JOURNAL OF NANJING FORESTRY UNIVERSITY ›› 2023, Vol. 47 ›› Issue (6): 183-191.doi: 10.12302/j.issn.1000-2006.202204048

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Study on spatial and temporal variation of forest fractional vegetation cover in Liyang based on multi-source remote sensing data

WANG Yanfang1(), TAN Lu1, GUO Hongli2, WU Fang2, QI Fei3, MENG Wenting1, XU Yannan1,*()   

  1. 1. College of Forestry and Grassland, Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing 210037, China
    2. Jiangsu Hydrology and Water Resources Investigation Bureau,Nanjing210009, China
    3. Jiangsu Hydraulic Science Institute,Nanjing 210017, China
  • Received:2022-04-20 Revised:2022-06-07 Online:2023-11-30 Published:2023-11-23

Abstract:

【Objective】This research aims to study the accuracy variation of forest fractional vegetation cover (FVC) extraction using images with different spatial resolutions in each season. The results can provide theoretical support and serve as a useful reference for choosing suitable remote sensing images to extract forest FVC. 【Method】 Selecting the forest area in Liyang, Jiangsu Province for the study, several commonly used remote sensing images with different spatial resolutions, such as Sentinel-2, Landsat-8, and MODIS were used to extract FVC based on the dimidiate pixel model. The spatial variability of FVC in different seasons was analyzed by using the semi-variance function. In addition, the confusion matrix was adopted to compare the accuracy of FVC extracted with different resolutions in each season. 【Result】 (1) The semi-variance function could effectively depict the spatial variability of FVC. The seasonal differences in spatial variability of FVC indicated the following order: winter>spring>autumn>summer. (2) Significant differences between FVC extracted using images with different spatial resolution were detected at the water-land junction and the edge of forest patch. The extraction accuracy of FVC with different resolutions indicated the following order: summer>autumn>spring>winter. In summer, the extraction accuracies of FVC using 30, 250 and 500 m resolutions were 90.99%, 76.28% and 76.71%, respectively. (3) The level of vegetation cover could affect the accuracy of FVC extraction significantly. The extraction accuracy for high vegetation cover was greater than that for other cover levels, and accordingly, the accuracy of FVC extracted from low-resolution images was enhanced in summer when vegetation grows abundantly. 【Conclusion】 The need for high-resolution imagery varied with the levels of FVC. It was more practical to extract FVC using low-resolution images in summer. The study findings are useful to improve the accuracy and efficiency of dynamic monitoring for vegetation.

Key words: fractional vegetation cover, Sentinel-2, Landsat-8, moderate-resolution imaging spectroradiometer(MODIS), semi-variance, Liyang,Jingsu Privince

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