Wednesday, June 24, 2009

What is GPS ?

The Global Positioning System (GPS) is a satellite-based navigation system made up of a network of 24 satellites placed into orbit by the U.S. Department of Defense. GPS was originally intended for military applications, but in the 1980s, the government made the system available for civilian use. GPS works in any weather conditions, anywhere in the world, 24 hours a day. There are no subscription fees or setup charges to use GPS.

How it works

GPS satellites circle the earth twice a day in a very precise orbit and transmit signal information to earth. GPS receivers take this information and use triangulation to calculate the user's exact location. Essentially, the GPS receiver compares the time a signal was transmitted by a satellite with the time it was received. The time difference tells the GPS receiver how far away the satellite is. Now, with distance measurements from a few more satellites, the receiver can determine the user's position and display it on the unit's electronic map.

A GPS receiver must be locked on to the signal of at least three satellites to calculate a 2D position (latitude and longitude) and track movement. With four or more satellites in view, the receiver can determine the user's 3D position (latitude, longitude and altitude). Once the user's position has been determined, the GPS unit can calculate other information, such as speed, bearing, track, trip distance, distance to destination, sunrise and sunset time and more.

How accurate is GPS?

Today's GPS receivers are extremely accurate, thanks to their parallel multi-channel design. Garmin's 12 parallel channel receivers are quick to lock onto satellites when first turned on and they maintain strong locks, even in dense foliage or urban settings with tall buildings. Certain atmospheric factors and other sources of error can affect the accuracy of GPS receivers. Garmin® GPS receivers are accurate to within 15 meters on average.

Newer Garmin GPS receivers with WAAS (Wide Area Augmentation System) capability can improve accuracy to less than three meters on average. No additional equipment or fees are required to take advantage of WAAS. Users can also get better accuracy with Differential GPS (DGPS), which corrects GPS signals to within an average of three to five meters. The U.S. Coast Guard operates the most common DGPS correction service. This system consists of a network of towers that receive GPS signals and transmit a corrected signal by beacon transmitters. In order to get the corrected signal, users must have a differential beacon receiver and beacon antenna in addition to their GPS.

The GPS satellite system

The 24 satellites that make up the GPS space segment are orbiting the earth about 12,000 miles above us. They are constantly moving, making two complete orbits in less than 24 hours. These satellites are travelling at speeds of roughly 7,000 miles an hour.

GPS satellites are powered by solar energy. They have backup batteries onboard to keep them running in the event of a solar eclipse, when there's no solar power. Small rocket boosters on each satellite keep them flying in the correct path.

Here are some other interesting facts about the GPS satellites (also called NAVSTAR, the official U.S. Department of Defense name for GPS):

  • The first GPS satellite was launched in 1978.
  • A full constellation of 24 satellites was achieved in 1994.
  • Each satellite is built to last about 10 years. Replacements are constantly being built and launched into orbit.
  • A GPS satellite weighs approximately 2,000 pounds and is about 17 feet across with the solar panels extended.
  • Transmitter power is only 50 watts or less.

What's the signal?

GPS satellites transmit two low power radio signals, designated L1 and L2. Civilian GPS uses the L1 frequency of 1575.42 MHz in the UHF band. The signals travel by line of sight, meaning they will pass through clouds, glass and plastic but will not go through most solid objects such as buildings and mountains.

A GPS signal contains three different bits of information — a pseudorandom code, ephemeris data and almanac data. The pseudorandom code is simply an I.D. code that identifies which satellite is transmitting information. You can view this number on your Garmin GPS unit's satellite page, as it identifies which satellites it's receiving.

Ephemeris data tells the GPS receiver where each GPS satellite should be at any time throughout the day. Each satellite transmits ephemeris data showing the orbital information for that satellite and for every other satellite in the system.

Almanac data, which is constantly transmitted by each satellite, contains important information about the status of the satellite (healthy or unhealthy), current date and time. This part of the signal is essential for determining a position.

