Gothos

There was an interesting article in the New York Times today about neighborhoods in New York that typically get under-counted in the Census. These include areas with high immigrant populations as well as places that have had new construction since the last census, as the buildings haven’t been added to the Census Bureau’s master address file.

What the article didn’t mention is that CUNY’s Center for Urban Research has created a great online ap called the Census 2010 Hard to Count mapping site. The site is built on the Census Bureau’s Tract Level Planning Database, which identified twelve population and housing variables, such as language isolation, recent movers, poverty, and crowded housing, that were associated with low mail response in the 2000 Census. This tool was designed to help Census reps, local government officials, and community activists identify traditionally under-counted areas to insure a more complete count this time around.

The database is national in scope, and you can easily map tracts for a particular state, county, city, metro area, or tribal area, and you can search for an area using an individual address. The map is built on a Google Maps interface, and zooming in will change the units mapped from larger units (states, counties, etc) to tracts. You can easily select one of the twelve variables color-coded in the menu to the left of the map, or a Hard to Count index of all the variables.

The fall semester is here, and I’m about to start teaching the class I mentioned in my last post (an information studies course on geographic information). I thought I’d share my reading list and try out the Open Book plugin. I chose my readings based on: my particular audience (undergraduate students from many disciplines with little or no background in geography), relevance (materials appropriate in a hybrid information studies / geography course), cost (wanting to assign the students a single textbook that’s reasonably priced and covers all the bases, and will supplement with other readings), and copyright (staying within the bounds of fair use by not assigning too much from a single work). Here goes:

I decided to go with Krygier and Woods Making Maps as my assigned text book. Since cartography is a visual and technical art, I thought it made sense to use a book that relies on visuals for explanations rather than text. It’s approachable, particularly for my students who won’t be coming from a geography background, affordable, wonderfully quirky, and covers all of the essentials of the geographic framework and map interpretation and design independent of specific GIS software.

I’m using the first chapter of Cresswell’s book as a succinct introduction to how individuals define places, but would recommend the rest of the text for classes that cover geographic concepts and methods.

I’m assigning the second and third chapters of Hill’s book. The second chapter, which discusses how people process, store, and use geographic information is the best summary of this topic that I’ve ever seen, and the third chapter is a good overview of the different types of geographic objects. As a librarian-geo nerd, I love the chapters that deal with coordinate metadata and gazetteers, but won’t be using them in this class.

This is an urban planning / design classic, and I’ll have my students read the summary of Lynch’s city elements (based on his research, Lynch proposed that people mentally break the urban environment down into five types of elements in order to organize and navigate the city: paths, barriers, districts, nodes, and landmarks).

This is the only traditional textbook that I’ll be borrowing from (I actually used it when I was a Freshmen, way back when). While I’m using the previous three books to discuss egocentric places, or how we as individuals conceive of place, I’m using the first chapter of this book to give the students an overview of geocentric places – the formal, defined hierarchy of places that exist in the world – and to introduce them to the concept of regions.

This has become a modern classic and I almost assigned it as a second textbook. I am assigning the chapter on maps for propaganda as a background to our discussion on map interpretation and communication, and will later use the chapter on census maps to talk about the effects of data classification and choice of enumeration units.

This is the only software book that I’ll be using chapters from, so the students have some formal guide for using QGIS (in addition to the QGIS documentation). I’m using the chapters on vector and raster data.

This concise, excellent book deals strictly with the concepts and principles behind GIS. I’m using the chapters on spatial search and geoprocessing, but would recommend the entire book for any GIS course, novice to advanced.

In addition to chapters from these books, I’ll also be using:

• “Revolutions in Mapping” by John Noble Wilford, National Geographic Feb 1998 – a great overview of the history of cartography
• USGS GIS poster – if there is such a thing, this is a “web classic” and an accessible intro to GIS
• One article from a scholarly journal and one article from a mass market magazine to illustrate how geographic research is covered and used
• And for shameless self-promotion, I summary I wrote about US Census data – In Three Parts

Finally, an honorable mention:

If I was teaching an introductory GIS course in a geography or earth sciences department, this is certainly the book I would use, and for those of you in that boat I’d recommend checking it out. It does an excellent job of covering GIS principles without being software specific, contains exercises at the end of each chapter, and is well written and affordable. Since the scope of my course is broader than GIS and my audience more general and diverse, I opted to leave it out (but may still assign a chapter).

