In+ersec+ion for Spatial People

I guess this would normally not be major news, but since a lot of iPhone users rely on it and that alternatives like Apple Maps and Blackberry Maps have not impressed the press so far, here it is: Google Maps for iOS version 1.1 has been released, but no iPad compatibility yet.

MacRumors informs about it: "What's New in Version 1.1:

• Search your Google Contacts; sign in to have your saved addresses show up when you search for friends and family by name.
• Quickly search for local places by selecting popular categories such as restaurants, bars, cafes, gas stations, etc.
• Choose between Kilometers or Miles for your preferred distance units.
• Note that some features may not be available in all countries."

You can now register to the FOSS4G 2013 conference.

The details: "There are three things you will need to plan:

• Which conference package do I want to book – Full, Day or Student?
• Which extra items do I want to book – workshops, icebreaker, closing party?
• Where am I going to stay – hotel on site, university accommodation, somewhere else?

Details of all the options are shown here. Note that the accommodation options are available once you’ve ticked your registration options checkbox(es), so you don’t need to book accommodation separately. It’s easiest to pay by credit card but if your organisation requires an invoice to pay you can tick that box when you register and we will send you an invoice.

• Please note that you must pay the full amount in £ sterling including any bank charges. 
• Invoices must be paid within 14 days of receipt to secure your room reservation and delegate place.

Early Bird prices are available until 31st May 2013 but we recommend booking as soon as you can as there are only a limited number of hotel rooms on the site."

Slashgeo is a proud media partner of FOSS4G 2013.

Still catching up, here's the recent open source geospatial news.

New software:

• VIa OGD, an easy to use website, OSM2GIS to directly download OpenStreetMap data in GIS formats such as shapefiles and kml
• MapTiler.org (mentioned in 2009), which is an open source map overlay generator for Google Maps / Earth and a GUI for GDAL2Tiles, now has a free Mac App Store version

Software updates front:

• Version 6.5 of the OSGeo-Live GIS software collection has been released, including 50 quality geospatial open source applications installed and pre-configured
• There's Leaflet.draw 0.2 released, and as you can guess it's for drawing/editing vectors in Leaflet
• Via UD, the color advice for cartography, ColorBrewer 2.0 has a no-flash version now
• Updated, MapStore 1.1.0 released
• Also available, GeoServer 2.2.5 released
• And so is GeoTools 8.7 Released
• Another one, ImageI/O-Ext 1.1.6 Released

Everything else:

• Here's an entry on the OSGeo Board priorities
• Related, a nice graph of the Moments in the History of OpenStreetMap
• Hyper-local data and news tool Everyblock closed, and it's open source code will continue as the OpenBlock Project, related, DM shared an article named OpenBlock Rural Finds Three Key Audiences for Open Data
• We love numbers right? At the beginning of last month was a user test between JTS Union VS ArcGIS Dissolve, result: 25 seconds vs 1.5 second in favor of the open source JTS
• Probably of interest to some of you, an entry on Optimizing OpenLayers for Mobile Applications
• DM shares an article named [U.S.] FedGeoDay: Advocating for Open Source, the summary: "FedGeoDay, held in Washington, D.C. this past week, can best be described as an advocacy forum for open source geospatial technology and data. Some of the leading organizations, government agencies and companies invested in open source tech sponsored the conference."
• Another article from the same source, The Arches Project: Turning Open Source GIS into a Heritage Inventory and Management System
• And a last article from DM, Palantir: An Open Source Development Success Story, which is really about leveraging PostGIS, the summary: "In late 2007 Palantir launched Gotham, a new geospatial and comprehensive analytics platform designed to meet the challenges of their vast array of customers. This article provides more information on Gotham that enables data integration, search and discovery, knowledge management, secure collaboration, and algorithmic analysis across a wide variety of data sources."

Catching up last month's geonews, here's a 5-parts series named Why Map Portals Don’t Work, here's Part II, Part III, Part IV, Part V.

