Generalization of heterogeneous alpine vegetation in air photo-based image classification, Latnjajaure catchment, northern Sweden
DOI:
https://doi.org/10.3989/pirineos.2006.v161.1Keywords:
Tundra, plant community, GIS, CIR-air photo, digital classificationAbstract
Mapping alpine vegetation at a meso-scale (catchment level) using remote sensing presents difficulties due to a patchy distribution and heterogeneous spectral appearance of the plant cover. We discuss issues of generalization and accuracy assessment in this case study when using a digital CIR air photo for an automatic classification of the dominant plant communities. Spectral information from an aerial photograph was supplemented by classified plant communities in field and by topographical information derived from a DEM. 150 control points were tracked in the field using a GPS. The outcome from three alternative classifications was analysed by Kappa statistics, user’s and producer’s accuracy. Overall accuracy did not differ between the classifications although producer’s and user’s accuracy for separate classes differed together with total surface (ha) and distribution. Manual accuracy assessment when recording the occurrence of the correct class within a radius of 5 meters from the control points generated an improvement of 16 % of the total accuracy. About 10 plant communities could be classified with acceptable accuracy where the chosen classification scheme determined the final outcome. If a high resolution pixel mosaic is generalized to units that match the positional accuracy of simple GPS this generalization may also influence the information content of the image.
Downloads
References
Alatalo, J. M. (1998). Response to simulated climatic change in an alpine and subarctic pollen-risk strategist, Silene acaulis. Global Change Biology, 3 (Suppl. 1): 74-79. doi:10.1111/j.1365-2486.1997.gcb133.x
Allard, A.; Ihse, M. & Nordberg, M-J. (1998).Vegetationsförändringar i fjällen-metodstudier i norra fjällen med hjälp av IRF-flygbilder och satellitbilder. Research report No. 109. University of Stockholm, Department of Physical Geography, Sweden. 47 pp. (in Swedish).
Andersson, L. (1981). Vegetationskarta över de svenska fjällen. Kartblad nr 2 Abisko.
Barrio, G. del; Alvera, B.; Puigdefàbregas, J. & Díez, C. (1997). Response of high mountain landscape to topographic variables: Central Pyrenees. Landscape Ecol., 12: 95-115. doi:10.1007/BF02698210
Beylich, A. A. (2003). Present morphoclimates and morphodynamics in Latnjavagge, the northern Swedish Lapland and Austadalur, east Iceland. Jökull., 52: 33-54.
Beylich, A. A. (2004). Intensity and spatio-temporal variability of chemical denudation in an arctic-oceanic periglacial drainage basin in northernmost Swedish Lapland. Nord. Hydrol., 36 (1): 21-36.
Brown, D. G. (1994). Predicting vegetation types at treeline using topography and biophysical disturbance variables. J. Veg. Sci., 5: 641-656. doi:10.2307/3235880
Cohen, J. (1960). A coefficient of agreement for nominal scales. Educ. Psychol. Measurement., 20: 37-46. doi:10.1177/001316446002000104
Congalton, R. G. (1991). A review of assessing the accuracy of classifications of remotely sensed data. Remote Sens. Environ., 37: 35-46. doi:10.1016/0034-4257(91)90048-B
Congalton, R. G. (2001). Accuracy assessment and validation of remotely sensed and other spatial information. Int. J. Wildland Fire, 10: 321-328. doi:10.1071/WF01031
Damsholt, K. (2002). Illustrated flora of Nordic Liverworts and Hornworts. Nordic Bryological Society, 837 pp., Lund.
Dirnböck, T.; Dullinger, S.; Gottfried, M.; Ginzler, C. & Grabherr, G. (2003). Mapping alpine vegetation based on image analysis, topographic variables and Canonical Correspondence Analysis. Appl. Veg. Sci., 6: 85-96. doi:10.1658/1402-2001(2003)006[0085:MAVBOI]2.0.CO;2
Evans, B. M.; Walker, D. A.; Benson, C. S.; Nordstrand, E. A. & Petersen, G. W. (1989). Spatial interrelationships between terrain, snow distribution and vegetation patterns at an arctic foothills site in Alaska. Holarctic Ecol., 12: 270-278.
ERDAS IMAGINE Field Guide (1999). Fifth edition. ERDAS®, Inc., Atlanta, Georgia.
Fisher, H. S. (1990). Simulating the distribution of plant communities in an alpine area. Coenoses, 5 (1): 37-43.
Frank, D. (1988). Mapping dominant vegetation communities in the Colorado Rocky Mountain Front Range with Landsat Thematic Mapper and digital terrain data. Photogramm. Engin. Remote Sens., 54: 1727-1734.
