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.
Image from Python Maps (@PythonMaps)
2
5
29
3,608
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.
Image from Python Maps (@PythonMaps)
3
17
78
5,006
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.
Image from Python Maps (@PythonMaps)
3
20
84
4,878
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
Image from Python Maps (@PythonMaps)
2
6
1
36
4,926
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.
Image from Python Maps (@PythonMaps)
1
11
3
26
30,872
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.
Image from Python Maps (@PythonMaps)
1
12
1
48
4,714
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.
Image from Python Maps (@PythonMaps)
9
22
2
107
23,331
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.
Image from Python Maps (@PythonMaps)
1
23
1
102
6,719
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.
Image from Python Maps (@PythonMaps)
1
1
20
2,796
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.
Image from Python Maps (@PythonMaps)
2
19
87
6,006
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.
Image from Python Maps (@PythonMaps)
2
14
2
69
5,470
Load more