Image-Based Angular Distortion Metric of Map Projections by Using Surface Fitting for Noise Reduction
Bibliographic Data
| ID | 22032084 |
|---|---|
| Authors | Jin Yan (0000-0001-8787-5472, Capital University of Economics and Business), Tiansheng Xu (Capital University of Economics and Business), Ni Li (0000-0003-1210-4993, Beihang University), Guanghong Gong (0000-0002-7082-9231, Beihang University, corresponding author) |
| Year | 2021 |
| Volume | 11 |
| Issue | 1 |
| Pages | 1 |
| Publication date | 2021-12-24 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | ISPRS International Journal of Geo-Information (JOURNAL) |
| Journal identifiers | ISSN: 2220-9964 • E-ISSN: 2220-9964 |
| Publisher | MDPI AG (PUBLISHER • IT) |
| DOI | 10.3390/ijgi11010001 |
| OpenAlex | W4200332907 |
| Language | EN |
| Citations received | 1 |
| References cited | 21 |
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 distortion metric. The mapping software performed the underlying transformation of map projections. Therefore, there was no direct explicit dependence on the forward equations of the map projections in our proposed metric. However, there were fairly large computation errors in the ordinary image-based approach without special correction. To reduce the error, we introduced surface-fitting-based noise reduction in our approach. We established and solved systems of linear equations based on bivariate polynomial functions in the process of noise reduction. Sufficient experiments were made to validate the proposed image-based metric and the accompanying noise reduction approach. In the experiment, the NASA G.Projector was employed as the mapping software for evaluating more than 200 map projections. Experimental results demonstrated that the proposed image-based approach and surface fitting-based noise reduction are feasible and practical for the evaluation of the angular distortion of map projections
Algorithm · Computer vision · Geometry · Linear map · Noise reduction · Projector · Computer Science · Geographic Information Systems Studies · Geophysics and Gravity Measurements · Historical Geography and Cartography · Mathematics · Artificial Intelligence
Julia
Regression and Evaluation on a Forward Interpolated Version of the Great Circle Arcs–Based Distortion Metric of Map Projections
Flexion and Skewness in Map Projections of the Earth
A statistical reinterpretation and assessment of criteria used for measuring map projection distortion
Automated map projection selection for GIS
| Unique citing works | 1 |
|---|---|
| Citations per year | 0,25 |
| Citation span | 2022 - 2022 (1) |
| Citation velocity | historical |
| Highly cited | No |
| Citation types | Neutral: 1 |