Mapping land cover gradients through analysis of hyper-temporal NDVI imagery

The green cover of the earth exhibits various spatial gradients that represent gradual changes in space of vegetation density and/or in species composition. To date, land cover mapping methods differentiate at best, mapping units with different cover densities and/or species compositions, but typica...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:ITC journal Jg. 23
Hauptverfasser: Ali, A, Bie, C.A.J.M., de, Skidmore, A.K, Scarrott, R.G, Hamad, A, Venus, V, Lymberakis, P
Format: Journal Article
Sprache:Englisch
Veröffentlicht: 01.08.2013
Schlagworte:
accuracy assessment
boundaries
classification
fuzzy-sets
multitemporal modis images
neural-networks
remotely-sensed imagery
species composition
time-series
vegetation
ISSN:0303-2434
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Abstract The green cover of the earth exhibits various spatial gradients that represent gradual changes in space of vegetation density and/or in species composition. To date, land cover mapping methods differentiate at best, mapping units with different cover densities and/or species compositions, but typically fail to express such differences as gradients. Present interpretation techniques still make insufficient use of freely available spatial-temporal Earth Observation (EO) data that allow detection of existing land cover gradients. This study explores the use of hyper-temporal NDVI imagery to detect and delineate land cover gradients analyzing the temporal behavior of NDVI values. MODIS-Terra MVC-images (250 m, 16-day) of Crete, Greece, from February 2000 to July 2009 are used. The analysis approach uses an ISODATA unsupervised classification in combination with a Hierarchical Clustering Analysis (HCA). Clustering of class-specific temporal NDVI profiles through HCA resulted in the identification of gradients in landcover vegetation growth patterns. The detected gradients were arranged in a relational diagram, and mapped. Three groups of NDVI-classes were evaluated by correlating their class-specific annual average NDVI values with the field data (tree, shrub, grass, bare soil, stone, litter fraction covers). Multiple regression analysis showed that within each NDVI group, the fraction cover data were linearly related with the NDVI data, while NDVI groups were significantly different with respect to tree cover (adj. R 2 = 0.96), shrub cover (adj. R 2 = 0.83), grass cover (adj. R 2 = 0.71), bare soil (adj. R 2 = 0.88), stone cover (adj. R 2 = 0.83) and litter cover (adj. R 2 = 0.69) fractions. Similarly, the mean Sorenson dissimilarity values were found high and significant at confidence interval of 95% in all pairs of three NDVI groups. The study demonstrates that hyper-temporal NDVI imagery can successfully detect and map land cover gradients. The results may improve land cover assessment and aid in agricultural and ecological studies.
AbstractList The green cover of the earth exhibits various spatial gradients that represent gradual changes in space of vegetation density and/or in species composition. To date, land cover mapping methods differentiate at best, mapping units with different cover densities and/or species compositions, but typically fail to express such differences as gradients. Present interpretation techniques still make insufficient use of freely available spatial-temporal Earth Observation (EO) data that allow detection of existing land cover gradients. This study explores the use of hyper-temporal NDVI imagery to detect and delineate land cover gradients analyzing the temporal behavior of NDVI values. MODIS-Terra MVC-images (250 m, 16-day) of Crete, Greece, from February 2000 to July 2009 are used. The analysis approach uses an ISODATA unsupervised classification in combination with a Hierarchical Clustering Analysis (HCA). Clustering of class-specific temporal NDVI profiles through HCA resulted in the identification of gradients in landcover vegetation growth patterns. The detected gradients were arranged in a relational diagram, and mapped. Three groups of NDVI-classes were evaluated by correlating their class-specific annual average NDVI values with the field data (tree, shrub, grass, bare soil, stone, litter fraction covers). Multiple regression analysis showed that within each NDVI group, the fraction cover data were linearly related with the NDVI data, while NDVI groups were significantly different with respect to tree cover (adj. R 2 = 0.96), shrub cover (adj. R 2 = 0.83), grass cover (adj. R 2 = 0.71), bare soil (adj. R 2 = 0.88), stone cover (adj. R 2 = 0.83) and litter cover (adj. R 2 = 0.69) fractions. Similarly, the mean Sorenson dissimilarity values were found high and significant at confidence interval of 95% in all pairs of three NDVI groups. The study demonstrates that hyper-temporal NDVI imagery can successfully detect and map land cover gradients. The results may improve land cover assessment and aid in agricultural and ecological studies.
