More Rigorous Correction of Refraction Effects in Two-media Stereophoto-grammetry

A more rigorous algorithm is presented for correction of refraction effects in two-media stereo photogrammetry. The mid-point of the shortest line segment joining two aerial corresponding rays of a point on an underwater object is used as a photogrammetric intersection point which doesn't exist when the two rays are non-intersecting. As a result, the uncertainty of the intersection point is removed, the positional relationship between the intersection point and the true object point becomes definite, and the refraction correction formula from the intersection point to the true object point can be strictly derived. The bad effect on the refraction correction is firstly analyzed, which caused by that the two rays are non-intersecting. Then the positional relationship between the intersection point and the true object point is studied. After that, the formulas regarding water depth and geodetic coordinates of points on an underwater object are deduced, that is often known as correction of refraction effects. Finally, the algorithm is tested by two experiments using the data of WorldView-2. The results show that the algorithm is suitable for any case in which whether or not the two aerial corresponding rays of an underwater object point are intersecting, and it can significantly improve the measurement accuracy of underwater object's elevation

The model of direct relative orientation with seven constraints for geological landslides measurement and 3D reconstruction

With the development of computer vision and high-precision 3D model reconstruction, used for the measurement and 3D reconstruction of the geological landslides, acquiring a high-precision relative orientation basing multiple images is crucial and the key point to ensuring and improving the accuracy of 3D model and space position. Currently, the conventional relative orientation model includes five independent parameters. For the linear relative orientation model, there are nine parameters to construct the linear space geometric relationship between the imaging and space point. To eliminate the impact of more parameterization and improve the accuracy and stability of solved parameters for the conventional direct relative orientation model, a new relative orientation model with seven constraints is proposed and validated in this paper. The additional constraints are derived from the orthogonal property of the rotation matrix of a stereo imaging pair and associated with the least squares adjustment to obtain a high-precision result of the relative orientation. Through the accuracy assessment using space position, it is revealed that the new proposed model is more advantage for the conventional type of direct relative orientation, especially at 3D model reconstruction and close range photogrammetric and applications for the geological landslides measurement. El modelo de orientación relativa directa con siete restricciones para la medida de deslizamientos de tierra y reconstrucción tridimensional ResumenCon el desarrollo del entorno computacional y la alta precisión del modelo de reconstrucción tridimensional, utilizados para la medida y reconstrucción de desprendimientos geológicos, es crucial la obtención de la orientación relativa de alta precisión basada en imágenes múltiples y es el punto clave para asegurar y mejorar la exactitud del modelo 3D y la posición espacial. Actualmente el modelo de orientación relativa incluye cinco parámetros independientes. En el modelo linear de orientación relativa hay nueve parámetros para construir la relación geométrica espacial linear entre el sondeo y la posición espacial. Para eliminar el impacto de más parametrización y mejorar la exactitud y la estabilidad de los parámetros resueltos el modelo de orientación relativa convencional, este artículo propone y valida un nuevo modelo de orientación relativa con siete restricciones. Las restricciones adicionales se derivan de la propiedad ortogonal de la matriz de rotación de la imagen estéreo y se asocian con el ajuste de los cuadrados mínimos para obtener un resultado de alta precisión de la orientación relativa. Al medir la exactitud con la posición espacial se revela que el nuevo modelo propuesto tiene más ventajas que aquel de orientación relativa directa, especialmente en el modelo de reconstrucción 3D y en las aplicaciones fotográmetricas de rango cercano para la evaluación de desprendimientos geológicos

The model of direct relative orientation with seven constraints for geological landslides measurement and 3D reconstruction

With the development of computer vision and high-precision 3D model reconstruction, used for the measurement and 3D reconstruction of the geological landslides, acquiring a high-precision relative orientation basing multiple images is crucial and the key point to ensuring and improving the accuracy of 3D model and space position. Currently, the conventional relative orientation model includes five independent parameters. For the linear relative orientation model, there are nine parameters to construct the linear space geometric relationship between the imaging and space point. To eliminate the impact of more parameterization and improve the accuracy and stability of solved parameters for the conventional direct relative orientation model, a new relative orientation model with seven constraints is proposed and validated in this paper. The additional constraints are derived from the orthogonal property of the rotation matrix of a stereo imaging pair and associated with the least squares adjustment to obtain a high-precision result of the relative orientation. Through the accuracy assessment using space position, it is revealed that the new proposed model is more advantage for the conventional type of direct relative orientation, especially at 3D model reconstruction and close range photogrammetric and applications for the geological landslides measurement.   El modelo de orientación relativa directa con siete restricciones para la medida de deslizamientos de tierra y reconstrucción tridimensional   Resumen Con el desarrollo del entorno computacional y la alta precisión del modelo de reconstrucción tridimensional, utilizados para la medida y reconstrucción de desprendimientos geológicos, es crucial la obtención de la orientación relativa de alta precisión basada en imágenes múltiples y es el punto clave para asegurar y mejorar la exactitud del modelo 3D y la posición espacial. Actualmente el modelo de orientación relativa incluye cinco parámetros independientes. En el modelo linear de orientación relativa hay nueve parámetros para construir la relación geométrica espacial linear entre el sondeo y la posición espacial. Para eliminar el impacto de más parametrización y mejorar la exactitud y la estabilidad de los parámetros resueltos el modelo de orientación relativa convencional, este artículo propone y valida un nuevo modelo de orientación relativa con siete restricciones. Las restricciones adicionales se derivan de la propiedad ortogonal de la matriz de rotación de la imagen estéreo y se asocian con el ajuste de los cuadrados mínimos para obtener un resultado de alta precisión de la orientación relativa. Al medir la exactitud con la posición espacial se revela que el nuevo modelo propuesto tiene más ventajas que aquel de orientación relativa directa, especialmente en el modelo de reconstrucción 3D y en las aplicaciones fotográmetricas de rango cercano para la evaluación de desprendimientos geológicos

