Tiansheng Xu
Biographic Data
| ID | 6746444 |
|---|---|
| NAME | Tiansheng Xu |
| GIVEN NAMES | Tiansheng |
| FAMILY NAME | Xu |
| SIGNATURE | XU T |
| AFFILIATIONS | Capital University of Economics and Business |
| VERIFIED | No |
| TOTAL WORKS | 3 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 3 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2021 |
| LATEST PUBLICATION YEAR | 2022 |
| H-INDEX | 0 |
Image-based approximation of derivatives of traditional differential metrics of angular distortion in map projections
Map projections are imaging procedures used to depict geographic features. We adopt the traditional differential metric and exploit the intrinsic image properties of map projections to establish an image-based differential metric for evaluating distortions in map projections, obtaining an effective, practical, and relatively accurate metric. We use bivariate polynomial functions to approximate the forward and inverse formulae of map projections. …
Image-Based Angular Distortion Metric of Map Projections by Using Surface Fitting for Noise Reduction
Measuring, analyzing, reducing, and optimizing distortions in map projections is important in cartography. In this study, we introduced a novel image-based angular distortion metric based on the previous spherical great circle arcs-based metric. Images with predefined patterns were used to generate distorted images using mapping software. The generated distorted images with known patterns were then exploited to calculate the proposed angular dist…
Regression and Evaluation on a Forward Interpolated Version of the Great Circle Arcs–Based Distortion Metric of Map Projections
We studied the numerical approximation problem of distortion in map projections. Most widely used differential methods calculate area distortion and maximum angular distortion using partial derivatives of forward equations of map projections. However, in certain map projections, partial derivatives are difficult to calculate because of the complicated forms of forward equations, e.g., equations with iterations, integrations, or multi-way branches…
No prominent works on this page.
Image-Based Angular Distortion Metric of Map Projections by Using Surface Fitting for Noise Reduction
Measuring, analyzing, reducing, and optimizing distortions in map projections is important in cartography. In this study, we introduced a novel image-based angular distortion metric based on the previous spherical great circle arcs-based metric. Images with predefined patterns were used to generate distorted images using mapping software. The generated distorted images with known patterns were then exploited to calculate the proposed angular dist…
Regression and Evaluation on a Forward Interpolated Version of the Great Circle Arcs–Based Distortion Metric of Map Projections
We studied the numerical approximation problem of distortion in map projections. Most widely used differential methods calculate area distortion and maximum angular distortion using partial derivatives of forward equations of map projections. However, in certain map projections, partial derivatives are difficult to calculate because of the complicated forms of forward equations, e.g., equations with iterations, integrations, or multi-way branches…
Image-based approximation of derivatives of traditional differential metrics of angular distortion in map projections
Map projections are imaging procedures used to depict geographic features. We adopt the traditional differential metric and exploit the intrinsic image properties of map projections to establish an image-based differential metric for evaluating distortions in map projections, obtaining an effective, practical, and relatively accurate metric. We use bivariate polynomial functions to approximate the forward and inverse formulae of map projections. …
Algorithm (3 works) · Computer Science (3 works) · Geophysics and Gravity Measurements (3 works) · Historical Geography and Cartography (3 works) · Mathematics (3 works) · Geographic Information Systems Studies (2 works) · 3D Modeling in Geospatial Applications (1 works) · Applied Mathematics (1 works) · Artificial Intelligence (1 works) · Computer vision (1 works)