基于卫星高光谱遥感的水体和林木面积测绘

Area mapping for water and forest based on satellite hyper-spectral remote sensing

  • 摘要: 高光谱卫星的出现和发展为遥感测绘提供了新的技术手段。与传统卫星图像相比,高光谱卫星图像含有更为丰富的光谱信息,能够对目标物进行更为准确的鉴别、分类、定位和测绘。以“珠海1号”高光谱卫星(OHS-C)所提供的高光谱卫星图片为样本,利用地物反射光谱结合自适应算法实现了对林木和水体的精确鉴别、增强标记和面积测量。利用比值法对光谱进行处理,在无需复杂校准的情况下便可去除大气情况及时间季节对光谱的影响。实验结果表明林木和水体鉴别的特异性和灵敏度均高于97%。依据本文设计的鉴别模型,计算得西丽水库官方水域计算总面积数约为4.6 km2,与官方数据的误差仅约为0.1446 km2;计算得淇澳岛的绿化面积为22.1713 km2,该岛总占地面积为23.8 km2,按照90%绿化面积计算得误差小于0.7513 km2,且误差主要源于商用卫星的空间分辨率不足。

     

    Abstract: The emergence and development of hyper-spectral satellites provide a new technical means for remote sensing and mapping. Compared with the traditional satellite images, the hyper-spectral satellite images contain the richer spectral information, which can carry out more accurate identification, classification, positioning and mapping of target objects. Taking the hyper-spectral satellite images provided by the Zhuhai No. 1 hyper-spectral satellite (OHS-C) as the sample, the accurate identification, enhanced marking and area measurement of forest and water were realized by combing ground clutter reflection spectrum with adaptive algorithm. The ratio method was used to process the spectrum, and the influence of atmospheric conditions and time as well as season on the spectrum can be removed without the complex calibration. The experimental results show that the specificity and sensitivity of identification of forest and water is higher than 97%, respectively. Based on the proposed identification model, the calculated total area of the official waters of Xili Reservoir is about 4.6 km2, and the error with the official data is only about 0.144 6 km2. The green area of Qi'ao Island is calculated to be 22.171 3 km2, and the total area of the island is 23.8 km2. According to the calculation of 90% of the green area, the error is less than 0.751 3 km2, and the error mainly comes from the insufficient spatial resolution of commercial satellites.

     

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