Franklin, J. (1995). Predictive vegetation mapping: geographic modelling of biospatial patterns in relation to environmental gradients. Progr. Phys. Geogr., 19: 447-499. doi:10.1177/030913339501900403
Franklin, J. & Woodcock, C. E. (1997). Multiscale vegetation data for the mountains of southern California: Spatial and categorical resolution. In: Quattrochi, D. A. & Goodchild, M. F. (eds.) Scale in remote sensing and GIS, pp. 141-171. CRC-Lewis Publishers, Boca Raton, FL., USA.
Goodchild, M. F. (1994). Integrating GIS and remote sensing for vegetation analysis and modelling: methodological issues. In: WALSH, S. J.; DAVIS, F. W. & PEET, R. K. (eds.) Special features in Vegetation Science 6. J. Veg. Sci., 5: 615-626.
Goward, S. N.; Huemmrich, K. F. & Waring, R. H. (1994). Visible-Near Infrared spectral reflectance of landscape components in Western Oregon. Remote Sens. Environ., 47: 190-203. doi:10.1016/0034-4257(94)90155-4
Grabherr, G. (1997). Polar and alpine tundra. In: Wiegolaski, F. E. (ed.) Ecosystems of the world 3, pp. 97-121, Elsevier, Amsterdam.
Guisan, A. & Zimmerman, N. (2000). Predictive habitat distribution models in ecology. Ecol. Model. 135: 147-186. doi:10.1016/S0304-3800(00)00354-9
Hoersch, B.; Braun, G. & Schmidt, U. (2002). Relation between landform and vegetation in alpine regions of Wallis, Switzerland. A multiscale remote sensing and GIS approach. Computers, Environment and Urban Systems, 26: 113-139. doi:10.1016/S0198-9715(01)00039-4
Ihse, M. (1975). Flygbildstolkning av fjällvegetation-en metodstudie för översiktlig kartering. SNV PM 596, Sweden. 134 pp. (In Swedish).
Jenson, S. K. & Dominique, J. O. (1988). Extracting topographic structure from digital elevation data for geomorphic information system analysis. Photogramm. Eng. Rem. Sens., 54: 1593-1600.
Jägerbrand, A. K. (2005). Subarctic bryophyte ecology: phenotypic variation and responses to simulated environmental change. Ph. D. Thesis, Botanical Institute, University of Göteborg. Sweden, 34 pp.
Jägerbrand, A.; Lindblad, K. E. M.; Björk, R. G.; Alatalo, J. M. & Molau, U. (2005). Bryophyte and lichen diversity under simulated environmental change compared with observed variation in unmanipulated alpine tundra. Biodiversity and Conservation (in press).
Kling, J. (1996). Sorted circles and polygons in northern Sweden. Ph. D. thesis, University of Göteborg, Botanical Institute, Sweden, 28 pp.
Körner, C. (1999). Alpine plant life: functional plant ecology of high mountain ecosystems. Springer-Verlag, Berlin. 343 pp.
Landis, J. R. & Koch, G. G. (1977). The measurement of observer agreement for categorical data. Biometrics, 33: 159-174. doi:10.2307/2529310
Larsson, E. (2002). Seed banks and dispersal in subarctic and arctic environments. Ph. D. Thesis, University of Göteborg, Botanical Institute, Sweden. 41 pp.
Lillesand, T. M. & Kiefer, R. W. (2001). Remote sensing and image interpretation. 4th ed. John Wiley & Sons, Inc. 704 pp. USA.
Moberg, R. & Holmåsen, I. (2000). Lavar: En fälthandbok. Interpublishing, Stockholm. (In Swedish).
MOLAU, U.(2001). Tundra plant responses to experimental and natural temperature changes. Mem. Nat. Inst. Polar Research, Special Issue, 54: 445-466.
Molau, U. & LARSSON, E.-L. (2000). Seed rain and seed bank along an alpine altitudinal gradient. Can. J. Botany, 78: 728-747. doi:10.1139/cjb-78-6-728
Molau, U. & ALATALO, J. M. (1998). Responses of subarctic-alpine plant communities to simulated environmental change: Biodiversity of bryophytes, lichens, and vascular plants. Ambio, 27: 322-329.
Molau, U.; Kling, J.; Lindblad, K.; Björk, R.; Dänhardt, J. & Liess, A. (2003). AGIS Assessment of Alpine Biodiversity at a Range of Scales. In: Nagy, L., Grabherr, G., Körner, C. & Thompson, D. B. A. (eds.) Alpine Biodiversity in Europe. Ecological Studies Vol. 167, pp. 221-229. Springer-Verlag, Berlin, Heidelberg.
