Julia for Geospatial part 3 – reading, displaying and writing raster data

This is part three of the Julia for Geospatial series. In part one, available here, I introduced Julia and showed you how to install it, plus how to get the packages you will need to work with raster data. In part two, available here, I directly compared the speed of Python and Julia by opening Read more about Julia for Geospatial part 3 – reading, displaying and writing raster data[…]

Julia for Geospatial part 2 – speed test

Last time, I introduced Julia and walked through some basic instructions on how to setup. If you missed it go here. Compared to my first experience of Python, installing Julia was a breeze. In this series I am exploring how suited Julia is for Geospatial programming. This is not to discourage you away from other Read more about Julia for Geospatial part 2 – speed test[…]

Julia for Geospatial Programming part 1 – setting up

The top six programming languages for Data Science, according to the first links returned to me from google are: Python R MATLAB Java Julia Scala When I searched for the top five programming languages for GIS, the top results returned this list: Python JavaScript R SQL (the most undervalued skill in Geospatial today) Java C++/C Read more about Julia for Geospatial Programming part 1 – setting up[…]

Virtual_env

Python for Geospatial work flows, part 3: Virtual Environments

In the summer of 2018 I began a series of posts about setting up Python for anyone who is new to using it. My focus is predominantly on Geospatial Python, but I think the principals should be applicable to any application of Python. If you want a recap then part 1 (setting up in Anaconda) Read more about Python for Geospatial work flows, part 3: Virtual Environments[…]

Google Earth Engine: Sentinel 5P, and the demise of Fusion Tables

Google Earth Engine seems to be updated pretty frequently. Towards the end of 2018, I noticed two interesting things – that some of the Sentinel 5P data is now available and that Google is shutting down Fusion Tables. Fusion Tables will be shut down at the start of December 2019, so you have just under Read more about Google Earth Engine: Sentinel 5P, and the demise of Fusion Tables[…]

up

A look at the growth and the polarity of sentiment of Earth Observation and Remote Sensing since 2008, with Python and Pandas

  About 18 months ago I looked at tweets from Twitter containing the phrases Earth Observation or Remote Sensing. Primarily I did this after the first Future EO event that ESA held. You can have a look at the post here: #FutureEO and twitter data mining With the next future EO event this November I Read more about A look at the growth and the polarity of sentiment of Earth Observation and Remote Sensing since 2008, with Python and Pandas[…]

Community GBDX Notebooks

GBDX notebooks are a great way of acessing a vast array of satellite data. You can get yourself a trial account here: https://notebooks.geobigdata.io/ No more downloading satellite imagery, just process it in the cloud. When you think about the sheer volume of satellite data that Digital Globe has and its size to download, processing it Read more about Community GBDX Notebooks[…]

Time series on Landsat data with Google Earth Engine

Almost a year ago I wrote a post on building time-lapse imagery with Google Earth Engine. It shows how to process the Landsat 8 top of atmosphere collection into an mp4 format. It talks about choosing the path and row and filtering on clouds, selecting the bands and converting to 8 bit imagery. I did Read more about Time series on Landsat data with Google Earth Engine[…]

Python for Geospatial work flows part 2: Use Jupyter Notebooks

In part 1 I looked at how to set up a Python 3 environment for use with Geospatial Workflows. If you want to recap take a look here In part 2 we will look at Jupyter Notebooks. Project Jupyter exists to develop open-source software, open-standards, and services for interactive computing across dozens of programming languages. Read more about Python for Geospatial work flows part 2: Use Jupyter Notebooks[…]

Python for Geospatial work flows part 1: Use anaconda

I have written a lot in the past about using Python for GIS and Earth Observation. If you have not used Python before and you are looking to get started here are a few recommendations to get you up and running. This blog post is for anyone who is new to programming with Python. There Read more about Python for Geospatial work flows part 1: Use anaconda[…]

Sentinel_5P

Sentinel-5P and Python

The data for Sentinel 5P was made available on 11th July 2018. #BreakingSince yesterday #Sentinel5P #opendata is available for downloadWith a resolution of up to 7×3.5 km, it enables detection of air pollution over individual cities.This high spatial resolution is key to locate the origin of pollutants and identifying #pollution hotspots pic.twitter.com/ncoP2ZkCmP — Copernicus EU Read more about Sentinel-5P and Python[…]