Remote Sensing Time Series: Revealing Land Surface Dynamics

458 Pages·2015·22.299 MB·English

by  Claudia Kuenzer, Stefan Dech, Wolfgang Wagner (eds.)

Remote Sensing and Digital Image Processing
Claudia Kuenzer
Stefan Dech
Wolfgang Wagner
Editors
Remote Sensing
Time Series
Revealing Land Surface Dynamics
Remote Sensing and Digital Image Processing
Volume 22
Series Editor
FreekD.vanderMeer,FacultyofGeo-InformationScienceandEarthObservation
(ITC), Department of Earth Systems Analysis, University of Twente, Enschede,
The Netherlands
EARSeL Series Editor
Anna Jarocin´ska, Department of Geoinformatics, Cartography and Remote
Sensing, Warsaw University, Poland
Editorial Advisory Board
Michael Abrams, NASA Jet Propulsion Laboratory, Pasadena, CA, U.S.A.
Paul Curran, City University London, U.K.
Arnold Dekker, CSIRO, Land and Water Division, Canberra, Australia
Steven M. de Jong, Department of Physical Geography, Faculty of Geosciences,
Utrecht University, The Netherlands
MichaelSchaepman,DepartmentofGeography,UniversityofZurich,Switzerland
EARSeL Editorial Advisory Board
Mario A. Gomarasca, CNR - IREA Milan, Italy
Martti Hallikainen, Helsinki University of Technology, Espoo, Finland
Ha˚kan Olsson, Swedish University of Agricultural Sciences, Umea, Sweden
Eberhard Parlow, University of Basel, Switzerland
Rainer Reuter, Carl von Ossietzky University of Oldenburg, Germany
More information about this series at http://www.springer.com/series/6477
Claudia Kuenzer (cid:129) Stefan Dech (cid:129)
Wolfgang Wagner
Editors
Remote Sensing Time Series
Revealing Land Surface Dynamics
Editors
ClaudiaKuenzer StefanDech
GermanRemoteSensingData GermanRemoteSensingData
Center,DFD Center,DFD
GermanAerospaceCenter,DLR GermanAerospaceCenter,DLR
Wessling,Germany Wessling,Germany
InstituteforGeographyandGeology
WolfgangWagner
UniversityofWuerzburg
DepartmentofGeodesy
Wuerzburg,Germany
andGeoinformation
ViennaUniversityofTechnology
Vienna,Austria
Responsible Series Editor:A.Marc¸al
ISSN1567-3200 ISSN2215-1842 (electronic)
RemoteSensingandDigitalImageProcessing
ISBN978-3-319-15966-9 ISBN978-3-319-15967-6 (eBook)
DOI10.1007/978-3-319-15967-6
LibraryofCongressControlNumber:2015938907
SpringerChamHeidelbergNewYorkDordrechtLondon
©SpringerInternationalPublishingSwitzerland2015
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Foreword
Our fragile planet experiences global change
atunprecedentedspeed.Muchofthischange
is man-made. We harness rivers and lakes,
clear-cut forests, transfer natural ecosystems
into agricultural land, and extract under-
ground resources. Through urbanization as
well as socio-economic transformation more
and more pristine habitats come under pres-
sure. Changes in climate variability impact
thedynamicsofsnowcoverandwaterbodies,
soilmoistureandvegetationphenology.
Satellite-based earth observation technol-
ogy allows us to monitor and quantify these
changes. Satellite remote sensing – and here
especiallytheanalysisoflong-termtimeseries–enablesustoreveallandsurface
dynamicsthatotherwisemightremainhiddentothehumaneye.ThebookRemote
Sensing Time Series Revealing Land Surface Dynamics focuses on exactly this
potentialofspace-borneearthobservation.
What can earth observation contribute to the understanding of global change?
Whichsatellitesensorsexist?Whichdatareallyallowforlong-termmonitoringand
time-series analysis? When is a time series long enough to shed light on climate
variability?Whichchallengesfacescientistswhouseremotesensingsatellitedatato
furtherknowledgeaboutourplanet?Howdodifferentecosystemschangeovertime?
This book, which has been initiated by scientists of DLR’s German Remote
Sensing Data Center (DFD), addresses all these questions. Experts from all over
Europe,theUSA,andChinahavecontributedtothiscomprehensivevolume.
In recent years many satellite data archives have been made available to the
public. The USA made nearly 40 years of Landsat data accessible free of charge.
