An object-based hierarchical classification method for nature reserve land cover classification

被引：0

作者：

Fu Zhuo ^{[1
]}

Liu Xiaolong ^{[2
]}

Xiao Rulin ^{[1
]}

Liu Xiaoman ^{[1
]}

Wen Ruihong ^{[1
]}

Xu Ru ^{[2
]}

机构：

[1] Minist Environm Protect, Satellite Environm Ctr, Beijing, Peoples R China

[2] Yunnan Normal Univ, Coll Tourism & Geog Sci, Kunming, Yunnan, Peoples R China

来源：

2018 2ND INTERNATIONAL WORKSHOP ON RENEWABLE ENERGY AND DEVELOPMENT (IWRED 2018) | 2018年 / 153卷

关键词：

IMAGE-ANALYSIS; SPECTRAL CASI; LIDAR DATA; VEGETATION; FUSION;

D O I：

10.1088/1755-1315/153/6/062026

中图分类号：

X [环境科学、安全科学];

学科分类号：

08 ; 0830 ;

摘要：

This study presents an object-based hierarchical classification method for nature reserve land cover classification using hyperspectral and multi-spectral data. The method firstly extracts several indices to identify non-vegetation land covers that are distinguishable with these indices, and then classify vegetation into grass land and crop. The classified land covers were finally assigned to image objects. In this study we obtained an overall classification accuracy of 95.05, with a Kappa of 0.89, which indicates the potential of this method in nature reserve change monitoring and management.

引用

页数：7

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