• Jody Garnett On Twitter: Tip For Mac

    Jody Garnett On Twitter: Tip For Mac
    • Watch the official music video for 'Steph Curry McFlurry' by RiFF RAFF. AQUABERRY AQUARiUS ALBUM DROPS JANUARY 29TH Pre-order here on iTunes: https://itunes.
    • OpenGeo’s Gabriel Roldan on GeoNode at Latinoware 2010. November 10, 2010 By Editor. Free Python Programming Cookbook. OpenGeo’s Gabriel Roldan to Speak on GeoNode at Latin-American Open Source Software Conference – Latinoware 2010 – Presentation Covers OpenGeo’s New Tools for Collaborative SDI Development.
    • More than a dozen Adobe products are not working properly on Mac OS X Lion, Apple's new desktop operating system, continuing Adobe's struggles to make its software compatible with Apple products.

    MAC takeaways from an upset-heavy Week 12 Five MAC games, four teams with the worse record emerged on top. This Article has a component height of 107. The sidebar size is long.

    Here is a little bit of fun for you to enjoy at a staff social, after your Xmas lunch or in the pub one evening This is how the Sh.thole Geography Standup Quiz works. “At the beginning everyone stands up. Quizmaster asks a question with 3 suggested answers. If you think the answer is the first one put your left hand up, if you think it is the second one both hands up, if you think it is the third one put your right hand up. QM tells you the correct answer, everyone who got it wrong sit down. If you didn’t make a choice then you also sit down. There are some other interesting stats in the speaker notes for each slide (you need to download the presentation) Then we go again until one person is left standing – if everyone gets knocked out you can all stand up again and keep answering questions.

    88 Chevrolet SS marks an elevated partnership between Hendrick Motorsports and Valvoline, which in September 2013 announced a four-year agreement that kicked off last season. Valvoline has been involved in NASCAR for a long time, and it’s awesome they wanted to do a program like this at Darlington.” The one-race sponsorship of Earnhardt’s No. “As Valvoline approaches its 150th anniversary, we are proud to support Hendrick Motorsports and Dale Earnhardt Jr. The new sponsorship at Darlington represents Valvoline’s first primary paint scheme since that time. Valvoline nascar drivers for mac

    There is a tie breaker question at the end” And you could ignore all my instructions and just have a fun time after Xmas lunch or even do the quiz on your own and see how many questions you can answer, you could tweet your score with the hashtag #ShitholeQuiz What’s the point of the maps at the end of each slide/question? I’m not sure!

    The quiz was first presented at FOSS4G with Ken and we had a cartographic spin to the whole talk. Maybe the maps disprove some of our preconceptions.     Don’t press the autoplay button on the quiz or it will go into auto advance mode which is not the ideal way to run the quiz, use the button to advance and the. An initial integration of PROJ master into GDAL has been started in a. This includes:. PROJ master, which will be released as 6.0, is now a required dependency of GDAL.

    It actually becomes the only required external third-party dependency (if we except the copies of a few libraries, such as libtiff, libgeotiff, etc. That have been traditionaly included into the GDAL source tree). The dozen of continuous integration configurations have been modified to build PROJ master as a preliminary step.

    Related to the above, we have including into PROJ a way to 'version' its symbols. If PROJ is built with -DPROJRENAMESYMBOLS in CFLAGS and CXXFLAGS, all its exported symbols are prefixed with 'internal'. This enables GDAL to link against PROJ master, while still using pre-compiled dependencies (such as libspatialite) that link against the system PROJ version, without a risk of symbol clash. This is particularly useful to be able to run GDAL autotests on continuous integration environments that use pre-packaged dependencies (or if you want to test the new GDAL without rebuilding all reverse dependencies of GDAL). This however remains a hack, and ultimately when PROJ 6 has been released, all reverse dependencies should be built against it.

    (this solution has been successfully tested in the past where GDAL had a libtiff 4.0 internal copy, whereas external libtiff used by some GDAL dependencies relied on the system libtiff 3.X). Compatibility mechanisms which were required to support older PROJ versions have been removed. In particular, the runtime loading (using dlopen / LoadLibrary mechanism) has been removed. It proved to cause code complication, and users frequently ran into headaches with different PROJ versions being loaded and clashing/crashing at runtime.

