Table Of ContentSpatial Statistics for Remote Sensing
Remote Sensing and Digital Image Processing
VOLUME 1
Series Editor:
Freek van der Meer, International Institute for Aerospace Survey and
Earth Sciences, ITC, Division of Geological Survey, Enschede, The Netherlands
and Department ofAppliedEarth Sciences, Delft University ofTechnology,
The Netherlands.
Editorial Advisory Board:
Michael Abrams, NASA Jet Propulsion Laboratoy, Pasadena, CA, U.S.A.
Paul Curran, University of Southampton, Department of Geography,
Southampton, U.K.
Arnold Dekker, CSIRO, Land and Water Division, Canberra, Australia
Steven de Jong, Utrecht University, Faculty of Geographical Sciences,
Department of Physical Geography, The Netherlands.
Michael Schaepman, ETH, Zurich, Switzerland
SPATIAL STATISTICS
FOR REMOTE SENSING
edited by
ALFRED STEIN
FREEK VAN DER MEER
and
BEN GORTE
International Institute for Aerospace Survey and Earth Sciences,
ITC, Enschede, The Netherlands
KLUWER ACADEMIC PUBLISHERS
NEW YORK, BOSTON, DORDRECHT, LONDON, MOSCOW
eBookISBN: 0-306-47647-9
Print ISBN: 0-7923-5978-X
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Preface
This book is a collection of papers on spatial statistics for remote sensing. The book
emerges from a study day that was organized in 1996 at the International Institute
for Aerospace Survey and Earth Sciences, ITC, in Enschede, The Netherlands. It
was by several means a memorable event. The beautiful new building, according to
a design by the famous modern Dutch architect Max van Huet was just opened, and
this workshop was the first to take place there. Of course, much went wrong during
the workshop, in particular as the newest electronic equipment regularly failed. But
the workshop attrackted more than hundred attendants, and was generally well
received. The results of the workshop have been published in Stein et al. (1998).
The aim of the workshop was to address issues of spatial statistics for remote
sensing. The ITC has a long history on collecting and analyzing satellite and other
remote sensing data, but its involvement into spatial statistics is of a more recent
date. Uncertainties in remote sensing images and the large amounts of data in
many spectral bands are now considered to be of such an impact that it requires a
separate approach from a statistical point of view. To quote from the justification
of the study day, we read:
Modern communication means such as remote sensing require an
advanced use of collected data. Satellites collect data with different
resolution on different spectral bands. These data all have a spatial
extension and are often related to each other. In addition, field data
are collected to interpret and validate the satellite data, and both
are stored and matched, using geographical information systems.
Often, statistical inference is necessary, ranging from simple de-
scriptive statistics to multivariate geostatistics. Classification, stat-
ististical sampling schemes and spatial interpolation are important
issues to deal with. Maximum likelihood and fuzzy classification
are now used intermixedly. Careful attention must be given as to
where and how to sample efficiently. Interpolation from points to
areas of land deserves thorough attention to take into account the
spatial variability and to match different resolutions at different
scales. Finally, the data have to be interpreted for making import-
ant environmental decisions.
This book reflects the set-up of the study-day. It addresses issues on remote
sensing, interpolation, modeling spatial variation, sampling, classification and de-
cision support systems, to namejust a few. Several of the authors were also speakers
v
vi
during the workshop, but some topics were at that day not addressed, and hence
the set of authors has been enlarged to guarantee a broad coverage of aspects of
spatial statistics for remote sensing purposes.
The book would not have been possible without contributions from various
people. First, we wish to thank the authors, who have all been working very hard
to give the book the level as it has just now. Second, we like to thank the ITC man-
agement for making book and workshop possible. We thank Dr. Elisabeth Kosters,
Mr. Bert Riekerk and Mrs. Ceciel Wolters for their contributions at various stages.
Finally, we like to thank Mrs. Petra van Steenbergen at Wolters Kluwer Academic
Publishers, for her patience and her continuing assistance of giving the book the
appearance it has by now.
