Tree Canopy Height Map

Welcome to our tree map. We set out to process the available data into a usable, compressed and simplified data set. It keeps an extremely high, usable resolution, yet after reprocessing it is small enough to be used on 32-bit microcontrollers with ease, and within prediction tools to fine tune radio pathing and wind predictions.

You are welcome to download and use the data from here, or through the Tree Canopy API for automated fetching and use. Combined with our Terrain Grid API, you can build a 3D view of the world below your flying device.

Most of the world with a real rocketry presence is covered. If you would like an area adding that is outside what we have processed, please contact us and it shouldn't be a problem.

Download the square File layout and API
Canopy height
3 m1019304661+
At the map centre
54.55000, -2.90000
Canopy height
no trees over 3 m
Within 100 m
no trees over 3 m
Ground
235 m above sea level
Canopy data
Hover over any tree on the map, or tap it on a phone, for its reading. The view is kept in the address bar, so a link opens the same place.

The tree database

Database tiles
369,272
Ground covered
about 31.4 million km²
On disk, compressed
171 GB
Unpacked, about
990 GB
Imagery
2017 to 2020
Updated
30/09/2026
Each database tile is a tenth of a degree square. The heights are the trees as they stood when the satellite imagery was taken, between 2017 and 2020 and mostly 2018 to 2020, so woodland felled or planted since then will not show yet. Where Meta's data has not been imported, the ETH fill-in describes 2020.

Canopy height key

3 to 5 m
5 to 7 m
7 to 10 m
10 to 13 m
13 to 16 m
16 to 19 m
19 to 22 m
22 to 26 m
26 to 30 m
30 to 35 m
35 to 40 m
40 to 46 m
46 to 53 m
53 to 61 m
61 m and over

What the map shows

Every coloured patch is tree canopy at least 3 m tall. The colour is its height, from deep indigo for young woodland and tall hedgerow trees through purple and pink to near white from 30 m up, the tallest stands of all pure white. Close in, each cell is about 3 by 5 metres, enough to pick out a single copse, a line of trees along a stream or the edge of a plantation.

Zoomed out, a pixel covers far more ground than one cell, so it shows two things at once: its colour is the mean height of the trees within it and its strength is how much of it is wooded. Solid forest stays bright, farmland with scattered trees fades to a faint wash, and open moor, water and towns stay clear.

Where the data comes from

The heights come from global canopy height models, which estimate the height of the vegetation from satellite imagery and are trained against airborne laser survey. The main source is Meta and WRI's CHMv2 model, made from imagery at about half a metre and reduced here to the cells above; where that has not been imported, the ETH Global Canopy Height map at 10 m fills in. Heights are held in 15 bands that widen from 2 m at the bottom to 8 m at the top, since the models quote errors of a few metres and a finer step would only record noise.

The database currently covers United Kingdom, Ireland, Europe, United States, Alaska, Canada, New Zealand, Japan, South Africa, Norway, Sweden, Finland (north of 60), Turkey, Australia 1, Australia 2, Australia 3 and Australia 4, and more is added as it is processed. Ground heights come from the same terrain store the line of sight and landing tools use.

Why a rocketry site maps trees

Trees are where rockets get lost. A rocket under a parachute drifts with the wind, and a launch site that looks clear from the flight line can have a plantation a few hundred metres downwind. Seeing where the woods are and how tall they grow shows where a recovery could end up hung in a canopy, how far the drift has to be kept short, and which way a field is safest to fly.

Trees matter to tracking as well. A radio or GPS tracker lying on the ground inside a wood loses most of its range, because the signal has to pass through the trunks and wet leaves around it. The same canopy data is going into the Altimeter Cloud Landing & Radio tool, for the chance of a recovery ending up in trees and for radio paths through woodland.

Use the data in your own projects

Everything on this map is available through the free Tree Canopy API, no key needed: any square up to 30 km across around a point, every cell of about 3 by 5 metres, either as its height band (4-bit) or simply tree or no tree (1-bit), uncompressed or packed with zlib or LZMA. The download panel on the map does the same thing from here: put the cross on your site, choose the size and format, and save the file.

Rough file sizes for each square, type and compression, near Windermere (54°N) over mixed woodland and fields. Rows marked ~ are estimates; the rest are real downloads.