Author Hamad, A
Venus, V
Ali, A
Lymberakis, P
Bie, C.A.J.M., de
Skidmore, A.K
Scarrott, R.G
Author_xml – sequence: 1
  fullname: Ali, A
– sequence: 2
  fullname: Bie, C.A.J.M., de
– sequence: 3
  fullname: Skidmore, A.K
– sequence: 4
  fullname: Scarrott, R.G
– sequence: 5
  fullname: Hamad, A
– sequence: 6
  fullname: Venus, V
– sequence: 7
  fullname: Lymberakis, P
BookMark eNotjstOwzAURL0oEqX0A9j5BxKuH3Ucdqi8KhXYANvoJnYSV6kT2SlV_p4gmM3RbM7MFVn43ltCbhikDJi6PaQHbFIOjM89BWALsgQBIuFSyEuyjvEAc2TOIVNLsn_FYXC-oR16Q6v-2wbaBDTO-jHSsQ39qWkpeuym6CLta9pOgw3JaI9DH7Cjbw9fO-qO2NgwXZOLGrto1_9ckc-nx4_tS7J_f95t7_dJJXU2JrKSggFqALUpjTKlBJRCsZqD4VyWUmtmJOeagzZQKWtzXWOtzIajEEaLFbn7857nWT-_t77wGCoXix5d0bkyYJiK8ykUvvvFcCpjIUWW6Vz8ABCdWoQ
CitedBy_id crossref_primary_10_1177_0309133316639403
crossref_primary_10_1016_j_catena_2019_104259
crossref_primary_10_1016_j_jag_2013_06_007
crossref_primary_10_1016_j_ijdrr_2018_03_007
crossref_primary_10_1016_j_landurbplan_2015_04_001
crossref_primary_10_1080_13658816_2015_1082565
crossref_primary_10_1007_s10113_020_01722_6
crossref_primary_10_1016_j_ecss_2013_11_007
crossref_primary_10_1016_j_ecoinf_2018_06_001
crossref_primary_10_1016_j_jenvman_2021_113917
ContentType Journal Article
Copyright Wageningen University & Research
Copyright_xml – notice: Wageningen University & Research
DBID QVL
DOI 10.1016/j.jag.2012.10.001
DatabaseName NARCIS:Publications
DatabaseTitleList
DeliveryMethod fulltext_linktorsrc
Discipline Engineering
ExternalDocumentID oai_library_wur_nl_wurpubs_437789
GroupedDBID 8RP
ALMA_UNASSIGNED_HOLDINGS
QVL
VH1
ID FETCH-LOGICAL-c487t-4c4310a80065bd6db40a4361f20d224b4881d4228208d0c6ee98faf6d52a33d83
ISICitedReferencesCount 27
ISICitedReferencesURI http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000317159800028&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
ISSN 0303-2434
IngestDate Tue Jan 05 18:06:08 EST 2021
IsDoiOpenAccess false
IsOpenAccess true
IsPeerReviewed true
IsScholarly true
Language English
LinkModel OpenURL
MergedId FETCHMERGED-LOGICAL-c487t-4c4310a80065bd6db40a4361f20d224b4881d4228208d0c6ee98faf6d52a33d83
OpenAccessLink https://research.utwente.nl/en/publications/8421d0c7-cbc5-497c-83f4-942a3a49eaa4
ParticipantIDs wageningen_narcis_oai_library_wur_nl_wurpubs_437789
ProviderPackageCode QVL
PublicationCentury 2000
PublicationDate 2013-08-01
PublicationDateYYYYMMDD 2013-08-01
PublicationDate_xml – month: 08
  year: 2013
  text: 2013-08-01
  day: 01
PublicationDecade 2010
PublicationTitle ITC journal
PublicationYear 2013
SSID ssj0000492076
Score 2.1426315
Snippet The green cover of the earth exhibits various spatial gradients that represent gradual changes in space of vegetation density and/or in species composition. To...
