Comparison Of The Analytical Functionality Of Mapinfo Information Technology Essay

Geographical Information Systems as a science requires data as shown from a real world to be modeled into a map and thereafter analysis can be performed on such. Two Software Vendors(Environmental Systems Research Institute and Pitney Bowes) are at the fore of designing solutions [ArcGIS 9.3 and MapInfo Professional10.5/ Vertical Mapper] respectively that will make this achievable but individual’s taste differ and this has resulted in a heated argument about which software package incorporates more functionality. This paper is aimed at examining the functionality of these packages in terms of user friendliness, interface issues and its analytical prowess. After this a glance will be taken at practical examples of how these have been applied to various sectors of the economy, then finally a critical overview of their pros and cons in relation to these applications.

Introduction

1.1 Definition of Geographical Information Systems

As Heywood et al., (2006) points out, Geographical Information Systems is a sophisticated Computer System capable of uploading, viewing and manipulating spatial data [data with references attached to them on the earth’s surface] with an aim of providing critical decision-making processes to improve living conditions of the human race.

1.1.1 Why GIS?

In our everyday activities, we are faced with a Geographical Inquiry Process/Procedure; these could take various forms as how to get to the nearest mall? What fastest routes to take? What is the address of the nearest cinema?

We query our minds which is seen as a natural database with a snapshot or as a Database Management System so when these questions are posed, we tend to look for locations, trends, patterns and supply feedbacks to the Geographical Inquiry of spatial data.

It is a result of complexities experienced in decision-making procedures that a team of Geographical Information experts have deployed a variety of ways to process spatial data, analyze it and display the output in diverse means which could either be in form of maps or graphs or mere PowerPoint Presentations. Two vendors; Environmental Systems Research Institute (ESRI) and Pitney Bowes Business Insight both came out with their solutions- ArcGIS and MapInfo respectively to address the situation of processing spatial data and displaying the accurate information [processed data] to the viewers or the people who are charged with the responsibility of applying such information.

Description of ArcGIS 9.3 and MapInfo Professional 10.5

User Friendliness and User Interface Issues Between Arcmap And Mapinfo

A close examination will be taken from statistical data analysis performed by this software to highlight the lapses and edge one has over the other. (Higgs, 2010)

For MapInfo, when attribute data is imported into the Browser Window, it has to be saved as a .tab [mapinfo table] before the columns can be edited while for ArcMap, this step is not necessary. For novices working with MapInfo, this can be a pitfall and a user can be stuck for long hours if he doesn’t know this fundamental principle.

MapInfo has a Bowser Window which I find very fascinating because of the ease of use of toggling between the Mapped Data itself and the Attribute Data while for ArcMap, you will need to access the Layer properties of the layer to view the attribute information.

When queries are executed in MapInfo, several times you get an error message saying ‘No record is selected’ however, the right parameters were chosen. It is observed also that queries are easier to construct with ArcMap because for inexperienced SQL Users, they will be more comfortable working with ArcMap as regards this because the query is constructed for them as an initial starting line and also a list of buttons are available to enhance the SQL Query criteria [Query By Example] interface (GeoCommunity, n.d.). This is also very noticeable when a relational join is performed. ArcMap makes it easier for you to select the field from one table and select another field from the second table from which the join is to be based upon but with MapInfo, query will have to be defined and this can be a uphill task for the inexperienced SQL User.

This can be shown in the table below.

Table 2.0

ArcGIS has a visible scale bar which can be manipulated to either let you view your mapped data on a large scale or small scale but MapInfo does not have this facility and to adjust the magnification of your data at anytime, you will have to use the ‘Zoom In’ and Zoom Out’ buttons, this might not be necessarily accurate to view the extent of the map.

The Radius Select Tool in MapInfo is a very useful tool that can be used to select features within a given circumference; ArcGIS on the other part does not have this option.

ArcMap comes with a preloaded feature which is ‘Select by Location’. ArcMap is very useful with extrapolating spatial data components GIS Users can use to answer various questions as viewed from (University of Glamorgan Blackboard, 2010). This allows spatial relationships to be defined between different datasets such as ‘Distance’, ‘Intersection’, ‘Containment’ and ‘Adjacency’. MapInfo does not have the tendency to identify these relationships.

