CINECA IRIS Institutional Research Information System
IRIS is the IT solution to facilitate the collection and management of data and activities related to research product.
ItalianoThis paper proposes a novel feature-level fusion approach for fire area change detection at a fine level. Two features, including a normalized burn ratio-SWIR (NBRSWIR) fire index based on Landsat-8 OLI SWIR data and the brightness temperature (BT) based on Landsat-8 TIRS data, are combined by using the gradient transfer fusion (GTF) algorithm and a change detection technique to generate a fine fire change map. A real Landsat-8 data set covering a complex fire disaster scenario was utilized to test the performance of the proposed approach. Experimental results demonstrated the effectiveness of the proposed feature-level fusion approach comparing with the reference methods in term of higher separability value and detection accuracy.
| Citation: | Liu, S.; Zheng, Y.; Dalponte, M.; Tong, X. (2019). Feature-level fusion of landsat-8 oli-swir and tirs images for fine burned area change detection. In: IGARSS 2019 - IEEE International Geoscience and Remote Sensing Symposium, Jokohama, Japan, July 28-August 2, 2019. handle: http://hdl.handle.net/10449/57770 |
| Internal authors: | |
| Organization unit: | Department of Sustainable Agro-ecosystems and Bioresources # CRI |
| Authors: | Liu, S.; Zheng, Y.; Dalponte, M.; Tong, X. |
| Title: | Feature-level fusion of landsat-8 oli-swir and tirs images for fine burned area change detection |
| Issue Date: | 2019 |
| Scientific Disciplinary Area: | Settore AGR/05 - Assestamento Forestale E Selvicoltura |
| Language: | English |
| Nature of content: | Contributo in Atti di convegno/Conference paper |
| Appears in Collections: | 03 - Conference object |
Files in This Item:
| File | Description | Type | License | |
|---|---|---|---|---|
| IGARSS-Fusion_for_fire-Final.pdf | N/A | Tutti i diritti riservati (All rights reserved) | Utenti riconosciuti Request a copy |
Copyright © 2020