chain management, business intelligence reporting, and executive dashboards.

In SQL Server 2008, Microsoft introduces two new spatial types—Geography and Geometry—both of which are supported by ESRI. The new spatial types meet the needs of many ESRI GIS customers who have been asking for structured query language (SQL) access to spatial features stored in SQL Server to integrate spatial data with other enterprise applications.

"ESRI has supported SQL Server for many years and is taking full advantage of SQL Server 2008 to help our government, utilities, and commercial enterprise customers take the geographic approach to improving their business processes," says ESRI president Jack Dangermond. "ESRI and Microsoft together provide the platform to organize and manage geographic information, leading to improved methods for analyzing and using information more effectively to make better decisions."

ArcGIS Server 9.3 Enterprise enables ESRI's support for SQL Server 2008 to extend across its ArcGIS 9.3 platform including server, desktop, mobile, and online technology. ESRI recommends installing the newly released Service Pack 1 for ArcGIS 9.3 for optimal performance with SQL Server 2008.

"Microsoft is excited about ArcGIS 9.3's support of SQL Server 2008 and its new spatial types," says Ed Katibah, program manager for SQL Server at Microsoft Corp. "The combination of ESRI’s ArcGIS 9.3 and Microsoft SQL Server provides customers with a powerful spatial-enabled application to seamlessly consume and extend location-based data—ultimately resulting in better decision-making."

To learn more about ESRI’s support for Microsoft SQL Server 2008 and view a demo that showcases ESRI’s integration with SQL Server 2008, Visit : ESRI’s DEMO and Documents

Tables and databases in GIS

Does GIS Use Tables or Databases?
The ability to combine data stored in tables and databases with geography is what makes GIS such a versatile technology. Many technologies are available to display and map natural and man-made geographic features, but it is GIS that relates those features to data stored in tables and databases. In order to make the most of this relationship of geographic feature information and the related tabular data, it is important to understand a few things about tables and databases.

The Elements of a Table
A table consists of rows and columns as in the example below. This table contains information about parcels of land. Within the table are categories of information in each column; each category is described by a column heading. Under the row containing the column headings are rows of information; each contains information about one parcel of land which is identified by the Parcel Number.

A row in a table is also known as a record. Each row, or record, contains a grouping of information about a single subject. The columns of a table may also be known as fields, items, and, commonly in GIS, attributes. Each column describes a certain attribute of the record. The record for Parcel Number 9726301001, read across the table and tells us the owner is J. Kennedy, the Zoning District for the parcel is RLP and the Drainage Basin for the Parcel is #1. In this record you see a very common practice used in tables, the use of abbreviations and keys. Rather than storing the complete, lengthy Zoning District or Storm Drainage Basin titles, a substitution of an acronym or a numbered key is used. This practice may or may not be appropriate depending upon the use or size of the table(s) involved.

The Elements of a Database
A database is simply a collection of tables of interrelated information that is stored and managed as a unit.

A relational database is a set of tables containing data fitted into predefined categories. Each table (which is sometimes called a relation) contains one or more data categories in columns. Each row contains a unique instance of data for the categories defined by the columns. For example, a typical land-record database might include a table that described a parcel with columns for Parcel#, Owner, Zoning District, Storm Drainage Basin #, and so forth. Another table would describe a Zoning District: District Acronym, Full Title, Description of Zone, City Code Reference, and so forth. A user of the database could obtain a view of the database that fitted the user's needs. For example, a Zoning Inspector might like a view or report on all parcels of land owned by a certain person, in a certain Zoning District, listing the full Zoning District information.

What Is a Relate?
A relate is an association or connection between corresponding records in two tables. This association is made possible by having at least one common item in each of the tables. Each column that relates to another column in a different table is know as a "key" and must contain the same data. Each relate is constructed of a "from table" and a "to table." The column which is being used to form the relate in the "from table" is know as the "primary key" or "local key." The column which is being used to form the relate in the "to table" is know as the "foreign key."

The tables below demonstrate a very simple table relate. Each table contains the common field, Parcel#, that is used to relate on. This example is a simplistic representation of how the City GIS Division maintains its' parcel database. The Parcel Table being maintained by GIS contains a record on each parcel in the database. The Larimer County Assessor maintains a record of each parcel and other related information such as valuations and record dates. By maintaining the relate keys in each table, these two tables can be related and used by City staff to submit queries against in order to find valuable information.

