We present a partition-enhanced least-squares collocation (PE-LSC) which comprises several modifications to the classical LSC method. It is our goal to circumvent various problems of the practical application of LSC. While these investigations are focused on the modeling of the exterior gravity field the elaborated methods can also be used in other applications. One of the main drawbacks and current limitations of LSC is its high computational cost which grows cubically with the number of observation points. A common way to mitigate this problem is to tile the target area into sub-regions and solve each tile individually. This procedure assumes a certain locality of the LSC kernel functions which is generally not given and, therefore, resul...
Least-squares collocation (LSC) is a widely used method applied in physical geodesy to separate obse...
The paper describes the estimation of covariance parameters in least squares collocation (LSC) by th...
The least squares collocation algorithm for estimating gravity anomalies from geodetic data is shown...
Geodesy deals with the accurate analysis of spatial and temporal variations in the geometry and phys...
Abstract Most geostatistical methods for spatial ran-domfield (SRF)predictionusingdiscrete data, inc...
Abstract. It has long been known that a spherical harmonic analysis of gridded (and noisy) data on a...
summary:Two general solutions of the collocation problem of physical geodesy are given. Their mutual...
Due to the successful operation of dedicated satellite gravity missions, nowadays highaccuracy globa...
Covariance determination as the heart of Least Squares Collocation gravity field modeling is based o...
We present a parallel distributed solver that enables us to solve incremental dense least squares ar...
Collocation is widely used in physical geodesy. Its application requires to solve systems with a dim...
Dans cette thèse, nous présentons le résultat de nos recherches dans le domaine du calcul scientifiq...
In our previous work [Ramouz et al. 2018], during the gravity field determination via Least Squares ...
Least-squares collocation (LSC) is a widely used method applied in physical geodesy to separate obse...
The paper describes the estimation of covariance parameters in least squares collocation (LSC) by th...
The least squares collocation algorithm for estimating gravity anomalies from geodetic data is shown...
Geodesy deals with the accurate analysis of spatial and temporal variations in the geometry and phys...
Abstract Most geostatistical methods for spatial ran-domfield (SRF)predictionusingdiscrete data, inc...
Abstract. It has long been known that a spherical harmonic analysis of gridded (and noisy) data on a...
summary:Two general solutions of the collocation problem of physical geodesy are given. Their mutual...
Due to the successful operation of dedicated satellite gravity missions, nowadays highaccuracy globa...
Covariance determination as the heart of Least Squares Collocation gravity field modeling is based o...
We present a parallel distributed solver that enables us to solve incremental dense least squares ar...
Collocation is widely used in physical geodesy. Its application requires to solve systems with a dim...
Dans cette thèse, nous présentons le résultat de nos recherches dans le domaine du calcul scientifiq...
In our previous work [Ramouz et al. 2018], during the gravity field determination via Least Squares ...
Least-squares collocation (LSC) is a widely used method applied in physical geodesy to separate obse...
The paper describes the estimation of covariance parameters in least squares collocation (LSC) by th...
The least squares collocation algorithm for estimating gravity anomalies from geodetic data is shown...