Comparison of vegetation classification performances on Putuoshan island using Sentinel-2A MSI and Landsat 8 OLI images

doi:10.13474/j.cnki.11-2246.2019.0326

Abstract

Abstract: Satellite remote sensing technique can be used to investigate resources of sea-islands. Both Sentinel-2A and Landsat 8 satellites freely provide multi-spectral remote sensing images with relatively high spatial resolution which means high potential of sea-island investigation. Taking Putuoshan island, Zhoushan, Zhejiang as example, vegetation classifications on sea-island using images of these two satellites are compared. Based on maximum likelihood classification method, classes of broad-leaved forest, coniferous and broad-leaved mixed forest, coniferous forest, shrub, grassland and other land uses are extracted respectively using Sentinel-2A MSI and Landsat 8 OLI images. And accuracy validation results show that the overall classification accuracy of MSI is a little higher than that of OLI.

Key words: Sentinel-2A, Landsat 8, remote sensing vegetation classification, maximum likelihood, overall classification accuracy

CLC Number:

P237

ZHANG Xiaojie, DENG Yanfen, ZHANG Yachao, JIANG Yunyun, QIU Jufei. Comparison of vegetation classification performances on Putuoshan island using Sentinel-2A MSI and Landsat 8 OLI images[J]. 测绘通报, 2019, 0(10): 97-100.

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