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Has come a long way since 2018 when I with GeoPandas for trajectory data handling.This week, MovingPandas passed peer review and was i. This technical review process was extremely helpful in ensuring code, project, and documentation quality. I would strongly recommend it to everyone working on new data science libraries!The lastest v0.3 release is now available from.All tutorials are available on MyBinderNew features include:. Support for 0.7.
Trajectory collection aggregation functions to generate flow maps. QGIS Cloud (www.qgiscloud.com) is a platform which provides a convenient geodata infrastructure including database, web services and web maps in the cloud. Recently, Sourcepole implemented the possibility to enable web-based editing in published maps. This blog post shows how to enable editing in QGIS cloud pro maps.We start with myeditproject.qgs, a project in QGIS desktop containing a background layer and a point vector layer (trees).We upload the data to QGIS Cloud using the QGIS Cloud plugin and publish the project. In an, we looked into how to visualise rasters and terrains in QGIS 3D.In this post, we will explore 3d vectors and how to view buildings and trees. Data SourcesFor the purpose of this blog post, we will be using.You can download all the dataset and final QGIS project from our.
Note that the DTM has been resized from 1m resolution to 5m. All of the datasets have been clipped to Luxembourg commune extent.After styling the layers you should be able to see an image like the one below in your map view.3D BuildingsYou can open a new 3D map window and set the DTM layer as your terrain as shown in the.The other layer we want to view in 3D canvas is the building layer. To adjust the settings, you need to change the layer styling (by pressing F7 to open the styling panel):.
By default, the 3D rendering of vector layer is set to No symbol. Click on it and set it to Single symbol.The buildings layer contain height information:.
Change Altitude clamping to Absolute. Change Altitude binding to Vertex.In case, your building layer is not a 3D dataset, you can apply height and/or extrusion to be able to see them in 3D map view.Culling mode helps rendering your scenes faster by not drawing certain features facing the camera. You can read more about culling modes and.You can change Diffuse, Ambient, Specular and Shininess of the polygons using relevant widgets. These parameters are based on.Finally to better display the buildings, you can define the Edges.You should be able to see a 3d scene similar to the one below:3D PointsPoints can be displayed in 3D map view as different type of objects.
In this example, we are going to display trees as combination of predefined shapes. You can extract tree points from the OpenStreetMap data (the osmpois layer with filter: 'fclass' LIKE 'tree').For tree trunks, we can set the 3D properties as follows:The tree trunks are represented by a Cylinder shape.
As you have noted, the Altitude clamping method for this layer is Relative.For the tree top, we can duplicate the same tree layer in the layer panel and change the styling to be a Sphere shape. You will also need to set the Transformation for Y to e.g. 10, so that the spheres sit on top of the cylinders. For the example below, we have set the styling to be a mix of spheres and cones ( Rule-based instead of Single symbol).3D point renderer allows you to import 3d models supported by.Fly-over animationsYou can create animations of 3d scenes, by defining key frames. Click on the Animation icon from the 3D map view window.
A new toolbar will appear at the bottom of your window.Click on the green plus sign to add the timing of the key frames and then move the camera to a different location. You can then play the fly-over using different interpolation methods. Alternatively, you can export them as images and generate an animation outside QGIS. We are happy to announce a new crowdfunding campaign to!This will be a great step for QGIS to support an increasingly popular technology used in web mapping to delivermaps that are faster and more flexible at the same time.With native support for Vector Tiles in QGIS, you will be able to add more resources to your QGIS map:. Support for remote resources (e.g. HTTP/HTTPS map tiles). Handling local vector tiles (in XYZ format).