From the intro: "[...] we’ll lay out some major drawbacks of standard web portals as well as suggest a few alternatives along the way.  While the baseline scenario I have in mind are public-facing government mapping portals, those rolling corporate intranet solutions would do well to take heed."

Some quotes taken from the entries, but go read the full 5 entries, it's worth:

• No one has widely circulated their own web metrics that shine a more positive light on map portals
• Problem #1: Map Portals Over-Focus on the Map, Under-focus on Text-Based Search and Discovery. Takeaway #1: Users Want and Need a Large, Obvious, Auto-Complete Text Box to Drive Search & Discovery
• Too many choices are psychologically debilitating and make people less happy (cue the TED talk). So yeah, your map portal has too many layers, leaving your users psychologically debilitated and unhappy
• Problem: Multiple map layers make it difficult to elicit a user’s intent and vastly overestimate the public’s interest in figuring out how to manipulate the map display
• Cures for Layerrhea:  a) break out most important layers into single-topic maps; b) provide data downloads for power-users; c) roll your own basemap with supporting, contextual layers baked-in

• Because if you are building any public-facing interface you have exactly four requirements: FAST  •  INTUITIVE  • INFORMATIVE  •  FAST

• The primary use of maps is quick information retrieval, NOT deep interaction with map interfaces
• The greatest recent improvement in map interactivity has been the work Mapbox has done with UTFGrid (interactive demo here) [this is a shame, I admit, that we never mentioned before UTFGrids on Slashgeo]
• Icon-laden toolbars are a desktop thing, not a web thing

I have a lot of geonews to catchup. You'll get everything that's pertinent (at least from my point of view ;-), but just a bit later than usual. Thanks for your patience!

Here's the recent Google-related geonews. Nothing major, but several interesting items.

From official sources:

• The first update to the Google Maps SDK for iOS
• Google informs us that Ski Resorts are now on Google Maps

From other sources:

• The GEB informs us that Google released 3D imagery in Berne (Switzerland), Anaheim (California) and other cities around the world
• Ogle Earth has an entry named Reconstructing the Chelyabinsk meteor’s path, with Google Earth, YouTube and high-school math
• Related, the GEB has an entry named Mapping meteor impacts
• Still the same source a book named "Google Earth and Virtual Visualizations in Geoscience Education and Research"
• The GEB shares a kmz to watch U.S. watersheds in Google Earth
• The GEB reminds us that we can animate GPS tracks in Google Earth
• You're an Olympics fan? Previewing the 2014 Winter Olympics in Sochi
• If you prefer Grand Prix racing, Ride along GP tracks from all over the world
• There has been games for Google Earth for a while, but now we're talking about multiplayer games: Two player driving shooter game in Google Earth

Understanding Simple Features

Introduction

Simple features are the basic building blocks of a simple vector based GIS. This article provides you with a simple definition of simple features and walks you through the conceptual design of a couple simple feature types.
We have two (2) regular features in Digital Surveying Magazine that deal almost exclusively with vector based GIS. The first of these regular features, entitled “JUMP Into GIS”, showcases the application of open source desktop GIS program OpenJUMP to real world GIS projects. The second of these regular features, entitled “Spatial Super Models”, teaches you how to design simple vector GIS data models, or implementation blueprints.
The information in this article will give you the foundation you need to understand the articles in these two (2) regular features of Digital Surveying Magazine.
We will begin our article by providing you with a basic definition of simple features.

A Basic Definition of Simple Features

What is a simple feature in the context of a discussion about vector GIS?
I have personally found this definition is helpful:
A simple feature is the digital representation of a real-world geographic feature in a GIS.
We can expand our basic definition of a simple feature with this additional information:
A simple feature has two primary elements. The first is a geometry used to represent the shape and location of the geographic feature. The second is a set of basic data attributes that describe the geographic feature’s non-spatial characteristics.
We can further increase our understanding of simple features by considering the Simple Feature Type.