    The OGRSpatialReference class which implements CRS manipulation in GDAL has been modified to use the new PROJ functions to import and export between WKT and PROJ strings. Previously GDAL had such code, which is now redundant with what PROJ offers. This preliminary integration caused a number of fixes to be made on PROJ to have compatibility with the input and output of GDAL for WKT.1 and PROJ strings. Besides 'moving' code from GDAL to PROJ, a practical consequence is that the addition of a new projection method into PROJ will no longer require changes to be made to GDAL for it to be usable for reprojection purposes. There have been reflections on how to use the new code developped in PROJ by the existing PROJ code. A is currently under review and implements:. changes needed to remove from the data/ directory the now obsolete EPSG, IGNF, esri and esri.extra files to rely instead of the proj.db dataase.

    making the projcreatecrstocrs API use the new late-binding approach to create transformation pipelines. updating cs2cs to use that new API. list and address backward compatibility issues related to honouring official axis order. Integration phase in GDAL continus with the aim of using more of the new PROJ code.

    Typically the OGRSpatialReference class that models in GDAL the CRS/SRS was up to now mostly a hierarchy of WKT nodes, where setters methods of OGRSpatialReference would directly create/modify/delete nodes, and getter methods query them. This approach was fine when you had to manage just one WKT version (with the caveat that it was also easy to produce invalid WKT representions, lacking mandatory nodes). However, this is no longer appropriate now that we want to support multiple WKT versions. Our goal is to make OGRSpatialReference act rather on osgeo::proj::CRS objects (and its derived classes). Switching between the two abstractions is a non-trivial task and doing it in a bing-bang approach seemed risky, so we are progressively doing it by using a dual internal modelling. A OGRSpatialReference instance will maintain as a primary source a osgeo::proj::CRS object, and for operations not yet converted to the new approach, will fallback to translating it internally to WKT.1 to allow direct manipulation of the nodes, and then retranslate that updated WKT.1 representation back to a osgeo::proj::CRS object.

    Ultimately the proportion of methods using the fallback way should decrease (it is not completely clear we can remove all of them since direct node manipulation is spread in a significant number of GDAL drivers). The task is slowly progressing, because each change can subtely modify the final WKT.1 representation (nodes being added, number of significant digits changing) and cause a number of unit tests to break (GDAL autotest suite is made of 280 000 lines of Python code) and be analyzed to see if there was a bug and or just an expected result to be slightly altered. Following a clarification from IGN France on the open licensing of their, their CRS and transformation XML registry is now processed to populate the IGNF objects in the proj.db database (the previous import used the already processed IGNF file containing PROJ string, which caused information losses).

    Fitness and nutrition tracking software for mac. The associated vertical shift grids have also been converted from their text-based format to the PROJ digestable.gtx format, integrated in the, and they have been referenced in the database for transformations that use them. The NGS GEOID 2012B vertical grids to convert between NAD83 ellipsoidal heights and NAVD88 heights have also been integrated in the. How much winning is enough?

    Have you been winning so much that you’re tired of winning now? I ask because last month I gave a talk to the, about open source and open data. My talk included a few points that warned about the downsides of being beholden to a single software vendor, and it included some information about the software available in the open source geospatial ecosystem.

    In a testament to the full-spectrum dominance of, the audience was almost entirely made up of Esri customers. The event was sponsored by Esri.

    Esri had a table at the back of the room. Before giving my talk, I made a little joke about the fact that my talk would in fact include some digs at Esri (though I left the most pointed ones on the cutting room floor). People seemed to like the talk. They laughed at my jokes.

    They nodded in the right places. Among the points I made:. Single-vendor dominance in our field is narrowing the understanding of “what is possible” amongst practitioners in that ecosystem. Maintaining a single-vendor policy dramatically reduces negotiating power with that vendor. Maintaining a single-vendor policy progressively de-skills your staff, as they become dependant on a single set of tooling. Practitioners have higher market value when they learn more than just the tools of one vendor, so self-interest dictates learning tools outside the single-vendor ecosystem. Point’n’click GIS tools from Esri have widened access to GIS, which is a good thing, but driven down the market value of practitioners who limit themselves to those tools.

