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GIPPY is made up of python bindings to a C++ library called GIPS. GIPS is built on top of GDAL and an image processing template library called CImg. GIPPY provides a similar, yet simpler interface than GDAL for opening, creating, and reading geospatial raster files. Convenience functions have been added to make common tasks achievable with fewer lines of code. Most notably GIPPY adds image processing functionality on top of GDAL for easier automation of processing functions. The main objects in the GIPPY library are the GeoRaster, which is a single raster band, and a GeoImage, which is a collection of GeoRaster objects (possibly from different files). GeoImage and GeoRaster objects support various processing operations (e.g., +, -, log, abs) that can be chained together and saved as a processing chain. The processing does not actually occur until the file is read (frequently followed by a write to a new file). Reading may also occur in chunks, thereby facilitating the processing of very large file. https://github.com/matthewhanson/gippy

D3 is a JavaScript data visualization library using HTML, SVG and CSS. D3 stands for Data Driven Documents and was developed by Mike Bostock, Jeff Heer and Vadim Ogievetsky as a successor to the Protovis framework. The 3.0 release of D3 now includes a geographic projection system. Common geographic projections are included in the default build of D3 such as Albers, Gnomic, and Mercator. Additional geographic projections can be accessed via the extended geographic projections plugin and the polyhedral projection plugin. Over forty different projections are support by the default D3 build and geographic projection plugin. The Geo Projections page has a listing of projections with links to sample pages and code. Tutorial : The tutorials page on the D3 wiki provides access to a range of instructions on getting started with D3. Mike Bostock has a tutorial on basic map making using D3 and TopoJSON in his tutorial, “Let’s Make a Map.” The tutorial steps you through finding GIS data, loading the data, and symbolizing the polygons and adding labels. EJ Fox has a tutorial on the Visual.ly blog about how to make a choropleth map in D3 using Google’s JSON data of the 2008 presidential election. as the example. Alex Rothenberg also uses 2008 Presidential Election data to create an interactive map by combining D3 with Ember. Example sites : There are a few pages interested users can browse to see examples of D3 in use showing a range of data visualization techniques. Mike Bostock, who now works for the NY Times has several sample pages. To see in use examples by the NY Times, visit Mike Bostock’s launch page for some of his D3 work. Included are some of the amazing post election results maps from the 2012 presidential election such as the Counties Blue and Red, Moving Right and Left map. mbostock’s blocks also has pointers to a wide range of data visualization examples as does the D3 Gallery. Jens Finnäs, a Finnish journalist has some interesting D3 mapping examples on his dataist blog such as his map of the Occupy Wallstreet movement over time. source : http://www.gislounge.com