SourceID wageningen
SourceType Open Access Repository
SubjectTerms accuracy assessment
boundaries
classification
fuzzy-sets
multitemporal modis images
neural-networks
remotely-sensed imagery
species composition
time-series
vegetation
Title Mapping land cover gradients through analysis of hyper-temporal NDVI imagery
URI http://www.narcis.nl/publication/RecordID/oai:library.wur.nl:wurpubs%2F437789
Volume 23
WOSCitedRecordID wos000317159800028&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
journalDatabaseRights – providerCode: PRVESC
  databaseName: Elsevier SD Freedom Collection Journals 2021
  issn: 0303-2434
  databaseCode: AIEXJ
  dateStart: 19990101
  customDbUrl:
  isFulltext: true
  dateEnd: 20191130
  titleUrlDefault: https://www.sciencedirect.com
  omitProxy: false
  ssIdentifier: ssj0000492076
  providerName: Elsevier
link http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtZ3Nb9MwFMAt9nHYDgjYJr7lA7cqkRM7tXOsyoBOrELQTb1Fju1sHSWbko7tz-fZcdO0HGBIXNIoUiPLP-vlfT-E3vFEKyFFElAQ_wGThAaCRlFg-ooZoZmSKnfDJvh4LKbT9Isfd1S7cQK8LMX9fXrzX1HDM4BtS2cfgLt9KTyAe4AOV8AO178CfypvXA3UvKlYg_X3LiqX2LWo27E8stOL5BJM0SrwParmvfH781Fv9kNuVkuPJsNedwHSzbNed4c2wY5hOAhPwlMnd3R7cL59n-k2qzdceVeVbQPZhKi-hh-7Xgg7EUIsvRC--goox8w7Jr1kbSqJfxPSjb_gKrySFza3Lg5del20-iIto_AbH6q1ltjeyZXd3VZZObc_cH7rjFHORbqFdmKepCDldgaj4-lJ63UDeygmvAlg-wUvQ90u6W9jSfto7w62u3R1bh29Y_IEPfYGAx40oJ-iR6Z8hvY7bSQP0GePHFvk2CHHLXLskeMlcnxd4HXk2CLHHvkhOvtwPBl-CvyUjECBsbkImAIdkEhhlcncjgdjRDLaj4qYaNDPcpDQkbaN3mIiNFF9Y1JRyKKvk1hSqgU9QtvldWmeI5zklMhCcrAyCTOwf6BMKxrTXKdcaGpeILrajqy0w67q7I8wXv7Tv16hvdU5e422F9WteYN21c_FrK7eeq6_ALBVYuM
linkProvider Elsevier
openUrl ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Mapping+land+cover+gradients+through+analysis+of+hyper-temporal+NDVI+imagery&rft.jtitle=ITC+journal&rft.au=Ali%2C+A&rft.au=Bie%2C+C.A.J.M.%2C+de&rft.au=Skidmore%2C+A.K&rft.au=Scarrott%2C+R.G&rft.date=2013-08-01&rft.issn=0303-2434&rft.volume=23&rft_id=info:doi/10.1016%2Fj.jag.2012.10.001&rft.externalDBID=n%2Fa&rft.externalDocID=oai_library_wur_nl_wurpubs_437789
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0303-2434&client=summon
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0303-2434&client=summon
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0303-2434&client=summon