I wrapped up a project recently where I created some thematic maps of 2005-2007 ACS PUMA level census data for New York State. I decided to do all the mapping in open source QGIS, and was quite happy with the result, which leads me to retract a statement from a post I made last year, where I suggested that QGIS may not be the best for map layout. The end product looked just as good as maps I’ve created in ArcGIS. There were a few tricks and quirks in using the QGIS Print Composer and I wanted to share those here. I’m using QGIS Kore 1.02, and since I was at work I was using Windows XP with SP3 (I run Ubuntu at home but haven’t experimented with all of these steps yet using Linux). Please note that the data in this map isn’t very strong – the subgroup I was mapping was so small that there were large margins of errors for many of the PUMAs, and in many cases the data was suppressed. But the map itself is a good example of what an ACS PUMA map can look like, and is a good example of what QGIS can do.

• Inset Map – The map was of New York State, but I needed to add an inset map of New York City so the details there were not obscured. This was just a simple matter of using the Add New Map button for the first map, and doing it a second time for the inset. In the item tab for the map, I changed the preview from rectangle to cache and I had maps of NY state in each map. Changing the focus and zoom of the inset map was easy, once I realized that I could use the scroll on my mouse to zoom in and out and the Move Item Content button (hand over the globe) to re-position the extent (you can also manually type in the scale in the map item tab). Unlike other GIS software I’ve experimented with, the extent of the map layout window is not dynamically tied to the data view – which is a good thing! It means I can have these two maps with different extents based on data in one data window. Then it was just a matter of using the buttons to raise or lower one element over another.

• Legend – Adding the legend was a snap, and editing each aspect of the legend, the data class labels, and the categories was a piece of cake. You can give your data global labels in the symbology tab for the layer, or you can simply alter them in the legend. One quirk for the legend and the inset map – if you give assign a frame outline that’s less than 1.0, and you save and exit your map, QGIS doesn’t remember this setting if when you open your map again – it sets the outline to zero.

• Text Boxes / Labels – Adding them was straightforward, but you have to make sure that the label box is large enough to grab and move. One annoyance here is, if you accidentally select the wrong item and move your map frame instead of the label, there is no undo button or hotkey. If you have to insert a lot of labels or free text, it can be tiresome because you can’t simply copy and paste the label – you have to create a new one each time, which means you have to adjust your font size and type, change the opacity, turn the outline to zero, etc each time. Also, if the label looks “off” compared to any automatic labeling you’ve done in the data window, don’t sweat it. After you print or export the map it will look fine.

• North Arrow – QGIS does have a plugin for north arrows, but the arrow appears in the data view and not in the print layout. To get a north arrow, I inserted a text label, went into the font menu, and chose a font called ESRI symbols, which contains tons of north arrows. I just had to make the font really large, and experiment with hitting keys to get the arrow I wanted.

• Scale Bar – This was the biggest weakness of the print composer. The scale bar automatically takes the unit of measurement from your map, and there doesn’t seem to be an option to convert your measurement units. Which means you’re showing units in feet, meters, or decimal degrees instead of miles or kilometers, which doesn’t make a lot of sense. Since I was making a thematic map, I left the scale bar off. If anyone has some suggestions for getting around this or if I’m totally missing something, please chime in.

• Exporting to Image – I exported my map to an image file, which was pretty simple. One quirk here – regardless of what you set as your paper size, QGIS will ignore this and export your map out as the optimal size based on the print quality (dpi) that you’ve set (this isn’t unique to QGIS – ArcGIS behaves the same way when you export a map). If you create an image that you need to insert into a report or web page, you’ll have to mess around with the dpi to get the correct size. The map I’ve linked to in this post uses the default 300 dpi in a PNG format.

• Printing to PDF – QGIS doesn’t have a built in export function for PDF, so you have to use a PDF print driver via your print screen (if you don’t have the Adobe PDF printer or a reasonable facsimile pre-installed, there are a number  of free ones available on sourceforge – PDFcreator is a good one). I tried Adobe and PDFcreator and ran into trouble both times. For some reason when I printed to PDF it was unable to print the polygon layer I had in either the inset map or the primary map (I had a polygon layer of pumas and a point layer of puma centroids showing MOEs). It appeared that it started to draw the polygon layer but then stopped near the top of the map. I fiddled with the internal settings of both pdf drivers endlessly to no avail, and after endless tinkering found the answer. Right before I go to print to pdf, if I selected the inset map, chose the move item content button (hand with globe), used the arrow key to move the extent up one, and then back one to get it to it’s original position, then printed the map, it worked! I have no idea why, but it did the trick. After printing the map once, to print it again you have to re-do this trick. I also noticed that after hitting print, if the map blinked and I could see all the elements, I knew it would work. But, if the map blinked and I momentarily didn’t see the polygon layer, I knew it wouldn’t export correctly.

