In+ersec+ion for Spatial People

On my morning commute I read about Betaville - "an open-source multiplayer environment for real cities, in which ideas for new works of public art, architecture, urban design, and development can be shared, discussed, tweaked, and brought to maturity in context, and with the kind of broad participation people take for granted in open source software development."

From what I read it seems to provide a platform for any interested party to provide a model of their urban design and see how it fits within the surrounding environment. It also supports discussion and collaboration between parties so potentially multiple iterations of a design can be undertaken (at a low cost) before the formal planning and design process begins. It can take models from tools such as Sketchup and Maya.

Via Datalibre, I learned about OpenTreeMap, an open source software for collaborative, geography-enabled urban tree inventory.

From the main site: "Urban street trees have myriad proven benefits for communities including providing shade, improving air quality, assisting with stormwater runoff, raising property values, decreasing utility bills, and enhancing the look and feel of communities. While tree inventories provide municipalities with vital data to consult when managing the urban forest, creating a complete inventory is a time consuming and resource intensive process.  OpenTreeMap provides an easy-to-use public inventorying platform that enables individuals, organizations, and governments to collaboratively contribute to an interactive and dynamic map of a community’s tree population. OpenTreeMap can be used in a single municipality or cover a broader geographic region with many communities.

Main Features:

• Search for trees by species, location, or advanced filters such as diameter, date planted, or tree characteristics (flowering, native, etc.)
• Add trees individually or load tree datasets to the system
• Edit and add information about existing tree records including species name, location, height, plot size and type, conditions, actions needed, funding sources, data owner
• Upload tree photos
• Export tree lists as KML or CSV files
• Automatically calculate ecosystem benefits (greenhouse gas, water, energy,  air quality) based on a tree’s species and diameter
• Monitor user accounts, comments, and system edits
• Get optional integrated tree key to assist in identifying tree species"

Geocoded trees have been mentioned a few times in the past, including Google Earth 6's native support of 3D trees, using lidar to identify urban trees, or even embedding RFID tags in trees.

This is not a freshly released dataset, but we never mentioned it before: the MODIS 500-m global map of urban extent.

From the official site: "The goal of this project was generate a current, consistent, and seamless circa 2001-2002 map of urban, built-up and settled areas for the Earth’s land surface. This work builds on previous mapping efforts using Moderate Resolution Imaging Spectroradiometer (MODIS) data at 1-km spatial resolution (Schneider et al., 2003; 2005), which was included as part of the MODIS Collection 4 (C4) Global Land Cover Product (Friedl et al., 2002). Here we addressed weaknesses in the first map as well as several limitations of contemporary global urban maps by developing a methodology that relies solely on newly released Collection 5 (C5) MODIS 500-m resolution data."

Does anyone knows how this dataset compares to GlobCover 2009's urban class?

This is not newly available datasets, but they recently came to my attention and since we never mentioned them before, they might be of interest to some of our users: the Gridded Population of the World, version 3 (GPWv3) and the Global Rural-Urban Mapping Project (GRUMP) datasets.

From the official page: "GPWv3 depicts the distribution of human population across the globe.  It is the most detailed
version of GPW to date with more than three times the amount of data as version 2, and includes population estimates to 2015. GRUMP builds on GPWv3 by incorporating urban and rural information, allowing new insights into urban population
distribution and the global extents of human settlements."