Burning-Corrected Assessment of Crop Residue Coverage Dynamics in Northeast China’s Black Soil Region

Accounting for crop residue burning is essential for reliably assessing crop residue coverage in Northeast China, which is needed to distinguish actual residue retention from surface signals affected by crop residue burning and to evaluate temporal stability in residue coverage patterns. We developed a burning-corrected assessment framework by integrating active-fire observations, multispectral time-series features, and a random forest model to map cropland residue burning from 2013 to 2021, and combined the resulting burned-area layer with corn residue coverage (CRC) data to classify residue coverage patterns. Compared with the VNP64A1 burned-area product, the derived burned-area layer reduced omission errors for burned cropland by 29.28–34.68 percentage points. Without excluding burned pixels, estimated CRC ≥ 30% area was overestimated by 2.16–14.55% across Northeast China and by up to 26.07% in Heilongjiang Province. After burning correction, CRC ≥ 30% area declined until 2018 and then increased, reaching 53.46% of the corn-growing extent in 2021. Across the nine-year period, 41.59% of all pixels were classified as CRC ≥ 30% in only one or two years. These results indicate that accounting for crop residue burning is significant for more reliably monitoring the dynamics of residue coverage.

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Publication Details

Journal
Sustainability
Published
2026-11-11
DOI
https://doi.org/10.3390/su182211496
Primary Topic
Remote Sensing in Agriculture
Type
article
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article

Burning-Corrected Assessment of Crop Residue Coverage Dynamics in Northeast China’s Black Soil Region

Huimin Yan, Wenpeng Du, Zhongen Niu, Bin Wang et al.
Sustainability
Remote Sensing in Agriculture
article

Burning-Corrected Assessment of Crop Residue Coverage Dynamics in Northeast China’s Black Soil Region

Huimin Yan, Wenpeng Du, Zhongen Niu, Bin Wang, Mingyue Sun, Xiaoyong Li, Zongtao Han, Longsheng Wang, Jing Wang, Pan Li
article en

Abstract

Accounting for crop residue burning is essential for reliably assessing crop residue coverage in Northeast China, which is needed to distinguish actual residue retention from surface signals affected by crop residue burning and to evaluate temporal stability in residue coverage patterns. We developed a burning-corrected assessment framework by integrating active-fire observations, multispectral time-series features, and a random forest model to map cropland residue burning from 2013 to 2021, and combined the resulting burned-area layer with corn residue coverage (CRC) data to classify residue coverage patterns. Compared with the VNP64A1 burned-area product, the derived burned-area layer reduced omission errors for burned cropland by 29.28–34.68 percentage points. Without excluding burned pixels, estimated CRC ≥ 30% area was overestimated by 2.16–14.55% across Northeast China and by up to 26.07% in Heilongjiang Province. After burning correction, CRC ≥ 30% area declined until 2018 and then increased, reaching 53.46% of the corn-growing extent in 2021. Across the nine-year period, 41.59% of all pixels were classified as CRC ≥ 30% in only one or two years. These results indicate that accounting for crop residue burning is significant for more reliably monitoring the dynamics of residue coverage.

SustainabilityVol. 18(22)
Shandong University of Technology (CN), Troy University (US), Tianjin University (CN), Ludong University (CN), Chinese Academy of Sciences (CN), Institute of Geographic Sciences and Natural Resources Research (CN), Sichuan Normal University (CN)
Remote Sensing in Agriculture
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