    None of these points is unique to Esri – they are true of any situation where a single tool has driven competitors off the field, whether it be Adobe graphics tools or Autodesk CAD tools or Microsoft office automation tools. Nor are any of these points indicative of any sort of ill will or malign intent on the part of Esri – they are just the systemic effects of market dominance. It is not contingent on Esri to change their behaviour or limit their success; it’s contingent on practitioners and managers to recognize the negative aspects of the situation and react accordingly. Last week the first official “” conference was held at Melbourne University. This was a fantastic event, and there’s simply no way I can extend sufficient thanks to all the organisers and volunteers who put this event together. They did a brilliant job, and their efforts are even more impressive considering it was the inaugural event! Upfront — this is not a recap of the conference (I’m sure someone else is working on a much more detailed write up of the event!), just some musings I’ve had following my experiences assisting deliver an introductory Python for QGIS workshop he put together for the conference.

    Microsoft releases Office 2019 for Mac and Windows. The company is rolling out Office 2019 for Mac and Windows, giving you a 'subset' of the upgrades that have come to Office 365 ProPlus in. Release notes for Office for Mac.; 26 minutes to read Contributors. In this article. Office for Mac that comes with an Office 365 subscription is updated on a regular basis to provide new features, security updates, and non-security updates. Microsoft Releases Office 2019 for Windows and Mac. Fortunately, Microsoft announced Office 2019, which delivers all of those tricks, and is available right now for Windows PCs and Macs. Microsoft releases office for mac. Microsoft on Monday released Office 2019, its 'perpetual-license' product for both Windows 10 and the Mac platform. However, the Office 2019 product is only available now for Microsoft's volume. Jun 12, 2018  Microsoft typically updates Office 365, while these individual releases of Office are available for those hesitant to move to the cloud. Office 2019 for Mac.

    In short, we both found that delivering this workshop to a group of PyQGIS newcomers was a great way for us to identify “pain points” in the PyQGIS API and areas where we need to improve. The good news is that as a direct result of the experiences during this workshop the API has been improved and streamlined! Let’s explore how: Part of Nathan’s workshop (notes are available ) focused on a hands-on example of creating a custom QGIS “Processing” script. I’ve found that preparing workshops is guaranteed to expose a bunch of rare and tricky software bugs, and this was no exception! Unfortunately the workshop was scheduled just before the QGIS 3.4.2 patch release which fixed these bugs, but at least they’re fixed now and we can move on The bulk of Nathan’s example algorithm is contained within the following block (where “distance” is the length of line segments we want to chop our features up into): for inputfeature in enumerate(features): geom = feature.geometry.constGet if isinstance(geom, QgsLineString): continue firstpart = geom.geometryN(0) start = 0 end = distance length = firstpart.length while start. As interest in LiDAR derived elevation increases, so grows the interest in the capabilities. LiDAR derived elevation data has been great for my visualization game and in helping me communicate the story out about what LiDAR can do.

    It all starts with a picture to get the imagination going. The Wellington model derived for this project is part of an ongoing project to help increase the exposure of the Wellington 1m DEM/DSM elevation data derived from LiDAR. Step one for me is getting a working model built in QGIS, capturing still images, and increasing interest in the data.

    I’ve talked about the processing of the elevation data for Wellington visualizations in the past, so for this post I’m only focusing on the blending of the data sets in building the model. This project is a good model since it encompasses a number of subtle techniques to get the model to stand out. This post is one of a two part series; the second post discusses the techniques used to derive and visualize the bathymetry for the surrounding harbor. Let’s start with the base, Aerial Imagery.

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    Blended with a hillshade DSM added for texture and context Slope added to define some edges Some darker shading added to the bathymetry to frame the elevation data And finally some added bathymetry to lighten the edges at the shoreline enhancing the frame a bit more. In the end there is some post-processing in Photoshop to lighten up the image.

    Honestly, this could have been done in QGIS, but I was being lazy. For the images produced, there was no need to retain the georeferencing, and when that is the case, I rely on Photoshop for color and light balancing.