Parcel Table

Assessor Valuation Table

Relate Types
One-To One
This is the simplest type of relate. In this type there is only one record in the table that is being related to that corresponds with exactly one record in the table that we are relating from.

Many-To One
In this instance, the table that we are relating from will have occurrences of identical values in the relate field. By having the same value, these fields can only correspond to a single record in the table being related to.

One-To-Many
This situation occurs when each record in the field being related from contains a unique value, but corresponds to multiple records in the table being related to.

Many-To-Many
The last situation occurs when multiple records in the table being related from correspond with multiple records in the table being related to.

GIS Data Queries and Selections
GIS data that is stored in a tabular format can be queried and viewed the same way data is stored in other database systems and applications. However, GIS provides the user with the ability to query that same data using a geographic component. Data can be selected and viewed based upon its proximity to a selected geographic element such as a road, lake, address, zoning district, utility infrastructure, etc… or any combination thereof

Geographical Data Sets

Geographic Data Types: Although the two terms, data and information, are often used indiscriminately, they both have a specific meaning. Data can be described as different observations, which are collected and stored. Information is that data, which is useful in answering queries or solving a problem. Digitizing a large number of maps provides a large amount of data after hours of painstaking works, but the data can only render useful information if it is used in analysis.
Spatial and Non-spatial data: Geographic data are organised in a geographic database. This database can be considered as a collection of spatially referenced data that acts as a model of reality. There are two important components of this geographic database: its geographic position and its attributes or properties. In other words, spatial data (where is it?) and attribute data (what is it?)

Attribute Data: The 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 data: Geographic position refers to the fact that each feature has a location that must be specified in a unique way. 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 cartographic projections 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, and continuous surfaces.


Point Data: Points are the simplest type of spatial data. They are-zero dimensional objects with only a position in space but no length.


Line Data: Lines (also termed segments or arcs) are one-dimensional spatial objects. Besides having a position in space, they also have a length.


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


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


Linkages and Matching: A GIS typically links different sets. Suppose you want to know the mortality rate to cancer among children under 10 years of age in each country. If you have one file that contains the number of children in this age group, and another that contains the mortality rate from cancer, you must first combine or link the two data files. Once this is done, you can divide one figure by the other to obtain the desired answer.
Exact Matching: Exact 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 to bring them together is easily achieved by using a key common to both files -- in this case, the town name. Thus, the record in each file with the same town name is extracted, and the two are joined and stored in another file.
Hierarchical Matching: Some types of information, however, are collected in more detail and less frequently than other types of information. For example, financial and unemployment data covering a large area are collected quite frequently. 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 of the same area is to use hierarchical matching -- add the data for the small areas together until the grouped 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. To obtain meaningful values for the city, the tract values must be added together.
Fuzzy Matching: On many occasions, the boundaries of the smaller areas do not match those of the larger ones. This occurs often while dealing with environmental data. For example, crop boundaries, usually defined by field edges, rarely match the boundaries between the soil types. If you want to determine the most productive soil for a particular crop, you need to overlay the two sets and compute crop productivity for each and every soil type. In principle, this is like laying one map over another and noting the combinations 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 be analysed and/or mapped individually. Alternatively, they may be combined. With two data sets, only one valid combination exists. Even if your data sets may be meaningful for a single query you will still be able to answer many more questions than if the data sets were kept separate. By bringing them together, you add value to the database. To do this, you need GIS.

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COMPUTER MAPPING ESSENTIALS

How will this workshop help me?

• Understanding of how computer mapping can help you with property planning
• Provide you with the knowledge and tools to assist with purchasing the right computer mapping software for your property, such as:
  • Ability to import data types
  • Inclusion of farm management tools
  • Inexpensive (i.e. below $700)
  • Ongoing technical support
  • Easy to use and learn
  • Links with different types of GPS units
  • Able to generate new data

What the workshop will cover?

Participants will become familiar with:

• Fundamental computer mapping concepts and principals

• Loading and displaying digital data

• Generating new maps for properties

• Linking GPS for data upload and download

• Creating and printing hard copy maps

• Using mapping software you will be able to add bio and physical features:

  • Draw fence boundaries, watering points, tracks, sheds and houses
  • Identify different ground surfaces

Participants are provided with:

• Computer Mapping Essentials Workbook

• Property digital data containing (based on your Lot on Plan):

  • Property boundaries

  • Landsat and/or SPOT5 satellite imagery

  • Regional Ecosystem boundaries

  • Preclear vegetation boundaries

  • Watercourses

  • Wetlands (if applicable)

• FarmKeeper and PhoenixFarms-Mapping software packages (demonstration licences)

AgForward makes available 10 training computers for the day and uses either the FarmKeeper or PhoenixFarms-Mapping software packages to demonstrate this capability. If you have a preference of software for the training day, please identify this on the registration form.

