2013 IEEE International Geoscience and Remote Sensing Symposium - IGARSS 2013
DOI: 10.1109/igarss.2013.6723602
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Weather radar data visualization using first-order interpolation

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Cited by 2 publications
(4 citation statements)
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“…Yoo et al [17] applied the multivariate linear regression method to correct the mean-field bias of radar rain rate data. Kvasovet al [18] proposed a bilinear interpolation method to enrich radar imaging details for better real-time radar data visualization. Foehnet al [19] compared and evaluated several spatial interpolation methods in geostatistics for radar-based precipitation field interpolation, including inverse distance weighting, regression inverse distance weighting, regression kriging, and regression co-kriging.…”
Section: Introductionmentioning
confidence: 99%
“…Yoo et al [17] applied the multivariate linear regression method to correct the mean-field bias of radar rain rate data. Kvasovet al [18] proposed a bilinear interpolation method to enrich radar imaging details for better real-time radar data visualization. Foehnet al [19] compared and evaluated several spatial interpolation methods in geostatistics for radar-based precipitation field interpolation, including inverse distance weighting, regression inverse distance weighting, regression kriging, and regression co-kriging.…”
Section: Introductionmentioning
confidence: 99%
“…However, our method is more effective in removing noise and edge continuity than conventional meth- Fig. 10 (a) Processing times of proposed method and conventional methods [7], [8], [11] and (b) the number of contour pixels and the processing time of MRF-MAP segmentation and contour interpolation.…”
Section: Ppi Quality Evaluationmentioning
confidence: 99%
“…Thus, conventional methods deal with the first two steps generally and apply differently to the last data interpolation, such as neighbor mapping [5], bilinear [6], [7], kriging [8]- [11] and Barnes [12] interpolations and also evaluate the accuracy of PPI data using RE (relative error) [7], RMAE (relative mean absolute error) [8], and NB (normalized bias)/NSE (normalized standard error) [9] between an interpolated data and an actually observed data. We compared the processing time and PPI quality of our method and Kvasov's method [7] of bilinear interpolation and War- We evaluated the quantitative quality using the mean relative error [7] (|I k − I k |/I k ) for all sweeps between an actually observed data I k and an interpolated data I k , which is shown in Table 1. From this table, we confirmed that our method has relative errors as low as 0.5%-1.8% compared to conventional methods and that kriging interpolation methods with relatively low noises have low relative errors with bilinear interpolation method.…”
Section: Ppi Quality Evaluationmentioning
confidence: 99%
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