title: [Quantification of crop residue burned areas based on burning indices using Landsat 8 image].
abstract: Crop residue burning leads to atmospheric pollution and is an enormous waste of crop residue resource. Crop residue burning can be monitored timely in large regions as the fire points can be recognized through remotely sensed image via thermal infrared bands. However, the area, the detailed distribution pattern and especially the severity of the burning areas cannot be derived only by the thermal remote sensing approach. The burning index, which was calculated with two or more spectral bands at where the burned and unburned areas have distinct spectral characteristics, is widely used in the forest fire investigation. However its potential application for crop residue burning evaluation has not been explored. With two Landsat 8 images that cover a part of the Songnen Plain, three burning indices, i.e., the normalized burned ratio (NBR), the normalized burned ratio incorporating the thermal band (NBRT), and the burned area index (BAI), were used to classify the crop residue burned and unburned areas. The overall classification accuracies were 91.9%, 92.3%, and 87.8%, respectively. The correlation analysis between the indices and the crop residue coverage indicated that the NBR and NBRT were positively correlated with the crop residue coverage (R2 = 0.73 and 0.64, respectively) with linear regression models, while the BAI was exponentially correlated with the crop residue coverage (R2 = 0.68). The results indicated that the use of burning indices in crop residue burning monitoring could quantify crop residue burning severity and provide valuable data for evaluating atmospheric pollution.
authors.forename: Jian-hang
authors.initials: JH
authors.lastname: Ma
authors.forename: Kai-shar
authors.initials: KS
authors.lastname: Song
authors.forename: Zhi-dan
authors.initials: ZD
authors.lastname: Wen
authors.forename: Tian-tian
authors.initials: TT
authors.lastname: Shao
authors.forename: Bo-nan
authors.initials: BN
authors.lastname: Li
authors.forename: Cai
authors.initials: C
authors.lastname: Qi
mesh_terms: D000383:Agriculture; D000397:Air Pollution / Q000032:analysis; D018556:Crops, Agricultural; D005390:Fires; D016014:Linear Models; D063809:Satellite Imagery; D013057:Spectrum Analysis