With ArcMap, when layer properties are viewed you can click on the Symbology tab and Normalize a field. When analyzing statistical data, this is a very useful tool because the true identity of a ratio of one value over the other is really seen when it is divided or graduated over a field like Area Size of a particular location. MapInfo on the other hand does not have this facility to normalize a field over another.

In ArcMap [a window in ArcGIS where graphical features are loaded has a data and layout view which is very friendly because both can be switched instantly to enable you view what your design is like in the layout view.

MapInfo is easier to use in the sense that you can explore the buttons by just fiddling around and actually discover what each one does but more complicated in ArcGIS and you will need a user manual to get around.

MapInfo makes use of the American Standard Code for Information Interchange (ASCII) format for defining its workspaces and file formats. This is very instable geodatabase because when alterations are to be made to the saved work, it will have to be edited manually and can’t just be updated the way coverages, shapefiles and geodatabases can be done in ArcCatalog of ArcGIS.

Attribute Data in ArcGIS can be sorted out in ascending and descending formats, this can be very helpful in identifying records faster but with MapInfo, this is not practicable

The Label Button in the Main toolbar of MapInfo makes it easier to label features on a map manually but with ArcGIS, labels on a map will have to be done altogether by switching on the labels field in the label tab under the layer’s properties window.

MapInfo basically has a more efficient way of arranging labels; arrows can be indicated beside labels of different wards when the labels in that region are clustered together. This will reposition the ward that is clustered and drag it away before showing its label. ArcGIS on the other hand cannot attain this feat.

MapInfo is faster when it comes to making basic map templates but with the enriched graphical and mapping suites embedded in ArcMap, this can slow you down as to where to start from because the tools for making maps are too numerous.

The Graphic User Interface in MapInfo Design is way outdated and not compatible with recent Windows Operating System’s interface in terms of colour resolution.

Backward compatibility is not supported with ArcGIS as a mxd file [map file format for ArcGIS] saved in ArcGIS 9.3 will not open when launched with ArcGIS 9.1. Mapinfo on the other hand does not encounter this problem.

A major setback of MapInfo is its file formats. ArcGIS has different ways of arranging its files; file geodatabase – which consumes little space but also fast; personal geodatabase – which can be linked to Microsoft Access and the SDE geodatabase – which houses large datasets and can be presented to the public.

ArcMap is associated with projection issues; when layerfiles are added with a geographic coordinate system (GCS) and another is added with a projection coordinate system (PCS), the GCS automatically converts the PCS so both are aligned properly but when a layerfile with a different GCS is added, then projection issues arises but this is not so with MapInfo.

2.3 Analytical Functionality of ArcGIS 9.3 over MapInfo 10.5 Professional

In ArcGis, there are two fundamental icons in the Standard Toolbar that allows for easy access to a host of functions ArcGis provides. A screenshot of this is shown underneath as taken from ArcView 9.3 [excerpts from this report will be taken from here] Software developed by Environmental Systems Research Institute.

ArcCatalog

ArcToolBox

Fig 2.0

The ArcToolbox contains the Analytical tools that were discussed earlier in this report and a close look will be explored later but for now, we will navigate some of the powerful feature ArcCatalog itself has that gives it an edge over Mapinfo/Vertical Mapper.

ARCCATALOG

ArcCatalog is a Geographical Information System application that allows you to browse, manage and view geographical data as viewed from (ESRI,nd.)

ArcCatalog enables you to be able to view the properties of layer files [files which are added into an ArcMap window] and also to be able to explore its attribute table to know if it belongs to the same category of data layer you will want to consider executing a GIS project. It is very important to make sure that when data is collated, data of the same type are grouped together and share common attributes. This is termed a feature class and ArcCatalog possesses this quality to enable us organize our data. It provides three different ways of attaining this; either grouping them as geodatabases, shapefiles or coverages but before these are looked at extensively, a diagram below illustrates how data can be added to an ArcMap Window after it has been viewed from ArcCatalog. This is a simplified way of making sure that same datasets are worked with in ArcMap. However, with MapInfo this is not achievable-being able to view a dataset from another application before it is added to your MapWindow.

From the diagram underneath, the Catalog Tree allows you to connect to a folder where the existing data files lie and also to basically browse for data as Windows Explorer will function in a Windows Operating System. Layerfiles are also identified from this postion after which they are dragged and dropped into ArcMap [this is not attainable with MapInfo].