    The greatest difficultly in this project so far has been trying to create a universal model for the data set. I’m finding that as I visualize different regions using this model, I need to adjust the hillshading quite significantly to draw out different features. It is the same model, but with the noticeably different gradients used in the hillshades. The techniques used for the images in this post worked well for the urban region shown, but fall apart as you move further out into the more mountainous regions. Much of the blending is too harsh and turns the mountains into a black muddled mess. I am almost there, but like any project, it takes a good bit of subtle tweaking of the blending to get a universal image to work.

    The entire base mapping work is completed in QGIS. The elevation data was processed using GDAL and the bathymetric interpolations were produced SAGA GIS. There are no color palettes for this project.

    The aerial imagery does all the work in that department. Base data can be found here: DEM: DSM: Aerial Imagery: The next post covers the. Thanks for having a look and let me know what you think. Sometimes there is simply not enough room for all the ideas.

    Sometimes you want all the images to make it to the final round. In a recent project to promote some of our elevation data, I was asked to present a number of ideas for a 2000mm x 900mm wall hanging. The piece was to act as a conversation starter and demonstrate some of the finer details elevation from LiDAR possesses. In the end, the image above was the chosen candidate. Below are the drafts I initially presented for review. You can see the difference in treatment from the original ideas to the final product. Personally, I really enjoyed the images developed for the draft series, I liked the silvery undertones, and I thought it was a shame to merely let these images sit on my hard drive.

    Below, you’ll find a brief description about a few challenges faced in the image development. Artifacts and Finer Details The hardest part of this job was drawing out the finer details of the chosen location. There was a strong interest in showing the ancient river bed; however, without a good bit of tweaking in the hillshades, the image is quite flat. After some trial and error, I found I could get a good contrast by limiting the hillshade values range to 170-190. That’s it, but the readability of the project really hinged on the simple tweak. It really made the details stand out. That said, the gain in detail also revealed a significant artifact in the data.

    If you go back up and have a closer look, you will find diagonal depressions running across the images in equal intervals. These are lines from where the LiDAR scans overlap. I haven’t quite had the time to figure out how to remove these from the original data source, so for now I leave them in as conversational piece around improving LiDAR capture practices. As usual, all map layout work was completed on QGIS, with the bulk of the data processing done using GDAL. The ‘Reject’ images for this post are direct exports from QGIS, with no manipulation apart from some down-sampling and cropping in Photoshop.

    Base data can be found here: DEM: DSM: Aerial Imagery: I produced a public repository for some of the scripting work. This repository is not specific to the above project but does contain some of the base processing I did on the Wellington elevation data: Hope you like and thanks for checking in! We are happy to announce the release of. Downloads are provided ( ) along with docs ( ). This is a stable release of the GeoServer 2.14 series and is recommended for all production systems.

    Users of prior releases of GeoServer are encouraged to upgrade. This release is made in conjunction with GeoTools 20.1 and GeoWebCache 1.14.1. Thanks to all who contributed to this release. For more information please see our release notes ( ). I was invited to deliver a keynote last week at KortDage to an audience of nearly 800 Danish (and Scandinavian) GI professionals.

    There were just a few snags:. The person who invited me said “Last year Jack Dangermond gave a keynote, this year we wanted something different”. No challenge there!.

    The slot was at 9.00am on the final morning after the delegates had been up till 1.30am boogying. I don’t speak Danish and I wasn’t sure how my dry (I’d like to think) Brit humour would go down So they wanted something different, they liked my #FAKEMAPS talk, I didn’t have a lot of time to come up with something completely new so I decided to re-invent Sh.thole Geography. Ken Field and I had done a double act at FOSS4G in Dar es Salaam around Donald Trump’s opinion that some countries were “shithole countries” whose citizens were not welcome in the US. We had riffed on the “Orange Clown” as Ken likes to call 45, we had played with UN Sustainable Development Goal stats, Ken gave a brief cartography master class on making global maps and I had created a pub style geography quiz.

    I could work with that and switch the focus to make a slightly different message for this audience (with apologies to Ken) – a map may not always be the best way to present global statistics. They didn’t record the whole talk so I can’t share that with you but you can get the drift of the points I was making from this short interview that the organisers did with me after my talk. At the end of the talk I offered Sh.thole Geography badges and stickers to the attendees in return for donations to the – the audience were amazingly generous and we raised almost $500 Apart from my talk I also got to meet Anna Webber, an artist who had made an “earth map” of Denmark You can p and why she made it on Ken’s and my Mappery site. Thanks to the organisers for inviting me to speak, thanks to all the people who laughed at my jokes and made me feel welcome. KortDage was a great event. Thanks to your donations, we were able to hire core developers to focus on solving Mac OS specific issues for QGIS.