Sources of GPS signal errors

Factors that can degrade the GPS signal and thus affect accuracy include the following:

  • Ionosphere and troposphere delays — The satellite signal slows as it passes through the atmosphere. The GPS system uses a built-in model that calculates an average amount of delay to partially correct for this type of error.
  • Signal multipath — This occurs when the GPS signal is reflected off objects such as tall buildings or large rock surfaces before it reaches the receiver. This increases the travel time of the signal, thereby causing errors.
  • Receiver clock errors — A receiver's built-in clock is not as accurate as the atomic clocks onboard the GPS satellites. Therefore, it may have very slight timing errors.
  • Orbital errors — Also known as ephemeris errors, these are inaccuracies of the satellite's reported location.
  • Number of satellites visible — The more satellites a GPS receiver can "see," the better the accuracy. Buildings, terrain, electronic interference, or sometimes even dense foliage can block signal reception, causing position errors or possibly no position reading at all. GPS units typically will not work indoors, underwater or underground.
  • Satellite geometry/shading — This refers to the relative position of the satellites at any given time. Ideal satellite geometry exists when the satellites are located at wide angles relative to each other. Poor geometry results when the satellites are located in a line or in a tight grouping.
  • Intentional degradation of the satellite signal — Selective Availability (SA) is an intentional degradation of the signal once imposed by the U.S. Department of Defense. SA was intended to prevent military adversaries from using the highly accurate GPS signals. The government turned off SA in May 2000, which significantly improved the accuracy of civilian GPS receivers.

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INFORMATION TECHNOLOGY MANAGEMENT PLAN, DATABASE DESIGN AND GIS APPLICATION DEVELOPMENT

E. Karagüllü

Ministry of Agriculture and Rural Affairs, General Directorate of Agricultural Research, Bagdat Cad. Istanbul Yolu No:238, 06171, P.O. box: 78, Ankara/Turkey, Tel +90 312 3157623, Fax +90 312 3152698

D. Sherrill
ESRI, 380 New York Street, Redlands, CA 92373-81000, USA, Tel. +1 909 793 2853, Fax +1 909 793 5953, email: dsherrill@esri.com

F. Ernst
ISLEM GIS, Kader Sok. 11/3, 06700 Ankara/Turkey, Tel. +90 312 4680830, Fax +90 312 4674148, email: fernst@islem.com.tr

M. Akdogan
ISLEM GIS, Kader Sok. 11/3, 06700 Ankara/Turkey, Tel. +90 312 4680830, Fax +90 312 4674148, email: makdogan@islem.com.tr

M. PeskIrcIoglu
Ministry of Agriculture and Rural Affairs, General Directorate of Agricultural Research, Bagdat Cad. Istanbul Yolu No:238, 06171, P.O. box: 78, Ankara/Turkey, Tel +90 312 3157623, Fax +90 312 3152698

S. Özbayrak
Ministry of Forests, General Directorate of Forests, Gazi Tesisleri 1 Nolu Bina 06560, Ankara/Turkey, Tel +90 312 2126300, Fax +90 312 2222078

E. Özek
Ministry of Environment, Eskisehir Yolu 8. Km., 06530, Ankara/Turkey, Tel +90 312 2879963, Fax +90 312 2862271



__________________________________

Abstract

Turkish government organizations are participating in the World Bank sponsored In-situ Conservation of Genetic Diversity Project. As part of this project a GIS and Remote Sensing Center has been established at the Ministry of Agriculture and Rural Affairs. This paper focuses on database design, data automation procedures, and a project atlas, in which the database and some applications as well are explained in detail. Besides, lessons learned from a project in which many different state agencies where involved are described.

INTRODUCTION

In the framework of the "Turkish Agricultural Research Project" and in conjunction with the "In-situ Protection of Genetic Resources Project" the Turkish Ministry of Agriculture and Rural Affairs, General Directorate of Agricultural Research obtained a World Bank loan for the implementation of the "Information Technology Management Plan, Database Desing, and GIS Application Development" Project. Environmental Systems Research Institute, (ESRI), Redlands, CA., USA and ISLEM GIS, Ankara, Turkey have been in charge for the implementation of this 6 month project. Because the "In-situ Protection of Genetic Resources Project" started as a cooperate project between the Turkish Ministry of Agriculture and Rural Affairs (MARA), Ministry of Environment (MOE), and Ministry of Forestry (MOF) project works were carried out by staff of the three mentioned ministries.

