geemap
geoparquet
| geemap | geoparquet | |
|---|---|---|
| 17 | 3 | |
| 3,207 | 723 | |
| 2.2% | 4.1% | |
| 9.2 | 5.5 | |
| 3 days ago | 1 day ago | |
| Python | Python | |
| MIT License | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
geemap
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I'm a senior in my CS major and it's incredible I didn't hear about GIS projects until now. Glad to be here.
Try out Google Earth Engine and browse through it's catalogue to get a feel for what's available. GEE allows you to work with global datasets and immediately see a preview of the results (there's also geemap if you prefer doing this from a Python notebook instead of the online JS editor)
- Getting started with Google Earth Engine
- I'm building an IDE and open source library to make it easier to work with geospatial data using Python
- Opinion on Earth Engine or Planetary Computer?
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Confusion Matrix using Google Earth Engine Python API
Suggest using the ML module from geemap https://geemap.org/ Iv had a lot of success with that library.
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Does anyone use Google Earth Engine?
Check our Jupyter notebook GEEMAP package it's awesome! https://geemap.org/ Just last month Google opened up Google Earth Engine for commerical use. as Microsoft has Planetary Computer now.
- Google Earth Engine Tutorials
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Creating a timelapse of an area with satellite data
This Jupyter notebook package is great for working with Google Earth Engine and does timelapse https://geemap.org/
- Remote sensing class that uses Google Earth Engine worth taking?
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Software suggestion?
Good place to start is: https://geemap.org/
geoparquet
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Friends don't let friends export to CSV
That's why I'm working on the GeoParquet spec [0]! It gives you both compression-by-default and super fast reads and writes! So it's usually as small as gzipped CSV, if not smaller, while being faster to read and write than GeoPackage.
Try using `GeoDataFrame.to_parquet` and `GeoPandas.read_parquet`
[0]: https://github.com/opengeospatial/geoparquet
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COMTiles (Cloud Optimized Map Tiles) hosted on Amazon S3 and Visualized with MapLibre GL JS
GeoParquet
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Postgres and Parquet in the Data Lke
> "Generating Parquet"
It is also useful for moving data from Postgres to BigQuery! ( batch load )
https://cloud.google.com/bigquery/docs/loading-data-cloud-st...
Thanks for the "ogr2ogr" trick! :-)
I hope the next blog post will be about GeoParquet and storing complex geometries in parquet format :-)
https://github.com/opengeospatial/geoparquet
What are some alternatives?
streamlit - Streamlit — A faster way to build and share data apps.
mbtiles-spec - specification documents for the MBTiles tileset format
opentopodata - Open alternative to the Google Elevation API!
odbc2parquet - A command line tool to query an ODBC data source and write the result into a parquet file.
wxee - A Python interface between Earth Engine and xarray for processing time series data
flatgeobuf - A performant binary encoding for geographic data based on flatbuffers
streamlit-geospatial - A multi-page streamlit app for geospatial
postgres_vectorization_test - Vectorized executor to speed up PostgreSQL
Awesome-GEE - A curated list of Google Earth Engine resources
BlenderGIS - Blender addons to make the bridge between Blender and geographic data
flood-sim - This repo simulates water flooding.
parquet_fdw - Parquet foreign data wrapper for PostgreSQL