Remote sensing classification method for divided areas applied to Xinjiang vegetation classification

Qingdong Shi; Guanghui Lu; Xiaoling Pan; Subai Anabiek; Chenghu Zhou; Shunli Chang

doi:10.1117/12.466718

14 July 2003 Remote sensing classification method for divided areas applied to Xinjiang vegetation classification

Qingdong Shi, Guanghui Lu, Xiaoling Pan, Subai Anabiek, Chenghu Zhou, Shunli Chang

Proceedings Volume 4890, Ecosystems Dynamics, Ecosystem-Society Interactions, and Remote Sensing Applications for Semi-Arid and Arid Land; (2003) https://doi.org/10.1117/12.466718
Event: Third International Asia-Pacific Environmental Remote Sensing Remote Sensing of the Atmosphere, Ocean, Environment, and Space, 2002, Hangzhou, China

Abstract

In this paper, the author make up a way of dividing whole remote sensing image into sub images to classify the type of vegetation. There are different types of vegetation in different geographic unit. So according to geographical region feature in a remote sensing image, the whole image is divided to several sub images, the types of vegetation in a sub image is less than in a whole image. Types of vegetation in a region graphic is easy to be showed, the threshold of classifying has a wide scope, with the assistance of Digital Elevation model (DEM) and slope maps, classification accurateness was improved. This way was applied in Xinjiang north, we hold NDVI (Normalized Difference Vegetation Index) image as data resource, dividing whole research area into four regions: Altai grassland region, West Zungaer region, Zhaosu region and East Tianshan region. Different classifying standard was used in different region, and then using GIS software together four regions into a whole classified image. Because this method was grounded on knowledge, the classification result of vegetation in Xinjiang north was improved to 89.33%.

Citation Download Citation

Qingdong Shi, Guanghui Lu, Xiaoling Pan, Subai Anabiek, Chenghu Zhou, and Shunli Chang "Remote sensing classification method for divided areas applied to Xinjiang vegetation classification", Proc. SPIE 4890, Ecosystems Dynamics, Ecosystem-Society Interactions, and Remote Sensing Applications for Semi-Arid and Arid Land, (14 July 2003); https://doi.org/10.1117/12.466718

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KEYWORDS

Vegetation

Remote sensing

Geographic information systems

Image classification

Classification systems

Environmental sensing

Basic research

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