On the other hand, the Preview Pane as stated by ESRI (nd.) is a sophisticated workspace that allows you to view the contents of the folder and its geography. This is the where most of the analysis takes place before it is finally concluded if a layerfile is to be dragged and dropped into ArcMap. From this section, you can view the contents of a folder in a detailed format, preview its geographical structure or attribute table and also view its metadata which is information that describes a geographic dataset as ESRI (nd.) notes.

Catalog Tree Preview Pane Fig 2.1

ARC TOOLBOX: This boasts of a variety of analytical functions ArcGIS came with. From the Spatial Analysis tools, data management tools e.t.c. The ArcTool Box will be closely examined here to highlight its functionality over MapInfo.

Embedded into ArcTool Box under Conversion Tools is the Layer to KML and Map to KML Conversion. KML which stands for Keyhole Markup Language is a file format in ArcGIS which can be used to represent geographic data in an Earth’s Browser like Google Earth or even in Mobile applications like Google Map. MapInfo on the other hand does not support KML file format and maps displayed in MapInfo cannot be seen in a browser format.

The Editor toolbox which is part of the extensions that came with ArcGIS is very helpful in snapping buildings back to its rightful location in events of a gradual change or displacements caused due to time change or rapid urbanization in the area. Basically various functions can be performed with this powerful tool; from cutting of polygons, dragging vertices of buildings to a new location. MapInfo on the other hand does not boast of this tool.

The Line Generalization Tools which consists of Aggregate Polygon, Dissolve, Eliminate, Collapse Dual Lines to Center lines, Simplify Building etc are excellent tools in ArcGIS that can perform cartographic functions aimed at representing the layerfile on a much smaller scale. MapInfo cannot achieve this objective.

MapInfo has a better way of storing multiple topographical data i.e. points, lines and polygons can all be stored in a single file as viewed from (Geocommunity, n.d.) while ArcGIS on the other hand ArcGIS does not allow you to project points, lines and polygons on the same layer.

MapInfo has a Universal Translator tool which is very fundamental when it comes to converting different ArcGIS shapefiles into MapInfo file formats and vice-versa and while this conversion is taken place not distorting the original characteristics of the file.

MapInfo is compatible with Crystal Report extension which makes it easy to draw charts from your mapped data and also represent your mapped data in a report format making it easy for your viewers to have a glance at what information your map is portraying while ArcGIS on the other hand does not have crystal report extension.

With MapInfo, a clone view of the actual map on display can be replicated, this move can be very useful when the mapped data is to be represented twice in a layout format while with ArcGIS a new dataframe will have to be created before the layerfile is copied from its initial dataframe and pasted into the newly created dataframe before viewing it in the layout toolbar [multiple processes involved here with ArcGIS].

Layerfiles can be exported into PDF formats with ArcGIS but not with MapInfo

In the ArcTool box section of ArcGIS, you have the Analysis tools which are a much easier way to analysis mapped data. Clipping, merging and intersection of features in a layerfile can be achieved quickly however with MapInfo, this is not as straightforward.

ArcGIS comes in different licenses; ArcView, ArcEditor and ArcInfo [in order of their functionlaity]. ArcView has few extensions which are available while with MapInfo, you get all the basic extensions including those for Computer Aided Designs (CAD) for just a token. To get the ArcInfo Edition of ArcGIS, a lot of money is required.

MapInfo is more stable but ArcGIS is a lot more susceptible to bugs [software failures/crashes] and furthermore takes a whole lot more of system performance when performing functions like Spatial Density Interpolation i.e. the system tends to freeze.

As said earlier, ArcGIS has arccatalog which enables easier data management especially when large datasets are considered. Also, ArcCatalog can be very buggy as I experienced once that even after connecting to the folder that has your shapefile, you still cannot access its contents and will have to shut the program down and restart [very buggy!!!]

2.4 Vertical Mapper/Spatial Analyst&3D Analyst Comparison

2.4.1 3D Analyst: This is an extension available in ArcGIS basically for creating, editing and displaying objects or shapefiles with 3-dimensional surfaces. With the 3D Analyst, you can display grids, TIN [Triangulated Irregular Network] and 3D Shapefiles. Also, satellite imagery can be imported into the layerfile and displayed.

