GEM-15: Global surface and terrain elevation models (15 meters) from sub-meter optical stereo imagery

Existing open global digital elevation models (DEMs) are limited to 30 m resolution, blur fine-scale urban and canopy structure, and rely on satellite missions flown between 2000 and 2015. We present Google's Global Elevation Models at 15 m (GEM-15), to our knowledge the first openly available near-global multi-layer elevation dataset at 15 m grid spacing. GEM-15 aggregates native 0.5 m optical stereo reconstructions acquired through 2024 (63.2% of mapped tiles primarily from 2022–2024 30 cm Pléiades Neo imagery) and provides four times the spatial sampling density of 30 m baselines, more current representation of the Earth's surface, and higher vertical accuracy over complex canopies, buildings, and steep relief. Alongside the primary 15 m digital surface model (DSM), GEM-15 includes within-cell elevation percentiles (P5, P50, P95), local elevation standard deviation (DSM σz), and a co-registered 15 m bare-earth digital terrain model (DTM) to capture within-cell 3D structure. We evaluate GEM-15 alongside the open 30 m DEMs Copernicus GLO-30, ALOS AW3D30, NASADEM and, for the terrain model, FABDEM against spaceborne GEDI lidar, 12 airborne and drone lidar benchmarks, and 4,071 GNSS CORS stations. Across the lidar benchmarks, the GEM-15 DSM has a 12.3% lower mean tile-debiased root-mean-square error (DRMSE) than Copernicus GLO-30 (3.37 m vs. 3.85 m), rising to 13.7% (3.69 m vs. 4.27 m) for the seven benchmarks with acquisition midpoints from 2021 onward; the margin increases with the reference survey date (Spearman ρ = 0.87 across the 10 non-rainforest campaigns) and reaches 27% for the 2024–2025 New Zealand survey. The co-registered DTM is comparable in accuracy to FABDEM in open terrain and less accurate beneath closed canopy. In repeat surveys at US NEON sites, the 30 m DEMs diverge increasingly from recent lidar, whereas GEM-15 has the lowest DRMSE in every year. The dataset is available under a CC BY 4.0 license at https://developers.google.com/earth-engine/datasets/catalog/projects_climate-and-sustainability_assets_gem-15_v1.

Authors

Publication Details

Published
2026-11-11
DOI
https://doi.org/10.31223/x55n75
Primary Topic
Satellite Image Processing and Photogrammetry
Type
preprint
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
NOV
preprint

GEM-15: Global surface and terrain elevation models (15 meters) from sub-meter optical stereo imagery

Christopher Van Arsdale, Vishal Batchu, Maxim Neumann, Brett Allen et al.
Satellite Image Processing and Photogrammetry
preprint

GEM-15: Global surface and terrain elevation models (15 meters) from sub-meter optical stereo imagery

Christopher Van Arsdale, Vishal Batchu, Maxim Neumann, Brett Allen, Tommy Li, Jie Zhang
preprint en

Abstract

Existing open global digital elevation models (DEMs) are limited to 30 m resolution, blur fine-scale urban and canopy structure, and rely on satellite missions flown between 2000 and 2015. We present Google's Global Elevation Models at 15 m (GEM-15), to our knowledge the first openly available near-global multi-layer elevation dataset at 15 m grid spacing. GEM-15 aggregates native 0.5 m optical stereo reconstructions acquired through 2024 (63.2% of mapped tiles primarily from 2022–2024 30 cm Pléiades Neo imagery) and provides four times the spatial sampling density of 30 m baselines, more current representation of the Earth's surface, and higher vertical accuracy over complex canopies, buildings, and steep relief. Alongside the primary 15 m digital surface model (DSM), GEM-15 includes within-cell elevation percentiles (P5, P50, P95), local elevation standard deviation (DSM σz), and a co-registered 15 m bare-earth digital terrain model (DTM) to capture within-cell 3D structure. We evaluate GEM-15 alongside the open 30 m DEMs Copernicus GLO-30, ALOS AW3D30, NASADEM and, for the terrain model, FABDEM against spaceborne GEDI lidar, 12 airborne and drone lidar benchmarks, and 4,071 GNSS CORS stations. Across the lidar benchmarks, the GEM-15 DSM has a 12.3% lower mean tile-debiased root-mean-square error (DRMSE) than Copernicus GLO-30 (3.37 m vs. 3.85 m), rising to 13.7% (3.69 m vs. 4.27 m) for the seven benchmarks with acquisition midpoints from 2021 onward; the margin increases with the reference survey date (Spearman ρ = 0.87 across the 10 non-rainforest campaigns) and reaches 27% for the 2024–2025 New Zealand survey. The co-registered DTM is comparable in accuracy to FABDEM in open terrain and less accurate beneath closed canopy. In repeat surveys at US NEON sites, the 30 m DEMs diverge increasingly from recent lidar, whereas GEM-15 has the lowest DRMSE in every year. The dataset is available under a CC BY 4.0 license at https://developers.google.com/earth-engine/datasets/catalog/projects_climate-and-sustainability_assets_gem-15_v1.

Satellite Image Processing and Photogrammetry
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Laika access coming soon