QUICKBIRD数据处理及其应用
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摘要
以高分辨率的QUICKBIRD卫星数据为研究对象 ,经反差增强和比值运算 ,使处理后的图像分辨率高且接近真彩色 ,具有较好的识别效果 ;在图像上均匀布设 1 3个地面控制点 (GCP) ,另选取 3个国家三级控制点参与静态GPS外业实测及内业解算 ,平差后各控制点坐标误差在 1cm左右。利用遥感图像处理软件ERMapper6 .2为平台 ,进行二次多项式几何精校正 ,校正时各控制点的RMS值控制在 1个像元以内 ;用 1∶5 0 0地形图对纠正后的图像进行精度检验 ,其点位误差在 1m左右 ,说明纠正后的图像具有较高的精度。本文还对纠正后的遥感图像进行了应用研究 ,结果表明 :各地类的判读精度均很高 ,其综合判对率为 95 .7% ;该图像能将针叶树种和阔叶树种分开 ,树种的识别仍有难度。通过纠正后的图像与已完成的研究区内土地利用现状图进行匹配与精度分析 ,发现土地利用现状图有的区域精度较高 ,但有的区域存在较大误差
This paper focused on the Quickbird data processing and its application.The processed image is up to real color, high resolusion and easy to be identified after contrast enhancement and ratio processing. 13 GCPs placed in the raw image evenly were measured by GPS in the field; another 3 points have also been selected as known points.The error of each measured point is about 1 centimeter, this showed that the GCPs are very accurate. The image was precisely corrected by ER Mapper 6.2, the RMSE were controlled to no more than 1 pixel; 1∶500 topographic map was used to check this corrected image to different appeiccdions, the displacement is about 1 meter, so the corrected image is very precisely. This paper also applied the corrected image to different applications, the result showed: the interpretation ratios of all sorts of land types are very high, but it is still difficult to identify the species of trees on this image; the composite interpretation ratio is 95.7%. The corrected image have been matched to the landuse map and the precision has also been analyzed, the result showed that some present landuse division is not accurate enough.
This paper focused on the Quickbird data processing and its application.The processed image is up to real color, high resolusion and easy to be identified after contrast enhancement and ratio processing. 13 GCPs placed in the raw image evenly were measured by GPS in the field; another 3 points have also been selected as known points.The error of each measured point is about 1 centimeter, this showed that the GCPs are very accurate. The image was precisely corrected by ER Mapper 6.2, the RMSE were controlled to no more than 1 pixel; 1∶500 topographic map was used to check this corrected image to different appeiccdions, the displacement is about 1 meter, so the corrected image is very precisely. This paper also applied the corrected image to different applications, the result showed: the interpretation ratios of all sorts of land types are very high, but it is still difficult to identify the species of trees on this image; the composite interpretation ratio is 95.7%. The corrected image have been matched to the landuse map and the precision has also been analyzed, the result showed that some present landuse division is not accurate enough.
引文
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2 宁小年,吕松棠,杨小勤等.遥感图像处理与应用[M].北京:地震出版社,1995:75～80.
3 章孝灿,黄智才,赵之洪编著.遥感数字图像处理[M].杭州:浙江大学出版社,1997:87.
4 孙家,舒宁,关泽群编著.遥感原理、方法和应用[M ].北京:测绘出版社,1997:195～202.
5 梅安新,彭望,秦其明,等.遥感导论[M ].北京:高等教育出版社,2001:109.
6 林辉,刘泰龙,李际平.遥感技术基础教程[M ].长沙:中南大学出版社,2002.
7 骆剑承,周成虎,杨艳.遥感地学智能图解模型与支持下的土地覆盖/土地利用分类[J].自然资源学报,2001(2):179～183.
8 胡伟平,吴志峰,何建邦.RS与GIS支持下珠江三角洲城镇近期发展对土壤资源利用的影响分析[J].自然资源学报,2002(5):549～555.
9 张定祥,李宪文,刘顺喜,等.基于遥感数据的常熟市耕地资源数量动态变化分析[J].地理与地理信息科学,2003(3):38～41.
10 苏伟,聂宜民,窦城坤.3S技术支持下的县(市)级土地利用数据库变更[J].国土资源科技管理,2003(2):32～35.
11 陈四清,刘纪远,庄大庆,等.基于LandsatTM /ETM数据的锡林河流域土地覆盖变化[J].地理学报,2003(1):45～51.
12 范海生,马蔼乃,李京.采用图像差值法提取土地利用变化信息方法[J].遥感学报,2001(5):75～80.
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