Handling database vector tiles (Mapbox Vector Tiles format)The target amount is 8,000 € and the campaign will be active until 20 March 2020.Please have a look at the dedicated page for further details and help us spread the word! With the, we were able to support six proposals that were aimed to improve the QGIS project, including software, infrastructure, and documentation. These are the reports on the work that has been done within the individual projects:. Profile and optimise the QGIS vector rendering code (Nyall Dawson)We conducted in-depth research into code “hot spots” and inefficiencies in the QGIS rendering code using a number of code profiling tools. This work resulted in in the vector rendering code and other parts of QGIS (such as certain Processing algorithms). These optimisations were made available in the QGIS 3.10.0 release. “Rebalance” the labeling engine and fix poor automatic label placement choices (Nyall Dawson)We first designed unit tests covering a range of different label placement situations and then used these tests as a guide to re-work the label placement engine.
Now, labels will never be placed over features from a layer with a higher obstacle weight, avoiding the complexities and bugs which were present in the older approach. To avoid disrupting existing projects, the new labeling logic is only used for newly created projects in QGIS 3.12 and later. (Existing projects can be upgraded via the project’s label settings dialog.). Reuse core functionality to provide DB manager features (Alessandro Pasotti & Nyall Dawson)We have developed a new QGIS core API, fully exposed to Python, that makes it possible to manage stored connections to various data provider source in a unified and consistent way.
This is part of a larger effort building a. Snapping cache improvements (Hugo Mercier)Snapping is crucial for editing geospatial features.
Snapping correctly supposes QGIS have in memory an indexed cache of the geometries to snap to. And maintainting this cache when data is modified, sometimes by another user or database logic, can be a real challenge. This it exactly what adresses. This feature has been merged into QGIS 3.12. Fix problems in larger 3D scenes (Martin Dobias)We worked on. The first one was that map tiles were only being prepared using a single CPU core – this is now fixed and we may use multiple CPUs to load tiles of 3D scenes faster.
The other (and greater) problem was that data from vector layers (when they have 3D renderer assigned) were all being prepared at once for the whole layer in the main thread. That resulted in possibly long freeze of the whole user interface while data were being loaded. This is now resolved as well and data from vector layers are being loaded in smaller tiles in background threads (and using multiple CPU cores). As a result, the overall user experience is now much smoother. Open documentation issues for pull requests (Matthias Kuhn and Denis Rouzaud)A documentation bot is and automatically create an issue in the documentation repo for merged PR.Thank you to everyone who participated and made this round of grants a great success and thank you to all our sponsor and donors who make this initiative possible! We recently published a new paper on (open access).
If you liked, you will find even more information about the context, challenges, and recent developments in this paper.It also presents for movement data exploration:. QGIS + PostGIS: a combination that will be familiar to most open source GIS users. Jupyter + MovingPandas: less common so far, but Jupyter notebooks are quickly gaining popularity (even in the ). GeoMesa + Spark: for when datasets become too big to handle using other meansand discusses their capabilities and limitations:This post is part of a series. Read more about.
QGIS Cloud (www.qgiscloud.com) is a platform which provides a convenient geodata infrastructure including database, web services and web maps in the cloud. Recently, Sourcepole implemented the possibility to enable web-based editing in published maps. This blog post shows how to enable editing in QGIS cloud pro maps.We start with myeditproject.qgs, a project in QGIS desktop containing a background layer and a point vector layer (trees).We upload the data to QGIS Cloud using the QGIS Cloud plugin and publish the project. In this post, we will walk you through basic steps to set up a survey project in QGIS desktop and using it in to collect data in field using your Android of iPhone/iPad deveice. Software neededTo start with, you will need to install the following software applications:.
for your PC/laptop: and install QGIS if you have not already done so. for your mobile table: you can download the app from orIn addition, you will need to register with the service. The service allows you to transfer data between your PC/laptop and mobile/table via the cloud.
Note that after signing up to the service, you have to activate the account by clicking on the link sent to your email. Configuring QGIS projectTo be able to survey data, we need to set up a project in QGIS. Usually, you will need some data for your background layer (so that you can locate yourself!). In addition, you need to set up a table (or layer), to store your survey information.For background data, we are going to use Open Street Map. For survey table, we need to decide on a form structure and the type of feature you want to survey (e.g. Point of interest, tracks or parcel of land).
