Integration of Multiple Spectral Data via a Logistic Regression Algorithm for Detection of Crop Residue Burned Areas: A Case Study of Songnen Plain, Northeast China-Reference-Cited by-同舟云学术

Integration of Multiple Spectral Data via a Logistic Regression Algorithm for Detection of Crop Residue Burned Areas: A Case Study of Songnen Plain, Northeast China

Published:2024-05-15 Issue:3 Volume:34 Page:548-563
ISSN:1002-0063
Container-title:Chinese Geographical Science
language:en
Short-container-title:Chin. Geogr. Sci.

Author:

Zhang Sumei,Zhang Yuan,Zhao Hongmei

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s11769-024-1432-y.pdf

Reference57 articles.

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3. Belenguer-Plomer M A, Tanase M A, Chuvieco E et al., 2021. CNN-based burned area mapping using radar and optical data. Remote Sensing of Environment, 260: 112468. doi: https://doi.org/10.1016/j.rse.2021.112468

4. Ben-Ze’ev E, Karnieli A, Agam N et al., 2006. Assessing vegetation condition in the presence of biomass burning smoke by applying the aerosol - free vegetation index (AFRI) on MODIS images. International Journal of Remote Sensing, 27(15): 3203–3221. doi: https://doi.org/10.1080/01431160500177380

5. Campagnolo M, Libonati R, Rodrigues J et al., 2021. A comprehensive characterization of MODIS daily burned area mapping accuracy across fire sizes in tropical savannas. Remote Sensing of Environment, 252: 112115. doi: https://doi.org/10.1016/j.rse.2020.112115

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