Difference between revisions of "Above-ground biomass estimation in Finland"
| (10 intermediate revisions by the same user not shown) | |||
| Line 7: | Line 7: | ||
==Dataset== | ==Dataset== | ||
| − | The dataset is a georeferenced subset of the | + | The dataset is a georeferenced subset of the [https://nascetti-a.github.io/BioMasster/ BioMassters dataset], containing 11,043 patches representing AGBM in Finnish forests from 2017 to 2021. Ground-truth measurements are obtained with airborne LiDAR. |
| + | |||
Each patch consists of 256×256 pixels, with each pixel covering a 10×10 meter area. The dataset is split into 8,689 training patches and 2,354 testing patches. | Each patch consists of 256×256 pixels, with each pixel covering a 10×10 meter area. The dataset is split into 8,689 training patches and 2,354 testing patches. | ||
| − | |||
| − | == | + | <div style="text-align: center;"> |
| − | < | + | <gallery widths="250" heights="250"> |
| + | File:Biomassters_locations.png|Patch locations by year of data collection | ||
| + | File:Agbm_distributions.png|AGBM distributions in train and test data. The area of each histogram is normalized to sum up to one. | ||
| + | </gallery> | ||
| + | </div> | ||
Latest revision as of 20:33, 26 May 2025
Objective
This subproject evaluates the performance of Tessera representation maps in above-ground biomass (AGBM) estimation in Finnish forests. Accurate AGBM estimation is essential for assessing the carbon sequestration capacity of forests and tracking changes caused by deforestation and recovery.
Dataset
The dataset is a georeferenced subset of the BioMassters dataset, containing 11,043 patches representing AGBM in Finnish forests from 2017 to 2021. Ground-truth measurements are obtained with airborne LiDAR.
Each patch consists of 256×256 pixels, with each pixel covering a 10×10 meter area. The dataset is split into 8,689 training patches and 2,354 testing patches.
Patch locations by year of data collection
AGBM distributions in train and test data. The area of each histogram is normalized to sum up to one.
