# FLAIR #2: textural and temporal information for semantic segmentation from multi-source optical imagery

Source: [FLAIR #2: textural and temporal information for semantic segmentation from multi-source optical imagery](<https://www.sota2.com/research/paper/68fa6f6c1e209131cea457ab>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-26T01:19:28.160Z

Authors: Anatol Garioud, Apolline De Wit, Marc Poup\\'ee, Marion Valette, S\\'ebastien Giordano, Boris Wattrelos

Published: 2023-05-23T18:47:19.000Z

## Abstract

The FLAIR #2 dataset hereby presented includes two very distinct types of data, which are exploited for a semantic segmentation task aimed at mapping land cover. The data fusion workflow proposes the exploitation of the fine spatial and textural information of very high spatial resolution (VHR) mono-temporal aerial imagery and the temporal and spectral richness of high spatial resolution (HR) time series of Copernicus Sentinel-2 satellite images. The French National Institute of Geographical and Forest Information (IGN), in response to the growing availability of high-quality Earth Observation (EO) data, is actively exploring innovative strategies to integrate these data with heterogeneous characteristics. IGN is therefore offering this dataset to promote innovation and improve our knowledge of our territories.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2305.14467>)

[PDF](<https://arxiv.org/pdf/2305.14467.pdf>)