Most of the works were carried out at Geographic Information Systems and Remote Sensing Center at the Ministry of Agriculture and Rural Affairs. The foundation works for this Center started in December 1993 and were completed with the official opening in June 1997. But, it was not before February 1998 when this project started that the Center reached an operational stage.

In the experience of ESRI and ISLEM GIS , clients that actively participate in and control their own Geographic Information System (GIS) implementation are the most successful. Therefore, the emphasis in this project was self-help combined with a mentoring, technology transfer approach designed to help make MARA, MOE, and MOF self-sufficient in GIS technology as rapidly as possible. The self-help aspect of the project was the formation of a GIS implementation team within the participating ministries whose sole responsibility was to participate actively in the project side by side with ESRI and ISLEM GIS staff.

PROJECT INITIATION AND USER NEEDS ASSESSMENT

At the beginning of the project a combined MARA/MOE/MOF/ISLEM GIS implementation team was established that conducted three initial tasks:

  • Compiling and prioritizing potential and existing users of GIS technology both within MARA/MOE/MOF and other organizations for participation in the user needs assessment.
  • Data inventory survey. For reasons of time shortage, instead of distributing inventory forms personel interviews had to been done with people at MARA/MOE/MOF departments, nongovernment organizations (NGOs), academic institutions, and other organizations important to the overall concept of data sharing.
  • Preparing a day-long GIS implementation seminar for MARA/MOE/MOF implementation departments. A key objective of the seminar was to begin the process of enhanced communciation among GIS users, both existing and potential. The seminar with over 150 attendees from MARA/MOE/MOF and other departments at the manager level was a great success. Beside an outstanding quality level this was due to the fact that the presentation of information on the scope, status, and results of projects especially in the initiation phase to a wider audience is not a common policy in Turkey.

Long-term administration of the MARA GIS Center will involve a broad range of functions, from oversight of application operations to coordination of user agencies involved in maintaining various components of the agricultural database, including the "In-situ Conservation of Genetic Diversity" project. The range of potential functions provide a foundation and context for the continued development of Information Technology Management Plan (ITMP) as the administrative structure for the MARA GIS. The needs assessment has been the first step in implementing a successful GIS within MARA.

In order to carry out a number of user needs interviews over a short time, the implementation staff was trained in GIS interview techniques as well as the use of a structured GIS interview form. A total of 21 organizations were interviewed during February 1998. Some details of the Information Technology Management Plan are given in the last section.

DATABASE DESIGN

ESRI staff began the database design task with a thorough review of existing project documentation resulting from the previous project works. In particular, the user needs interviews from staff involved in the ongoing projects "In-situ Conservation of Genetic Diversity" and "Turkish Agricultural Research Project" was important in terms of defining immediate data needs. The survey of available data as well as information about interagency relationships from the draft ITMP was primary input into the definition of databases of long-term utility.

Out of a detailed study of the survey of available data came an understanding of the current status of existing geographic data, both manual and digital. Based on this understanding, ESRI staff and the implementation team worked toward a statement of data standards in terms of resolution, scale, projection, and use of coordinate systems. These standards included recommendations as to graphic symbolization of features, physical directory structure and how the cooperate GIS database ultimately had to be physically partitioned.

ESRI staff was responsible for bringing the design of all data categories into one integrated database design. This integrated design was documented in a written report form and in an on-line data dictionary as well. The starting point for the on-line data dictionary was one currently in prototype version for the ArcWorld II data product. This prototype data dictionary is a series of dBase IV tables that store descriptions, names, sources, compilation information, scale, and other metadata. It has been developed taking into account the U.S. Federal Geographic Data Committee (FGDC) metadata standards.

