基于CCDC算法的大兴安岭森林扰动监测

doi:10.3969/j.issn.0255-8297.2025.06.006

Abstract

Abstract: The Greater Khingan Mountains serve as a crucial ecological barrier in northern China. Accurately assessing its long-term forest disturbance dynamics is vital for regional ecological supervision and evaluating the effectiveness of the “natural forest protection project”. However, traditional bi-temporal remote sensing change detection methods struggle to capture the complex intra-annual and inter-annual dynamics of large-area forests. This study used the Google Earth Engine (GEE) platform to construct a Landsat time-series stack for the period 2000—2021. To improve monitoring sensitivity to sub-pixel changes such as forest degradation and selective logging, this study first adopted spectral mixture analysis (SMA) to perform per-pixel unmixing of Landsat imagery, generating a normalized difference fraction index (NDFI) sequence. By taking NDFI as the input for the continuous change detection and classification (CCDC) algorithm, a harmonic model was established for each pixel to fit its change trend, and breakpoints in the time series were automatically identified based on statistical thresholds to capture and refine the occurrence time and location of forest disturbances. The results indicate that: 1) During 2000—2021, the total area of forest disturbances was 28 958 km², with disturbance hotspots concentrated in the northeastern part (Huma County) and northwestern part (Mohe County). 2) The annual disturbance area showed significant fluctuations, with peaks in 2002 (4 092 km²) and 2013 (4 120 km²). 3) Accuracy verification shows that the CCDC algorithm has an overall accuracy of over 91% and a Kappa coefficient of 0.85, which is highly consistent with the results of manual interpretation. This study realizes the monitoring of subtle disturbances of forest degradation in the Greater Khingan Mountains region and can provide important data support for the ecological environment monitoring of this region.

Key words: forest disturbance, continuous change detection and classification, monitoring of vegetation change, Google Earth Engine

CLC Number:

S771.8

MU Hongtao, ZHANG Shuo, WANG Shuqing. Monitoring of Forest Disturbance in the Greater Khingan Mountains Based on CCDC Algorithm[J]. Journal of Applied Sciences, 2025, 43(6): 962-977.

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Monitoring of Forest Disturbance in the Greater Khingan Mountains Based on CCDC Algorithm

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