A Structure Feature for Automatic Extraction of Plantation from High-resolution Remote Sensing Imagery

doi:10.11947/j.AGCS.2016.20150511

Abstract

Abstract: Satellite remote sensing is an invaluable tool to manage land resources. However, data analysis procedures should satisfy the good adaptability, wide application prospects and high accuracy levels demanded by users. This study presented a novel multi-scale and multi-direction structure index (MMI) to describe the structure feature of plantation caused by cultivation. Plantation are extracted by performing a threshold on the MMI feature map, and combined with morphological operators to refine the extraction results. We designed three groups of experiments to test our method, each group used panchromatic and multispectral imagery respectively with various cultivation mode, different vegetated background and structure complexity. The results show our method is much more adaptive on plantation extraction than traditional methods. It is efficient for various complex plantations, e.g. multi-direction, multi-scale, highly vegetated backgrounds, low regularity of planting mode with deformation of textons and planting lines, the accuracy results exceed 90%. And panchromatic images achieve accuracies as high as multispectral images, which indicate our method has low dependence on spectrum, thus it is more flexible for data selection and application.

Key words: high resolution, multi-scale and multi-direction, structure feature, plantation, automatic extraction

CLC Number:

P237

YAN Li, JIANG Weiwei. A Structure Feature for Automatic Extraction of Plantation from High-resolution Remote Sensing Imagery[J]. Acta Geodaetica et Cartographica Sinica, 2016, 45(9): 1065-1072.

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