Despite a few quirks (what software doesn’t have them), I was really happy with the end result and find myself using QGIS more and more for making basic to intermediate maps at work. Not only was the print composer good, but I was also able to complete all of the pre-processing steps using QGIS or another open source tool. I’ll wrap up by giving you the details of the entire process, and links to previous posts where I discuss those particular issues.

I used 2005-2007 American Community Survey (ACS) date from the US Census Bureau, and mapped the data at the PUMA level. I had to aggregate and calculate percentages for the data I downloaded, which required using a number of spreadsheet formulas to calculate new margins of error; (MOEs). I downloaded a PUMA shapefile layer from the US Census Generalized Cartographic Boundary files page, since generalized features were appropriate at the scale I was using. The shapefile had an undefined coordinate system, so I used the Ftools add-on in QGIS I converted the shapefile from single-part to multi-part features. Then I used Ftools to join my shapefile to the ACS data table I had downloaded and cleaned-up (I had to save the data table as a DBF in order to do the join). Once they were joined, I classified the data using natural breaks (I sorted and eyeballed the data and manually created breaks based on where I thought there were gaps). I used the Color Brewer tool to choose a good color scheme, and entered the RGB values in the color / symbology screen. Once I had those colors, I saved them as custom colors so I could use them again and again. Then I used Ftools to create a polygon centroid layer out of my puma/data layer. I used this new point layer to map my margin of error values. Finally, I went into the print composer and set everything up. I exported my maps out as PNGs, since this is a good image format for preserving the quality of the maps, and as PDFs.

I recently went through my pages of suggested links for data and resources to update and clean them up. I’ve included many of the cool resources I’ve discovered since I started writing this blog, which ended up in individual posts but not in these pages. I went over the resources page in particular, to try and classify the reference materials, tools, and software into useful categories rather than just having one large blob of stuff.

The GDAL / OGR tools are an open source, cross platform, command-line toolkit that can be used for viewing GIS metadata, performing attribute queries, and converting file formats, among other things. It can also be used for transforming coordinate systems and projections for GIS files. I’ll demonstrate in this brief tutorial how to accomplish this using the OGR tools, which are for vector based GIS. The raster based GDAL tools work in a similar fashion.

Viewing basic coordinate system / projection info:

ogrinfo -al -so world_wgs.shp

Where ogrinfo is the name of the tool, -al is a switch to get detailed info about the layer, -so is a switch to display summary info, and world_wgs.ship is the name of our file. Run that command and we’ll get something that looks like this, with info about the features, coordinate system, and attribute fields of our shapefile:

INFO: Open of `world_wgs.shp’
using driver `ESRI Shapefile’ successful.

Layer name: world_wgs
Geometry: Polygon
Feature Count: 243
Extent: (-179.808664, -89.677397) – (179.808664, 83.435942)
Layer SRS WKT:
GEOGCS["GCS_WGS_1984",
DATUM["WGS_1984",
SPHEROID["WGS_1984",6378137,298.257223563]],
PRIMEM["Greenwich",0],
UNIT["Degree",0.017453292519943295]]
CNTRY_NAME: String (254.0)
FIPS_CNT_1: String (254.0)
ISO_2DIGIT: String (254.0)
ISO_3DIGIT: String (254.0)
STATUS: String (254.0)
COLORMAP: Real (18.6)
CONTINENT: String (254.0)
UN_CONTINE: String (254.0)
REGION: String (254.0)
UN_REGION: String (254.0)

Convert coordinate systems supported by EPSG

GDAL / OGR and most of the open source GIS software supports projections and coordinate systems that are part of the EPSG library. If you want to do a conversion between two coordinate systems and they are both supported by EPSG, you just have to reference the EPSG code that’s used to identity the system that you want to project to. You can look up codes using spatialreference.org.

