Spaceborne LiDAR Surveying and Mapping

Laser point cloud data have the characteristics of high elevation accuracy, fast processing efficiency, strong three-dimensional (3D) vision, and wide application fields. It will be one of the core datasets of the new generation national global topographic database. The rapid advancement of spaceborne laser earth observation technology allows the collection of global 3D point cloud data, which has brought a new breakthrough in the field of satellite-based earth observation, and its significant advantages of all-day time, high accuracy and high efficiency will lead the future development of space precise mapping technology. This chapter firstly introduces the principle and development status of satellite-based LiDAR technology, then presents the basic technical framework of satellite-based LiDAR 3D mapping, and analyzes the data processing methods of spaceborne photon point clouds, and finally, focuses on the application research in various fields including precise geolocation of combined with satellite images, fusion of multi-source topographic information, polar mapping, 3D objects reconstruction, and shallow sea topographic mapping, etc

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

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

Biases Analysis and Calibration of ICESat-2/ATLAS Data Based on Crossover Adjustment Method

The new-generation photon-counting laser altimeter aboard the Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) has acquired unprecedented high-density laser data on the global surface. The continuous analysis and calibration of potential systematic biases in laser data are important for generating highly accurate data products. Current studies mainly calibrate the absolute systematic bias of laser altimeters based on external reference data. There are few studies that focus on the analysis and calibration of relative systematic biases in long-term laser data. This paper explores a method for systematic biases analysis and calibration of ICESat-2 laser data based on track crossovers for the first time. In the experiment, the simulated data and ICESat-2 data were used to verify the algorithm. The results show that, during the three-year period in orbit, the standard deviation (STD) and bias of the crossover differences of the ICESat-2 terrain data were 0.82 m and −0.03 m, respectively. The simulation validation well demonstrate that the crossover adjustment can calibrate the relative bias between different beams. For ICESat-2 data, the STD of the estimated systematic bias after crossover adjustment was 0.09 m, and the mean absolute error (MAE) was 0.07 m. Compared with airborne lidar data, the bias and root mean square error (RMSE) of the ICESat-2 data remained basically unchanged after adjustment, i.e., −0.04 m and 0.38 m, respectively. This shows that the current ICESat-2 data products possess excellent internal and external accuracy. This study shows the potential of crossover for evaluating and calibrating the accuracy of spaceborne photon-counting laser altimeter data products, in terms of providing a technical approach to generate global/regional high-accuracy point cloud data with consistent accuracy

Biases Analysis and Calibration of ICESat-2/ATLAS Data Based on Crossover Adjustment Method

The new-generation photon-counting laser altimeter aboard the Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) has acquired unprecedented high-density laser data on the global surface. The continuous analysis and calibration of potential systematic biases in laser data are important for generating highly accurate data products. Current studies mainly calibrate the absolute systematic bias of laser altimeters based on external reference data. There are few studies that focus on the analysis and calibration of relative systematic biases in long-term laser data. This paper explores a method for systematic biases analysis and calibration of ICESat-2 laser data based on track crossovers for the first time. In the experiment, the simulated data and ICESat-2 data were used to verify the algorithm. The results show that, during the three-year period in orbit, the standard deviation (STD) and bias of the crossover differences of the ICESat-2 terrain data were 0.82 m and −0.03 m, respectively. The simulation validation well demonstrate that the crossover adjustment can calibrate the relative bias between different beams. For ICESat-2 data, the STD of the estimated systematic bias after crossover adjustment was 0.09 m, and the mean absolute error (MAE) was 0.07 m. Compared with airborne lidar data, the bias and root mean square error (RMSE) of the ICESat-2 data remained basically unchanged after adjustment, i.e., −0.04 m and 0.38 m, respectively. This shows that the current ICESat-2 data products possess excellent internal and external accuracy. This study shows the potential of crossover for evaluating and calibrating the accuracy of spaceborne photon-counting laser altimeter data products, in terms of providing a technical approach to generate global/regional high-accuracy point cloud data with consistent accuracy

On-orbit Geometric Calibration and Preliminary Accuracy Evaluation of GF-14 Satellite

GF-14 satellite is a new generation of sub-meter stereo surveying and mapping satellite in China, carrying dual-line array stereo mapping cameras to achieve 1:10000 scale topographic mapping without Ground Control Points (GCPs). In fact, space-based high-precision mapping without GCPs is a challenging task that depends on the close cooperation of several payloads and links, of which on-orbit geometric calibration is one of the most critical links. In this paper, the on-orbit geometric calibration of the dual-line array cameras of GF-14 satellite was performed using the control points collected in the high-precision digital calibration field, and the calibration parameters of the dual-line array cameras were solved as a whole by alternate iterations of forward and backward intersection. On this basis, the location accuracy of the stereo images using the calibration parameters was preliminarily evaluated by using several test fields around the world. The evaluation result shows that the direct forward intersection accuracy of GF-14 satellite images without GCPs after on-orbit geometric calibration reaches 2.34 meters (RMS) in plane and 1.97 meters (RMS) in elevation

ICESAT-2 Shallow Bathymetric Mapping Based on a Size and Direction Adaptive Filtering Algorithm

The US Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) satellite adopts 532 nm single-photon lidar with shallow sea bathymetry capability. In order to realize high-precision and automated shallow sea bathymetric mapping based on ICESat-2 photon data, an adaptive underwater point denoising algorithm that considers the search direction and search size is proposed in this article, and a detailed data processing process is discussed to further verify the technical feasibility. The accuracy of direct bathymetry and active–passive fusion bathymetry from ICESat-2 is systematically analyzed using airborne in situ data. First, the underwater photon points are separated by surface position identification; then, the signal point cloud search strategy is improved, the search size increases with water depth, the search angle is rotated and the direction of the maximum number of point clouds is taken as the main direction, and the threshold is automatically determined by histogram Gaussian fitting of the point cloud density to achieve automatic underwater signal extraction; then, the refraction correction is carried out based on the light geometry and the water depth is obtained; finally, the active–passive fusion bathymetry is performed by combining the optical remote sensing images WorldView-2 and Sentinel-2, and the accuracy is verified by using the airborne lidar bathymetric data provided by NOAA. The experimental results show that the proposed denoising algorithm can accurately discriminate the underwater signal/noise, and the overall accuracy is better than 86%; the root-mean-square error (RMSE) of ICESat-2 direct bathymetry is between 0.42 and 0.98 m; the RMSE of active–passive fusion bathymetry is between 0.84 and 1.88 m. Our workflow and experimental results demonstrate a means of using ICESat-2 to produce relatively accurate bathymetric maps in shallow, clear water environments