In this case, we want to survey potholes. Also, it would be good to attach some notes for each pothole, take a photo of it and add a date for survey. The GIS format best suited to store spatial information, is Geopackage.Let’s start by opening QGIS and add the above layers to our project. To simplify things, we can create a folder on Desktop (referred to in this tutorial as data collection folder) and store everything there.Open QGIS from your PC/laptop. From the Browser panel (usually located on the top left side), expand XYZ Tiles and double-click on OpenStreetMap to add it to QGIS:You should see the OSM layer:Save your project as pothole survey in the data collection folder.To create a survey layer, in QGIS, from the main menu select Layer Create Layer New Geopackage Layer. Note that Geopackage is a file based database where you can store multiple tables (spatial or non-spatial). A new window will appear:For Database click on and select the data collection folder on your Desktop and then type survey-db.gpkg for the name of your database.For Table name, type Potholes.For Geometry type, select Point.For Coordinate Reference System (CRS), click on the icon to the right of EPSG:4326 - WGS84.
A new window will appear. Under Filter section on the top of the window, type: 3857 and under Predefined Coordinate Reference Systems, select WGS 84 / Pseudo-Mercator EPSG:3857.
Then click OK.We can now create the column headers for our table under New Field section. For this form, we want to create the following columns to store data: Date, Notes, PhotoFor Name, type DateFor Type, select DateClick on Add to Field lists to add your column.Repeat the same process for Notes and Photos columns, but make sure to change the Type for those columns to Text. At this stage, you should see an image similar to the one below:Go ahead and click OK to create the layer and add it to QGIS. Styling layers and setting up formsThe default style applied to Potholes layer is not very visible probably. To change it:In the Layer Panels right-click on Potholes layer and select Properties.
A new window will appear. From the left panel, select Symbology. Try to change the style to something shown in the image below:Click on Apply.We can also change the way user fills in the form. By default, you have to type in the values. But by using different widgets, we can simplify filling the form in the field.In the Properties window, from the left panel, select Attribute forms.We are going to change the Widget Type for each of the Fields.fid is an auto-increment field and we can keep it hidden from users.
So, highlight the fid field under Field section and then from the Widget Type select HiddenFor Data, it should have automatically selected the correct widget type:For Notes, you can also leave the Widget Type as Text Edit.For Photos, we need to change the Widget Type to Attachment. Also make sure to select the option for Relative paths. This will allow us to attach photos using mobile camera or gallery folder to the pothole point.Tip: You can scroll further down and under Integrated Document Viewer and select Type as Image.
This will show the image in QGIS forms too.Project set up is completed and we can save the project. Transferring data to mobile devicesYou have 2 options to transfer your data to the mobile through the Mergin service: through website or through Mergin plugin in QGIS.
In this tutorial we are going to use the plugin from within QGIS.In QGIS, from the main menu, select Plugins Manage and Install Plugins. A new window will appear. From the left panel, select All and then in the search section (on the top) search for Mergin. Select the plugin from the list and click on Install plugin. After installation, you need to restart your QGIS.After the restart, you should be able to see the Mergin icon in your Browser Panel:In the Browser Panel, right click on the Mergin and select Configure. Type in your username (or email address) and password that you have registered with the Mergin service.Click on Test Connection and you should see a green OK.If you have selected to Save credentials (so you do not need to type in the username and password again) and you have not configured QGIS password manager, you will be prompted to set a password for your QGIS password manager.After clicking OK, you should see a list of folders on your Mergin connection in your browser panel:We can know upload the data:Right click on the Mergin and select Create new project. A new window will appear:For Project name type Potholes surveySelect Initialize from local driveClick on and and select data collection folderOnce click OK, the project will be created and content of the data collection folder will be uploaded there.The project is now ready to be downloaded on your mobile device.
