Planted: a dataset for planted forest identification from multi-satellite time series
arxiv(2024)
Abstract
Protecting and restoring forest ecosystems is critical for biodiversity
conservation and carbon sequestration. Forest monitoring on a global scale is
essential for prioritizing and assessing conservation efforts. Satellite-based
remote sensing is the only viable solution for providing global coverage, but
to date, large-scale forest monitoring is limited to single modalities and
single time points. In this paper, we present a dataset consisting of data from
five public satellites for recognizing forest plantations and planted tree
species across the globe. Each satellite modality consists of a multi-year time
series. The dataset, named , includes over 2M examples of 64 tree label
classes (46 genera and 40 species), distributed among 41 countries. This
dataset is released to foster research in forest monitoring using multimodal,
multi-scale, multi-temporal data sources. Additionally, we present initial
baseline results and evaluate modality fusion and data augmentation approaches
for this dataset.
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