Neural-based hierarchical approach for detailed dominant forest species classification by multispectral satellite imagery

Svetlana Illarionova, Alexey Trekin, Vladimir Ignatiev, Ivan Oseledets

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)

Abstract

Among different forest inventory problems, one of the most basic is defining dominant species. These data are crucial in forest management to determine forest category, and a cheaper remote sensing-based approach would be a useful supplement to field surveys. We used WorldView multispectral satellite imagery to address this problem as an image segmentation task dividing the image into regions with particular dominant species. Neural networks have recently become one of the most useful tools for this kind of problem, including incomplete or erroneous training labels. However, it is still challenging to distinguish between such similar patterns as different forest compositions. To handle this, we represented the multiclass forest classification problem as a hierarchical set of binary classification tasks, which allowed us to reach better results with both high- and medium-resolution satellite imagery. We also examined supplementary data, such as tree height, to improve the species classification results for wider tree age diversity. We conducted experiments considering six neural network architectures to find the best one for each task in the hierarchical decomposition. The proposed approach was tested on sample territories in Leningrad Oblast of Russia, for which the field-based observations were acquired and made publicly available as a single dataset. The proposed approach showed significantly better results (average F1-score 0.84) than multiclass classification (average F1-score 0.7).

Original languageEnglish
Article number9311828
Pages (from-to)1810-1820
Number of pages11
JournalIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Volume14
DOIs
Publication statusPublished - 2021

Keywords

  • Convolutional neural network (CNN)
  • forest species classification
  • remote sensing
  • semantic segmentation

Fingerprint

Dive into the research topics of 'Neural-based hierarchical approach for detailed dominant forest species classification by multispectral satellite imagery'. Together they form a unique fingerprint.

Cite this