I was recently introduced to Prezi, a rapid presentation package for those sick of the usual Powerpoint interface. It is programmed in Adobe AIR and so requires Flash. There is a free version which has limited storage and makes presentations freely available. A personal version (which is free to teachers and students) and a professional version (which gives the option of an offline app). It broadly tales the paradigm of a mindmap (and for those interested, FreeMind is an excellent open source implementation) and lets you type text and then add further ideas around it. It doesn’t use branches though, rather just allowing you to dump text, images, audio and video on to the “canvas”. What is unique is the zooming concept which presents unlimited zoom levels and allows you to nest mindmaps within mindmaps. When it comes to finalising the presentation you add “paths” for the presentation to follow and zoom in and out to each area. Formatting is very limited amounting to colour for text, size, rotation and boxes. Thats about it. But the power lies in the simplicity and speed. I’m doing my first talk with Prezi tomorrow so will see what the audience thinks; its certainly a paradigm shift to the speaker as it bypasses the whole “dump everything on to a slide” so you have to spend more time preparing.
Paul Beaty has an interesting comparison of the effect of multiple processors when using ERDAS Imagine for processor intensive tasks. In his testing he did two large exports using ECW and JPEG2000. Now I’ve always found Imagine to be pretty robust and fast; the algorithms appear well written, stable and designed to complete efficiently (although I can’t comment on the 2010 version as the disc is currently sitting on my desk unused). Perhaps harking-back to the days when raster processing was costly in computing terms (and so monetarily as well). Anyway, the comparison is stark and clearly 2 and 3 cores are where the biggest gains are made, but if you do this alot then the more cores the merrier!
I blogged last year on the increasing use of Python as the preferred language for geospatial automation driven, in no small part, but ESRIs uptake. Anyway, a useful post on essential Python modules for the geospatial programmer.
Plenty of Eyjafjallajökull stuff in the blogs at the moment (not surprisingly!) so I thought I would compile a few remote sensing bits together:
MODIS RapidFire had one of the earlier sets of imagery of the ash cloud as it spread out over Europe. The high spatial resolution and twice a day imaging makes it very good for this type of stuff.
Robert Peston provides a nice summary. Couple of nice quotes: “[This] shows that the issue isn’t whether the cloud is real and dangerous - but whether its extent can be accurately mapped.” Spatial extent is clearly the most important, but vertical mixing is rapidly becoming a key issue. And, of course:
“Right now, the biggest impact for business is the sheer number of executives who are stuck abroad, unable to come home. ‘The real danger for them is that we’ll discover we don’t really need them,’ one business leader joked.” Nice touch!
Lidar News has covered how Doppler LiDAR is being used to determine vertical extent.
A nice series of images over at Earth Observatory
So, plenty going on in the remote sensing world.
The Geoprocessing blog over at ESRI highlights an interesting (well, in an academic sense!) book on spatial statistics which they have contributed a chapter to on ArcGIS. The chapter has been made available for download so is well worth checking out.
It is clearly going to take some time for the dust to settle, but GoGeo have a nice summary of the datasets “in” and “out” of each prospective license. No doubt about it, the JISC-OS licensed data from EDINA is good value, but…..
and here’s the big “but” the new JISC-OS licence is very poor. There is almost (and I say almost as there is some residual value) no point in using the data if you want to publish anything electronically (which means just about any journal article). The raster-only requirement and miniscule pixel count is severely restrictive. Which means, that if you want to use anything with a “yes” in it in the right-hand column, you need to download it from the OS as you would likely be breaking the JISC-OS licence if you used a version downloaded from EDINA. If you want unrestricted publication of spatial data (or maps), avoid EDINA sourced data.
I was reminded to day of the EDINA run Digimap for Schools service which offers access to twelve different datasets (including Mastermap) for Primary and Secondary schools at an incredibly reasonable cost (£60-120). For those schools needing geospatial data for teaching its a very good place to start.
The loess record in China constitutes one of the most important archives of past environmental change and specifically, the East Asian monsoon system. Changes in summer monsoon driven pedogenesis are commonly inferred from magnetic susceptibility of loess. However, there is still controversy as to the signal’s origin and the uncertain effects of sediment accumulation rates. This is linked to a wider problem that is emerging from recent work; that of the relative importance on proxy records such as magnetic susceptibility of both regional climate patterns (i.e. the monsoon) and local site-specific influences, particularly modulated through site-specific sedimentation rate. At present this is poorly constrained and significantly increases the degree of uncertainty over the wider-scale applicability of climate reconstructions from individual sites. To resolve this issue for sub-orbital timescales, a rapidly deployable technique is needed that can be used to test multiple sites and differentiate between local and regional signals. This research develops the first use of full spectrum reflectance spectroscopy in studying loess in the field at one site on the south of the Loess Plateau, and utilises statistical analyses to compare such data with magnetic susceptibility records. Establishment of loess reflectance as a proxy for climate variability will potentially allow extension of the technique from point measurements to an imaging system and so enable the compilation of large data sets in order to investigate lateral facies variations in loess profiles. This may allow the extraction of a broad scale climate record.
Field spectra were obtained from 350-1100 nm, with red edge reflectance spectra indicating the presence of iron-oxides, previously demonstrated to be indicators of pedogenesis through laboratory measurements. An off the shelf camera was also tested with visible wavelength spectra being useful for rapid but general profile characterisation. In order to mitigate the effects of bidirectional reflectance distribution function (a potential problem in field measurements), further laboratory measurement was made of powdered samples (400-2400 nm). Absorption features indicative of montmorillonite and illite/muscovite were noted and stepwise regression modelling utilising absolute reflectance, first derivative spectra and continuum removed spectra indicated strong predictive relationships with magnetic susceptibility, particularly against the presence of montmorillonite. The abundance of such clay minerals could be used to infer weathering rates and hence be used as a proxy for pedogensis. Reconstructions for the studied site are presented and demonstrate the potential power of loess reflectance environmental reconstruction.
Ed Parsons covers the licensing for the free OS data, which as he notes is Creative Commons style and means no problems for derived data. Good news indeed.
Yes, OS data is here. Download to your heart’s content and, more importantly, it is going to be fascinating to see the new uses that this data is going to be put to. With unhindered access the potential for some really good mashups and web services is great. The Guardian nicely summarise the datasets. For DEM users note that the vector version of Panorama is included which, in my mind, is *better* than the higher resolution Profile (although Profile Plus is a different beast). And MySociety have already produced some derivative products (e.g. WGS84 version of CodePoint).