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TIMESAT3.3版本用户手册
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TIMESAT 3.3
with seasonal trend decomposition
and parallel processing
Software Manual
1 37 73 109 145 181 217 253 289 325 361 397
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Time
Data
Row: 1 Col: 1
Lars Eklundh
a
and Per Jönsson
b
a
Department of Physical Geography and Ecosystem Science, Lund University, Sweden
b
Department of Materials Science and Applied Mathematics, Malmö University, Sweden
http://www.nateko.lu.se/TIMESAT/
2017-05-29
Contents
1 Introduction 5
1.1 About TIMESAT and the software manual . . . . . . . . . . . . . . . . . . . 5
1.2 TIMESAT version 3.3 vs. version 3.2 . . . . . . . . . . . . . . . . . . . . . . . 6
1.3 TIMESAT home page . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
1.4 Using and citing TIMESAT . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
1.5 Applications of TIMESAT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
1.6 About the authors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
2 Overview of data processing 10
2.1 Sequential data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
2.2 Image data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
3 Methodology 13
3.1 Least-squares fitting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
3.2 On the use of ancillary quality data for assigning weights . . . . . . . . . . . . 14
3.3 Pre-processing to remove spikes and outliers . . . . . . . . . . . . . . . . . . . 14
3.4 Adaption to the upper envelope . . . . . . . . . . . . . . . . . . . . . . . . . . 16
3.5 Determination of the number of seasons . . . . . . . . . . . . . . . . . . . . . 16
3.6 Adaptive Savitzky-Golay filtering . . . . . . . . . . . . . . . . . . . . . . . . . 17
3.7 Fits to asymmetric Gaussians and double logistic functions . . . . . . . . . . . 18
3.8 Separable non-linear least-squares fits . . . . . . . . . . . . . . . . . . . . . . . 20
3.9 Merging of local functions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
3.10 Seasonal trend decomposition . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
4 Extraction of seasonality parameters 23
4.1 Seasonality parameters derived from time-series spanning n years . . . . . . . 23
4.2 Extracting seasonality parameters from one year of data . . . . . . . . . . . . 23
4.3 Defining start and end of season . . . . . . . . . . . . . . . . . . . . . . . . . . 24
4.4 Extracted seasonality parameters . . . . . . . . . . . . . . . . . . . . . . . . . 26
5 Aspects of processing 27
5.1 Characteristics of the processing methods . . . . . . . . . . . . . . . . . . . . 27
5.2 Controlling the processing: input settings . . . . . . . . . . . . . . . . . . . . 28
5.3 Description of input settings . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32
6 Output data 36
6.1 Files with time-series: *.tts . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36
6.2 Files with seasonality parameters: *.tpa . . . . . . . . . . . . . . . . . . . . . 37
6.3 Files with output from STL trend analysis . . . . . . . . . . . . . . . . . . . . 38
6.4 Extracting images of seasonality parameters . . . . . . . . . . . . . . . . . . . 38
6.5 Output files from ASCII data . . . . . . . . . . . . . . . . . . . . . . . . . . . 38
6.6 Index files . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39
7 Installation of TIMESAT and program structure 41
2
7.1 System requirements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41
7.2 Installation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41
8 Program and processing overview 42
8.1 Processing logic . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42
8.2 Naming convention of programs . . . . . . . . . . . . . . . . . . . . . . . . . . 43
8.3 Program versions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43
9 Getting started with TIMESAT – a quick tutorial 45
9.1 Preparing the data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45
9.2 Starting the TIMESAT menu system . . . . . . . . . . . . . . . . . . . . . . . 47
9.3 TSM_imageview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48
9.4 TSM_GUI . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50
9.5 TSM_settings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55
9.6 TSF_process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57
9.7 TSF_process parallel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58
9.8 Post-processing the results of a TSF_process run . . . . . . . . . . . . . . . . 59
9.9 Checklist for processing new vegetation index image data . . . . . . . . . . . 66
10 Reference manual 69
10.1 TSM_menu . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69
10.2 TSM_imageview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71
10.3 TSM_GUI . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72
10.4 Data input for TSM_GUI . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74
10.5 Settings in TSM_GUI . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75
10.6 Output files from TSM_GUI . . . . . . . . . . . . . . . . . . . . . . . . . . . 76
10.7 TSM_settings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76
10.8 TSF_process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78
10.9 TSF_process parallel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78
10.10TSF_readheader (obsolete) . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79
10.11TSM_fileinfo . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79
10.12TSM_printseasons . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79
10.13TSM_viewfits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80
10.14TSF_fit2time . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80
10.15TSF_fit2img . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80
10.16TSF_seas2img . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81
10.17TSF_merge . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82
10.18Running from the command prompt to automate processing . . . . . . . . . . 83
10.19Working in Linux as compared to Windows . . . . . . . . . . . . . . . . . . . 83
10.20Input files for TIMESAT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84
10.21Output files for TIMESAT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88
10.22Index files . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89
11 Acknowledgements 89
12 References 90
3
Part I
Introduction to TIMESAT
4
1 Introduction
Time-series of vegetation index derived from satellite spectral measurements can be used to
gain information on seasonal vegetation development. This information aids analyzes of the
functional and structural characteristics of the global and regional land cover and adds to our
current knowledge of global cycles of energy and matter. Long time-series of vegetation index
data can also provide information on shifts in the spatial distribution of bio-climatic zones,
indicating variations in large-scale circulation patterns or land-use changes.
Although the value of remotely sensed time-series data for monitoring vegetation seasons
has been firmly established, only a limited number of generally available methods exist for
exploring and extracting seasonality parameters from such data series. For this reason the
Timesat program package for extracting seasonal parameters has been developed.
1.1 About TIMESAT and the software manual
The Timesat 3.3 software manual consists of three parts. Part I gives general information
together with examples of some applications of Timesat. Part II describes the algorithms
underlying the software package. Also the settings affecting the processing are discussed in
detail. Part III is the software user’s guide, with detailed information on how to install, run,
and handle the program package.
The Timesat program package is designed primarily for analyzing time-series of satellite
data and uses an adaptive Savitzky-Golay filtering method and methods based on upper
envelope weighted fits to asymmetric Gaussian and double logistic model functions (Jönsson
and Eklundh, 2002, 2003, 2004). From the fitted model functions a number of seasonality
parameters, e.g. beginning and end of the growing season, can be extracted. Parameters for
a number of pixels can be merged into a map displaying seasonality on a regional or global
scale.
Timesat consists of a number of numerical and graphical routines coded in Matlab and
Fortran. Timesat is normally run from Matlab. However, also users without Matlab installed,
or even without a Matlab license, can use the software. Processing is then done through a
runtime engine called the Matlab Compiler Runtime (MCR), that is set up on the users
machine by executing the file MCRinstall.exe (see section 7.2). The latter file is provided
along with the Timesat program package. Fortran routines are highly vectorized and efficient
for use with large data sets. The Fortran routines are pre-compiled for Windows and Linux.
Timesat has been developed over many years. During these years a number of new features
have been added. Below are the main features of Timesat 3.3:
• Contains several smoothing methods for time-series data
• Includes seasonal trend decomposition by LOESS (STL)
• Contains several methods for detection of outliers
• Allows for weighting of data using quality information
• Allows for fitting to the upper envelope of the data
5
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