Mapping the world with Python. Buy my book here - locatepress.com/book/pymaps
Planet Earth
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Ending 2023 with my favourite map. South American forests. See you next year!
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Trying my hand at infographics. Mapping maritime choke points. Unfortunately the publicly available data used to produce this was recorded between 2015 and 2021 - Prior to the Houthis actions in the Red Sea and the war in Iran, which no doubt change this picture.
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I am excited to be representing @SynMaxInt at the #EsriUC2026. If anyone is attending and wants to discuss maps or ships, please get in touch,
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Forest Loss. This map shows forest loss since 2000 in Africa. Defined as a stand-replacement disturbance, or a change from a forest to non-forest state.
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Forest Loss. This map shows forest loss since 2000 in South America. Defined as a stand-replacement disturbance, or a change from a forest to non-forest state.
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Forest Loss. This map shows forest loss since 2000 in Asia. Defined as a stand-replacement disturbance, or a change from a forest to non-forest state.
For those who care - projection is EPSG:27703 is WGS 84 / Equi7 Asia
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Forest Loss. This map shows forest loss since 2000 in Oceania. Defined as a stand-replacement disturbance, or a change from a forest to non-forest state.
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Forest Loss. This map shows forest loss since 2000 in North America. Defined as a stand-replacement disturbance, or a change from a forest to non-forest state.
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Forest Loss. This map shows forest loss since 2000 in Europe. Defined as a stand-replacement disturbance, or a change from a forest to non-forest state.
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This bivariate map uses WRI's Aqueduct 4.0 data to show projected gross water demand (white→orange) vs. blue water availability (blue→purple) under a business-as-usual scenario by 2065–2095.
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This bivariate map uses WRI's Aqueduct 4.0 data to show projected gross water demand (white→orange) vs. blue water availability (blue→purple) under a business-as-usual scenario by 2065–2095.
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This bivariate map uses WRI's Aqueduct 4.0 data to show projected gross water demand (white→orange) vs. blue water availability (blue→purple) under a business-as-usual scenario by 2065–2095.
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This bivariate map uses WRI's Aqueduct 4.0 data to show projected gross water demand (white→orange) vs. blue water availability (blue→purple) under a business-as-usual scenario by 2065–2095.
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This bivariate map uses WRI's Aqueduct 4.0 data to show projected gross water demand (white→orange) vs. blue water availability (blue→purple) under a business-as-usual scenario by 2065–2095.
For those who care - projection is EPSG:27703 is WGS 84 / Equi7 Asia
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This bivariate map uses WRI's Aqueduct 4.0 data to show projected gross water demand (white→orange) vs. blue water availability (blue→purple) under a business-as-usual scenario by 2065–2095.
Inspiration came from this post from @Esri - esri.com/arcgis-blog/product…
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Python Maps retweeted
Average colors of the USA from satellite imagery, by Erin Davis
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Mercury! We may as well continue the series and explore the rest of the rocky worlds in the Solar System.
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Mars
I made this map for Earth last week and you seemed to like it so here is it for Mars, the distribution of elevation levels on the earths surface. I have used a blue-red colourmap to give it the illusion of oceans. Negative values indicate terrain below the Mars areoid — a gravitational reference surface defined where atmospheric pressure equals 610.5 Pa (the triple point of water) — which serves as the zero-elevation datum in place of a sea level.
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