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.
ItalianoChange detection from multi-temporal remote sensing images is an effective way to identify the burned areas after forest fires. However, the complex image scenario and the similar spectral signatures in multispectral bands may lead to many false positive errors, which make it difficult to exact the burned areas accurately. In this paper, a novel-burned area change detection approach is proposed. It is designed based on a new Normalized Burn Ratio-SWIR (NBRSWIR) index and an automatic thresholding algorithm. The effectiveness of the proposed approach is validated on three Landsat-8 data sets presenting various fire disaster events worldwide. Compared to eight index-based detection methods that developed in the literature, the proposed approach has the best performance in terms of class separability (2.49, 1.74 and 2.06) and accuracy (98.93%, 98.57% and 99.51%) in detecting the burned areas. Simultaneously, it can also better suppress the complex irrelevant changes in the background.
| Citation: | Liu, S.; Zheng, Y.; Dalponte, M.; Tong, X. (2020). A novel fire index-based burned area change detection approach using Landsat-8 OLI data. EUROPEAN JOURNAL OF REMOTE SENSING, 53 (1): 104-112. doi: 10.1080/22797254.2020.1738900 handle: http://hdl.handle.net/10449/60108 |
| Internal authors: | |
| Organization unit: | Department of Sustainable Agro-ecosystems and Bioresources # CRI |
| Authors: | Liu, S.; Zheng, Y.; Dalponte, M.; Tong, X. |
| Title: | A novel fire index-based burned area change detection approach using Landsat-8 OLI data |
| Journal: | EUROPEAN JOURNAL OF REMOTE SENSING |
| Issue Date: | 2020 |
| Scientific Disciplinary Area: | Settore AGR/05 - Assestamento Forestale E Selvicoltura |
| Keywords ENG: | Change detection Burned area Spectral index NBRSWIR Separation index Landsat-8 OLI |
| Language: | English |
| IF: | With Impact Factor ISI |
| Publication status: | Published |
| Nature of content: | Articolo in rivista/Article |
| Digital Object Identifier (DOI): | http://dx.doi.org/10.1080/22797254.2020.1738900 |
| Appears in Collections: | 01 - Journal article |
Files in This Item:
| File | Description | Type | License | |
|---|---|---|---|---|
| 2020 IJRS Dalponte.pdf | Versione editoriale (Publisher’s layout) |  | Open AccessView/Open |
Copyright © 2020