A Quadratic Morphological Deep Neural Network Fusing Radar and Optical Data for the Mapping of Burned Areas
Author:
Affiliation:
1. School of Surveying and Geospatial Engineering, College of Engineering, University of Tehran, Tehran, Iran
2. Universite Grenoble Alpes, CNRS, GIPSA-Lab, Grenoble INP, Grenoble, France
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Atmospheric Science,Computers in Earth Sciences
Link
http://xplorestaging.ieee.org/ielx7/4609443/9656571/09775605.pdf?arnumber=9775605
Reference70 articles.
1. Monitoring Wildfires in the Northeastern Peruvian Amazon Using Landsat-8 and Sentinel-2 Imagery in the GEE Platform
2. Integration of Multiple Spectral Indices and a Neural Network for Burned Area Mapping Based on MODIS Data
3. Burned Area Mapping Using Support Vector Machines and the FuzCoC Feature Selection Method on VHR IKONOS Imagery
4. Burned area estimations derived from Landsat ETM+ and OLI data: Comparing Genetic Programming with Maximum Likelihood and Classification and Regression Trees
5. A VIIRS direct broadcast algorithm for rapid response mapping of wildfire burned area in the western United States
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