I have an older project that used the https://github.com/osm2vectortiles/osm2vectortiles project to generate vector map data in the mbtiles format. I now see the notice about possible intellectual property infringement from Mapbox, so i want to replace it. I'm considering just purchasing an extract from https://openmaptiles.org, but those files also use the mbtiles format. Is the IP issue related to just the vector data storage or the schema of the mbtiles db as well? In other words, have the files available for purchase been updated to use the new vector schema (https://openmaptiles.org/schema/). If so, I assume those files available for purchase are free of potential licensing issues from Mapbox? Thanks!
Files from OpenMapTiles using same mbtiles format for storing tiles and metadata but schema in vector tiles are updated to the new vector schema without license problems.
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I uploaded OSM network to my server. Now, I'm working directly in Postgres (using dBeaver), and the file format is OSM format.
The imported file has a lot of areas outside of Montreal Island. This makes a lot of extra data and slowing the process. For example running the inner join takes like 2 hours.
Also, when I open the OSM file in JOSM, it has a lot of extra information that I don't need it.
Do you know is there any query to limit and clip the data only to the Montreal Island in dBeaver?
I know I can do this in ArcGIS but I prefer working on OSM data directly. Mainly because bringing shapefile to Postgres is tricky and breaking the original file. I prefer to work directly on the original file and not importing it form somewhere else.
I am looking to extract some Point of Interest (POI) data from OpenStreetMap in a tabular format. I have used this link navigated to the relevant country and downloaded the file,
http://download.geofabrik.de/
What I get is a file with the .osm.pbf extension. However, I think it is possible to download the files in other formats like .shp.zip and .osm.bz2. Is there some way that I can convert this data into a tabular format like a CSV file?
I came across a tool called Osmosis which can be used to manipulate data in these formats, but I am not sure if it can be used for this purpose,
https://wiki.openstreetmap.org/wiki/Osmosis
I was able to successfully install in on my Windows machine though.
To be frank, I am not even sure if this gives me what I want.
In essence, what I am looking for is Sri Lankan POI data that contains the following attributes,
https://data.humdata.org/dataset/hotosm_lka_points_of_interest
If the conversion of this file does not give me data in this format, then I am open to other approaches as well? What is the best way to go about acquiring this data?
I found that Google ml engine expects data in cloud storage, big query etc. Is there any way to stream data to ml-engine. For example, imagine that I need to use data in WordPress or Drupal site to create a tensorflow model, say a spam detector. One way is to export the whole data as CSV and upload it to cloud storage using google-cloud--php library. The problem here is that, for every minor change, we have to upload the whole data. Is there any better way?
By minor change, do you mean "when you get new data, you have to upload everything--the old and new data--again to gcs"? One idea is to export just the new data to gcs on some schedule, making many csv files over time. You can write your trainer to take a file pattern and expand it using get_matching_files/Glob or multiple file paths.
You can also modify your training code to start from an old checkpoint and train over just the new data (which is in its own file) for a few steps.
I have found a source for geo data that represents a country, and its constituents. I am building a service where I would like to have a user select a country and then based on that country select an area they would like results from. I am trying to download the data and import it into MongoDB but I am unsure which file format is best to download, and what tools I will need to convert the data to import it. The file options are ESRI file geodatabase, Shapefile, R file, Google Earth (.kmz), Geopackage, and ESRI personal geodatabase. Which one do I choose and what tools do I need for the next step? Is this even the correct approach to having the collection of countries and their states/territories?
Here is the open source data
gadm.org
MongoDB uses a subset of the GeoJSON format for its geo-spatial data. I would look at which formats are closest to that. A quick web-search turned up this tool for converting kml files to GeoJSON.
I am a recent convert to IBM's DashDB, and I considering proposing to use it at my work. My case would greatly be bolstered if I could show good, easy integration for geospatial analytics data, namely loading and performing SQL filtering on geodata currently in .shp or .kml formats. If it would be possible to also export the filtered data into a KML as a result that would be AMAZING.
So, to give a practical example, say I have an .SHP file with all the zipcodes in the US, I want to select the shape for the 02138 zip code and send it to the query-sender in KML format.
Does anyone have experience with that?
Loading .kml file directly to dashDB is currently not possible, as answered by another post here. You may use ArcGIS for Desktop to connect to dashDB if you want to do this.
https://gis.stackexchange.com/questions/141194/importing-and-exporting-kml-into-and-from-dashdb-for-geospatial-analysis
On the other hand, uploading a .shp file is natively supported and is demonstrated in this tutorial below. Note that dashDB requires the upload file to be compressed in .zip, .tar or .gz file formats.
https://www-01.ibm.com/support/knowledgecenter/SS6NHC/com.ibm.swg.im.dashdb.doc/tutorial/analyze-geospatial-data.html
Also, ArcGIS for Desktop should let you use its export features as well.
There are 2 options loading shape files: via the gui ("Load geospatial data") or via the CLPPlus command IDA LOADGEOSPATIALDATA .
Once the data is loaded it resides in the internal geometry format (e.g. as ST_Polygon), and can then be accessed in various formats through spatial functions imbedded in SQL calls. Unfortunately, kml is not one of the formats that dashDB supports as of now - options are GML, WKT, WKB.