Collecting data using Input appsThe project can now be accessed from Input app. In December, I wrote about. Back then, I also tried to get working but without luck. (While GeoPandas can be installed using Databricks’ dbutils.library.installPyPI('geopandas') this PyPI install just didn’t want to work for MovingPandas.)Now that, I gave it another try and.spoiler alert. it works!First of all, conda support on Databricks is in beta. It’s not included in the default runtimes. At the time of writing this post, “6.0 Conda Beta” is the latest runtime with conda:Once the cluster is up and connected to the notebook, a quick conda list shows the installed packages:Time to install MovingPandas!
I went with a 100% conda-forge installation. This takes a looong time (almost half an hour)!When the installs are finally done, it get’s serious: time to test the imports!Success!Now we can put the MovingPandas data structures to good use. But first we need to load some movement data:Or course, the points in this GeoDataFrame can be plotted.
However, the plot isn’t automatically displayed once plot is called on the GeoDataFrame. Instead, Databricks provides a display function to display Matplotlib figures:MovingPandas also uses Matplotlib. Therefore we can use the same approach to plot the TrajectoryCollection that can be created from the GeoDataFrame:These Matplotlib plots are nice and quick but they lack interactivity and therefore are of limited use for data exploration.MovingPandas provides interactive plotting (including base maps) using hvplot.
Hvplot is based on Bokeh and, luckily, the tells us that bokeh plots can be exported to html and then displayed using displayHTML:Of course, we could achieve all this on as well (and much more quickly). However, Databricks gets interesting once we can add (Py)Spark and distributed processing to the mix. For example, “ shows a spatial join function that adds polygon information to a point GeoDataFrame.A potential use case for MovingPandas would be to speed up flow map computations. The recently added aggregator functionality (currently in master only) first computes clusters of significant trajectory points and then aggregates the trajectories into flows between these clusters. Matching trajectory points to the closest cluster could be a potential use case for distributed computing. Each trajectory (or each point) can be handled independently, only the cluster locations have to be broadcast to all workers.
QGIS users who have adopted the 3.10 version when initially released at the end of October 2019 have likely noticed a sharp drop in reliability. The underlying issues have now been addressed in 3.10.2, all users are advised to update.now.When QGIS 3.10 was first released in the end of October 2019, a pair of libraries – namely GDAL and PROJ – were updated to their next-generation versions. The advantages are plenty: GeoPDF export1 support, more accurate coordinate transformation, etc. For those interested, more technical information on this is available here2.The update of these crucial libraries led to a number of regressions.
While we expected some issues to arise, the seriousness of the disruption caught us off guard. Yet, it was also somewhat inevitable: QGIS is the first large GIS project to expose these next-generation libraries to the masses. The goal of the new API is twofold:. provide a unified way to store and retrieve data provider connections in the QGIS settings. provide an abstract set of methods to perform most common operation on DB data sources (e.g. Ready for 3D meshes, vector streamlines or contour export?The releases of QGIS 3.12, MDAL 0.5.0 and Crayfish 3.2.1 are planned for end of February 2020.We are proud to present you few of upcoming features we implemented for this release:. vector trace animation.
3D stacked meshes. mesh calculator enhancements. export contours. various smaller enhancements (reference time support, resampling, export plot data, mdaltranslate utility)If you are hesitant to wait till end of February, feel free to get nightly build and test it out! Support for vector trace animation and streamlines (QGIS)Last feature from QGIS 2.x/Crayfish 2.x series that was not ported to QGIS 3 is finally available.
You would be able tovisualize streamlines and particles for vector datasets in mesh layers. In QGIS main menu, under MeshCrayfishExport Traceyou are also able to export animation with the particle traces to various video formatsThis feature was funded by Support for 3d Stacked Meshes (e.g.