PILOT STUDY

In this project, selected target species are forest trees (cedar and fir), wild relatives of field crops (wheat, chickpea, lentils), and fruit trees (chestnut and plum. The pilot areas have been selected and described as: The Kaz Dag Area of Northwestern Aegean Region; Ceylanpinar in Southeastern Turkey; Bolkar and Aladaglar Mountains in South Turkey.

Although the need of 1:25 000 scale topographic maps as base maps and digital elevation data for the pilot areas had been determined these data could not be acquired and used for this project. Instead, the following data resources that contained some base map data were automated: 1:30 000 scale soil maps for the Ceylanpinar pilot area, and 1:25 000 scale forest maps for the Kazdag Mountains pilot area. These maps were automated, referenced to UTM coordinates and link to attribute data. The presence of these base and thematic maps provided the means for the linkage of plant species related fieldwork data.

Other datas related with the pilot areas were transects points and Gene Managements Zones that were intagrated to GIS by connecting all the points. Those points and their attributes are shown in figure 1 and figure 2;


Figure 1 (Soil Map of Ceylanpinar Tim and Transects for target species)


Figure 2 (Forest Map of Kazdagi and Transects for target species)

Two other important data sources used in this project were the "Turkish Geographic Database" produced by ISLEM GIS and "National Plan". The "Turkish Database" consists mainly of the following data layers: Political boundaries, settlement, drainage network, transportation and digital terrain data. The database served to reference tabular data that did not contain coordinate information (Figure 3).


Figure 3 (influence of air pollution to some target species)

The distribution of target species that were shown in the National Plan digitized and integrated to GIS. (Figure 4)


Figure 4. (Distribution of Target Species in TURKEY)

The data that were taken from ARC ATLAS II and target species maps are analyzed together to determined the gene protection and conservation area in TURKEY (Figure 5).


Figure 5 (Land use, settlements and plant density)

The need to collect all the works that had been carried during the project works gave way to the creation of an Atlas. Spatially grouped, maps showing the content of the database are followed by maps of analysis that were performed in regard of establishment and management of actual and potential Gene Management Zones (GMZ).

CONCLUSION

GENERAL CONSIDERATIONS

Generally, it can be stated that the project had been a success in terms of reaching the overall purpose to establish the operationality of the MARA GIS Center. While a 3 million USD investment of the World Bank for founding the Center's hardware, software, and network (the biggest investment World Bank ever did in this sector) brought about nothing in respect of operation, this low-budget project created a motivated GIS team that is capable to carry out its own GIS projects. Despite being a newcomer, the MOF project team won the third award of the poster session at the 5th Turkish ArcInfo and ERDAS User Conference in June 1998. Unfortunately, World Bank funds are usually not available for projects with major consulting components like this case.

ORGANIZATIONAL COOPERATION

The overall interorganizational cooperation appeared to be much better as it was anticipated in the beginning. This circumstance should influence World Bank decisions on further investments in this sector positively, because it is expected that the Center should play an important role in coordinating GIS activities between the three participating ministries.

According to the recommendations that are an important part of the Information Technology Management Plan "The GIS center will support the Genetic-diversity project for the three participating ministries, Ministry of Agriculture and Rural Affairs (MARA), Ministry of Forestry, (MOF), and Ministry of Environment (MOE). The GIS center must also support the broader GIS needs of the departments and research institutes of MARA."

Agreements should establish the following roles for the GIS Center:"

  • Genetic-diversity data clearing house,
  • Equipment availability to support Genetic-diversity projects,
  • GIS training functions for MARA and other ministries,
  • Provision of specialized GIS staff by MARA to support GIS projects of MARA departments, and
  • Provision of specialized GIS staff by MARA to support other ministries GIS project.

DATA

During the data inventory works it has become clear that there is a wealth of valuable data that could be useful for projects like the current one. Unfortunately, several constraints hinder the efficient use of these data and could not be included in the current project:

  • Most of the data are not available in digital format.
  • The quality of maps is very heterogenous and documentation is not sufficient. Often information on used projection parameters is totally missing.
  • The greatest obstacle that has to be removed in the future is the attitude of government organizations to data sharing. Data are usually regarded as at least proprietary or even secret goods that should not be given to anyone outside, or if so, only for a very high price.

