汪沛, 张俊雄, 兰玉彬, 周志艳, 罗锡文. 多光谱低空遥感图像光照辐射度校正[J]. 农业工程学报, 2014, 30(19): 199-206. DOI: doi:10.3969/j.issn.1002-6819.2014.19.024
    引用本文: 汪沛, 张俊雄, 兰玉彬, 周志艳, 罗锡文. 多光谱低空遥感图像光照辐射度校正[J]. 农业工程学报, 2014, 30(19): 199-206. DOI: doi:10.3969/j.issn.1002-6819.2014.19.024
    Wang Pei, Zhang Junxiong, Lan Yubin, Zhou Zhiyan, Luo Xiwen. Radiometric calibration of low altitude multispectral remote sensing images[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2014, 30(19): 199-206. DOI: doi:10.3969/j.issn.1002-6819.2014.19.024
    Citation: Wang Pei, Zhang Junxiong, Lan Yubin, Zhou Zhiyan, Luo Xiwen. Radiometric calibration of low altitude multispectral remote sensing images[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2014, 30(19): 199-206. DOI: doi:10.3969/j.issn.1002-6819.2014.19.024

    多光谱低空遥感图像光照辐射度校正

    Radiometric calibration of low altitude multispectral remote sensing images

    • 摘要: 为了提高受云层阴影影响的遥感图像的信息提取准确度,该文以水稻小区试验过程中为进行氮素水平检测而采集的低空机载高分辨率多光谱遥感图像为对象,对受云层阴影影响的高光谱图像进行光谱校正,从而提高氮素水平检测的精度。试验中采用机载的双摄像机同步采集可见光和近红外的水稻遥感图像,并将两摄像机的图像进行几何校正后合成得到彩红外(color infrared, CIR)光谱图像;同时在图像采集区域布置3块不同反射率的1.2 m×1.2 m标定靶,利用便携式光谱仪测定标定靶的反射光谱曲线,并统计标定靶在图像中各通道的亮度均值。以标定靶在晴天无云和有云图像中的亮度值为节点,对G、R和近红外(near infrared, NIR)通道分别建立分段的线性变换模型进行校正。为验证校正精度,在遥感图像中分别选择大田水稻、小区试验田块和裸地3个不同区域的图像的G、R和NIR通道像素亮度均值及归一化植被指数(normalized differential vegetation index, NDVI)作为评价指标。试验结果表明,和传统的整体线性变换相比,采用分段线性变换校正具有较高精度,G、R和NIR通道校正后的平均误差为8.6%,9.1%和11.7%,NDVI平均误差为11.5%,有效提高了阴影条件下的遥感图像的信息提取精度,提高了受云层影响遥感图像的利用率。研究为低空遥感的图像校正提供了参考。

       

      Abstract: Abstract: The small size and low cost micro-UAV information acquisition technology platforms have been widely applied in agricultural field in recent years. It has become the inevitable trend of development of precision agriculture and has offered a fast and flexible way to acquire data for crop management and monitoring, capable of timely provision of high resolution images. The key technology for remote Sensing information acquisition based on micro UAV in the world, which includes the development of micro UAV remote sensing platforms, information acquisition technology, image processing, and analysis and application of crop management, is reviewed in this paper. Micro UAV mainly has two types: rotor helicopter and fixed-wing aircraft. The rotor helicopter has been used more widely in acquiring information of the field, because it has the ability of taking off and landing vertically, fixed-point hovering, and slow cruising. Japan was the first country that has used the micro-UAV in agricultural production, and is one of the countries that have the best and most mature technologies in using remote UAV in agriculture today. The United States, Netherlands, Israel, and the United Kingdom also have a very good development all over the world. The beginning of research and development of micro UAV in China was much later than the other developed countries, but it has a booming development and grows rapidly. In this paper, parameters and characteristics of different models of the micro UAVs from eight companies in China have been listed for comparison. In remote sensing information acquiring systems, due to the limited load capacity of micro-UAV, digital camera and light-weight multispectral camera are two main instruments that are used on micro UAV for remote sensing information acquiring. How to adjust the posture of airborne remote sensors quickly and accurately so that the detecting target is always in the center of monitoring view, and how to realize remote controlling, image and information capturing, and transmission wirelessly are some of the focuses of UAV remote sensing technology at present. Limited by the stability and load capacity of the micro UAV, the remote sensing image always appears with the defects including a small view, large angle inclination, and serious irregular image overlap. So, solving the problem of correction, matching, mosaicing, fusing, and analyzing of the remote sensing images is one of the most important research work in this field. Nowadays, the main application of micro UAV focuses on the detection of growing nitrogen levels and the generation of fertilization strategy for rice, cotton, and other staple crops. However, the usage of micro UAV is limited due to the following defects: 1) its small size, making it easily influenced by wind, and short battery life; 2) poor accuracy of navigation system and balance control system; 3) serious leakage or reduplication of capturing images caused by the imprecise heading overlapping and routes bending; 4) difficulty of image correcting, matching, mosaicing, fusing, and analyzing for the remote sensing images; 5) the error of UAV equipment and usage is difficult to control. According the review, the further research on key technology focusing on high stability, big load capacity, long life time, and high resolution data for crop management have been proposed. The micro UAV information acquisition platform is a good complement of satellite and aerial remote sensing technologies for monitoring agricultural information and generating prescription maps for precision agriculture.

       

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