TUFLOW FV format)MDAL and QGIS now supports 3D Stacked Meshes, particularly for TUFLOW-FV format.For this release, you need to choose appropriate averaging method in the QGIS interface and you are able to browse the data similarlyto any other 2D dataset.In Crayfish 3.2.1, you can create plots of the profile showing the variation along Z-axis.The technical description can be found in the followingThis feature was funded by On the fly resampling of data defined on faces to verticesFor datasets defined on faces, one can choose to interpolate data to vertices with neighbour average method. When no data interpolationmethod is chosen, each pixel on a single face has a single value/color. With data on vertices, the rendering for each pixel isinterpolated from the values on the vertices, making smoother figures.Use mesh contours styling panel to switch between the data interpolation methods.This feature was funded by Smooth export of the contours (Crayfish processing algorithm)We have implemented a new algorithm in QGIS’s analysis library to export directly contour lines and polygons. The method is notbased on GDAL as it was in the Crayfish 2.x releases. It is both faster and with smoother shapes, matching rendered images from QGIS.You can find the new processing algorithm in Crayfish processing toolbox.This feature was funded by Support of datasets defined on faces in QGIS Mesh CalculatorFrom QGIS 3.12 you can use mesh calculator for all datasets, both defined on faces and vertices.Additionally, it allows users to store the result of mesh calculator under different name or format.
This allows forexample to work with FLO-2D or HEC-RAS data in the QGIS mesh calculatorThis feature was funded by Support for reference time (QGIS)For various dataset type, for example GRIB and NetCDF, the reference time in QGIS time settings dialog is prepopulated from theraw data and does not need to be set manually. Also we fixed various bugs related to time parsing, so in QGIS 3.12 it should bepossible to format and show your time in plots/animations in proper way.This feature was funded by Support for conversion of 2dm to UGRID mesh (mdaltranslate utility)MDAL library now has a new utility: mdaltranslate. For now, use can use the utility to convert text-based 2dm mesh definition filesto UGRID NetCDF/HDF5 binary-based format and save up to 80% disk and speed up loading of your mesh by similar amount.This feature was funded by Support for export of 2D plot data (processing)With Crayfish 3.2.1 you can export your time series or cross section raw dat to CSV format for further processing.This feature was funded by Lutra Consulting. This post is a follow-up to I wrote about in my previous post. Specifically, I want to address step 4: Exploring patterns in trajectory and event data.The patterns I want to explore in this post are clusters of trip origins. The case study presented here is an extension of the ship data analysis notebook.The analysis consists of 4 steps:. Splitting continuous GPS tracks into individual trips.
Extracting trip origins (start locations). Clustering trip origins. Exploring clustersSince I have already removed AIS records with a speed over ground (SOG) value of zero from the dataset, we can use the splitbyobservationgap function to split the continuous observations into individual trips. Trips that are shorter than 100 meters are automatically discarded as irrelevant clutter:trajcollection.minlength = 100trips = trajcollection.splitbyobservationgap(timedelta(minutes=5))The split operation results in 302 individual trips. A few months ago, we proposed to the to make improvements to the snap cache in QGIS.
The community vote selected our project which was funded by QGIS.org. Developments are now mostly finished.In short, snapping is crucial for editing geospatial features. It is the only way to ensuring they are topologically related, ie, connected vertices have exactly the same coordinates even if manual digitizing on screen is imprecise by nature. Snapping correctly supposes QGIS have in memory an indexed cache of the geometries to snap to. And maintainting this cache when data is modified, sometimes by another user or database logic, can be a real challenge. This it exactly what this work adresses.The proposal was divided into two different tasks:.
Manage circular dependencies. Relax the snap cache index buildManage cicular data dependencies Data dependenciesData dependency is an existing feature that allows you to configure QGIS to reload layers (and their snapping cache) when a layer is modified.It is useful when you store your data in a database and you set up triggers to maintain consistency between the different tables of your data model.For instance, say you have topological informations containing lines and nodes.
Nodes are part of lines and lines go through nodes. Then, you move a node in QGIS, and save your modifications to the database. In order to keep the data consistent, a trigger updates the geometry of the line going through the modified node.Node 2 is modified, Line 1 is updated accordinglyQGIS, as a database client, has no information that the line layer currently displayed in the canvas needs to be refreshed after the trigger. Although the map canvas will be up to date, because QGIS fetches data for display without any caching system, the snapping cache is not and you’ll end up with ghost snapping highlights issues.Snapping highlights (light red) differ from real line (orange)Defining a dependency between nodes and lines layers tells QGIS that it has to refresh the line layer when a node is modified.Dependencies configuration: Lines layer will be refreshed whenever Nodes layer is modifiedIt also have to work the other way, modifying a line should update the nodes to ensure they still are on the line.