Currently, under the framework of a National Information System government initiatives are under way to promote data sharing between all government agencies.

HARD AND SOFTWARE

When the Center was established 4 years before the hardware, software, and network configuration was considered to be state-of-the-art. Due to missing project activities nearly no upgrade of the Center's system had been made since then. This resulted in a very low performance of the system in general and the PC's (all 486s) and the network in particular. Data corruption and loss was a very common problem and caused a big delay in the data automation process.

Fortunately, responsible managers could be convinced that upgrade has to be done. Acquisition of new system components has already started - hopefully to be used in coming projects.

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What is a Geodatabase ?

A geodatabase represents geographic features and attributes that are stored inside a Relational Database Management System (RDMS).

ESRI first introduced the geodatabase with the new generation of ArcInfo product - ArcGIS 8. Geodatabases are supported in all of the current ArcGIS desktop products - ArcReader, ArcView, ArcEditor, ArcInfo, and other on-line mapping platforms such as ArcIMS (Internet Map Server) and ArcExplorer.

There are two types of geodatabases - Personal and Enterprise. The personal geodatabase in fact is in the format of Microsoft ACCESS (.mdb); Enterprise geodatabases are hosted in server-based DBMS such as SQL Server, Oracle, or IBM DB2.

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ArcView 3.x terminology (Projects, Views, Themes, Layouts, etc.)

In a nutshell:

Views are visual displays of the highlighted themes of data sets.

Tables display the attributes of data sets.

Charts are visual displays of selected attributes of data sets.

Layouts are composites of views, tables, charts, legend material and title text.

Scripts provide a way to modify the standard ArcView interface.

Projects contain related views, tables, charts, layouts, and scripts.

Projects

A "project" is the mechanism by which views, scripts, layouts, and other work done on a particular problem are kept together within ArcView. You can think of it as a manila folder. To the user, opening a 'project' is like opening a file in any other application. A project file points to certain data sets, and selected data within them, without itself containing the data (thus project files are typically quite small). The project file contains the instructions necessary for ArcView to recreate saved views, plots or charts of the data when the project is opened. Because a project file typically points (with a path) to external data sets and requires them to generate views or plots, if a project file is moved to another computer, the paths to the data may have to be adjusted for the project file to function in its new location.



Data Sets

Data sets useable with ArcView are of two basic types: those which have embedded geometric (coordinate) information, and those which have no embedded geometric information, but instead an attribute which can be used to link the data set to one which does have geometric information. In metadata parlance, these two types of data have 'Direct Spatial Reference' and 'Indirect Spatial Reference,' respectively.

Examples of data sets with embedded geometric information are Arc/Info coverages, shapefiles, TIF images with associated world files, or ERDAS .LAN or .IMG (usually satellite or remote sensing imagery) files. The geometric information usually provides x and y values in one of a group of standard coordinate systems, such as latitude-and-longitude, Universal Transverse Mercator (UTM) or State Plane Coordinates (SPC). The geometric information may describe points, lines, polygons, or grid data. These are the sort of data sets one would use to create a graphic recognizable as a map. Typically these data sets also contain some attribute information; in the case of a coverage consisting of tax parcel polygons an expected attribute would be something like the parcel identification number.

Examples of Indirect Spatial Reference data sets include tabular data such as INFO files, .dbf (database) files, and comma delimited ASCII files with an attribute that allows them to be related to another data set with Direct Spatial Reference. A specific example might be a tax revenue data set which includes owner information and a parcel identification number to link it to the tax parcel coverage mentioned above. Indirect Spatial Reference data sets cannot be used alone to produce a map (because they do not contain the necessary geometric information), but they could be used alone to produce a chart.

Data sets may have many attributes and as a result each geometric object in Direct Spatial Reference data will also. One or more attributes from a data set are used to create the themes of a view.

Views

A view is a window display of selected themes. In general terms, it is a "map." For a useful view, it is necessary that it contain at least one selected theme.

