基于摄影测量的云顶高度和云移动速度耦合解算模型研究
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摘要
由卫星资料反演的云顶高度和云移动速度是天气学、气候学的重要科学资料,然而,目前云顶高度和云移动速度解算的精度尚存在较多问题,限制了云顶高度和云移动速度参数的实际应用,如何提高云顶高度和云移动速度已成为卫星气象学的一项待解难题。准确的云顶高度和云移动速度,将会大大提高天气分析和数值预报的质量,具有重要的科学意义。
气象卫星立体像对云顶高度和云移动速度解算方法是一种全新的、高精度的云几何参数解算方法。目前,普遍采用重投影技术先解算云移动速度,并把最大风速或平均风速作为修正项解算云顶高度,其解算精度受重投影的精度限制,并且风速和云顶高度分开解算。本文依据摄影测量理论共线方程,引进了云移动速度参量,建立了云顶高度及云移动速度耦合模型,并给出了云顶高度和云移动速度严密解算算法；针对中分辨率影像云阴影和分辨率不高的特点,提出了基于单通道阈值云(雪)检测和图像增强的相关系数法双向匹配方法。并利用多时次的多角度卫星影像三个角度(AN、AF和AA)的红光影像,建立立体像对,利用云顶高度及云移动速度耦合模型对云区、雪区和云雪混合区的云顶高度和云移动速度进行了解算,得到如下结论：
(1)单通道阈值云(雪)检测法可以有效去除云移动以及云阴影影响,可以提高匹配速度和匹配成功率；利用图像增强方法,增加中分辨率卫星影像云(雪)区信息量,提高同名云(雪)点匹配覆盖率,使得AN、AF和AA影像之间的匹配成功率能达到100%,最大误差不超过2个像元。
(2)NASA认为MISR未考虑风速的云顶高度产品稳定性较好,精度较高,与本文解算结果基本一致,其差值在300米以内；MISR一代考虑风速的云顶高度产品由于采用最大风速作为修正项,解算的云高普遍偏高,而二代考虑风速的云顶高度产品由于采用了平均风速作为修正项,有了明显的改善,与本文解算结果相近。
(3)利用云顶高度及云移动速度耦合模型进行了地面控制点的解算,认为云顶高度及云移动距离理论误差应该在300米左右；通过间接法平差,其估算的云顶高度和云移距离理论中误差也在300米以下；通过与MISR未考虑风速的云顶高度产品对比,其差值在300米以内；MISR二代云顶高度产品与本文解算的云顶高度差值也在300米以内,再次证明本文解算的云顶高度误差为300米；通过11万个云点数据的测试,云顶高度及云移动速度耦合模型稳定性较好,能够有效的区分云雪；通过云雪混合区解算,模型能够有效的区分出云雪；尤其是在纯雪区的解算中,能够有效地识别雪,其解算的误差也在300米。因此,可以认为模型既能解算有较大移动云三维坐标,也可以解算静止的云三维坐标。
(4)通过对地面点风速的解算,其误差在1米／秒左右；解算的连续云点的风向一致,速度相近,也符合地面观测的风向。
(5)利用云顶高度解算总云量,可得到分辨率为275米的总云量产品,并且能够较好的表现出有云区和无云区的细节,对云雪区分较为准确,能够弥补云量产品由于云雪误判而产生的云量估计偏高的不足。
本文的创新点包括：
(1)本文依据摄影测量理论共线方程,建立了云顶高度及云移动速度耦合模型,并研发了云顶高度和云移动速度严密解算算法,实现了云顶高度及云移动速度联立解算,该方法不依赖云的物理特征,为利用中分辨率影像定量解算云顶高度及云移动速度提供全新的方法。
(2)本文详细分析相关系数法、最小二乘法和松弛法在多角度影像同名云点匹配存在的问题,针对中分辨率影像云阴影和分辨率不高的特点,提出了基于单通道阈值云(雪)检测和图像增强的相关系数法双向匹配方法。
Cloud-top-height and cloud-vector retrieved by satellite data are two kinds of important data in synoptic meteorology and climatology. However, there are still a lot of problems existed in the calculation of Cloud-top-height and cloud-vector, which limits the application of Cloud-top-height and cloud-vector. Now, how to improve cloud-top-height and cloud-vector has become a crucial question to be solved. More accuracy cloud-top-height and cloud-vector could highly improve the quality of weather analysis and mathematical forecast, which means a lot to scientific research.
The calculation method of cloud-top-height and cloud-vector by using stereogram based on meteorological satellite is a new and highly precise calculation method based on geometrical parameters. Currently, cloud-top-height is solved by using re-projection firstly, then by using maximum wind speed or average wind speed as correction term. The accuracy of this method is limited by the accuracy of re-projection, and wind speed and cloud-top-height is solved, separately.