Let’s say we want to convert our shapefile that’s in WGS 84 (common lat and long) to NAD 83 (used frequently in North America):

ogr2ogr -t_srs EPSG:4269 world_new.shp world_wgs.shp

Where ogr2ogr is the name of the tool, -t_srs is the command for transforming from one coordinate system to the other, EPSG:4269 is the code that identifies the coordinate system we want the new file to have – NAD83, world_new.shp is the name of the output file that will have the new projection that we want, and world_wgs.shp is our input file. If you run the command and get no error message, you’re in good shape. Just run the ogrinfo command on the new file to verify that it’s been re-projected.

Convert coordinate system not supported by EPSG

The EPSG library is extensive, but doesn’t contain everything, particularly some global and continental map projections. GDAL / OGR can still do the job, but you’ll have to provide the tool with the proper frame of reference since the EPSG library doesn’t have the info. Let’s say we want to project our WGS file to the Robinson Projection, which is not part of EPSG.

First, go back to spatialreference.org and search for Robinson. Its ID code is ESRI 54030 – not part of the EPSG library. Click on the link for the projection to open its window. You’ll be able to look at the projection data in a number of standard file formats. Select OGC_WKT from the list, and it will open the text in a new window, showing you the parameters of that projection. In your browser, go up to file, save as, and save the file as robinson_ogcwkt.txt in the same directory as the shapefile you want to reproject.

Now that you have the projection info stored in the text file, run the following command to make the conversion:

ogr2ogr -t_srs robisnon_ogcwkt.txt world_rob.shp world_wgs.shp

It’s the same command as our previous one, except that you’re referencing the text file with your data instead of an EPSG code.

Define an undefined coordinate system

If you run the ogrinfo command and your coordinate system is undefined, you should define it before doing anything else, and you must define an undefined projection before converting to another projection. Look at the metadata that came with you file or go back to the source to figure out what it is. For example the US Census Bureau Generalized Cartographic Boundary Files for 2000 are in NAD83 according to their metadata, but the files lack a projection definition.

To define one, use the following command:

ogr2ogr -a_srs EPSG:4269 states_nad83.shp states_unknown.shp

The only difference here is the -a_srs command is used to assign a coordinate system to a file – the rest of the parameters are the same. If you’re defining a non-EPSG projection, use the same method from the previous example – download a definition file from spatialreference.org and use the file name in place of the EPSG code.

More help and where to download:

UC Santa Barbara NCEAS and the UC Davis Soil Lab both have short tutorials and sample commands of GDAL / OGR.

If you want to thumb through the world’s map projections, the folks at radicalcartography have a nice projection reference page with visuals and brief descriptions.

Visit the GDAL / OGR page for downloading, or if you’re a Windows or Mac user, you can download QGIS and GDAL / OGR together from the QGIS download page. Linux users can get GDAL / OGR via your package handler – depending on your distro, you may have it already.

A little while ago I posted a text file with geographic centroids (centers) for each of the world’s countries. The reason why I put this together was that I wanted to test the data defined labeling features in QGIS. While automatic labeling in QGIS isn’t so hot (overlapping labels, multiple lables for each polygon), there are some powerful features for storing and referencing columns for annotation within the attribute table of shapefiles. One of the neat features is the ability to place labels based on coordinates stored in the attribute table.

The first step was to take the centroids file and join in to a shapefile of the worlds countries based on a common ID field, in this case FIPS country codes. QGIS doesn’t support table joins directly, but you can accomplish this with a good plugin called fTools, which includes a lot of additional and useful features. The instructions for getting fTools up and running are available on the fTools website; the installation doesn’t require you to download any files, you just handle everything through the QGIS plugin manager (if you have trouble seeing the plugin manager or getting fTools to appear, check to make sure that you have python installed on your machine). Once fTools is up and running, you’ll see a Tools dropdown menu next to your other menus – drop it down, select data management tools and join attribute tables. You’ll get a dialog box asking which shapefile and field you want to join and which shapefile or table you want to join to it. The plugin only supports joins from other shapefiles and dbf tables, so you have to save the save the country centroids text file as a dbf before you do the join (you can do this in Calc or a pre-2007 version of Excel). These aren’t dynamic joins; fTools will create a new shapefile with the table fields attached.

Once the join is complete, you can add the new shapefile with the new fields, click on the layer, and navigate to the labels tab. Hit the checkbox to turn the labels on, select the field that contains the label in the dropdown box at the top, then select data defined position from the menu below. You’ll see a new series of dropdowns on the right, and you can select your longitude column for the X coordinate and latitude column for the Y coordinate. Hit OK, and voila! You’ll have labels that are centered in the middle of each country.

