ASSESSMENT OF A RANDOM FOREST CLASSIFIER IN URBAN LOCAL CLIMATE ZONE CLASSIFICATION USING SENTINEL-2 AND PALSAR-2

Chaomin Chen, Hasi Bagan, Xuan Xie, Luwen Tan, Yoshiki Yamagata

研究成果: Conference contribution

抄録

This study evaluated different input features for the local climate zone (LCZ) classification using a random forest (RF) classifier. The input features included spectral reflectance and textural features from Sentinel-2 multi-spectral imagery and polarimetric features from dual-polarized (HH+HV) PALSAR-2 data. The analysis of the feature importance for the RF classifier was measured by Gini and permutation importance. The analysis of the feature contributions to each LCZ class was performed by a feature contribution method based on decision paths in the RF. The results showed that the multi-spectral bands from Sentinel-2 imagery played a dominant role in LCZ classification, especially Band 12 (short-wave infrared-2). The contributions of the PALSAR-2 HV polarization band were higher in land cover LCZ types than in built LCZ types. The combined analysis of feature importance and contribution would provide a reference for the performance of RF classifiers in terms of LCZ mapping.

本文言語English
ホスト出版物のタイトルIGARSS 2021 - 2021 IEEE International Geoscience and Remote Sensing Symposium, Proceedings
出版社Institute of Electrical and Electronics Engineers Inc.
ページ6797-6800
ページ数4
ISBN(電子版)9781665403696
DOI
出版ステータスPublished - 2021
外部発表はい
イベント2021 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2021 - Brussels, Belgium
継続期間: 2021 7月 122021 7月 16

出版物シリーズ

名前International Geoscience and Remote Sensing Symposium (IGARSS)
2021-July

Conference

Conference2021 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2021
国/地域Belgium
CityBrussels
Period21/7/1221/7/16

ASJC Scopus subject areas

  • コンピュータ サイエンスの応用
  • 地球惑星科学(全般)

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