Laboratory for Remote Sensing

Hydrology and Spatial Modeling (RSLAB)

Professor Ke-Sheng Cheng

Dept of Bioenvironmental Systems Engineering &
Master Program in Statistics

National Taiwan University

Email: rslab@ntu.edu.tw

RSLAB_BSE_NTU
No. 1, Section 4, Roosevelt Road
Bioenvironmental Syst. Eng., National Taiwan University

Geostatistics (地理統計)

Dept. of Bioenvironmental Systems Engineering/Master Program in Statistics

National Taiwan University

Professor Ke-Sheng Cheng 鄭克聲教授

Course description

Geostatistics is a branch of statistics which focuses on characterization, estimation, prediction, and simulation of spatially varying phenomena, using data obtained at a limited number of spatial locations. Geostatistical methods have been applied to many areas such as hydrology, soil science, epidemiology, meteorology, corps science, environmental sciences, and in general where data are collected at spatial (geographical or hypothetical) locations.

This course aims to introduce fundamentals of random field modeling and simulation. In addition to in-class theoretical derivations and explanations, practices of geostatistical modeling, prediction, and simulation will be conducted using the R package gstat. Several examples of geostatistical application will also be demonstrated in class.

Data set to be used in class: Typhoon.csv (Hourly rainfalls of 24-hr event maximum rainfalls recorded at 30 rainfall stations in nothern Taiwan)

Introduction (PPT-1 )
08-18-2020
- Characterizing natural phenomena – deterministic vs. stochastic
- Random variables, random processes and random fields
- Stochastic simulation
Semi-Variogram Modeling (PPT-2 )
08-18-2020
- Spatial correlation structure
- Isotropic semi-variogram modeling
- Scale effect - change of support
- Anisotropic semi-variogram modeling
- Proportional effect
- Dimensionless (climatological) variogram
- Demonstrative PPT for sample semi-variogram claculation
- Demonstrative PPT using the meuse data
Homework 1
Spatial Estimation (PPT-3, PPT-4, PPT-5, PPT-7 )
08-18-2020
- Simple kriging
- Ordinary kriging
- Block kriging
- Universal kriging
- Co-kriging
- Indicator kriging
Uncertainty Assessment (PPT-6)
08-18-2020
- Bivaraite gamma distribution
- Gamma random field simulation
- Conditional random field simulation
Homework 2
Homework 3 (Study area shapefile)
Spatiotemporal Modeling and Simulation (PPT-8A, PPT-8B, PPT-8C)
Examples of Geostatistical Applications
08-18-2020
- Monitoring network evaluation and augmentation
- Contouring of design storm depths
- Image classification by indicator kriging
- Conditional simulation of heavy metal concentrations
- Stochastic simulation of random vector field (Image Simulation)
References
08-18-2020
Journel, A.G. and Huijbregts, C.J., 1978. Mining Geostatistics, Academics Press, London.
Isobel Clark, Practical Geostatistics, 1979. (http://www.kriging.com/PG1979/PG1979.pdf)
Goovaerts, P., 1997. Geostatistics for Natural Resources Evaluation. Oxford University Press, New York.
Chilès, J.P. and Delfiner, P., 1999. Geostatistics – Modeling Spatial Uncertainty, John Wiley & Sons, Inc., New York.
Diggle, P.J., Ribeiro, P.J., 2007. Model-based Geostatistics, Spronger.
Oliver, M.A. and Webster, R., 2015. Basic Steps in Geostatistics: The Variogram and Kriging, Springer.

RSLAB - NTU

Prof. Ke-Sheng Cheng

RSLAB_BSE_NTU
No. 1, Section 4, Roosevelt Road
Bioenvironmental Syst. Eng., National Taiwan University

Laboratory for Remote Sensing

Hydrology and Spatial Modeling (RSLAB)

Introduction (PPT-1 )

Semi-Variogram Modeling (PPT-2 )

Spatial Estimation (PPT-3, PPT-4, PPT-5, PPT-7 )

Uncertainty Assessment (PPT-6)

Spatiotemporal Modeling and Simulation (PPT-8A, PPT-8B, PPT-8C)

Examples of Geostatistical Applications

References

Grade policy

Laboratory for Remote Sensing

Hydrology and Spatial Modeling (RSLAB)

Introduction﻿ (PPT-1 )

Semi-Variogram Modeling (PPT-2 )

Spatial Estimation (PPT-3, PPT-4, PPT-5, PPT-7 )

Uncertainty Assessment (PPT-6)

Spatiotemporal Modeling and Simulation (PPT-8A, PPT-8B, PPT-8C)

Examples of Geostatistical Applications

References

Grade policy

Introduction (PPT-1 )