Comparing methods for the approximation of rainfall fields in environmental applications

Patanè, Giuseppe; Cerri, Andrea; Skytt, Vibeke; Pittaluga, S.; Biasotti, Silvia; Sobrero, D.; Dokken, Tor; Spagnuolo, Michela

doi:10.1016/j.isprsjprs.2016.09.011

Cited by 5 publications

(9 citation statements)

References 31 publications

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“…It is located in the Liguria region, in the north-west of Italy. The Liguria morphology, with several small catchments and even small rivers, is very challenging for the approximation methods to capture and preserve the most important and potentially critical characteristics [46]. The data are obtained with multiple swipes by airplane lidar acquisition.…”

Section: Surface Approximationmentioning

confidence: 99%

“…The network is spread over the whole region, with 143 measure stations. These data come from the use case adopted for the comparison of six rainfall precipitation methods in [46].…”

Section: Approximation Of Surface Propertiesmentioning

confidence: 99%

“…Here, we compare wQISA with k-NN weight functions with two other methods: radial basis functions (RBF) with Gaussian kernel, as considered in [46], and the Multilevel B-splines Approximation (MBA) [50]. In the RBF implementation a global support [51] is adopted (all the 143 rain samples are considered) and a direct solver is applied to the linear system, which is symmetric and positive-definite.…”

Section: Approximation Of Surface Propertiesmentioning

confidence: 99%

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Weighted quasi-interpolant spline approximations: Properties and applications

Raffo

Biasotti

2020

Numer Algor

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Continuous representations are fundamental for modeling sampled data and performing computations and numerical simulations directly on the model or its elements. To effectively and efficiently address the approximation of point clouds we propose the Weighted Quasi Interpolant Spline Approximation method (wQISA). We provide global and local bounds of the method and discuss how it still preserves the shape properties of the classical quasi-interpolation scheme. This approach is particularly useful when the data noise can be represented as a probabilistic distribution: from the point of view of nonparametric regression, the wQISA estimator is robust to random perturbations, such as noise and outliers. Finally, we show the effectiveness of the method with several numerical simulations on real data, including curve fitting on images, surface approximation and simulation of rainfall precipitations.

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Section: Surface Approximationmentioning

confidence: 99%

“…The network is spread over the whole region, with 143 measure stations. These data come from the use case adopted for the comparison of six rainfall precipitation methods in [46].…”

Section: Approximation Of Surface Propertiesmentioning

confidence: 99%

Section: Approximation Of Surface Propertiesmentioning

confidence: 99%

See 1 more Smart Citation

Weighted quasi-interpolant spline approximations: Properties and applications

Raffo

Biasotti

2020

Numer Algor

View full text Add to dashboard Cite

show abstract

“…It is located in the Liguria region, in the north-west of Italy. The Liguria morphology, with several small catchments and even small rivers, is very challenging for the approximation methods to capture and preserve the most important and potentially critical characteristics [41]. The data are obtained with multiple swipes by airplane lidar acquisition.…”

Section: Surface Approximationmentioning

confidence: 99%

“…The network is spread over the whole region, with 143 measure stations. These data come from the use case adopted for the comparison of six rainfall precipitation methods in [41].…”

Section: Approximation Of Surface Propertiesmentioning

confidence: 99%