Shallow Water Bathymetry through Two-medium Photogrammetry Using High Resolution Satellite Imagery

This paper develops an automated shallow water bathymetry procedure based on two-medium photogrammetry using high resolution satellite multispectral imagery. In this method, near-infrared band were used for sunglint elimination and rational function model (RFM) was applied for raw DEM generation. By extracting the water-land edge and interpolating edge elevation, water surface position could be determined. An approximation refraction correction model, in which all homonymy lights were regarded as intersect to the same observed point, was adopted to correct the vertical offsets. Experimental results indicate that DEM accuracy of satellite two-medium photogrammetry is better than 20% of the average depth under the circumstance of relatively calm water and rich bottom texture

Aerosol Characterization of Northern China and Yangtze River Delta Based on Multi-Satellite Data: Spatiotemporal Variations and Policy Implications

Horizontal and vertical distributions of aerosol properties in the Taklimakan Desert (TD), North central region of China (NCR),North China Plain(NCP), and Yangtze River Delta (YRD) were investigated by statistical analysis using Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) L3 data from 2007 to 2020, to identify the similarities and differences in atmospheric aerosols in different regions, and evaluate the impact of pollution control policies developed in China in 2013 on aerosol properties in the study area. The aerosol optical depth (AOD) distribution had substantial seasonal and spatial distribution characteristics. AOD had high annual averages in TD (0.38), NCP (0.49), and YRD (0.52). However, these rates showed a decline post-implementation of the long-term pollution control policies; AOD values declined by 5%, 13.8%, 15.5%, and 23.7% in TD, NCR, NCP, and YRD respectively when comparing 2014–2018 to 2007–2013, and by 7.8%, 11.5%, 16%, and 10.4% when comparing 2019–2020 to 2014–2018. The aerosol extinction coefficient showed a clear regional pattern and a tendency to decrease gradually as height increased. Dust and polluted dust were responsible for the changes in AOD and extinction coefficients between TD and NCR and NCP and YRD, respectively. In TD, with change of longitude, dust aerosol first increased and then decreased gradually, peaking in the middle. Similarly in NCP, polluted dust aerosol first increased and then decreased, with a maximum value in the middle. The elevated smoke aerosols of NCP and YRD were significantly higher than those observed in TD and NCR. The high aerosol extinction coefficient values (>0.1 km−1) were mainly distributed below 4 km, and the relatively weak aerosol extinction coefficients (>0.001 km−1) were mainly distributed between 5–8 km, indicating that the high-altitude long-range transport of TD and NCR dust aerosols affects NCP and YRD

Quantitative Inversion Method of Surface Suspended Sand Concentration in Yangtze Estuary Based on Selected Hyperspectral Remote Sensing Bands

The distribution of the surface suspended sand concentration (SSSC) in the Yangtze River estuary is extremely complex. Therefore, effective methods are needed to improve the efficiency and accuracy of SSSC inversion. Hyperspectral remote sensing technology provides an effective technical means of accurately monitoring and quantitatively inverting SSSC. In this study, a new framework for the accurate inversion of the SSSC in the Yangtze River estuary using hyperspectral remote sensing is proposed. First, we quantitatively simulated water bodies with different SSSCs using sediment samples from the Yangtze River estuary, and analyzed the spectral characteristics of water bodies with different SSSCs. On this basis, we compared six spectral transformation forms, and selected the first derivative (FD) transformation as the optimal spectral transformation form. Subsequently, we compared two feature band extraction methods: the successive projections algorithm (SPA) and the competitive adaptive reweighted sampling (CARS) method. Then, the partial least squares regression (PLSR) model and back propagation (BP) neural network model were constructed. The BP neural network model was determined as the best inversion model. The new FD-CARS-BP framework was applied to the airborne hyperspectral data of the Yangtze estuary, with R2 of 0.9203, RPD of 4.5697, RMSE of 0.0339 kg/m3, and RMSE% of 8.55%, which are markedly higher than those of other framework combination forms, further verifying the effectiveness of the FD-CARS-BP framework in the quantitative inversion process of SSSC in the Yangtze estuary