Circular data dependenciesSo here we are, lines depend on nodes which depend on lines which depend on nodes whichThat’s what circular dependencies is about. This specific behavior was previously forbidden and needed a special way to deal with it.
Thanks to this, it is now possible.It’s also possible to add the layer itself as one of its own dependencies. It helps dealing with specific cases where one feature modification could lead to a modification of another feature in the same layer (to keep consistency on road networks for instance).Road 2 is modified, Road 1 is updated accordinglyThis feature is available in the next QGIS LTR version 3.10. Relax the snapping cache index buildIf you work in QGIS with huge projects displaying a lot of vector data, and you enable snapping while editing these data, you probably already met this dialog:Snap indexing dialogThis dialog informs you that data are currently being indexed so you can snap on them while you will edit feature geometry. And for big projects, this dialog can last for a really long time. Let’s work on speeding it up! What’s a snap index?Let’s say you want to move a line and snap it onto another one.
While you drag your line with the mouse, QGIS will look for an existing geometry beneath the mouse cursor (with a certain pixel tolerance) every time you move your mouse. Without spatial index, QGIS will have to go through every geometry in your layer to check if the given geometry is beneath the cursor position.
This would be very ineffective.In order to prevent this, QGIS keeps an index where vector data are stored in a way that it can quickly find out what geometry is beneath the mouse cursor. The building of this data structure takes time and that is what the progress dialog is about. Firstly: Parallelize snap index buildIf you want to be able to snap on all layers in your project, then QGIS will have to build one snap index for each layer. This operation was made sequentially meaning that if you have for instance 20 layers and the index building last approximatively 3 seconds for each, then the whole index building will last 1 minute. We made modifications to QGIS so that index building could be done in parallel.
As a result, the total index building time could theoretically be 3 seconds!4 layers snap index being built in parallelHowever, parallel operations are limited by the number of CPU cores of your machine, meaning that if you have 4 cores (core i7 for instance) then the total time will be up to 4 times faster than when the building is sequential (and last 15 seconds in our example). Secondly: relax the snap buildFor big projects, parallelizing index building is not enough and still takes too much time.
Futhermore, to reduce snap index building, an existing optimisation was to build the spatial index for a specific area of interest (determined according to the displayed area and layer size). As a consequence, when you’ve done waiting for an index currently building and you move the map or zoom in/out, you could possibly trigger another snap index building and wait again.So, the idea was to avoid waiting at all. Snap index is now built whenever it needs to (when you first enable snapping, when you move or zoom) but the user doesn’t have to wait for the build to be over and can continue what it was doing (creating feature, moving). Snapping highlights will be missing when the index is currently being built and will appear gradually as soon as they finished.
That’s what we call the relaxing mode.No waiting dialog, snapping highlights appears as soon as snap index is readyThis feature has been merged into current QGIS master and will be present in future QGIS 3.12 release. We keep working on this feature in order to make it more stable and efficient. What’s nextWe’ll continue to improve this feature in the coming days, if you have the chance to test it and encounter issues please let us know on the. If you think about a missing feature or just want to know more about QGIS, feel free to contact us at.
And please have a look at our.Many thanks to QGIS grant program for funding these new features. Thanks also to all the people involved in reviewing the code and helping to better understand the existing mechanism. Exploring new datasets can be challenging. Addressing this challenge, there is a whole field called that focuses on exploring datasets, often with visual methods.Concerning movement data in particular, there’s a comprehensive book on the visual analysis of movement by Andrienko et al. (2013) and a host of papers, such as the recent state of the art summary by Andrienko et al. (2017).However, while the literature does provide concepts, methods, and example applications, these have not yet translated into readily available tools for analysts to use in their daily work.
To fill this gap, I’m working on a template for movement data exploration implemented in Python using.
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