Detection and area estimation for photovoltaic panels in urban hyperspectral remote sensing data by an original nmf-based unmixing method

Moussa Sofiane Karoui (1, 2, 3) , Fatima Zohra Benhalouche (1, 2, 3) , Yannick Deville (2) , Khelifa Djerriri (1) , Xavier Briottet (4) , Arnaud Le Bris (5, 6)

1 Centre National des Techniques Spatiales
2 IRAP - Institut de recherche en astrophysique et planétologie
3 LSI - Laboratoire Signaux et Images
4 DOTA, ONERA, Université de Toulouse [Toulouse]
5 LaSTIG - Laboratoire des Sciences et Technologies de l'Information Géographique
6 MATIS - Méthodes d'Analyses pour le Traitement d'Images et la Stéréorestitution

Hyperspectral remote sensing data offer unique opportunities for the characterization of land surface in urban areas. However, no hyperspectral-unmixing based studies have been conducted to automatically detect photovoltaic panels, which represent one of the important components of energy systems in such areas. In this paper, a hyperspectral-unmixing based method is proposed to detect photovoltaic panels and to estimate their areas. This approach is based on an original multiplicative nonnegative matrix factorization (NMF) algorithm with some known photovoltaic panel spectra. The proposed method can be considered as a partial/informed NMF approach. Experiments are conducted on realistic synthetic and real data to evaluate the performance of the proposed approach. In both cases, obtained results show that the proposed method yields much better overall performance than a method from the literature.

Domaines: Sciences de l'ingénieur [physics]; Physique [physics]

Moussa Sofiane Karoui, Fatima Zohra Benhalouche, Yannick Deville, Khelifa Djerriri, Xavier Briottet, et al.. Detection and area estimation for photovoltaic panels in urban hyperspectral remote sensing data by an original nmf-based unmixing method. IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium, Jul 2018, VALENCE, Spain. pp.1640-1643, ⟨10.1109/IGARSS.2018.8518204⟩. ⟨hal-02339360⟩