Aerosol Characterization of Northern China and Yangtze River Delta Based on Multi-Satellite Data: Spatiotemporal Variations and Policy Implications

Horizontal and vertical distributions of aerosol properties in the Taklimakan Desert (TD), North central region of China (NCR),North China Plain(NCP), and Yangtze River Delta (YRD) were investigated by statistical analysis using Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) L3 data from 2007 to 2020, to identify the similarities and differences in atmospheric aerosols in different regions, and evaluate the impact of pollution control policies developed in China in 2013 on aerosol properties in the study area. The aerosol optical depth (AOD) distribution had substantial seasonal and spatial distribution characteristics. AOD had high annual averages in TD (0.38), NCP (0.49), and YRD (0.52). However, these rates showed a decline post-implementation of the long-term pollution control policies; AOD values declined by 5%, 13.8%, 15.5%, and 23.7% in TD, NCR, NCP, and YRD respectively when comparing 2014–2018 to 2007–2013, and by 7.8%, 11.5%, 16%, and 10.4% when comparing 2019–2020 to 2014–2018. The aerosol extinction coefficient showed a clear regional pattern and a tendency to decrease gradually as height increased. Dust and polluted dust were responsible for the changes in AOD and extinction coefficients between TD and NCR and NCP and YRD, respectively. In TD, with change of longitude, dust aerosol first increased and then decreased gradually, peaking in the middle. Similarly in NCP, polluted dust aerosol first increased and then decreased, with a maximum value in the middle. The elevated smoke aerosols of NCP and YRD were significantly higher than those observed in TD and NCR. The high aerosol extinction coefficient values (>0.1 km−1) were mainly distributed below 4 km, and the relatively weak aerosol extinction coefficients (>0.001 km−1) were mainly distributed between 5–8 km, indicating that the high-altitude long-range transport of TD and NCR dust aerosols affects NCP and YRD

Quantitative Inversion Method of Surface Suspended Sand Concentration in Yangtze Estuary Based on Selected Hyperspectral Remote Sensing Bands

The distribution of the surface suspended sand concentration (SSSC) in the Yangtze River estuary is extremely complex. Therefore, effective methods are needed to improve the efficiency and accuracy of SSSC inversion. Hyperspectral remote sensing technology provides an effective technical means of accurately monitoring and quantitatively inverting SSSC. In this study, a new framework for the accurate inversion of the SSSC in the Yangtze River estuary using hyperspectral remote sensing is proposed. First, we quantitatively simulated water bodies with different SSSCs using sediment samples from the Yangtze River estuary, and analyzed the spectral characteristics of water bodies with different SSSCs. On this basis, we compared six spectral transformation forms, and selected the first derivative (FD) transformation as the optimal spectral transformation form. Subsequently, we compared two feature band extraction methods: the successive projections algorithm (SPA) and the competitive adaptive reweighted sampling (CARS) method. Then, the partial least squares regression (PLSR) model and back propagation (BP) neural network model were constructed. The BP neural network model was determined as the best inversion model. The new FD-CARS-BP framework was applied to the airborne hyperspectral data of the Yangtze estuary, with R2 of 0.9203, RPD of 4.5697, RMSE of 0.0339 kg/m3, and RMSE% of 8.55%, which are markedly higher than those of other framework combination forms, further verifying the effectiveness of the FD-CARS-BP framework in the quantitative inversion process of SSSC in the Yangtze estuary

Monitoring and Analysis of Water Level–Water Storage Capacity Changes in Ngoring Lake Based on Multisource Remote Sensing Data

Mastering the fluctuation of water levels and the water storage capacity of plateau lakes is greatly important for monitoring the water balance of the Tibetan Plateau and predicting regional and global climate change. The water level of plateau lakes is difficult to measure, and the ground measured data of long-time series are difficult to obtain. Ngoring Lake is considered in this study, using spaceborne single-photon lidar ICESat-2/ATL13 inland lake standard data products, the water level values provided by Hydroweb laboratory, and the image data of an optical remote sensing satellite. A new method is proposed in the absence of measured data. The method uses multisource remote sensing data to estimate the long-term changes in the water levels, surface area, and water storage capacity of Ngoring Lake in the past three decades. The results show that the water level values of ICESat-2 and Hydroweb on overlapping observation days are highly correlated, with R2 = 0.9776, MAE = 0.420 m, RMSE = 0.077 m, and the average absolute height difference is 0.049 m. The fusion of multiple altimetry data can obtain more continuous long-time series water-level observation results. From 1992 to 2021, the water body information of Ngoring Lake basin fluctuated greatly and showed different variation characteristics in different time periods. The lowest water level in January 1997 was approximately 4268.49 m, and it rose to its highest in October 2009, approximately 4272.44 m. The change in the water level in the basin was mainly affected by natural factors, such as precipitation, air temperature, and human activities. The analysis shows that ICESat-2 can be combined with other remote sensing data to realize the long-time series dynamic monitoring of plateau lakes, showing great advantages in the comprehensive observation of plateau lakes in no man’s land