Registration

See the Workshop Calendar for a list of workshop locations and dates, download the Computer Mapping Essentials registration form for the desired location, complete the form and return it to our Brisbane office.

This workshop commences at 9am and finishes around 4pm.

The workshop is restricted to 10 participants.

Useful Computer Mapping Links:

• www.agdata.com.au

• www.farmkeeper.com.au

• www.fairport.com.au/gpmapper

• www.psystems.com.au/farmmap

• www.oziexplorer.com

• www.esriaustralia.com.au

• www.mapinfo.com.au

Computer Mapping

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Annex 9 of Visualization of International Relationship Networks

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The data collected together in the sections of the Encyclopedia of World Problems and Human Potential has been deliberately organized in a manner which stresses the interrelationships between the entities within a section and between those in different sections. (Each section is characterized by entities of a different type, and several types of relationship may exist between the same two entities). In effect, therefore, the entities and relationships in each section constitute a network, possibly composed of many subnetworks. Similarly, since entities in each section may be linked to those in other sections, the whole is constituted by a system of interlinked networks in which the relationships have a limited number of distinct meanings. The entities and relationships are currently held in computer files in a form which should facilitate analysis of these networks. It is hoped that the availability of data in this form will encourage the development of new types of analysis more appropriate to the structural complexity portrayed, especially since both the quantitative data and the mathematical functions representing the nature of particular relationships under different conditions (which are a precondition for the application of current methods of quantitative analysis of social systems), are absent and in most cases unavailable.

As François Lorrain notes (1) the abstract notion of a network is undoubtedly called to play a role in the social sciences comparable to the role played in physics by the concept of euclidean space and its generalizations. But the poverty of concepts and methods which can currently be applied to the study of networks stands in dramatic contrast to the immense conceptual and methodological richness available for the study of physical spaces. A whole reticular imagery remains to be developed. At this time a network is understood to contain simply nodes and links and little else. An attempt to define anything like a reticular variable results in very little. This is not surprising, since to succeed would require the establishment of a general mathematical theory of networks which as yet has been little developed. In contrast to this situation, consider the multitude of spatial variables which are available: coordinates, length, surface, volume, curves, classes of curves, classes of surfaces, parameters of curves, parameters of surfaces, and so on, and all these in a space of any number of dimensions and manifesting any type of curvature.

(a) Social networks: The types of network which occur in the social sciences are of such a diverse nature that only a purely formal definition of this notion is of sufficient generality.

A network is constituted by a certain set of points. In the social sciences these points may represent any or all of the following: individuals, groups, organizations, beliefs, roles, etc. In this exercise they represent: international organizations, multilateral treaties, world problems, strategies, concepts (human development, integrative, patterns), metaphors, symbols, modes of awareness, values. Such points may represent the existence of entities at the present time, or they may represent the existence of entities at some past or future time (or such points may also be used to represent intervals of time).

The points in a data set may be linked by one or more kinds of relationship. In this exercise three basic types of relationship are distinguished:

• (i) Simple relationship, namely A is related to B which implies that B is related to A;
• (ii) Hierarchical relationship, namely A is a part of B which implies that B is in contextual relationship to A;
• (iii) Functional relationship, namely A acts on B which implies that B is acted upon by A.

In the first case above a relationship is further defined by the types of entity between which it occurs, namely whether they are of the same type, or whether they are of different types. In the second and third case, a relationship is further defined by distinguishing the direction of the relationship, which is further developed in the third case by distinguishing several ways in which A can act upon B.