Of course, the label placement will not be perfect in every case. There will be label overlap in areas with small countries, areas with many countries clustered together, and with countries that have long names. The scale and size of the font will also be a factor, and placing the country name in the center is not always ideal for small island nations. However, you can easily change the label placement by going into an edit mode and changing the coordinates in the attribute table to get optimal placement. You can mouse over the map and use the coordinate information that’s displayed beside the scale in the lower right-hand corner of the window to determine which coordinates are most optimal for a given situation. If you produce several maps at the same area and scale, you can use the same settings over and over again. You can also globally change the placement of all the labels using some of the other label options, such as placing all labels above or to the top-right of the centroid.

Now in order for all of this to work, the coordinates in the country centroid file must be in the same coordinate system as the shapefile. Since the country centroid file uses basic latitude and longitude, I was able to do this with a shapefile that was in the basic WGS 84 geographic coordinate system. If you’re using a different geographic coordinate system or a projected coordinate system, you’ll have to convert the coordinates in the centroid file to match that system. I haven’t delved into this too deeply yet, but there are a number of free tools that you can download that should do this – one of them is called GEOTRANS, and it’s available for free download from the NGA. It can handle batch transformations of coordinate data stored in text files, and supports conversions to several different geographic and projected systems.

QGIS Label Placement With XY Coordinates

I just added a new resource and updated another one on the resources page. I put together a file that contains the centroids (geographic centers) of all of the countries in the world, plus a few territories and dependencies. The centroids are in latitude and longitude coordinates based on WGS 84 in two formats: decimal degrees and degrees / minutes / seconds. It’s a tab delimited text file that you can open or import into any spreadsheet or database program. Each record is uniquely identified by a FIPS 10 code.

I downloaded most of the data from the NGA’s GeoNames Server (GNS). I blogged about the GNS awhile back, pointing out that you could query this gazetteer for individual places or you could download files that have all the features for each country in the world. While it took some time to figure out, you can actually take a middle road and query the database for specific categories of features that you can download. I used the text-based search and the links on the left side of the screen actually open different input boxes that you can use to query or exclude data. I managed to query top-level administrative units (countries) and to exclude most variant country names. After I downloaded the file, I still had to go in and do some clean-up, and I had to go back and get countries I missed by hand – these were mostly dependencies and territories that were excluded based on the search I did (Greenland, French Guiana, Netherlands Antilles, and a number of others).

Then I realized that the GNS excludes the United States and all of its territories. So, I went over to the USGS Geographic Names Information Service (GNIS) and grabbed the data for the US territories. The GNIS is simpler to navigate and you can download records pretty easily. They didn’t have a record for the United States as a whole, so I had to go over to the Census Bureau to get coordinates for the US centroid.

I brought all of these records into one file and placed it on the resources page for download, along with some metadata to describe it. Why would you want to use this stuff? You can use if for basic distance calculations, or as a annotated label field for label placement in GIS. More about that in my next post.

I also updated the country code cross-reference file that I took from the CIA World Factbook. You can use this as a bridge table to relate tables that use different identifiers. So if you wanted to join the fips-based centroid file to an iso-based shapefile of countries, you can join the centroids to the bridge first based on fips, and then that new table to the shapefile based on iso.

This is kind of a follow-up to my last post – the Social Explorer, a great interactive mapping site that allows you to map US Census data, has added the 2005-2007 American Community Survey data to their site at the PUMA level. This is the smallest geographic area that is available for recent data, until we get to the 2010 Census and 2010 ACS. At this point you can look at total population, race, and Hispanic ethnicity. It looks like you can make maps, but you can’t export the data unless you subscribe to the full version.

The Social Explorer allows you to map a wide selection of decennial census data all the way back to the 1790 census (they have a partnership with NHGIS, which provides historical data and boundary files for free download with registration). Tract-level data is available back to 1940. While you can map the data, and you can generate slideshows and download static maps as image files, you can only generate reports for the 2000 census. In order to get full access for report generation and other features, you’ll have to subscribe (or find access to a library that does).

Social Explorer also works with ARDA (Association of Religious Data Archives) to create maps of county-level religious affiliation (since the US Census does not collect this data by law). Of all the interactive mapping sites I’ve seen, the Social Explorer is one of the slickest and easiest to use.

I’ve been on an open source GIS tear this month, so in this post I’ll wrap up some odds and ends:

• There is a project called Sextante, which is essentially an open source ArcToolbox for gvSIG. It adds a lot of geoprocessing and analysis functions and is pretty easy to install. There are 200 + tools in the box, but for some reason not all of them are active. I’m not sure why this is the case, but haven’t poked around much to find out.

• There are also a number of extra plugins for QGIS that are available through the QGIS wiki under PluginRepository; they include plugins that add more symbolization and that make table joins possible. Haven’t had a chance to try this yet either, but it sounds like these extras could make QGIS a lot more viable as a thematic mapping option.

• I found out about the QGIS plugins from this article, which offers a good overview of QGIS. The article also discusses one of the other shortcomings of open source GIS – the lack of a support for a simple, desktop geodatabase similar to the Microsoft Access personal geodatabases. PostGIS is certainly powerful and there has been a lot written about it, but a server based geodatabase is not always the best solution, particularly for small, stand-alone projects. There is a cool project called Spatiallite, where someone has created geographically enabled SQLite databases (which are small, stand alone dbs). You can export shapefiles to them, or simply view and edit the attributes in a shapefile via a virtual connection. Based on what I’ve looked at thus far, you can access SQlite databases directly in GRASS and when using GRASS datasets via QGIS, but I haven’t been able to connect to a SQlite db with the other software I’ve looked at – it’s just not supported yet.

• In researching open source GIS, I’ve looked at a book specifically on GRASS, Open Source GIS: A Grass Approach, as well as two books on web mapping (GIS for Web Developers: Adding ‘Where’ to Your Web Applications and Web Mapping Illustrated: Using Open Source GIS Toolkits)which cover GDAL and OGR, QGIS, GIS servers, PostGIS and PostgreSQL, and a few other tools. There is a book that’s recently been published that focusses specifically on Open Source Desktop GIS – Desktop GIS: Mapping the Planet with Open Source Tools. I pre-ordered a copy on Amazon that was supposed to ship in Mid September, but is now being delayed until late October. Based on the table of contents it looks pretty thorough and covers many of the choices I listed in my previous post, and I’m looking forward to its arrival.

Last week I shared my adventures evaluating open source software. Why bother looking at alternatives to ArcGIS? There are significant barriers of entry to ArcGIS. Whenever I give an introductory GIS presentation to anyone, I inevitably have to answer the question of “How can I get access to this software?” Inevitably, the answer is you have to spend a lot of money, or if your institution already has a subscription, you need to go through a lengthy process to get access.

• Price. A single, stand-alone copy of ArcView costs $1500. Not only is that prohibitively expensive for me, it’s impossible for students. Which means that students who are taking a GIS class have to use the software in a computer lab on campus to complete assignments. This is not always convenient for many students, and is particularly problematic where I work since we are primarily a commuter campus.

• License limitations. If you’re running Arc through a central license server, PCs have to be connected to the server through a hardwired connection – no wireless. Our library has a laptop checkout program for students which would give students an alternative to using a computer lab. But not being able to install the software on a laptop eliminates this possibility. It also makes it a pain for me to give presentations, as I always have to make sure that the room I’ll be presenting in has the software. My short term solution is to use an eval copy on a laptop. You can purchases USB keys that have the license info on them, but if you work in a large, complex academic or government setting, getting one can be a challenge. And every year we have to go through the process of getting the license renewed.

• Installation and Bugs. As Arc users know, installation can be time consuming, particularly since you can’t have two versions of Arc installed concurrently – you have to uninstall one before installing the new one. And how many service packs have been issued for version 9.2? Six. IT people love it when they have to install fixes in a dozen labs / classrooms in the middle of a semester, particularly when they have to do it 5 or 6 times a year. In reality, we skip several service packs and live with the bugs.

• Forced Obsolescence. This is particularly aggravating. Every year or two, we all have to go through the ritual of making an upgrade, which involves time consuming un-installation and installation. And you need to make sure that different branches of your organization that use GIS are on the same page, otherwise you’ll run into incompatibility issues (like when mxd files created in version  9.2 don’t work in 9.1).

• Cross platform. I run a linux box at home and occasionally would like to take my work with me. There are a number of students and faculty members at my school who are ardent Mac users. But ArcGIS runs only on Windows.

The open source alternatives are free, easy to install (usually), can be installed anywhere without restrictions, the software doesn’t expire, and upgrades are a rather simple affair. The obvious downside is that none of them have the power, scope, or usability that ArcGIS has. At least, not yet.