Simple Feature Types

A simple feature type defines a set of requirements that all simple features belonging to that type must obey. They are essentially an organizational tool to help classify simple features.
The most important set of requirements defined by a simple feature type are the data types of the simple feature’s geometry and set of attributes.
These concepts will become more clear with a couple of concrete examples.
Let’s conclude our article with those two (2) examples.

Example #1: Modeling Land Parcels as Simple Features

In our first example we’ll imagine we are building a GIS to manage survey data about land parcels.
What geometry type should our land parcel simple feature type define for land parcel simple features?
A polygon seems like the geometry data type choice that makes the most sense for this simple feature type.
What non-spatial attributes would a land surveyor like to know about a land parcels? What data types would we use to model those attributes?
Most surveyors would be interested in the following attributes:

1) Identity of the most recent vesting grant deed.
2) Tax assessor parcel number.
3) Identity of the written instrument that created the parcel (survey map or deed).

What data types would we use to store these attributes for each simple feature? We would likely use a simple text value or numeric value for each of these attributes, depending on how the values are represented.
Diagram #1 shows a graphical representation of our land parcel simple feature.

Example #2: Road Segment

In our second example we’ll imagine we are building a GIS for a local City road maintenance department.
What geometry type should our land parcel simple feature type define for road segment simple features?
A linear geometry like a simple line segment seems like the geometry data type choice that makes the most sense for this simple feature type. (Depending on the map scale, you might also use polygons to represent the actual footprint of a road segment.)
What non-spatial attributes would a maintenance supervisor like to know about a road segments? What data types would we use to model those attributes?
A road maintenance supervisor would be interested in the following attributes:

1) The width of the physical road surface.
2) The paving material type.
3) The date of the last maintenance activity on the segment.
4) The type of maintenance activity last performed.

What data types would we use to store these attributes for each simple feature? We would likely use a simple numeric value for the width attribute, simple text value for the paving material type, a date data type for the third attribute, and a simple text value to identify the type of the maintenance activity last performed.
Diagram #2 shows a graphical representation of our land parcel simple feature.

Conclusion

This article provided you with a basic definition of simple features, explained the requirements put into place by a simple feature type, and looked at two (2) examples of how simple features could be designed.
Future articles in the Digital Surveying Magazine newsletter will look in more depth and simple features, their design, and their role in a GIS.

This article was shared with Slashgeo in a media partnership with Digital Surveying Magazine.

UC Berkeley GIS Day 2012

A GIS Day 2012 Event was held at US Berkeley's Mulford Hall . The event was co-hosted by the Bay Area Automated Mapping Association and the Geospatial Innovation Facility, with support from the Northern California Region of the Association for Photogrammetry and Remote Sensing. Landon Blake, the Assistant Editor of Digital Surveying Magazine, was at the event, and provided media coverage of the event for Digital Surveying Magazine and Slashgeo. In this article of the newsletter Landon shares his summary of the event.

Cynthia Powell: Climate Space Trends In Yellowstone National Park

At 5:30 in the evening Cynthia Powell of Ecoclim gave the talk entitled “Climate Space Trends in Yellowstone National Park”. The talk provided a summary of the work performed by Ecoclim analyzing the minimum and maximum temperatures and amount of rainfall in Yellowstone National Park over the past 100 years.

As part of this project, Ecoclim attempted to answer three (3) questions.

1. How do we measure if the climate is changing within the park?

2. If the climate is changing, what are the spatial and temporal patterns of that change?

3. How can land managers in and around the park use this information?

One aspect of the analysis discussed by Cynthia dealt with Canadian Lynx habitat. Yellowstone National Park is home to the southernmost finger of the Lynx habitat. This “habitat finger” is especially susceptible to climate change because of its southerly location. The work Ecoclim performed in the park examined how the Lynx habitat would changed in the future based on different climate models.

An interesting concept discussed by Cynthia in the talk was that of “climate refuges”. These are areas within the park that appear to be resistent to changes in temperature and rainfall brought about by climate change. This resistance could be due to microclimate factors. It will be important to preserve these climate refuges for climate sensitive species like the Canadian Lynx. Information about the location of these climate refuges can help land managers make land use and land conservation decisions at the park.