(b) Analysis of networks: Classical mathematics, summarizing François Lorrain's (1) remarks, is not able to handle complex structural features characteristic of social systems. Organization is best depicted as a network. The mathematical theory of networks derives largely from certain branches of topology and abstract algebra rather than from analysis, which underlies classical mathematics. The theory of graphs is often presented as a kind of general theory of networks with numerous possible applications in the social sciences. However, other than in the area of operations research, the theory of graphs has not proved itself to be very useful in sociology. The reason is probably that the theory has mainly been developed in the context of relatively limited problems in such a way that the results collected under the graph theory label, although numerous and of great interest, have little unity. In addition, the theory rarely handles networks with several distinct types of relationships each with its own configuration of links. It is precisely such networks which are of most interest in sociology. The theory also tends to exclude networks in which some of the points have links back to themselves when it is often just such networks which are important in representing social structures.

A final disadvantage of the theory of graphs is that it only offers a fairly limited number of means of global analysis of networks. It seriously neglects an important aspect of the study of any type of mathematical structure, namely the level of transformation relations between graphs. Because of its composition, a category possesses a richerstructure than a simple graph, and it is therefore possible to define more rigorous and fruitful criteria of transformation (namely the concepts of function and functional reduction). In addition a set of points and a set of relations can be treated in their totality and simultaneously, in contrast to the methods of graph theory which considers individual paths between particular points in the graph. In the universe of categories (the universe of objects and relationships), transformations between categories may also be considered as relationships within a category whose objects are themselves categories, and so on. All this emerges from consideration of the global structure resulting from the manner of composition which relates the relationships themselves, thus providing a dialectic of levels of structure and a new imagery of networks. At all levels of this universe, the functional relationships between categories play a central role. They are the fundamental instruments which may be used in the exploration of structural complexity and the tools for extraction of information in global studies.

(c) Use of graph theory methods: Despite the limitations noted above, graph theory methods have been applied to the analysis of social structures although such applications are not very common (see references below).

The image of a "network or web" of problems (or organizations, etc) to represent a complex set of interrelationships is a fairly familiar one. This use of "network", however, is purely metaphorical and is very different from the notion of a network of concepts as a specific set of linkages among a defined set of concepts, with the additional property that the characteristics of these linkages as a whole may be used to interpret the semantic significance of the concepts involved.

(d) Some features of graphs: Using graph theory, a number of characteristics of networks can be determined. Points 1 to 3 below are concerned with the shape of the network, 4 to 8 with interactions within the network.

• (i) Centrality: A measure (in topological not quantitative terms) of the extent to which a given entity (eg a problem) is directly or indirectly "related" via links to other entities (ie, the extent to which it is "distant" from another entity). One can speak of a "key" problem or of an organization being "central" to the concerns of a particular complex. It may also be considered a measure of the degree of "isolation" of the entity. A systematic analysis of the centrality of entities in a network could indicate where new entities are necessary to bridge gaps and link isolated domains.
  
  
• (ii) Coherence: A measure of the degree of "interconnectedness" or "density" of a group of entities. This may be considered as the degree to which a system of problems is "complete". Differences in density would reflect the tendency for more highly coherent problem systems to appear more self-reinforcing in comparison to less organized parts of the network. In some respects this is an indication of the degree of "development" of a problem system.
  
  
• (iii) Range: Some entities are directly related to many other entities, others to very few. The range of an entity is a measure of the number of other entities to which it is directly related. Range could be considered an indication of the "vulnerability" of a problem to the extent that a high range problem would be less vulnerable to attack than a low range problem, since it has more relationships anchoring it to its problem environment and preserving it in existence. High range points are therefore either key points in resistance to problem change or else key points in terms of which orderly change can be introduced.
  
  
• (iv) Content: The "content" of a relationship between entities is the nature or reason for existence of that relationship. Simple graphs have only one link between any two entities; multigraphs have two or more links, each of different content.
  
  
• (v) Directedness: A relationship between two entities may have some "direction" (ie, A to B, or B to A). There may be several types of directedness. Two types are important for this project: A is a sub-element of B; A acts on B. In a multigraph, one link may point from A to B and the other from B to A.
  
  
• (vi) Durability: A measure of the period over which a certain relationship between entities is activated and used. At one extreme, there are the links activated only on a "one-shot" basis (eg a single crisis), at the other there are links, and sets of links, which are considered stable over centuries (eg between the more permanent problems).
  
  
• (vii) Intensity: A measure of the strength of the link or bond between two entities. Two problems may be said to be "strongly bound together". In some cases, the intensity is a measure of the amount of the "flow" or "transaction" between the entities. The link from A to B may be strong, and that from B to A, weak.
  
  
• (viii) Frequency: A link between two entities may only be established intermittently.
  