Dataarchiveslikethisone,whichallowustolookintothepastforseveraldecades,
v
vi Foreword
areofimmensevalue.MediumresolutiondatacollectedbytheUSAVHRRsensor
have also been available for several decades. Additionally, since the year 2000,
MODISdataalsoallowustomonitorourentireplanetatdailyintervals.Europehas
followed this lead to facilitate satellite data access. Free optical, thermal infrared,
andradardatafromsensorsonboardtheESAresearchsatelliteENVISAT,enabled
dense, multifaceted analysis of the land surface between 2002 and 2012. Further-
more, data of the novel and upcoming European Sentinel missions operated by
the European Space Agency on behalf of the European Union are currently being
madeavailablefreeofchargebothtoscientificandcommercialusers.
Amongst other institutions, our German Remote Sensing Data Center will
provide and operate the processing and archiving facilities for the data from
Sentinel-1 C-band SAR sensors that grants continuity for ENVISAT-ASAR,
aswellasforSentinel-3OLCIdata,continuingtheENVISATMERISinstrument.
Sentinel-5precursordatawillalsobeprocessedandarchivedatDFD.
However, the large amount of earth observation data contained in satellite
data archives globally also poses great challenges for the science community.
The analysis of time series of data is much more complex than just comparing
a few multitemporal satellite scenes. Time-series analysis requires the processing
of hundreds, thousands, or even a hundreds of thousands of data sets. This
“big data” needs to be calibrated, preprocessed, harmonized, interpolated, and
statistically analyzed. At frequent intervals – monthly or annually – time series
have tobere-processedtoderive updated mean,minima, maxima, variabilityand
anomalies.Thisisanextremelydemandingtask.Additionally,thechallengeofbig
dataandthechallengetofullyexploitallthewealthofinformationthatiscontained
indataarchivesaregettingbiggereveryday.Moreandmorespacenationslaunch
satellites into orbit. The life span of sensors increases. And data access is eased
further.Thecomputerandprogrammingliteracyofscientistsandyoungpeoplein
general is rapidly increasing. Envisioning this trend, one of ourtechnical answers
is that algorithms should rather come to the data instead of routing mass-data
archives to the analysts. So, hopefully, as the challenges grow, so will our means
to address them. I am confident that we will be able to manage the upcoming
challenges,andthattheEuropeanCopernicusprogramwillhelptoblazethetrail.
I hope that this book will trigger or deepen your interest in remote sensing
time-seriesanalysisasavaluablemeanstoassessthestateofourPlanetEarth.
Iwishyoustimulatingreading.
Prof.Dr.-Ing.Johann-DietrichW€orner
ChairmanoftheExecutiveBoard
GermanAerospaceCenterDLR
Cologne,Germany
Acknowledgements
Thechapterspresentedinthisbookwerecontributedbyrenownedscientistsinthe
fieldofremotesensingtimeseriesanalysisfromaroundtheworld.Thisworkwould
not have been possible without each author’s voluntary and enthusiastic commit-
ment to this book project. We thank all authors for the very smooth process of
chaptercompilation.
We are extremely grateful to the following experts who have volunteered
to peer-review the chapters of this book. Investing their time and knowledge,
the reviewers significantly helped to shape the final chapters with their critical
commentsandsuggestions.
Alphabetically,weexpressoursincerethanksto:
Terry Arvidson (Lockheed Martin, Greenbelt, MD, USA); Kirsten de Beurs
(Department of Geography, University of Oklahoma, Norman, OK, USA);
ChristopherConrad(InstituteofGeographyandGeology,UniversityofWu¨rzburg,
Wu¨rzburg, Germany); Stefan Dech (German Aerospace Center, DLR, Earth
ObservationCenter,EOC,GermanRemoteSensingDataCenter,DFD,Oberpfaf-
fenhofen, Germany); Andreas Dietz (German Aerospace Center, DLR, Earth
ObservationCenter,EOC,GermanRemoteSensingDataCenter,DFD,Oberpfaf-
fenhofen, Germany); Jeffery Eidenshink (Earth Resources Observation and Sci-
ence, EROS, U.S. Geological Survey, Sioux Falls, SD, USA); Christina Eisfelder
(German Aerospace Center, DLR, Earth Observation Center, EOC, German
RemoteSensingDataCenter,DFD,Oberpfaffenhofen,Germany);UrsulaGessner
(German Aerospace Center, DLR, Earth Observation Center, EOC, German
