Arid
DOI10.1016/j.proenv.2011.09.143
Using ALOS High Spatial Resolution Image to Detect Vegetation Patches
Liu, Qingsheng; Liu, Gaohuan; Huang, Chong; Xie, Chuanjie; Shi, Lei
通讯作者Liu, Qingsheng
会议名称3rd International Conference on Environmental Science and Information Application Technology (ESIAT)
会议日期AUG 20-21, 2011
会议地点Xian, PEOPLES R CHINA
英文摘要

Vegetation often exists as patch in arid and semi-arid region. Numbers and areas and locations and spatial structure characteristics of vegetation patch are the important parameters for vegetation function and structure researches in landscape ecology. Visual interpretation of high spatial resolution remote sensing image to study landscape structure characters is often used, which needs lot of time and labours. In this paper, vegetation patches are detected using the canny edge detector and ellipticity measurement based on ALOS fusion image, and the whole processing steps were given. The detection accuracy of the patches is about 89.3%, which is better than that of the methods that only used the spectral difference between vegetation patches and background. The experiments show that integration the canny edge detector with the algorithm for extracting circle and ellipse objects is simple and effective for detecting vegetation patches. (C) 2011 Published by Elsevier Ltd. Selection and/or peer-review under responsibility of Conference ESIAT2011 Organization Committee.


英文关键词ALOS Canny edge detector Vegetation patch ellipticity measurement
来源出版物2011 3RD INTERNATIONAL CONFERENCE ON ENVIRONMENTAL SCIENCE AND INFORMATION APPLICATION TECHNOLOGY ESIAT 2011, VOL 10, PT A
ISSN1878-0296
出版年2011
卷号10
页码896-901
EISBN*****************
出版者ELSEVIER SCIENCE BV
类型Proceedings Paper
语种英语
国家Peoples R China
收录类别CPCI-S
WOS记录号WOS:000312273000143
WOS关键词GRASSLAND
WOS类目Environmental Sciences
WOS研究方向Environmental Sciences & Ecology
资源类型会议论文
条目标识符http://119.78.100.177/qdio/handle/2XILL650/299706
作者单位Chinese Acad Sci, IGSNRR, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China
推荐引用方式
GB/T 7714
Liu, Qingsheng,Liu, Gaohuan,Huang, Chong,et al. Using ALOS High Spatial Resolution Image to Detect Vegetation Patches[C]:ELSEVIER SCIENCE BV,2011:896-901.
条目包含的文件
条目无相关文件。
个性服务
推荐该条目
保存到收藏夹
导出为Endnote文件
谷歌学术
谷歌学术中相似的文章
[Liu, Qingsheng]的文章
[Liu, Gaohuan]的文章
[Huang, Chong]的文章
百度学术
百度学术中相似的文章
[Liu, Qingsheng]的文章
[Liu, Gaohuan]的文章
[Huang, Chong]的文章
必应学术
必应学术中相似的文章
[Liu, Qingsheng]的文章
[Liu, Gaohuan]的文章
[Huang, Chong]的文章
相关权益政策
暂无数据
收藏/分享

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。