Square4-bit, height bands1-bit, tree or not
RawzlibLZMARawzlibLZMA
1 km40 KB13 KB13 KB10 KB4 KB4 KB
3 km352 KB90 KB82 KB88 KB28 KB23 KB
5 km967 KB~250 KB~230 KB242 KB~70 KB~60 KB
10 km3.8 MB1.0 MB0.9 MB967 KB268 KB217 KB
20 km15.1 MB~4 MB~3.6 MB3.8 MB~1 MB~0.85 MB
30 km33.9 MB~9 MB~8 MB8.5 MB~2.4 MB~1.9 MB
Nearer the equator the raw files shrink (a 30 km 4-bit square is 28.5 MB at 45°N), and dense forest packs less well than open ground: a mostly forested 30 km square in the French Alps came to 9.5 MB with LZMA.

The files are made to be carried by the systems that fly. A rocket flight computer or a drone can hold its launch site's trees in its own memory, a 3 km square of tree or no tree fits in about 23 KB, and check what is below it or within a set distance without any signal at the field. That opens up experiments such as guided and steerable recovery that steers away from woodland, drones picking a clear spot to land, landing warnings sent back to a ground station, and research into how often and where recoveries end up in trees.

For firmware there is a free reader in C, ready to drop into an Arduino sketch, with the LZMA decoder our own Jupiter flight computer uses. The same data is going into our predicted landing tools, so a site survey can show the chance of a landing in trees before anyone flies.

Tree Canopy API   Reader for flight computers (zip)

Questions

How accurate are the heights?

To within a few metres in most woodland. The models are least sure over very tall or very sparse trees and along woodland edges, and anything under 3 m, including scrub, bracken, hedges and tall crops, is treated as no trees.

How old is the data?

It shows the trees as they stood when the satellite imagery was taken: for the Meta data, between 2017 and 2020 and mostly 2018 to 2020, and for the ETH fill-in, 2020. Woodland felled or planted since then will not show yet.

Why is an area blank?

Either there are no trees over 3 m there, or the area is not in the database yet. Hovering says which: it names the canopy data source where there is coverage and says when an area is not in the database.

Canopy height: Version 2 High Resolution Canopy Height Maps by WRI and Meta was accessed in September 2026 from https://registry.opendata.aws/dataforgood-fb-forestsv2. Meta and World Resources Institute (WRI) - 2026. Version 2 High Resolution Canopy Height Maps (CHMv2). Source imagery for CHM © 2016 Vantor, licensed under CC BY 4.0. Where that is not yet in the database: ETH Global Canopy Height 2020, CC BY 4.0, from Lang, N., Jetz, W., Schindler, K. and Wegner, J. D. (2023), A high-resolution canopy height model of the Earth, Nature Ecology & Evolution. Both are reduced here to height bands, which changes them: they are not the original data. Ground height: Terrain Tiles (Mapzen / Tilezen, on AWS Open Data), reduced into resolution tiers by Altimeter Cloud: ArcticDEM terrain data DEM(s) were created from DigitalGlobe, Inc., imagery and funded under National Science Foundation awards 1043681, 1559691, and 1542736; Australia terrain data © Commonwealth of Australia (Geoscience Australia) 2017; Austria terrain data © offene Daten Österreichs – Digitales Geländemodell (DGM) Österreich; Canada terrain data contains information licensed under the Open Government Licence – Canada; Europe terrain data produced using Copernicus data and information funded by the European Union - EU-DEM layers; Global ETOPO1 terrain data U.S. National Oceanic and Atmospheric Administration; Mexico terrain data source: INEGI, Continental relief, 2016; New Zealand terrain data Copyright 2011 Crown copyright (c) Land Information New Zealand and the New Zealand Government (All rights reserved); Norway terrain data © Kartverket; United Kingdom terrain data © Environment Agency copyright and/or database right 2015. All rights reserved; United States 3DEP (formerly NED) and global GMTED2010 and SRTM terrain data courtesy of the U.S. Geological Survey. Imagery © Esri, Maxar, Earthstar Geographics. Map data © OpenStreetMap contributors, OpenTopoMap (CC BY-SA). Place search by Photon (komoot).