Alfred Stein
Freek van der Meer
Ben Gorte
Enschede, April 1999
Contributors and editors
Peter Atkinson
Dept of Geography, Univ of Southampton, Highfield, Southampton
SO17 1BJ, United Kingdom
[email protected]
Sytze de Bruin
Wageningen University, Dept of GIRS, PO Box 33, 6700 AH Wageningen,
The Netherlands
[email protected]
Paul Curran
Dept of Geography, Univ of Southampton, Highfield, Southampton
SO17 1BJ, United Kingdom
[email protected]
Jennifer Dungan
Johnson Controls World Services Inc, NASA Ames Research Center,
MS242-2, Moffet Field, CA 94035-1000. USA
[email protected]
Ben Gorte
ITC, Division of Geoinformatics, PO Box 6, 7500 AA Enschede, The Neth-
erlands
[email protected]
Jaap de Gruijter
SC-DLO, PO Box 125, 6700 AC Wageningen, The Netherlands
[email protected]
Cees van Kemenade
CWI, PO Box 04079, 1090 GB Amsterdam, The Netherlands
[email protected]
Freek van der Meer
ITC, Division of Geological Survey, PO Box 6, 7500 AA Enschede, The
Netherlands
[email protected]
Robert J Mokken
University of Amsterdam, Sarphatistraat 143, 1018 GD Amsterdam,
The Netherlands
[email protected]
vii
viii
Martien Molenaar
ITC, Division of Geoinformatics, PO Box 6, 7500 AA Enschede, The Neth-
erlands
[email protected]
Andreas Papritz
ETH Zurich, Inst. Terrestrial Ecology, Soil Physics, Grabenstraße 11a, CH-
8952 Schlieren, Switzerland [email protected]
Han laPoutré
CWI, PO Box 04079, 1090 GB Amsterdam, The Netherlands
[email protected]
Ali Sharifi
ITC, Division of Social Science, PO Box 6, 7500 AA Enschede, The Neth-
erlands
[email protected]
Andrew Skidmore
ITC, Division of Agriculture, Conservation and Environment, PO Box 6,
7500 AA Enschede, The Netherlands
[email protected]
Alfred Stein
ITC, Division of Geoinformatics, PO Box 6, 7500 AA Enschede, The Neth-
erlands
[email protected]
Contents
Preface v
Contributors and editors vii
Introduction xv
I 1
1 Description of the data used in this book — Ben Gorte 3
1.1 The Landsat Program 4
1.2 Imageradiometry 4
1.3 Image geometry 6
1.4 Study area 7
2 Some basic elements of statistics — Alfred Stein 9
2.1 Population vs. sample 10
2.2 Covarianceandcorrelation 15
2.2.1 Significance of correlation 17
2.2.2 Example 18
2.3 Likelihood 18
2.4 Regression and prediction 21
2.5 Estimation and Prediction 22
3 Physical principles of optical remote sensing — Freek van der
Meer 27
3.1 Electromagnetic Radiation 27
3.2 Physics of Radiation and Interaction with Materials 28
3.3 Surface Scattering 29
3.4 Reflectance properties ofEarth surface materials 30
3.4.1 Minerals andRocks 30
3.4.2 Vegetation 34
3.4.3 Soils 35
3.4.4 Man-made and other materials 36
3.4.5 Spectral re-sampling 36
ix
x
3.5 Atmospheric attenuation 37
3.6 Calibration of LANDSAT TM to at-sensor spectral radiance 38
4 Remote sensing and geographical information systems — Sytze de
Bruin and Martien Molenaar 41
4.1 Data modeling 42
4.1.1 Geographic data models of real world phenomena 42
4.1.2 GIS data structures 42
4.2 Integrating GIS and remote sensing data 45
4.2.1 Geometric transformation 46
4.2.2 GIS data used in image processing and interpretation 47
4.2.3 GeographicinformationextractionfromRS imagery 49
4.3 Propagation of uncertainty through GIS operations 53
4.4 Software implementation 54
II 55
5 Spatial Statistics —Peter M. Atkinson 57
5.1 Spatial variation 57
5.1.1 Remote sensing 57
5.1.2 Spatial data and sampling 58
5.1.3 Remotely sensed data 59
5.1.4 Spatial variation and error 60
5.1.5 Classicalstatistics and geostatistics 61
5.2 Geostatistical background 61
5.2.1 Structure functions 62
5.2.2 The Random Function model 64
5.2.3 The sample variogram 66
5.2.4 Variogrammodels 68
5.3 Examples 71
5.3.1 Remotely sensed imagery 71
5.3.2 Sample variograms 74
5.3.3 Indicator variograms 77
5.3.4 Cross-variograms 79
5.4 Acknowledgments 81
6 Spatial prediction by linear kriging — Andreas Papritz and Alfred
Stein 83
6.1 Linear Model 87
6.2 Single Variable Linear Prediction 90
6.2.1 Precision criteria 90
6.2.2 Simple kriging 90
6.2.3 Universalkriging 95
6.2.4 Ordinary Kriging 99
