An adaptive RBF interpolation that picks its shape factor from local sample density estimates missing elevation values more accurately than kNN and adaptive IDW on three DEM datasets, but runs slower.
Journal of Computational Physics 345, 732–751 (2017)
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
math.NA 1years
2019 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Adaptive RBF Interpolation for Estimating Missing Values in Geographical Data
An adaptive RBF interpolation that picks its shape factor from local sample density estimates missing elevation values more accurately than kNN and adaptive IDW on three DEM datasets, but runs slower.