| 广东大宝山矿区植被污染信息的遥感识别方法研究 |
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| 引用本文： | 黄铁兰,王耿明,李文胜,等.广东大宝山矿区植被污染信息的遥感识别方法研究[J].地质学刊,2014,38(2):284-288. |
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| 作者姓名： | 黄铁兰 王耿明 李文胜 等 |
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| 作者单位： | 广东省地质调查院 |
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| 基金项目： | 中国地质调查局项目“广东省矿山开发遥感调查与监测”（1212011220081） |
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| 摘 要： | 为了探索遥感技术识别矿山植被污染信息的有效方法,基于ASTER和QuickBird 2种数据源,采用植被指数法和植被绿度法2种方法,对广东大宝山矿区的植被污染信息进行了识别研究。通过不同数据源、不同识别方法的对比分析,为遥感技术识别矿山植被污染信息的推广应用提供了工作思路和科学依据。
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| 关 键 词： | 矿山环境 植被污染 遥感 植被指数 植被绿度 广东韶关 |
| 收稿时间： | 2013/11/8 0:00:00 |
| 修稿时间： | 2013/11/22 0:00:00 |
Study on recognition of vegetation contamination by remote sensing in Dabaoshan mine of Guangdong |
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| HUANG Tie-lan,WANG Geng-ming,LI Wen-sheng,ZHU Jun-feng.Study on recognition of vegetation contamination by remote sensing in Dabaoshan mine of Guangdong[J].Jiangsu Geology,2014,38(2):284-288. |
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| Authors: | HUANG Tie-lan WANG Geng-ming LI Wen-sheng ZHU Jun-feng |
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| Institution: | ( Guangclong Institute of Geological Survey, Guangzhou 510080, China) |
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| Abstract: | In order to explore an effective remote sensing method to mine vegetation contamination recognition, the authors recognized mine vegetation contamination of Dabaoshan mine in Guangdong Province, used the two methods of vegetation index and vegetation greenness, based on ASTER and QuickBird data. Through contrast analysis of different data sources, different recognition methods, the authors could provide a scientific basis and good working thought for the recognition of mine vegetation contamination using remote sensing technology. |
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| Keywords: | Mine environment Vegetation contamination Remote sensing Vegetation index Vegetation greenness Shaoguan Guangdong |
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