Remote Sensing Data Center, DFD, Oberpfaffenhofen, Germany); Huadong Guo
(KeyLaboratoryofDigitalEarthSciences,InstituteofRemoteSensingandDigital
Earth, RADI, Chinese Academy of Sciences, CAS, Beijing, China); Xulin Guo
(Department of Geography and Planning, University of Saskatchewan, Canada);
Geoffrey M. Henebry (Geospatial Sciences Center of Excellence, GSCE, South
Dakota State University, Brooking, SD, USA); Martin Herold (Wageningen
University and Research Centre, WUR, Laboratory of Geo-information Science
andRemoteSensing,Wageningen,TheNetherlands);KoenHufkens(Department
vii
viii Acknowledgements
of Organismic & Evolutionary Biology, Harvard University, Cambridge, MA,
USA); Juliane Huth (German Aerospace Center, DLR, Earth Observation Center,
EOC, German Remote Sensing Data Center, DFD, Oberpfaffenhofen, Germany);
Igor Klein (German Aerospace Center, DLR, Earth Observation Center, EOC,
German Remote Sensing Data Center, DFD, Oberpfaffenhofen, Germany); Kim
Knauer(GermanAerospaceCenter,DLR,EarthObservationCenter,EOC,German
Remote Sensing Data Center, DFD, Oberpfaffenhofen, Germany); Patrick
Leinenkugel (German Aerospace Center, DLR, Earth Observation Center, EOC,
German Remote Sensing Data Center, DFD, Oberpfaffenhofen, Germany);
Sebastian van der Linden (Geographisches Institut, Humbold-Universita¨t Berlin,
Berlin, Germany); V. E. Nethaji Mariappan (Centre for Remote Sensing and
Geoinformatics, Sathyabama University, Chennai, India); Markus Niklaus
(German Aerospace Center, DLR, Earth Observation Center, EOC, German
RemoteSensingDataCenter,DFD,Oberpfaffenhofen,Germany);MarcoOttinger
(German Aerospace Center, DLR, Earth Observation Center, EOC, German
Remote Sensing Data Center, DFD, Oberpfaffenhofen, Germany); Stuard Phinn
(School of Geography, Planning and Environmental Management, University of
Queensland, Brisbane, Australia); Andreas Rienow (Department of Geography,
University Bonn, Bonn, Germany); Achim R€oder (Umweltfernerkundung und
Geoinformatik, Universita¨t Trier, Germany); David Roy (Geospatial Science
Center of Excellence, South Dakota State University, Brookings, SD, USA);
Mauritio Santoro (GAMMA Remote Sensing Research and Consulting AG,
Gu¨mligen,Switzerland);JosephO.Sexton(GlobalLandCoverFacility,University
of Maryland, MD, USA); Pascal Sirguey (School of Surveying, University of
Otago,Dunedin,NewZealand);RuthSonnenschein(InstituteforAppliedRemote
sensing, European Academy of Bolzano/Bozen, EURAC, Bolzano, Italy);
Wolfgang Wagner (Department of Geodesy and Geoinformation, Vienna Univer-
sityofTechnology,Vienna,Austria);JunWang(BeijingUniversity,China).
Special thanks go to Susan Giegerich for her support in proofreading
and language editing selected chapters, as well as to Nils Sparwasser (Science
VisualizationandGeoinformation,DLR,EOC,DFD)fordesigningthetitlepage.
Furthermore, we are especially grateful to Philipp Koch for his excellent
cooperationandeditingworkduringthepreparationofthisvolume.
Our gratitude also goes to the European Association of Remote Sensing
Laboratories(EARSeL)forsupportingthisbookproject.
Contents
1 RemoteSensingTimeSeriesRevealingLandSurface
Dynamics:StatusQuoandthePathwayAhead. . . . . . . . . . . . . . . 1
ClaudiaKuenzer,StefanDech,andWolfgangWagner
2 TimeSeriesAnalysesinaNewEraofOpticalSatelliteData. . . . . 25
PatrickHostert,PatrickGriffiths,SebastianvanderLinden,
andDirkPflugmacher
3 CalibrationandPre-processingofaMulti-decadal
AVHRRTimeSeries. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43
MartinBachmann,PadsurenTungalagsaikhan,ThomasRuppert,
andStefanDech
4 AnalysisofSnowCoverTimeSeries–Opportunities
andTechniques. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75
AndreasJ.Dietz,ClaudiaKuenzer,andStefanDech
5 GlobalWaterPack:Intra-annualAssessment
ofSpatio-TemporalVariabilityofInlandWaterBodies. . . . . . . . . 99
IgorKlein,AndreasJ.Dietz,UrsulaGessner,andClaudiaKuenzer
6 Analysinga13YearsMODISLandSurface
TemperatureTimeSeriesintheMekongBasin. . . . . . . . . . . . . . . 119
CorinneMyrthaFreyandClaudiaKuenzer
7 TIMESAT:ASoftwarePackageforTime-SeriesProcessing
andAssessmentofVegetationDynamics. . . . . . . . . . . . . . . . . . . . . 141
LarsEklundhandPerJ€onsson
ix