Geometric Correction and Digital Elevation Extraction Using Multiple MTI Datasets

Mercier, Jeffrey Alan; Schowengerdt, Robert A.; Storey, James C.; Smith, Jody L.

doi:10.14358/pers.73.2.133

Cited by 1 publication

(3 citation statements)

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“…where h is the ground vertical extent, d is the footprint diameter, η is the estimated terrain slope, θ is the intersection angle between the terrain aspect and footprint orientation, and a and b are the semi-major and semi-minor axes of each footprint, respectively. The four threshold values of the intersection angle used for choosing the estimation method can be calculated by Equations (8)- (11). The left and right sides of each equation represented the theoretical absolute errors by two methods of the left and right sides of the threshold value in Figure 2, respectively.…”

Section: Terrain Slope Estimation Methodsmentioning

confidence: 99%

“…Hence, we obtained the intersection angle as the difference of the terrain aspect from ASTER GDEM2 and the footprint orientation from GLAS data. Afterward, four threshold values were calculated by substituting the footprint major axis, minor axis, and ground extent into Equations (8)- (11). The optimal footprint diameter was determined by comparing the intersection angle with four threshold angles.…”

Section: Choice Of Footprint Diametermentioning

confidence: 99%

“…Development of space-borne remote sensing techniques has addressed this challenge to some extent [8][9][10]. For instance, the optical stereo photogrammetry and Synthetic Aperture Radar have generated the available global digital elevation models (DEMs) [10,11]. However, complex matching operations must be done to produce DEMs from stereos and the optical images are susceptible to the weather.…”

Section: Introductionmentioning

confidence: 99%

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Application and Validation of a Model for Terrain Slope Estimation Using Space-Borne LiDAR Waveform Data

et al. 2018

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The terrain slope is one of the most important surface characteristics for quantifying the Earth surface processes. Space-borne LiDAR sensors have produced high-accuracy and large-area terrain measurement within the footprint. However, rigorous procedures are required to accurately estimate the terrain slope especially within the large footprint since the estimated slope is likely affected by footprint size, shape, orientation, and terrain aspect. Therefore, based on multiple available datasets, we explored the performance of a proposed terrain slope estimation model over several study sites and various footprint shapes. The terrain slopes were derived from the ICESAT/GLAS waveform data by the proposed method and five other methods in this study. Compared with five other methods, the proposed method considered the influence of footprint shape, orientation, and terrain aspect on the terrain slope estimation. Validation against the airborne LiDAR measurements showed that the proposed method performed better than five other methods (R2 = 0.829, increased by ~0.07, RMSE = 3.596°, reduced by ~0.6°, n = 858). In addition, more statistics indicated that the proposed method significantly improved the terrain slope estimation accuracy in high-relief region (RMSE = 5.180°, reduced by ~1.8°, n = 218) or in the footprint with a great eccentricity (RMSE = 3.421°, reduced by ~1.1°, n = 313). Therefore, from these experiments, we concluded that this terrain slope estimation approach was beneficial for different terrains and various footprint shapes in practice and the improvement of estimated accuracy was distinctly related with the terrain slope and footprint eccentricity.

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Section: Terrain Slope Estimation Methodsmentioning

confidence: 99%

Section: Choice Of Footprint Diametermentioning

confidence: 99%