The Importance of Adding Short-Wave Infrared Bands for Forest Disturbance Monitoring in the Subtropical Region

Xi Li, Yao Chen (), Shixiong Jiang, Chongqing Wang, Sunxian Weng and Dengyong Rao
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Xi Li: Electric Power Research Institute of State Grid Fujian Electric Power Co., Ltd., Fuzhou 350007, China
Yao Chen: Electric Power Research Institute of State Grid Fujian Electric Power Co., Ltd., Fuzhou 350007, China
Shixiong Jiang: Electric Power Research Institute of State Grid Fujian Electric Power Co., Ltd., Fuzhou 350007, China
Chongqing Wang: Electric Power Research Institute of State Grid Fujian Electric Power Co., Ltd., Fuzhou 350007, China
Sunxian Weng: Electric Power Research Institute of State Grid Fujian Electric Power Co., Ltd., Fuzhou 350007, China
Dengyong Rao: GeoScene Information Technology Co., Ltd., Wuhan 430061, China

Sustainability, 2022, vol. 14, issue 16, 1-9

Abstract: Forest disturbance, such as harvest and fire, can cause a huge amount of carbon emission from soil to the atmosphere. Monitoring forest disturbance at a high spatial resolution is critical for soil carbon modeling. The short-wave infrared bands are important bands in monitoring forest disturbance. However, many high spatial resolution satellites do not contain the short-wave infrared bands in their band designs, and whether the lack of short-wave infrared (SWIR) bands will cause a large influence on forest disturbance monitoring remains unclear. This study aims to evaluate the values of adding SWIR bands in forest disturbance monitoring using the modified continuous monitoring of land disturbance (COLD) approach. Results showed that without the SWIR bands the accuracy of detecting forest disturbance will be reduced by 19–26%. The highest accuracy of modified COLD using the optimal band combination with SWIR bands was 76.3% for monitoring harvest and 86.6% for monitoring fire, while it decreased to 49.8% in detecting harvest and 67.6% in detecting fire without using any SWIR bands. The results demonstrated the importance of adding SWIR bands in forest disturbance monitoring and would guide users to select the satellite data with at least one SWIR band to monitor forest disturbance for improving the soil carbon modeling.

Keywords: soil carbon release; forest disturbance; harvest; fire; SWIR; high resolution satellites; land change (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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