基于SPOT-5多光谱影像的矿区塌塘水体提取方法研究

韩晶; 邓喀中; 李北城; 范洪冬

基于SPOT-5多光谱影像的矿区塌塘水体提取方法研究

韩晶^{1, 2},
邓喀中^{1, 2},
李北城¹,
范洪冬^{1, 2}

1.
中国矿业大学环境与测绘学院，江苏徐州221116
2.
中国矿业大学国土环境与灾害监测国家测绘局重点实验室，江苏徐州221116

基金项目:

国家自然科学基金资助项目(41071273)

高等学校博士学科点专项科研基金资助课题(20090095110002)

中央高校基本科研业务费专项资金资助项目(2010QNA21)

矿山空间信息技术国家测绘局重点实验室（河南理工大学，河南

详细信息

中图分类号: TD67
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出版历程
- 刊出日期: 2012-12-10

Research of Water Body Extraction Methods of Mining Area Collapsed Pond Based on SPOT-5 Multispectral Image

HAN Jing^{1, 2},
DENG Ka-zhong^{1, 2},
LI Bei-cheng¹,
FAN Hong-dong^{1, 2}

1.
School of Environment Science and Spatial Informatics of CUMT., Xuzhou 221116, China. 2.Key Laboratory for Land Environment and Disaster Monitoring of SBSM of CUMT., Xuzhou 221116, China

摘要

摘要: 针对基于遥感影像的水体提取方法存在水体提取不完整和误提的现象，提出了一种基于SPOT-5多光谱影像的矿区塌塘水体提取方法。在利用波段合成增加一个可用波段的基础上对已有的水体提取方法进行适当的改进，并基于决策树分类器和改进后的方法进行矿区水体的四级提取，保证了水体提取的完整性，同时减少了误提率；最后利用实测数据对水体提取的精度进行了评定。试验结果表明，基于决策树分类器的水体提取方法具有较高的精度，能满足矿区实际应用的需要。
- 矿区塌塘 /
- 水体提取 /
- SPOT-5多光谱影像 /
- 决策树分类器 /
- 精度评价
Abstract: For phenomenon of incomplete water extraction and false extraction in existing water extraction method based on remote sensing images, a water extraction method of mining area collapsed pond based on SPOT-5 multispectral images was proposed.On the basis of adding a available band by use of band synthetic, existing water extraction method was improved appropriately, and mining area water body was extracted by decision tree classifier and improved method with four-level extraction, so as to ensure the water body extraction integrity and reduce error rate. Finally, accuracy of the water body extraction was assessed by the extracted data. The test results showed that the water body extraction method based on decision tree classifier has higher accuracy and can meet with demand of practical application in mining area.
- mine area collapsed pond, water body extraction, SPOT-5 multispectral image, decision tree classifier, accuracy assessment /