It is possible to set the projection or coordinate system of a view if the geometric data is in decimal latitude/longitude form. A view cannot be printed directly, but it can be printed indirectly by placing it into a layout and printing the layout.

Themes

A theme is created when a particular attribute of a data set is chosen and used to set the graphical presentation (color, pattern, size) of the geometric component of the data set. A single data set may be used to create several themes. A theme is selected (and will be drawn) when a check mark appears in the box next to the theme title. A theme is 'active,' and may have its properties set (e.g. that the theme is only visible in a view at certain scales) when it appears raised in the themes window. Double-clicking on a theme title brings up the legend editor which can be used to set the theme name and the symbol type and color for the theme. Any individual theme is drawn on top of, and may obscure, any themes listed below it in the themes window.


Tables

The 'virtual table' capabilities of ArcView Tables give this module great flexibility. Essentially, a virtual table is a view of tabular data which can be saved in a project. It is possible to rearrange the order of fields in a table, hide fields, give aliases to field names, sort columns, and attach tables to one another 'virtually,' i.e. without actually creating any new tables, or editing the underlying tables. A virtual table may be exported to create a 'real' table. A query tool in tables allows records to be selected based on logical expressions. If the selected records are tied to spatial data (points, lines, or polygons) in a view, they will also will also be shown as selected in the view



Charts

Charts gives ArcView the capability to show tabular information graphically in forms other than a map. ArcView can produce six types of charts: area, bar, column, line, pie, and xy scatter.



Layouts

Layouts are the mechanism by which the visual components of an ArcView project are arranged on a 'page' for presentation on screen or in preparation for printing or exporting. Views and their legends, charts, tables, scale bars, north arrows, title and explanatory text are all possible components of an ArcView layout.


Scripts

Scripts provide a way to customize the standard ArcView environment or to automatically carry out functions one might otherwise do manually through built-in ArcView functions. They provide a way to build a simplified user environment into a project file. Scripts can be assigned to (and run from) the menu bar, to icons on the button or tool bars, or the project window. The properties of a project can be set to run specific scripts when the project starts up or shuts down.

The scripting language for ArcView, Avenue, is an object based language. The ArcView interface itself is built from Avenue scripts. All of these system scripts are available for the user to look at as examples of Avenue programming and to modify into their own specialized scripts if desired. Before you write a complex Avenue script from scratch, you might want to look at documented user contributed scripts available for download from ESRI.







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How to add a script in ArcView

There are many script resources out there: sample scripts from ESRI included with ArcView, free scripts that you can download at ESRI's ArcScripts website, and scripts that you may receive from other GIS users. Sometimes these scripts may come with text files describing how to use them, but often they do not. This page will help you get started with using scripts. Included are instructions for how to load, compile, and run scripts, and also how to add a custom button associated with a script to the View interface.

Directions

The first step in using your script is to load it into your project.; In this example, you'll add a Sample Script that comes with ArcView. This script adds X and Y coordinates for every feature into your shapefile's attribute table. The first step is to open a New Script window in the Project window, as shown below:

Load the sample script into this new script window, by going to the Script Menu --> Load Text File. If we wanted to customize a System Script (something you might do once you are quite comfortable with Avenue), you would use the Load System Script menu entry. Write Text File is used to save your scripts to a text file; otherwise, your scripts are only saved within your ArcView project file (.apr file).

If you have ArcView loaded in the default location, the ArcView sample scripts are found in the following directory: C:\ESRI\AV_GIS30\ArcView\Samples\Scripts. Avenue scripts are text files with a .ave extension.

Once a script is loaded, or after you have written or edited a script, you need compile it. Compiling the script means that ArcView goes through the entire script, looks for syntax errors, and translates the script into a form that ArcView can use. To compile a script, simply press the Compile button (the black checkmark) or go to Script> Compile in the menus. Sample scripts should readily compile. If you are writing your own Avenue script, you may have syntax errors that you will then need to go through and fix before your script will properly compile.

Now you can rename your script and add comments to allow you and other users to know something about the script. Go to Script --> Properties to change the name to something more descriptive than Script1 (just as you would use Theme Properties and View Properties to rename your themes and views).