Based on collinearity equation, this paper introduced the parameter of cloud movement speed, and established the coupling model of cloud-top-height and cloud-vector and the exactly calculation method of cloud-top-height and cloud-vector. Then, this paper offered a bidirectional matching method based on correlation coefficient method, which is based on image intensification and Cloud(Snow) detection according to single channel threshold, owing to the low resolution and the cloud shadows of Medium-Resolution image. We also calculated the cloud-top-height and cloud-vector in cloudy areas, snow areas and cloudy-snow areas by using stereogram constructed by multi-time and multi-angel (AN,AF and AA) satellite images and coupling model of cloud-top-height and cloud-vector. The conclusions are as follows.
(1)Cloud(Snow) detection based on single channel threshold can effectively remove the effect of cloud movement and cloud shadows, and can improve matching speed and matching success rate; the information content of medium resolution satellite image in cloud(snow) areas are added and the rate of coverage in matching homonymy cloud (snow) points is improved by using image enhancement method. Therefore, the matching success rate between AN, AF and AA image can achieve100%, and the maximum error is less than2pixels.
(2)NASA insists that MISR Cloud-top-height products without wind speed is more stable and more precise; the result of the first generation of MISR product is generally higher, because this product takes maximum wind speed as correction term. However, the result of the new generation of MISR product is getting better because it takes average wind speed as correction term.
(3) Used coupling model of cloud-top-height and cloud-vector to calculate the ground control points. The theoretical error of cloud-top-height and cloud-vector is approximately300m, respectively; The mean square error(MSE) in terms of theory of cloud-top-height and cloud-moved-distance is below300meters through adjustment methond of indirect observations; The D-value is almost300m after comparing MISR product without wind with our result; The D-value between second generation of MISR product and our result, is also below300m, which once again proves that the error of cloud-top-height we calculated is300m; Mass data detection proves that coupling model of cloud-top-height and cloud-vector is stable and can be used to distinguish cloud and snow.
(4)The error is approximately1m/s after calculating the wind speed of ground points; the wind direction of continuous cloud points are almost the same, and their wind speed are really close, which consists with the ground observation.
(5)Accomplished total cloud cover product with the resolution of275m, by using cloud-top-height to calculate total cloud cover. This kind of product can not only better perform the details of Cloudy areas and non-cloudy areas, but also distinguish Snow areas with Cloud areas, which can makes up for the high cloud cover caused by the erroneous judgement of snow or cloud.
The creative points of this study include:
(1)Established the coupling model of cloud-top-height and cloud-vector based on collinearity equation and put forward precise calculation method for calculating cloud-top-height and cloud-vector. This method offers a new way to quantitative calculate cloud parameters in Medium-Resolution image, because this method is based on geometric principle rather than physical characteristics of cloud.
(2) Analyzed existed problems in matching homonymy points in multi-angle image when we are respectively using correlation coefficient method, least square method or relaxation method. Owing to the low resolution and the cloud shadows of Medium-Resolution image, we therefore provided a bidirectional matching method based on correlation coefficient method, which is based on image intensification and Cloud(Snow) detection according to single channel threshold.
气象卫星立体像对云顶高度和云移动速度解算方法是一种全新的、高精度的云几何参数解算方法。目前,普遍采用重投影技术先解算云移动速度,并把最大风速或平均风速作为修正项解算云顶高度,其解算精度受重投影的精度限制,并且风速和云顶高度分开解算。本文依据摄影测量理论共线方程,引进了云移动速度参量,建立了云顶高度及云移动速度耦合模型,并给出了云顶高度和云移动速度严密解算算法；针对中分辨率影像云阴影和分辨率不高的特点,提出了基于单通道阈值云(雪)检测和图像增强的相关系数法双向匹配方法。并利用多时次的多角度卫星影像三个角度(AN、AF和AA)的红光影像,建立立体像对,利用云顶高度及云移动速度耦合模型对云区、雪区和云雪混合区的云顶高度和云移动速度进行了解算,得到如下结论：
(1)单通道阈值云(雪)检测法可以有效去除云移动以及云阴影影响,可以提高匹配速度和匹配成功率；利用图像增强方法,增加中分辨率卫星影像云(雪)区信息量,提高同名云(雪)点匹配覆盖率,使得AN、AF和AA影像之间的匹配成功率能达到100%,最大误差不超过2个像元。
(2)NASA认为MISR未考虑风速的云顶高度产品稳定性较好,精度较高,与本文解算结果基本一致,其差值在300米以内；MISR一代考虑风速的云顶高度产品由于采用最大风速作为修正项,解算的云高普遍偏高,而二代考虑风速的云顶高度产品由于采用了平均风速作为修正项,有了明显的改善,与本文解算结果相近。
(3)利用云顶高度及云移动速度耦合模型进行了地面控制点的解算,认为云顶高度及云移动距离理论误差应该在300米左右；通过间接法平差,其估算的云顶高度和云移距离理论中误差也在300米以下；通过与MISR未考虑风速的云顶高度产品对比,其差值在300米以内；MISR二代云顶高度产品与本文解算的云顶高度差值也在300米以内,再次证明本文解算的云顶高度误差为300米；通过11万个云点数据的测试,云顶高度及云移动速度耦合模型稳定性较好,能够有效的区分云雪；通过云雪混合区解算,模型能够有效的区分出云雪；尤其是在纯雪区的解算中,能够有效地识别雪,其解算的误差也在300米。因此,可以认为模型既能解算有较大移动云三维坐标,也可以解算静止的云三维坐标。
(4)通过对地面点风速的解算,其误差在1米／秒左右；解算的连续云点的风向一致,速度相近,也符合地面观测的风向。
(5)利用云顶高度解算总云量,可得到分辨率为275米的总云量产品,并且能够较好的表现出有云区和无云区的细节,对云雪区分较为准确,能够弥补云量产品由于云雪误判而产生的云量估计偏高的不足。
本文的创新点包括：
(1)本文依据摄影测量理论共线方程,建立了云顶高度及云移动速度耦合模型,并研发了云顶高度和云移动速度严密解算算法,实现了云顶高度及云移动速度联立解算,该方法不依赖云的物理特征,为利用中分辨率影像定量解算云顶高度及云移动速度提供全新的方法。
