Please wait a minute...
Frontiers of Environmental Science & Engineering

ISSN 2095-2201

ISSN 2095-221X(Online)

CN 10-1013/X

Postal Subscription Code 80-973

2018 Impact Factor: 3.883

Front.Environ.Sci.Eng.    2008, Vol. 2 Issue (2) : 187-197    https://doi.org/10.1007/s11783-008-0004-1
|
Spectral characteristics of plant communities from salt marshes: A case study from Chongming Dongtan, Yangtze estuary, China
ZHANG Liquan1, GAO Zhanguo2, Armitage Richard3, Kent Martin4
1.State Key Laboratory of Estuarine and Coastal Research, East China Normal University; 2.State Key Laboratory of Estuarine and Coastal Research, East China Normal University;Environment Monitoring Center of Ningbo; 3.Research Institute for the Built and Human Environment, School of Environment and Life Science, University of Salford; 4.School of Geography, University of Plymouth
 Download: PDF(284 KB)   HTML
 Export: BibTeX | EndNote | Reference Manager | ProCite | RefWorks
Abstract The spectral reflectance of recently formed salt marshes at the mouth of the Yangtze River, which are undergoing invasion by Spartina alterniflora, were assessed to determine the potential utility of remotely sensed data in assessing future invasion and changes in species composition. Following a review of published research on remote sensing of salt marshes, 53 locations along three transects were sampled for paired data on plant species composition and spectral reflectance using a FieldSpec Pro JR Field Portable Spectroradiometer. Spectral data were processed concerning reflectance, and the averaged reflectance values for each sample were re-analysed to correspond to a 12-waveband bandset of the Compact Airborne Spectral Imager. The spectral data were summarised using principal components analysis (PCA) and the relationships between the vegetation composition, and the PCA axes of spectral data were examined. The first PCA axis of the reflectance data showed a strong correlation with variability in near infrared reflectance and ‘brightness’, while the second axis was correlated with visible reflectance and ‘greenness’. Total vegetation cover, vegetation height, and mudflat cover were all significantly related to the first axis. The implications of this in terms of the ability of remote sensing to distinguish the various salt marsh species and in particular the invasive species S. alterniflora were discussed. Major differences in species with various physiognomies could be recognised but problems occurred in separating early colonising S. alterniflora from other species at that stage. Further work using multi-seasonal hyperspectral data might assist in solving these problems.
Issue Date: 05 June 2008
 Cite this article:   
GAO Zhanguo,ZHANG Liquan,Armitage Richard, et al. Spectral characteristics of plant communities from salt marshes: A case study from Chongming Dongtan, Yangtze estuary, China[J]. Front.Environ.Sci.Eng., 2008, 2(2): 187-197.
 URL:  
http://academic.hep.com.cn/fese/EN/10.1007/s11783-008-0004-1
http://academic.hep.com.cn/fese/EN/Y2008/V2/I2/187
1 Zhang R S Shen Y M Lu L S Yan S G Wang Y H Li J L Zhang Z L Formation of Spartina alterniflora salt marshes on thecoast of Jiangsu Province, ChinaEcologicalEngineering 2004 2395105.
doi:10.1016/j.ecoleng.2004.07.007
2 Xu G W Zhou R Z Preliminary studies of introduced Spartina alterniflora Loisel in ChinaJournal of Nanjing University (Advances in Spartina Research) 1985 212–225 (in Chinese)
3 Gray A J Marshall D F Raybould A F A century of evolution in SpartinaanglicaAdvances in EcologicalResearch 1991 21162
4 Daehler C C Strong D R Status, prediction and preventionof introduced cordgrass Spartina sp. invasions in Pacific estuaries, USA.Biological Conservation 1996 785158.
doi:10.1016/0006‐3207(96)00017‐1
5 Tessier M Vivier J P Ouin A Gloaguen J C Lefeuvre J C Vegetationdynamics and plantspecies interaction under grazed and ungrazed conditions in a westernEuropean salt marshActa Oecologica 2003 24103111.
doi:10.1016/S1146‐609X(03)00049‐3
6 Roughgarden J Running S Matson P What does remote sensing do for ecologyEcology 1991 72(6)9181922.
doi:10.2307/1941546
7 Liu J Y Zhuang D F Ling Y R Awaya Y Vegetation integratedclassification and mapping using remote sensing and GIS techniquesin northeast ChinaJournal of Remote Sensing 1998 4(2)285291 (in Chinese)
8 Treitz P M Howarth P J Hyperspectral remote sensingfor estimating biophysical parameters of forest ecosystemsProgress in Physical Geography 1999 23359390
