ArcGIS 10 Download: June 21 (partner) or 28 (public)

“ESRI says ArcGIS 10 available for partner download on 6/21/2010, public download on 6/28/2010…”

- @MT_AppGeo (at ESRI-Boston [Danvers] at an ESRI Developer Network Event)

From their website:
“We developed Natural Earth as a convenient resource for making custom maps. Unlike other map data intended for scientific analysis or military mapping, Natural Earth is designed to meet the needs of production cartographers using a variety of software applications. Maximum flexibility is a goal.”

Go to Natural Earth Website

Reference: http://hansvandermaarel.wordpress.com/

Many within the GIS community working on global data are familiar with the Gridded Population of the World (GPW). This global gridded population estimate has now been more available through a web-service. This lets the user zoom around to investigate the data without having to download the rasterdata.
Additionally and more interesting are the population estimation service, that can be accessed through OGC, REST and SOAP interface to estimate the population within a drawn polygon.

One of the new mapping tools also released, based on the technology used by Google Maps, demonstrates the Population Estimation Service. It lets users select an area of interest by drawing a polygon on the map and submit the request to the service, and it displays the results. (CIESIN News)

The google map based Population Estimation Service can be accessed here.

What i wanted to do was to create polygons representing each of the rastercells, and extract the value from the raster and copy this value to the attribute table of the polygon.

I started off importing the raster to my workspace. One could also do this as a batch operation, importing multiple rasters.
To convert the raster cell to polygon i used the the ‘RasterCellCoercer’. This transformer decomposes each of the raster features into individual points or polygons. However, the transformer does not extract the value, even when enabling the “preserve attributes” option.
To be able to extract the value from each of the raster cells into an attribute i used the transformer ‘ElevationExtractor’. This tool extracts the z-value from each of the raster cells into a defined attribute. The default is “_elevation”.
That is basically it. You can now add your output writer and add the user attribute you want to store the raster cell value from the “_elevation” attribute. Remember that your output feature must be equal to either the point or polygon option that you selected in the ‘RasterCellCoercer’.
If you have selected multiple rasters, you could write each out to its original filename using fanout by “fme_basename”.
Here is my workspace:

The 2010 Olympic Games in Vancouver has just started and we had to do some elementary investigation on GIS and this event.

First off, as gisuser.com wrote about , google has introduced street view to the 2010 winter olympics. Now you can see all the ski slopes and navigate around in some of the inaccessible areas you probably would not be able to see.
The street view has been made using a google street view snowmobile, and they have set up their own page linking the events to the map.
Google Street View Olympics – Get inside the games!

Google has also made a olympic torch relay interactive map where you can see the route the torch has taken on its way to light the 2010 olympic fire.
More here

Microformats.dk has an interactive 3D tour of the Olympic venue sites using google earth plugin.
Watch it here.

You can download Vancouver olympic data here (Thanks to Kay at cartotalk.com for this link).

Lets hope for fair and enjoyable games.

A new report from CIESIN and the Austrian Insitute of Technology has released an global assessment on light pollution on protected areas.

The analysis is done to reveal how light pollution affects protected areas. Hence, two new variables was created from combining the global protected area distribution data and nighttime lights data: a Protected
Area Light Pollution Index (PALI) and a Protected Area Human Impact Index (PAHI).

Results indicate that regions in Europe and Asia Minor, the Caribbean, South and East Asia as well as in
the Eastern part of the United States are most affected. Introducing aggregated data on biomes reveals that
temperate broadleaf and mixed forests suffer the biggest impact both in terms of general light pollution as
well as lighting in protected areas. The presented risk assessment underscores the need for accurate and
consistent spatial data on a global scale and can help to indicate which protected areas globally and
nationally are at greatest risk of human activities. It is also an important step towards public communication
and raising general awareness on the topic of light pollution.

Aubrecht et al. (2010): GLOBAL ASSESSMENT OF LIGHT POLLUTION IMPACT
ON PROTECTED AREAS.

Read the whole report here:
http://www.ciesin.columbia.edu/documents/light-pollution-Jan2010.pdf

Click the map for full size:

The service is built up with Open Layers on Geoserver.

WildAreas