(2)本文详细分析相关系数法、最小二乘法和松弛法在多角度影像同名云点匹配存在的问题,针对中分辨率影像云阴影和分辨率不高的特点,提出了基于单通道阈值云(雪)检测和图像增强的相关系数法双向匹配方法。
Cloud-top-height and cloud-vector retrieved by satellite data are two kinds of important data in synoptic meteorology and climatology. However, there are still a lot of problems existed in the calculation of Cloud-top-height and cloud-vector, which limits the application of Cloud-top-height and cloud-vector. Now, how to improve cloud-top-height and cloud-vector has become a crucial question to be solved. More accuracy cloud-top-height and cloud-vector could highly improve the quality of weather analysis and mathematical forecast, which means a lot to scientific research.
The calculation method of cloud-top-height and cloud-vector by using stereogram based on meteorological satellite is a new and highly precise calculation method based on geometrical parameters. Currently, cloud-top-height is solved by using re-projection firstly, then by using maximum wind speed or average wind speed as correction term. The accuracy of this method is limited by the accuracy of re-projection, and wind speed and cloud-top-height is solved, separately.
Based on collinearity equation, this paper introduced the parameter of cloud movement speed, and established the coupling model of cloud-top-height and cloud-vector and the exactly calculation method of cloud-top-height and cloud-vector. Then, this paper offered a bidirectional matching method based on correlation coefficient method, which is based on image intensification and Cloud(Snow) detection according to single channel threshold, owing to the low resolution and the cloud shadows of Medium-Resolution image. We also calculated the cloud-top-height and cloud-vector in cloudy areas, snow areas and cloudy-snow areas by using stereogram constructed by multi-time and multi-angel (AN,AF and AA) satellite images and coupling model of cloud-top-height and cloud-vector. The conclusions are as follows.
(1)Cloud(Snow) detection based on single channel threshold can effectively remove the effect of cloud movement and cloud shadows, and can improve matching speed and matching success rate; the information content of medium resolution satellite image in cloud(snow) areas are added and the rate of coverage in matching homonymy cloud (snow) points is improved by using image enhancement method. Therefore, the matching success rate between AN, AF and AA image can achieve100%, and the maximum error is less than2pixels.
(2)NASA insists that MISR Cloud-top-height products without wind speed is more stable and more precise; the result of the first generation of MISR product is generally higher, because this product takes maximum wind speed as correction term. However, the result of the new generation of MISR product is getting better because it takes average wind speed as correction term.
(3) Used coupling model of cloud-top-height and cloud-vector to calculate the ground control points. The theoretical error of cloud-top-height and cloud-vector is approximately300m, respectively; The mean square error(MSE) in terms of theory of cloud-top-height and cloud-moved-distance is below300meters through adjustment methond of indirect observations; The D-value is almost300m after comparing MISR product without wind with our result; The D-value between second generation of MISR product and our result, is also below300m, which once again proves that the error of cloud-top-height we calculated is300m; Mass data detection proves that coupling model of cloud-top-height and cloud-vector is stable and can be used to distinguish cloud and snow.
(4)The error is approximately1m/s after calculating the wind speed of ground points; the wind direction of continuous cloud points are almost the same, and their wind speed are really close, which consists with the ground observation.
(5)Accomplished total cloud cover product with the resolution of275m, by using cloud-top-height to calculate total cloud cover. This kind of product can not only better perform the details of Cloudy areas and non-cloudy areas, but also distinguish Snow areas with Cloud areas, which can makes up for the high cloud cover caused by the erroneous judgement of snow or cloud.
The creative points of this study include:
(1)Established the coupling model of cloud-top-height and cloud-vector based on collinearity equation and put forward precise calculation method for calculating cloud-top-height and cloud-vector. This method offers a new way to quantitative calculate cloud parameters in Medium-Resolution image, because this method is based on geometric principle rather than physical characteristics of cloud.
(2) Analyzed existed problems in matching homonymy points in multi-angle image when we are respectively using correlation coefficient method, least square method or relaxation method. Owing to the low resolution and the cloud shadows of Medium-Resolution image, we therefore provided a bidirectional matching method based on correlation coefficient method, which is based on image intensification and Cloud(Snow) detection according to single channel threshold.
引文
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