Once you have successfully compiled your script, you can run it in one of several ways.

1. You could press the run button next to the compile button while the script is active.
2. You could press the run button next to the Open button in the Project window (the same window where you first opened up your new script window)
3. You could add a custom button to your View interface from which you can run your script.(Shown Below)

To add a custom button, you first need to open up the Customize Dialog Box. To do this, double click in the gray area of the button bar in the main ArcView interface, as shown below.

You will now see the Customize dialog box, and can view the properties of existing buttons and menus, as well as add your own. When this dialog first opens, the default Category is "Menu"; switch this Category to "Buttons." You'll see all of the existing buttons display, and you can scroll along to where you want to place you new button, then click "New." Click on some of the existing buttons and look at their attributes ("Click", "Disabled", "Help", "Icon", etc) to get a feel for how the buttons work. It is here that you attach the script to the button, as shown below.

Each button is associated with a script that runs when a user clicks the button. The "Click" attribute contains the name of this script. A new button has an empty Click attribute by default, but by clicking on this attribute you can bring up a dialog box to choose the script you want to associate with the new button.

Double click on the Icon field to choose your icon for your new button.

You can add text into the Help dialog box to specify what you want the user to see as a yellow po-up text when the user puts the mouse over the new button, as well as what text will appear in the lower right hand corner of the ArcView application window.

When entering your text into this Help Dialog box, the first text is what will appear when you move your mouse over the button, and the text following the two forward slashes is what will appear in the lower right hand corner (generally more descriptive text), as you can see in the following figure.

Make your shapefile active in your view, and then press your new button to
execute the script AddXYCoordinates. Open the table and scroll to the end of the fields, and you will see the two new fields added by the script, X-coordand Y-coord, and the XY coordinates for each feature in the units of the shapefile (here, decimal degrees for Latitude and Longitude).

Now you know the basics of adding scripts in ArcView!




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Websites for Digital GIS Data

See our Finding Data page for general guidelines about finding GIS data.

National Data Clearinghouses
International Data

For an extensive listing of foreign data sites please see the GIS Data Bookmarks section.

Imagery

Mostly free access to satellite and aerial imagery

Land Cover Data

Land Cover Data
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How to Design a GIS Project

Careful design at the beginning of a project will help you avoid hours of unnecessary work and redundant tasks. There are five basic steps to carrying out a GIS project:

1. Research question and project goals. What is the purpose of the project? What is the research question? What is the spatial extent (total area) and grain size (ground resolution) of the study? Even a soils map is the answer to the question, “What is the spatial distribution of soils in California?” Identify the information needs: What type of spatial data do you need to achieve your goals? What are the sources of these data, and what are the appropriate types of data to answer these questions?

2. Methodology. Constructing a logical spatial analysis flow chart that details the project steps will make the success of the analysis more likely. What types of analyses will you perform? Overlays? Multivariate regressions? Spatial interpolations? The spatial analysis flow diagram should include:

o An outline of the procedures required for the data
o A logical sequence of procedures to be performed
o A list of all the data required for each step


3. Data. Before you embark on your project, you should do an inventory of the data requirements and sources of information. Even with the widespread availability of digital data on the Internet, many GIS projects are mired in data collection, input, and integration. Check if the data are already in digital format. Will you have to scan in paper maps or input data from statistical yearbooks?

4. Analysis and accuracy assessment. Often you will find that once you start the project, there is a need to revise the procedures originally intended. Once the analysis is complete, you should evaluate the accuracy and validity of the results. Fieldwork may be required.

5. Presentation. The results will have to be presented in a format suitable for the audience, and this can include a poster-sized map, journal paper, PowerPoint presentation, etc.
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Digital Elevation Model (DEM)


A digital elevation model (DEM) is a digital representation of ground surface topography or terrain. It is also widely known as a digital terrain model (DTM). A DEM can be represented as a raster (a grid of squares) or as a triangular irregular network. DEMs are commonly built using remote sensing techniques, however, they may also be built from land surveying. DEMs are used often in geographic information systems, and are the most common basis for digitally-produced relief maps.