  
• (ix) Rearrangeability and blocking: A connecting network is an arrangement of entitites and relationships allowing a certain set of entities to be connected together in various possible combinations. Two suggestive properties of such networks, which are extensively analyzed in telephone communications, are: (a) rearrangeability (a networkis rearrangeable, if alternative paths can be found to link any pair of entities by rearranging the links between other entities); (b) blocking (a network is in a blocking state if some pair of entities cannot be connected).

(e) Implications of artificial intelligence research: In considering the possibility of analyzing networks of problems (organizations, concepts, etc), it is important to benefit as much as possible from related work on artificial intelligence, and possibly pattern recognition. Artificial intelligence projects to simulate human personality or belief systems have had to develop mathematical techniques and computer programmes which can handle and interrelate entitites such as concepts and propositions, some of which may be positively or negatively loaded to represent positive values and perceived problems (the credibility and importance of a belief in a network, and the intensity with which it is held, may also be indicated). Clearly the objective of such projects is not achieved once a simple inventory of entities can be examined, even if it is highly structured in the form of a thesaurus. Of particular interest is the work on "dialogues" with such belief systems, some of which are established over a period by extensive interviews with individuals and others which are specially constructed to simulate paranoia, for example (see references). Presumably it would be possible to conduct somewhat similar dialogues with the collective beliefs constituted by problem/value netwroks such as might be developed during the course of this project.

(f) Comment: Despite the available techniques noted above, and others which have been applied to non-social networks, much would seem to remain to be accomplished, as François Lorrain's (1) remarks indicated, in order to grasp networks in their totality.

The question is what it would be useful to know about networks at this time. What indicators would it be useful to attach to individual problems (organizations, etc) to indicate the characteristics of their relationship to the network(s) in which they are embedded? What similar indicators would be useful in describing the relationships between relatively dense networks and the larger network in which they themselves are embedded? What sort of concept about networks need to be embodied in a network vocabulary so that such matters can be discussed intelligently and unambiguously in public debate? In other words, what are the elements of an adequate vocabulary of structure and in what disciplines has the basis for such a vocabulary already been established: chemistry, crystallography, architecture, design in general, etc? What can be learnt from biologists about the growth and development of the many reticular structures they encounter (eg radiolaria)? More interesting perhaps, in which occupations do some individuals develop a special (instinctive or intuitive) sensitivity to the structural and dynamic characteristics of the networks with which, or within which, they work: airline pilots, urban bus drivers, electricity grid controllers, counter-espionage directors, factory process controllers, computer-based data network designer/controllers, telephone exchange designer/ controllers, institutional fund controllers, etc? What do such people say, or want to say, about their networks? Why has the term "networking" suddenly sprung into common use and consequently what could "to network" mean? It is questionable whether any adequate organizational response (a network strategy) to the world problem complex can be elaborated until such rich experience is collected together and matched to an elaborated, mathematically-based concept structure, and an associated vocabulary. A conceptual quantum jump is required to grasp problem (and other organized) structures in their totality and be able to communicate such insights.

It is hoped that the availability of the data in this publication will help to stimulate such fresh thinking on the conceptual containment of societal networks.

Basics of Digital Mapping

Vector vs Raster Maps: The most fundamental concept to grasp about any type of graphic data is making the distinction between vector data and raster data. These two data types are as different as night and day, yet they can look the same. For example, a question that commonly comes up is "How can I convert my TIFF files 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. Raster maps are best suited to some applications while vector maps are suited to others.

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

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

Basic properties of raster and vector data: Each entity in a vector file appears as an individual data object. It is easy to record information about an object or to compute characteristics such as its exact length or surface area. It is much harder to derive this kind of information from a raster file because raster files contain little (and sometimes no) geometric information.

Some applications can be handled much more easily with raster techniques than with vector techniques. Raster works best for surface modeling and for applications where individual features are 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 of the road itself. Terrain elevations can be recorded in a raster format and used to construct digital elevation models (DEMs). Some land-use information comes in raster format.

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


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Maps in GIS

The early concept of map handling had a serious difficulty, as they could not handle the tabular data or attribute data in conjunction with the spatial information. This let the development of additional methods and techniques wherein both the spatial and attribute data could be handled and integrated so that the outputs were more meaningful and dynamic for planning and decision-making.

