资源一号02C卫星海岸带影像二级产品质量评价  

Image Quality Evaluation for ZY-1 02C Satellite in Coastal Zone Area

作　　者：王霄鹏[1,2] 张杰[1] 马毅[1] 任广波[1] 

机构地区：[1]国家海洋局第一海洋研究所,山东青岛266061 [2]青岛大学,山东青岛266071

出　　处：《海洋科学进展》2016年第1期129-137,共9页Advances in Marine Science

基　　金：国家自然科学青年基金项目--海岸带遥感影像半监督学习自动化分类方法研究--以黄河三角洲滨海湿地分类为例(41206172);国家科技支撑计划项目--海礁探测与礁盘测量关键技术(2012BAB16B01-02)

摘　　要：为分析资源一号02C卫星在海岸带地区的应用潜力,对其遥感数据成像质量进行评价。采用主观评价和客观评价相结合的评价方法,对资源一号02C卫星P/MS影像二级产品进行质量评价,并与应用广泛且波段设置、空间分辨率相近的SPOT-5影像数据进行对比,分析其在海岸带遥感应用方面的潜力。结果表明:采用目视解译的主观评价显示,资源一号02C全色、多光谱以及融合影像在海岸带典型地物表现能力方面接近SPOT-5影像,而SPOT-5影像颜色过渡更自然,影像纹理和细节信息更丰富。采用统计分析量的客观评价显示,资源一号02C与SPOT-5影像的各统计参数互有高低。就全色影像而言,资源一号02C的信息量较高,而SOPT-5的亮度、灰度离散程度和空间分辨率较高;就多光谱影像而言,SPOT-5的灰度离散程度较高,其他指标无明显规律,不易比较;就融合影像而言,SOPT-5的空间分辨率较高,而资源一号02C的信息量、灰度离散程度和波段间独立性较高。因此,资源一号02C影像数据在一定程度上可以替代SPOT-5影像,在海岸带遥感研究与应用领域具有相当潜力。The ZY-1 02C satellite is a wide-breadth remote sensing satellite with high spatial resolution developed in China. To analyze the application potential of the satellite in coastal zone area, the imaging quality evaluating research on the remote sensing data is necessary. The combined method of subjective evaluation and objective evaluation is used in this research, to evaluate the imagery captured by ZY-1 02C P/MS sensor, and then compared with SPOT-5 imagery data, which is widely used and with similar bands and spatial resolution. The subjective evaluation results of visual interpretation suggests, the performance ability of the multi spectral, panchromatic, and fusion images of ZY-102C satellite is close to SPOT-5 image in typical coastal ground object, while the color transition, texture and detail information of the SPOT- 5 image are better. The objective evaluation results of statistical analysis suggests, the statistical parameters of ZY-1 02C and SPOT-5 images of the cross level. Therefore, the ZY-1 02C image data can replace the SPOT-5 image to a certain extent, and with considerable potential in the coastal zone remote sensing research and application fields.

关 键 词：资源一号02C SPOT-5 海岸带 遥感影像 质量评价 

分 类 号：TP751.1[自动化与计算机技术—检测技术与自动化装置]