In two campaigns (2016/2017 and 2017/2018), we collected LiDAR transects across the Brazilian Amazon. Some transects were randomly distributed over the forest and secondary forest, some were randomly distributed over the deforestation arch, and others overlapped field plots to allow for model calibration. Each transect covered a minimum of 375 hectares (12.5 km x 300 m) and was surveyed by emitting full-waveform laser pulses from a Trimble Harrier 68i airborne sensor (Trimble; Sunnyvale, CA) aboard a Cessna aircraft (model 206). The average point density was set at four returns per m², the field of view was 30°, the flying altitude was 600 m, and the transect width on the ground was approximately 494 m. Global Navigation Satellite System (GNSS) data were collected on a dual-frequency receiver (L1/L2). The pulse footprint was below 30 cm, based on a divergence angle between 0.1 and 0.3 milliradians. Horizontal and vertical accuracy were controlled to be under 1 m and 0.5 m, respectively. We used the PRODES forest mask (2015) and secondary vegetation (forest regrown after complete forest clearing) from TerraClass (2014) to distribute the transects. To calibrate and validate the airborne LiDAR predictions of biomass, we intentionally overlapped some transects with field plots from 15 research partners. In 2017/2018, we complemented the expanded the transects survey improving the representation of secondary forest based on TerraClass (INPE, 2014). To calibrate and validate the airborne LiDAR predictions of biomass. The metadata about each transect is included in the shapefile hosted at Zenodo repository (https://doi.org/10.5281/zenodo.4968706). To position the transects, we randomly generated center points with X, Y coordinates and assigned a random alpha slope angle to each point. We visually inspected the start points to ensure they were within the forest or secondary vegetation mask. If the start point was not entirely within a forest, as seen by satellite image, we discarded the seed point and selected another one. For each point, we created a shapefile with a 12.5 km x 300 m polygon. For both campaigns, if there were any conflicts with the flight plan (e.g., proximity to an airport or military restrictions), the company making the flights requested repositioning it to the closest allowed area. This deposit delivers data from Maranhão (1 zip file) and Tocantins (1 zip file).

Data were supported by Amazon Fund (grant 14.2.0929.1) and National Academy of Sciences and US Agency for International Development (grant AID-OAA-A-11–00012).