Production

Digital elevation models may be prepared in a number of ways, but they are frequently obtained by remote sensing rather than direct survey. One powerful technique for generating digital elevation models is interferometric synthetic aperture radar; two passes of a radar satellite (such as RADARSAT-1) suffice to generate a digital elevation map tens of kilometers on a side with a resolution of around ten meters. One also obtains an image of the surface cover.

Another powerful technique for generating a Digital Elevation Model is using the digital image correlation method. It implies two optical images acquired with different angles taken from the same pass of an airplane or an Earth Observation Satellite (such as the HRS instrument of SPOT5).

Older methods of generating DEMs often involve interpolating digital contour maps that may have been produced by direct survey of the land surface; this method is still used in mountain areas, where interferometry is not always satisfactory. Note that the contour line data or any other sampled elevation datasets (by GPS or ground survey) are not DEMs, but may be considered digital terrain models. A DEM implies that elevation is available continuously at each location in the study area.

The quality of a DEM is a measure of how accurate elevation is at each pixel (absolute accuracy) and how accurately is the morphology presented (relative accuracy). Several factors play an important role for quality of DEM-derived products:

* terrain roughness;
* sampling density (elevation data collection method);
* grid resolution or pixel size;
* interpolation algorithm;
* vertical resolution;
* terrain analysis algorithm;

Methods for obtaining elevation data to used to create DEMs

* Real Time Kinematic GPS
* stereo photogrammetry
* LIDAR
* Topographic Maps
* Theodolite or total station
* Doppler,
* Inertial surveys

Uses

Common uses of DEMs include:

* extracting terrain parameters
* modeling water flow or mass movement (for example avalanches and landslides)
* creation of relief maps
* rendering of 3D visualizations.
* creation of physical models (including raised-relief maps)
* rectification of aerial photography or satellite imagery.
* reduction (terrain correction) of gravity measurements (gravimetry, physical geodesy).
* terrain analyses in geomorphology and physical geography
* Geographic Information Systems (GIS)
* Engineering and infrastructure design
* Global positioning systems (GPS)
* Line-of-sight analysis
* Base mapping
* Flight simulation
* Precision farming and forestry
* Surface analysis
* Intelligent transportation systems (ITS)
* Auto safety / Advanced Driver Assistance Systems (ADAS)

Differences between DEMs and DSMs

A digital elevation model — also sometimes called a digital terrain model (DTM) [1]— generally refers to a representation of the Earth's surface (or subset of this), excluding features such as vegetation, buildings, bridges, etc. The DEM often comprises much of the raw dataset, which may have been acquired through techniques such as photogrammetry, LiDAR, IfSAR, land surveying, etc. A digital surface model (DSM) on the other hand includes buildings, vegetation, and roads, as well as natural terrain features. [2] The DEM provides a so-called bare-earth model, devoid of landscape features. While a DSM may be useful for landscape modeling, city modeling and visualization applications, a DEM is often required for flood or drainage modeling, land-use studies, geological applications, and much more.
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The most popular GIS software packages

I tried to list only the general-use GIS software here. There are lots of GIS software that are made for certain professions, such as hydrologic scientists, petroleum industry specialists, etc. that aren't listed here. Note that most of the software descriptions were written by the Software Makers/Distributors.

GIS Software

The most popular GIS software packages are:

  • ESRI
  • MapInfo
  • IDRISI
  • Manifold
  • InterGraph GeoMedia
  • SmallWorld
  • GRASS
  • MS MapPoint
  • ERDAS Imagine

    • Current Stanford students, faculty and staff may install the following ESRI software programs on any Stanford owned computer.

    Windows
    Unix
    • ArcInfo Workstation
    • ArcView 3.3

    ArcPress
    Spatial Analyst
    Network Analyst
    3D Analyst

    • ArcSDE
    • ArcIMS
    • ArcView Internet Map Server
    1 Programs available from our Download Page.
    2 Programs loaded on Branner GIS machines.
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