    More than 30 MacOS QGIS users donated a little more than 3000 € for this bug fixing round. After an effort of triage and testing, here is what has been achieved:. The map canvas is now in HiDPI. The issue was that Mac OS handles differently high DPI scaling by providing a scaling ration to scale graphics output. For more information, read and for even more info.

    You may not have noticed, but the scale shown under the canvas was wrong in former QGIS 3.x versions. It has been fixed too. Zooming with trackpad is now fluent The track pad is apparently sending more events than the scrolling and are now discarded to avoid scale jumps. Size of mouse cursors with map tools has been fixed. The scaling previously introduced could be removed thanks to the HiDPI fixes, and this has fixed by the same occasion the active point of the cursor being misplaced. The size of the map canvas at startup was not an issue in QGIS in itself and has been fixed by upgrading to a newer Qt version. Rendering slowness issue.should.

    also have been fixed by an upgrade of Qt version. At the moment, the “default” theme of QGIS (as opposed to the “Night Mapping” theme), has a few glitches when used in Mojave with “Dark” theme activated. Mainly text in widgets cannot be read since they are white on white.

    Jody Garnett On Twitter: Tip For Machine

    This is a Qt issue and the upcoming Qt 5.12 released by the end of november should fix it. In the mean time, the QGIS “Night Mapping” theme is automatically applied when running on Mojave with Dark theme.

    While the theme is probably not perfect, it allows to work properly and the situation will be evaluated again when Qt 5.12 is released. Unfortunately, some issues remain. Mainly, the text being rendered as outlines in PDF export remains for now. It might be fixed in a following effort. Thanks to all donors who helped in this effort and to Denis Rouzaud as a core developer who spent a lot of time investigating and fixing these issues! The PostGIS development team is pleased to provide bug fix 2.5.1 for the 2.5 stable branch.

    Although this release will work for PostgreSQL 9.4 thru PostgreSQL 11, to take full advantage of what PostGIS 2.5 offers, you should be running PostgreSQL 11 and GEOS 3.7.0. Best served with. WARNING: If compiling with PostgreSQL+JIT, LLVM = 6 is required Supported PostgreSQL versions for this release are: PostgreSQL 9.4 - PostgreSQL 11 GEOS = 3.5 2.5.1. PDF docs. html online,. pgsql help files for non-english languages:,.

    Continue Reading by clicking title hyperlink. The material of the workshop about environmental modelling using gvSIG and the HortonMachine, given at 14th International gvSIG Conference some days ago, is now available. Although the screen image is not very clear it can be followed with the teacher instructions, and using the cartography and tutorial available to download at this. The is an open geospatial library integrated in gvSIG containing tools for the management of environmental data and hydro-geomorphological analyses. The algorithms contained in the library are the result of more than 10 years of research, development and real application by different researchers and professionals working in the field of natural hazards. Recording of this workshop is available here.

    If you follow me on Twitter, you have probably already heard that the ebook of has now been published and we are expecting the print version to be up for sale later this month. And I – together with our editor Gary Sherman (yes, that!) – have been working hard to provide you with tons of new and improved map design workflows and many many completely new maps. By, this edition contains 23 new maps, so it’s very hard to pick a favorite! Like the 1st edition, we provide increasingly advanced recipes in three chapters, each focusing on either layer styling, labeling, or creating print layouts. If I had to pick a favorite, I’d have to go with “Mastering Rotated Maps”, one of the advanced recipes in the print layouts chapter.

    It looks deceptively simple but it combines a variety of great QGIS features and clever ideas to design a map that provides information on multiple levels of detail. Besides the name inspiring rotated map items, this design combines. map overviews.

    map themes. graduated lines and polygons. a rotated north arrow. fancy leader lines all in one: provides how-to instructions, as well as data and project files for each recipe. So you can jump right into it and work with the provided materials or apply the techniques to your own data.

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    Jody Garnett On Twitter: Tip For Mac