9 Yang C J Liu J Y Luo J C Correlation analysis of landsat TM data and its deriveddata, meteorological data and topographic data with the biomass ofdifferent aged tropical forestsActa PhytoecologicaSinica 2004 28862867 (in Chinese)
10 Curran P J Theproblems of remote sensing of vegetation canopies for biomass estimates In: Fuller R M. Ecological Mapping from Ground, Air and SpaceCambridge, UKInstitute of TerrestrialEcology 1983 83100
11 Morton A J Moorlandplant community recognition using Landsat MSS dataRemote Sensing of Environment 1986 20291298.
doi:10.1016/0034‐4257(86)90049‐0
12 Trodd N M Analysisand representation of heathland vegetation from near-ground levelremote sensingGlobal Ecology and BiogeographyLetters 1996 5206216.
doi:10.2307/2997789
13 Blackburn G A Pitman J I Biophysical controls on thedirectional reflectance properties of bracken (Pteridium aquilinum)canopies: Results of field experimentsInternationalJournal of Remote Sensing 1999 2022652282.
doi:10.1080/014311699212245
14 Thomas V Treitz P Jelinski D Miller J Lafleur P McCaughey J H Imageclassification of a northern peatland complex using spectral and plantcommunity dataRemote Sensing of Environment 2002 848399.
doi:10.1016/S0034‐4257(02)00099‐8
15 Armitage R P Kent M Weaver R E Identification of the spectral characteristics of Britishsemi-natural upland vegetation using direct ordination: A case studyfrom Dart moor, UKInternational Journalof Remote Sensing 2004 2533693388.
doi:10.1080/01431160310001654464
16 Armitage R P Weaver R E Kent M Remote sensing of semi-natural upland vegetation: The relationshipbetween species composition and spectral responseIn: Alexander R, Millington A. Vegetation Mapping: Patch to PlanetChichesterJohnWiley and Sons 2000 83102
17 Cochrane M A Usingvegetation reflectance variability for species level classificationof hyperspectral dataInternational Journalof Remote Sensing 2000 2120752087.
doi:10.1080/01431160050021303
18 Artigras F J Yang J Hyperspectral remote sensingof habitat heterogeneity between tide-restricted and tide-open areasin the New Jersey MeadowlandsUrban Habitats 2004 2112129
19 Silvestri S Defina A Marani M Tidal regime, salinity and salt marsh plant zonationEstuarine, Coastal and Shelf Sciences 2005 62119130.
doi:10.1016/j.ecss.2004.08.010
20 Schmidt K S Skidmore A K Spectral discrimination ofvegetation types in a coastal wetlandRemoteSensing of Environment 2003 8592108.
doi:10.1016/S0034‐4257(02)00196‐7
21 Thomson A G Fuller R M Yates M G Brown S L Cox R Wadsworth R A Theuse of airborne remote sensing for extensive mapping of intertidalsediments and salt marshes in eastern EnglandInternational Journal of Remote Sensing 2003 2427172737.
doi:10.1080/0143116031000066918
22 Zhang M Pinzon J Rejmankova S L Sanderson E W Differentiatingsalt marsh species using foreground/background analysisIn: Proceedings of ERIM 2nd Annual Airborne Remote Sensing Conference, Volume 1San Francisco, USA 1996 8392
23 Silvestri S Marani M Marani A Hyperspectral remote sensing of salt marsh vegetation,morphology and soil topographyPhysics andChemistry of the Earth 2003 281525
24 Salvitori R Grignetti A Casacchia R Mandrone S The role of spatialresolution in vegetation studies by hyperspectral airborne imagesIn: Proceedings of Spectral Remote Sensing of VegetationConferenceLas Vegas, USA 2003
25 Brown K Increasingclassification accuracy of coastal habitats using integrated airborneremote sensingEARSEL eProccedings 2004 13442
26 Thomson A G Fuller R M Huiskes A Cox R Wadsworth R A Boorman L A Short-term vegetation succession and erosion identifiedby airborne remote sensing of Westerschelde salt marshes, The NetherlandsInternational Journal of Remote Sensing 2004 2541514176.
doi:10.1080/01431160310001647688
27 Thomson A G Fuller R M Sparks T H Yates M G Eastwood J A Ground and airborne radiometry over intertidalsurfaces: Waveband selection for cover classificationInternational Journal of Remote Sensing 1998a 1911891205.
doi:10.1080/014311698215685
28 Rocchini D Chiarucci A Loiselle S A Testing the spectral hypothesis by using satellite multispectralimagesActa Oecologica 2004 26117120.
doi:10.1016/j.actao.2004.03.008
29 Malthus T J Mumby P J Remote sensing of the coastalzone: An overview and priorities for future researchInternational Journal of Remote Sensing 2003 2428052815.
doi:10.1080/0143116031000066954
30 Thomson A G Fuller R M Eastwood J A Supervised and unsupervised methods for classificationof coasts and river corridors using airborne remote sensingInternational Journal of Remote Sensing 1998b 1934233431.