Brian Quinn: Community 1:1000 Base Mapping

At 6:00 in the evening Brian Quinn described the development of a GIS basemap for Marin County. Marin County now has a set of basemap tiles for 10 scales or “zoom levels” between 1:1080 and 1:570,000.

Brian described two (2) challenges encountered during the basemap creation process. The first was discrepancies that became apparent when GIS data layers are overlaid on one another. The second is that GIS data layers maintained by the various county departments are not always suitably designed for cartographic representation.

Brian also described two (2) benefits from having a standard basemap at different scales available to County staff. The first benefit is the elimination – of time employees previously wasted in developing a custom basemap for every mapping project. The second benefit is the delivery of county map products with a consistent basemap background.

One unexpected benefit of showing structures on the basemap is improved response time for emergency responders using the County GIS data. For example: Many residents of Marin County live on the water in houseboats or other floating structures. These floating residences are not usually accessible from a public street like a typical residence. The Marin County basemap allows emergency responders to determine how to best reach a particular floating residence from the nearest public street

Brian also mentioned the County is no longer using photogrammetry for to map terrain in the County basemap. Photogrammetry has been replaced with LIDAR data for all of the County's basemap terrain needs.

Jeremy Wood: Location Anonymization

At 7:45 Jeremey Wood of locationanonymization.com gave a talk on his process for making geospatial data more “anonymous”. According to Jeremey stripping GPS tracks provided by a consumer doesn't make it sufficiently anonymous. The consumer can be still be identified by his travel patterns and the locations he regularly travels to (for example: their home or office). Jeremey's anonymization process involves intentionally degrading location data when a consumer travels outside of a “public area”.

Although Jeremey's concept was intriguing, the definition of “public areas” versus “private areas” in which location data would be intentionally degraded seems to be a critical element that could prove challenging.

This article was shared with Slashgeo in a media partnership with Digital Surveying Magazine.

https://www.coursera.org/course/maps

Learn how advances in geospatial technology and analytical methods have changed how we do everything, and discover how to make maps and analyze geographic patterns using the latest tools.

The world's first geo-MOOC. At least according to Directions Magazine.

[MOOC stands for massive open online course]

I'm abroad this week, expect return to normal geonews coverage next week, thank you for your patience.

Slashdot discusses a story named Why Hasn't 3D Taken Off For the Web?

Their summary: "With HTML5 we're closer to the point where a browser can do almost everything that a native app can do. The final frontier is 3D, but WebGL isn't even part of the HTML5 standard, Microsoft refuses to support it, Apple want to push their native apps and it's not supported in the Android mobile browser. Flash used to be an option but Adobe have dropped mobile support. To reach most people you'd have to learn Javascript, WebGL and Three.js/Scene.js for Chrome/Firefox, then you'd have to learn actionscript + flash for the microsofties, then learn objective c for the apple fanboyz, then learn Java to write a native app for Android. When will 3D finally become available for all? Do you think it's inevitable or will it never see the light of day?"

We mentioned WebGL often lately, with many geospatial web tools betting on it.

Google is not alone trying to take advantage of trillions, Slashdot runs a story named Oxford Tests Self-Driving Cars.

Their summary: "Using advances in 3D laser mapping technology, Oxford University has developed a car that is able to drive itself along familiar routes. This new self-driving automobile uses lasers and small cameras to memorize everyday trips such as the morning commute. This car is not dependant on GPS because this car is able to tell where it is by recognizing its surroundings. The intent is for this car to be capable of taking over the drive when on routes that it has traveled before. While being driven, the car is capable of developing a 3D model of its environment and learning routes. When driving a particular journey a second time, an iPad on the dashboard informs the driver that it is capable of taking over and finishing the drive. The driver can then touch the screen and the car shifts to 'auto drive' mode. The driver can reclaim control of the car at any time by simply tapping the brakes."