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International Journal of Remote Sensing Volume 36, 2015 - Issue 4
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Articles

Detection of burned areas from mega-fires using daily and historical MODIS surface reflectance

Rui ZhangDepartment of Geographical Sciences, University of Maryland, College Park, MD20742, USACorrespondence[email protected]
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,
John J. QuThe Global Environment and Natural Resources Institute, College of Science, George Mason University, Fairfax, VA22030, USAView further author information
,
Yongqiang LiuCenter for Forest Disturbance Science, USDA Forest Service, Athens, GA30602, USAView further author information
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Xianjun HaoThe Global Environment and Natural Resources Institute, College of Science, George Mason University, Fairfax, VA22030, USAView further author information
,
Chengquan HuangDepartment of Geographical Sciences, University of Maryland, College Park, MD20742, USAView further author information
&
Xiwu ZhanCenter for Satellite Applications and Research (STAR), NESDIS/NOAA, College Park, MD20740, USAView further author information
Pages 1167-1187 | Received 31 May 2014, Accepted 30 Nov 2014, Published online: 23 Feb 2015

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Maitrik Shah, Mehul S Raval, Srikrishnan Divakaran, Debajyoti Dhar & Hasit Parmar. (2023) SAAC-Net: deep neural network-based model for atmospheric correction in remote sensing. International Journal of Remote Sensing 44:23, pages 7365-7389.
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Lara Vilar, Andrea Camia & Jesús San-Miguel-Ayanz. (2015) A comparison of remote sensing products and forest fire statistics for improving fire information in Mediterranean Europe. European Journal of Remote Sensing 48:1, pages 345-364.
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Articles from other publishers (7)

A. F. Militino, H. Goyena, U. Pérez-Goya & M. D. Ugarte. (2024) Logistic regression versus XGBoost for detecting burned areas using satellite images. Environmental and Ecological Statistics 31:1, pages 57-77.
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Tonkla Maneerat. (2022) XAI Approach to Improved and Informed Detection of Burnt Scar. XAI Approach to Improved and Informed Detection of Burnt Scar.
Lanbo Feng, Huashun Xiao, Zhigao Yang & Gui Zhang. (2022) A Multiscale Normalization Method of a Mixed-Effects Model for Monitoring Forest Fires Using Multi-Sensor Data. Sustainability 14:3, pages 1139.
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Lisa Knopp, Marc Wieland, Michaela Rättich & Sandro Martinis. (2020) A Deep Learning Approach for Burned Area Segmentation with Sentinel-2 Data. Remote Sensing 12:15, pages 2422.
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Muhammad Bilal, Majid Nazeer, Janet E. Nichol, Max P. Bleiweiss, Zhongfeng Qiu, Evelyn Jäkel, James R. Campbell, Luqman Atique, Xiaolan Huang & Simone Lolli. (2019) A Simplified and Robust Surface Reflectance Estimation Method (SREM) for Use over Diverse Land Surfaces Using Multi-Sensor Data. Remote Sensing 11:11, pages 1344.
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Ana I.R. Cabral, Sara Silva, Pedro C. Silva, Leonardo Vanneschi & Maria J. Vasconcelos. (2018) Burned area estimations derived from Landsat ETM+ and OLI data: Comparing Genetic Programming with Maximum Likelihood and Classification and Regression Trees. ISPRS Journal of Photogrammetry and Remote Sensing 142, pages 94-105.
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A. Papayannis, A. Argyrouli, A. Bougiatioti, E. Remoundaki, S. Vratolis, A. Nenes, S. Solomos, M. Komppula, E. Giannakaki, J. Kalogiros, R. Banks, K. Eleftheriadis, E. Mantas, E. Diapouli, C.G. Tzanis, S. Kazadzis, I. Binietoglou, L. Labzovskii, J. Vande Hey & C.S. Zerefos. (2017) An overview from hygroscopic aerosols to cloud droplets: The HygrA-CD campaign in the Athens basin. Science of The Total Environment 574, pages 216-233.
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