GIS technology is relatively recent and over the past 30 years, there has been a rapid increase in theoretical, technological and applications level. Today the advancement of mapping, modeling, spatial analysis, and time series analysis has overcome the limitations of the traditional manual process buy powerful GIS toolsi.

Recent advancement in processing technology provides an unprecedented opportunity for computer based mapping and spatial information management. Present mapping and analytical technology, known as Geographic Information System (GIS), is a very advance tool that facilitates the large scale data analysis, manipulation and visualization of natural, social, physical, economic and cultural landscape.

In many developing countries in Asia, GIS has been used as an integral part of the decision making process for last 10 years. In the field of planning and monitoring of the natural resources it is now clear that the spatial information technology provide a powerful organization and analytical tool for decision-making. Moreover the ever-increasing volume of Earth observation data intensifies the usefulness of GIS as a tool for integration different data types and enhancing our capacity to manipulate and analyze this information for planning and monitoring.

What is a Map?
According to the International Cartographic Association, a map is: a representation, normally to scale and on a flat medium, a selection of material or abstract features on, or in relation to, the surface of Earth. Map is the most powerful visualization tool for any implementation and monitoring processii. Briefly we can say: A graphic representation of features on the earth's surface or other geographically distributed phenomena is called a map.

Types of Maps
Maps are usually classified in two types:

Topographic map is a reference tool, showing the outlines of selected natural and represented by contours and/or shading, but topographic maps also shows roads, rivers, contours and other prominent features (Figure 1.1).

Thematic map is a tool to communicate geographical concepts such as the distribution of population densities, climate, movement of goods, land use etc. (Figure 1.1)

Coordinate system
A coordinate system specifies the units used to locate features in two-dimensional space and the origin point of those units. Latitude and longitude is a coordinate system (often called the "geographic" coordinate system).

A reference system used to measure horizontal and vertical distances on a plan metric map. A co-ordinate system is usually defined by a map projection, a spheroid of reference, a datum, one or more standard parallels, a central meridian, and possible shifts in the x- and y-directions to locate x,y positions of point, line, and area features. In ARC/INFO, a system with units and characteristics defined by a map projection. A common co-ordinate system is used to spatially register geographic data for the same area.

Geographic Coordinates
A measurement of a location on the earth's surface expressed in degrees of latitude and longitude.

Types of Coordinate Systems uses in Afghanistan are:
1. DD (Decimal Degree)
2. DMS (Degree Minute Seconds)

DD Coordinate System
Values of latitude and longitude expressed in decimal format rather than in degrees, minutes, and seconds.

DMS Coordinate System
Degree, Minute and Seconds (DMS): Values of latitude and longitude expressed in degrees, minutes, and seconds.

Datum
In the most general sense, any set of numeric or geometric constants from which other quantities, such as coordinate systems, can be defined. A datum defines a reference surface. There are many types of datums, but most fall into two categories: horizontal and vertical.

In surveying, a reference system for computing or correlating the results of surveys. There are two principal types of datums:

Vertical datum: is a level surface to which heights are referred. In the United States, the generally adopted vertical datum for leveling operations is the national geodetic vertical datums of 1929 (differing slightly from mean sea level).

Horizontal datum: The horizontal datum, used as a reference for position, is defined by: the latitude and longitude of an initial point, the direction of a line between this point and a specified second point, and two dimensions which define the spheroid.

Map Projection
A map projection translates the locations on the globe onto the flat surface of your map. 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.

A projection is a method by which the curved surface of the earth is represented on a flat surface. The Earth’s surface is curved but it must be shown on a flat sheet, some distortion is inevitable. Distortion is least for when the map only shows small areas, and greatest when a map attempts to show the entire surface of the Earth. A complex mathematical transformation is involved in representing three dimensional earth surfaces to a two-dimension paper map. Considering the size and shape of Afghanistan, projection would be critical for measuring the surface of the land, because map projection influences the underlying database of an area.

There are several types of projections. Below two example types:
1. Universal Transverse Mercator (UTM)
2. Geographic

Map Scale
The scale of the map is the ratio between distances on the map and corresponding actual distances on the earth. If a map has a scale of 1:50,000, then 2cm on the map equals 1km on the Earth’s surface.

The Most Popular way to define map scales are: “Small scale” and “Large scale” maps. The easiest ways to remember a large scale map that shows great detail, small features representative fraction is large, e.g. 1:10,000 and a small scale map shows only large features representative fraction is small, e.g. 1:250,000.