2.4.2 Spatial Analyst: This is an extension in ArcGIS that can be used for spatial analysis and modeling. Raster data can be queried and also a vector-raster analysis can be made.

2.4.3 Vertical Mapper: This is an extension available in MapInfo. It can be used for overlaying raster grids and visualizing the relationship between them.

Advantages and Disadvantages of Vertical Mapper as viewed from (Geocommunity, n.d.)

Vertical Mapper extension is cheaper than Spatial Analyst and 3D Analyst

It is easy to use and documentation is available which acts as a guide

It supports many data formats for importing

It is highly programmable

It allows you to easily import United States Geological Survey Digital Elevation Model (USGS DEM) and SDTS raster formats

It has an excellent support system in place because of its large user base

It processes large datasets at a glance

It can merge DEM files

It can export to USGS DEM

It cannot perform kriging [which is an interpolation of the value of a random field at any location by looking at the values around its vicinity]

Advantages and Disadvantages of Spatial Analyst & 3D Analyst as viewed from (Geocommunity, n.d.)

It is way costlier than Vertical Mapper to purchase these extensions

Calculations are executed rapidly

The documentation is not as elaborate as it is in Vertical Mapper

The Raster Calculator is a very fascinating tool to work with

When rotating a 3D scene, you can lose track of your positioning

Grids cannot be re-projected

You encounter problems when you want to print out from a Spatial Analyst modeling.

It is a challenge to import USGS DEM data

2.5 Spatial Statistical Functions in ArcGIS

One major breakthrough ArcGIS has over MapInfo is embedded in its ability to analyze spatial data by the abundance of a deluge of tools which is aimed at spatial statistical functions. It is imperative in viewing trends and patterns of a geographical data. They are grouped into 4 classes; Measuring Geographic Distributions, Analyzing Patterns, Modeling Spatial Relationships and Mapping Clusters.

2.5.1 Measuring Geographic Distributions: These tools here help us to be able to ask spatial questions about a geographical distribution and proffer answers. Such questions could be;

Where is the centre of crime spots within vicinity?

Are there any directional trends?

Are the features around the centre of crime spots dispersed or clustered and by how much?

From the ArcTool Box function in the Standard toolbar, spatial statistics tools is selected and then Measuring Geographic Distributions is expanded. From here, several tools are listed and the table below shows their names and the functions each performs

Tool

Function

Linear Directional Mean

This shows the mean of various set of vectors representing a geographic distribution

Mean Centre

Shows the centre of geographic features by way of computing its mean

Standard Distance

Looks at the rate at which distribution is located around the mean value of occurrences. It checks the how concentrated or how dispersed the features are.

Central Feature

This depicts the central point (feature) of any geographic distribution

Directional Distribution

This shows a pattern in relation to the distribution of features around the geographic mean and tells whether any directional trend is exhibited.

Applications of the Above Toolset

Mean Center

Fig 2.2

Looking at the above diagram as viewed from (Scott et al, n.d.), the mean center (Population) can be spotted by computing the mean value of population as seen in various counties of California in the United States for over a period of years and the drifting of these spots can be identified as the years passes by thereby movement in population growth extending to different counties observed. Channels (basic amenities) can now be provided in these areas to match the anticipated growth of population in these areas.

Central Feature: Looking at crime incidents in a particular area, the central spot of crime distribution can be identified and that way police patrol vehicles can be drafted in to curb crime.

Standard Distance: In a health context, this can be applied for instance to measure the distribution of cholera outbreak in an area and to estimate the length in km or miles to which this extends.

Directional Distribution: This can be applied in curtailing crime by looking at the directions of events of crime in a geographic distribution.

2.5.2 Analyzing Patterns: This is suitable for understanding spatial patterns and trends (Mitchell, 2005). The table below shows the various tools within and their functions

Tools

Functions

Average Nearest Neighbor

Computes the average distance between features based on an area

Spatial Autocorrelation

Determines how clustered, dispersed or randomly distributed a pattern is

Multi-Distance Spatial Cluster Analysis

Looks at how clustered or dispersed features are over long distances

High/Low Clustering

Looks at concentration of high and low values in a distribution

These toolsets can find its applications in the Health Sector especially the spatial autocorrelation tool.

A value called Moran’s index is to be calculated and a figure close to +1 shows a cluster in the distribution while a value close to -1 shows dispersion. Knowing these can aid a health specialist to detect whether there is a cluster in cholera outbreaks or it is being dispersed within a given location.