doi:10.1080/014311698214091
31 Cracknell A P Remotesensing techniques in estuaries and coastal zones: An updateInternational Journal of Remote Sensing 1999 20485496.
doi:10.1080/014311699213280
32 Gray A J Saltmarsh plant ecology: Zonation and succession revisitedIn: Allen J R LPye KSalt Marshes: Morphodynmics, Conservation and EngineeringSignificanceCambridge, UKCambridge University Press 1992 6379
33 Silvestri S Marani M Settle J Benvenuto F Marani A Salt marsh vegetation radiometry:Data analysis and scalingRemote Sensingof Environment 2002 80473482.
doi:10.1016/S0034‐4257(01)00325‐X
34 Zhang L Q Yong X K Studies on phenology and spatialdistribution of Scirpus mariqueter populationActa Phytoecologica Sinica 1992 164351 (in Chinese)
35 Huang H M Zhang L Q Gao Z G A study into the vegetation resource at the intertidalzone in Shanghai using remote sensingActaEcologica Sinica 2005 25(10)26862693 (in Chinese)
36 Eastwood J A Yates M G Thomon A G Fuller R M The reliabilityof vegetation indices for monitoring saltmarsh vegetation coverInternational Journal of Remote Sensing 1997 1839013907.
doi:10.1080/014311697216739
37 Milton E J Rollin E M Emmery D R Advances in field spectroscopyIn: Danson F MPlummer S EAdvances in Environmental Remote SensingChichesterJohnWiley and Son 1995 932
38 Crist E P Cicone R J A physical-based transformationof Thematic Mapper data–the Tasselled CapIEEE Transaction on Geosciences and Remote Sensing 1984a GE22256263.
doi:10.1109/TGRS.1984.350619
39 Crist E P Cicone R J Application of the TasselledCap concept to simulated Thematic Mapper dataPhotogrammetric Engineering and Remote Sensing 1984b 50343352
40 Crist E P Kauth R J The Tasselled Cap de-mystifiedPhotogrammetric Engineering and Remote Sensing 1986 528186
41 Canas A D D Barnett M E The generation and interpretationof false colour composite principal component imagesInternational Journal of Remote Sensing 1985 6867881.
doi:10.1080/01431168508948510
42 McCune B Mefford M J PC-ORD. Multivariate Analysisof Ecological Data. Version 4.GlenedenBeach, Oregon, USAMjM SoftwareDesign 1999
43 Atkinson M D Plummer S E The influence of percentagecover and biomass of clover on the reflectance of mixed pastureInternational Journal of Remote Sensing 1993 1414391444.
doi:10.1080/01431169308953978
44 Sims D A Gamon J A Relationship between leaf pigmentcontent and spectral reflectance across a wide range of species, leafstructures and development stagesRemoteSensing of Environment 2002 81337354.
doi:10.1016/S0034‐4257(02)00010‐X
45 Wang Y R Yong S P The use of multitemporal near-groundspectral reflectance to discriminate among degraded grasslandsActa Phytoecologica Sinica 2004 28406413 (in Chinese)
46 Tucker C J Maxwell E L Sensor design for monitoringvegetation canopiesPhotogrammetric Engineeringand Remote Sensing 1976 4213991410
47 Filella I Penuelas J The red edge position and shapeas an indicator of plant chlorophyll content, biomass and hydric statusInternational Journal of Remote Sensing 1994 1514591470.
doi:10.1080/01431169408954177
48 Bowers S A Hanks R J Reflection of radiant energyfrom soilsSoil Science 1965 2130138
49 Hoffer R M Johannsen J Ecological potentials in spectralsignature analysisIn: Johnson P LRemote Sensing in EcologyAthens, Georgia, USAAthens Universityof Georgia Press 1969 129
50 Price J C Variabilityof high resolution crop reflectance spectraInternational Journal of Remote Sensing 1992 1425932610.
doi:10.1080/01431169208904066
51 Price J C Howunique are spectral signatures?Remote Sensingof Environment 1994 49181186.
doi:10.1016/0034‐4257(94)90013‐2
52 Davidson D A Watson A I Spatial variability in soilmoisture as predicted from Airborne Thematic Mapper (ATM) dataEarth Surface Processes 1995 20219230.
doi:10.1002/esp.3290200304
53 Muller E Décamps H Modeling soil moisture reflectanceRemote Sensing of Environment 2000 76173180.
doi:10.1016/S0034‐4257(00)00198‐X
54 Bork E W West N E Price K P Calibration of broad- and narrow-band spectral variablesfor rangeland cover component quantificationInternational Journal of Remote Sensing 1999 2036413662.
doi:10.1080/014311699211255
55 Chavez A Y Kwarteng P S Change detection study of KuwaitCity and environs using multi-temporal Landsat Thematic Mapper dataInternational Journal of Remote Sensing 1998 1916511662.
doi:10.1080/014311698215162
56 Pu R L Gong P Hyperspectral Remote Sensingand Its ApplicationsBeijingHigher Education Press 2000 8186 (in Chinese)
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed