✦ LIBER ✦

Verification region selection and data assimilation for adaptive sampling

✍ Scribed by Craig H. Bishop; Brian J. Etherton; Sharanya J. Majumdar

Book ID: 111775880
Publisher: John Wiley and Sons
Year: 2006
Tongue: English
Weight: 275 KB
Volume: 132
Category: Article
ISSN: 0035-9009
DOI: 10.1256/qj.05.48

No coin nor oath required. For personal study only.

📜 SIMILAR VOLUMES

An adaptive variational method for data

An adaptive variational method for data assimilation with imperfect models

✍ Jiang Zhu; Masafumi Kamachi 📂 Article 📅 2000 🏛 John Wiley and Sons 🌐 English ⚖ 923 KB

Application and improvement of an adapti

Application and improvement of an adaptive ensemble Kalman filter for soil moisture data assimilation

✍ XiaoKang Shi; Jun Wen; JianWen Liu; Hui Tian; Xin Wang; YaoDong Li 📂 Article 📅 2010 🏛 Science in China Press (SCP) 🌐 English ⚖ 812 KB

On an adaptive filter for altimetric dat

On an adaptive filter for altimetric data assimilation and its application to a primitive equation model, MICOM

✍ H. S. HOANG; R. BARAILLE; O. TALAGRAND 📂 Article 📅 2005 🏛 John Wiley and Sons 🌐 English ⚖ 410 KB

ICAROS: An Integrated Computational Envi

ICAROS: An Integrated Computational Environment for the Assimilation of Environmental Data and Models for Urban and Regional Air Quality

✍ D. A. Sarigiannis; N. Soulakellis; K. Schäfer; M. Tombrou; N. I. Sifakis; D. Ass 📂 Article 📅 2002 🏛 Springer 🌐 English ⚖ 428 KB

Recursive SVM feature selection and samp

Recursive SVM feature selection and sample classification for mass-spectrometry and microarray data

✍ Xuegong Zhang; Xin Lu; Qian Shi; Xiu-qin Xu; Hon-chiu E Leung; Lyndsay N Harris; 📂 Article 📅 2006 🏛 BioMed Central 🌐 English ⚖ 325 KB

The implications of data selection for r

The implications of data selection for regional erosion and sediment yield modelling

✍ Joris de Vente; Jean Poesen; Gerard Govers; Carolina Boix-Fayos 📂 Article 📅 2009 🏛 John Wiley and Sons 🌐 English ⚖ 731 KB

## Abstract Regional environmental models often require detailed data on topography, land cover, soil, and climate. Remote sensing derived data form an increasingly important source of information for these models. Yet, it is often not easy to decide what the most feasible source of information is