2.5.3 Mapping Clusters: This toolset is good at determining where clusters occur in a geographic distribution. The table underneath shows the various tools contained in it.

Tools

Functions

Cluster and outlier Analysis

Shows clusters of high and low values and the spatial outliers

Hot Spot Analysis

Identifies clusters of distribution with high concentration (hot spots) and those with low concentration (cold spots)

Its application can be found in the Government for instance a in the Fig below

Fig 2.3: Map showing clusters of high Poverty and Low Poverty in Ecuador as viewed from (Scott et al., n.d.)

Also, in a Dot Density Map showing Earthquake Distribution over a period of years; clusters of high earthquake activities can be shown as Hot spots while those of Low earthquake as Cold spots.

2.6 Case Studies showing functionality of ArcGIS:

2.6.1 Disaster Monitoring and Early-Warning System for Snow Avalanche Along Tianshan Highway (Liu et al. , 2009)

A critical look using a particular technique at this location is implemented using ArcGIS. It is aimed at warning the public of anticipated outcomes of snow avalanche. This is achieved by creating a Snow avalanche database and Snow avalanche danger analysis and a prototype put in place which interfaces with the live database access of these incidents and the model library recently created with ArcGIS. This system carries out warning information to the public and this entire configuration is set up using the Analytic Hierarchy Process (AHP) under the Environment Settings which is under ArcTool Box option.

2.6.2 Use of Geographical Information Systems in Epidemiology: A Case Study of Dilovas District (Geymen, 2010)

Dilovas District of Turkey was hit with massive urbanization in the 20th Century (second half of the year). Such activities involved setting up of industries on public land in which proper acquisition was not consented. As a result, activities from the industry (chemical combustion, radioactive emission) contributed to increased rate of cancer among its inhabitants. The Spatial Statistical Toolset of ArcGIS (as described earlier in this essay) is used to show the distribution of cancer cases and a comparison is done with the world’s statistics.

2.6.3 Digitizing, Preparing Application and Setting Plan by using GPS: A Case Study from Agricultural faculty Area of Tekirdag (Sisman, 2010)

The purpose of this study was to digitize, outline a survey plan and set up an agricultural faculty area with the aid of Global Positioning System (GPS). Three methods were used to take measurement of the surveyed area; an electronic planimeter, a theodolit and a GPS. Meanwhile the estate deed showed measurement of the area of study. These readings taken were transferred into ArcGIS using a Trackmaker software. 3D Analyst extension in ArcGIS processed the data which was transferred into the computer into 3-dimensional surfaces and a 3-dimensional view was projected with the help of Triangulated Irregular Network (TIN). A difference between the value estimated on the estate deed and those by the GPS readings were conspicuously visible and an accurate measurement from the GPS readings were however obtained.

2.7 Case Studies showing functionality of MapInfo

2.7.1 Geographical Information Systems-based pavement management system – Case Study (Medina et al., 1999)

This study proposed the use of MapInfo to manage a low-volume road pavement management system for a platform of Fountain Hills in Arizona, USA. This involved some steps; civil engineers provided a database of road construction works undertaken and their conditions and AutoCAD (an application MapInfo supports) mapping of the streets. The Road Surface Management System software was implemented and interfaced into a menu option inside MapInfo. When launched, it imports the maintenance works done on pavements and this is displayed as coloured maps after which a full analysis is prepared.

2.7.2 Construction of Regional Groundwater Environmental Quality Evaluation System (Wiu et al., 2008)

MapInfo is used here to create a regional underground water quality evaluation and management system. This was achieved by integrating MapBasic with MapInfo platform. The system put in place here also analyzed spatial and attribute data of the regional underground water.

3.0 Conclusion:

It will be unjust to conclude and say one software package is better over the other. A lot of factors will have to be considered as budget available, expertise of staff, training to be provided, job functions and responsibilities observed.

ArcGIS comes with so many extensions which can be very confusing and rarely used, however it is an excellent package when Analytical functions are to be performed. Also, it is very expensive to purchase a full license key with all the extensions and training of staff is exorbitant.

MapInfo on the other hand boasts of its simplicity, scalability, fewer extensions which are cheaper and it is an excellent tool in site optimization planning which has its application in telecommunications, transportation etc