Mapping burned surfaces in Sub-Saharan Africa based on multi-temporal neural classification-Reference-Cited by-同舟云学术

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Mapping burned surfaces in Sub-Saharan Africa based on multi-temporal neural classification

Published:2003-01 Issue:20 Volume:24 Page:4003-4016
ISSN:0143-1161
Container-title:International Journal of Remote Sensing
language:en
Short-container-title:International Journal of Remote Sensing

Author:

Brivio P. A.¹,Maggi M.²,Binaghi E.³,Gallo I.⁴

Affiliation:

1. a Institute for Electromagnetic Sensing of the Environment (IREA) , CNR 15 Via Bassini, Milan, I-20133, Italy E-mail:

2. b Institute for Electromagnetic Sensing of the Environment (IREA) , CNR 15 Via Bassini, Milan, I-20133, Italy

3. c Universit@ degli Studi dell'Insubria , Varese, Italy

4. d Istituto per le Tecnologie Informatiche Multimediali (ITIM), CNR , Milan, Italy

Publisher

Informa UK Limited

Subject

General Earth and Planetary Sciences

Link

https://www.tandfonline.com/doi/pdf/10.1080/0143116031000103835

Reference37 articles.

1. Tropical forest mapping from coarse spatial resolution satellite data: Production and accuracy assessment issues

2. Burned area mapping system and fire detection system, based on neural networks and NOAA-AVHRR imagery

3. An Algorithm for Extracting Burned Areas from Time Series of AVHRR GAC Data Applied at a Continental Scale

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4. Spectral Characteristic Analysis of Burned Area Based on MODIS Data;The Proceedings of 11th Asia-Oceania Symposium on Fire Science and Technology;2020

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