Moore, I. D.; Grayson, R. B. & Ladson, A. R. (1991). Digital terrain modelling: a review of hydrological, geomorphological and biological applications. Hydrol. Process, 5: 3-30. doi:10.1002/hyp.3360050103
Moore, I. D.; Gessler, P. E.; Nielsen, G. A. & Peterson, G. A. (1992). Soil attribute prediction, using terrain analysis. Soil Society of American Journal, 57: 443-452.
Mosbech, A. & Hansen, B. U. (1994). Comparison of satellite imagery and infrared aerial photography as vegetation mapping methods in an arctic study area; Jameson Land, East Greenland. Polar Res., 13: 139-152. doi:10.1111/j.1751-8369.1994.tb00444.x
Nilsen, L.; Brossard, T. & Joly, D. (1999). Mapping plant communities in a local arctic landscape applying a scanned aerial photograph in a geographical information system. Int. J. Remote Sensing, 20: 463-480. doi:10.1080/014311699213541
Nilsson, Ö. (1991). Nordisk fjällflora. Bonniers fakta bokförlag, Stockholm, Sweden. 272 pp. (In Swedish).
Påhlsson, L. (1998). Vegetationstyper i Norden. TemaNord 1998:510. Nordiska Ministerrådet, Köpenhamn. European vegetation types: the Nordic countries. –CD-Rom, DIVS 1998:801.
Pfeffer, K., Pebesma, B. J. & Burrough, P. A. (2003). Mapping alpine vegetation using vegetation observations and topographic attributes. Landscape Ecol., 18: 759-776. doi:10.1023/B:LAND.0000014471.78787.d0
Rosenfield, H. G. & Fitzpatrick-Lins, K. (1986). A coefficient of agreement as a measure of thematic classification accuracy. Photogramm. Engin. Remote Sens., 52: 223-227.
Schmidt, F. & Persson, A. (2003). Comparison of DEM data capture and Topographic Wetness Indices. Precision Agriculture, 4: 179-192. doi:10.1023/A:1024509322709
Skidmore, K. (1989). An expert system classifies Eucalypt forest types using Thematic Mapper Data and digital terrain model. Photogramm. Engin. Remote Sens., 55: 1449-1464.
Smith, J. H.; Stehman, S. V.; Wickham, J. D. & Yang, L. (2003). Effects of landscape characteristics on land-cover class accuracy. Remote Sensing of Environment, 84: 342-349. doi:10.1016/S0034-4257(02)00126-8
Söderström, L. & Hedenäs, L. (1998). Checklista över Sveriges mossor. (in swedish). Myrinia, 8: 58-90.
Stenström, M. (1998). Controls on reproductive effort and success in Saxifraga oppositifolia, an arctic-alpine perennial. Ph. D. Thesis, University of Göteborg, Botanical Institute, Sweden.
Stenström, A. (1999). Sexual reproductive ecology of Carex bigelowii, an arctic-alpine sedge. Ecography, 22: 305-313. doi:10.1111/j.1600-0587.1999.tb00506.x
Stenström, A. (2000). From pollination to variation reproduction in arctic clonal plants and the effects of simulated climate change. Ph. D. Thesis, University of Göteborg, Botanical Institute, Sweden.
Stenström, A. & Jónsdóttir I. S. (1997). Responses of the clonal sedge, Carex bigelowii, to two seasons of simulated climate change. Global Change Biol., 3 (Suppl. 1): 89-96. doi:10.1111/j.1365-2486.1997.gcb134.x
Stenström, M. & Molau, U. (1992). Reproductive biology in Saxifraga oppositifolia: phenology, mating systems, and reproductive success. Arct. Alp. Res; 24: 337-343. doi:10.2307/1551289
Story, M. & Congalton, R. G. (1986). Accuracy assessment: A User’s perspective. Photogramm. Engin. Remote Sens., 52: 397-399.
Treitz, P. M., Howarth, P. J. & Suffling, R. C. (1992). Application of detailed ground information to vegetation mapping with high spatial resolution digital imagery. Remote Sens. Environ., 42: 65-82. doi:10.1016/0034-4257(92)90068-U
Van Niel, K. P.; Laffan, S. W. & Lees, B. G. (2004). Effect of error in the DEM on environmental variables for predictive vegetation modelling. J. Veg. Sci., 15: 747-756. doi:10.1658/1100-9233(2004)015[0747:EOEITD]2.0.CO;2
Verbyla, D. L. & Hammond, T. O. (1995). Conservative bias in classification accuracy assessment due to pixel-by-pixel comparison of classified images with reference grids. Int. J. Remote Sensing, 16: 581-587. doi:10.1080/01431169508954424
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2006 Consejo Superior de Investigaciones Científicas (CSIC)
This work is licensed under a Creative Commons Attribution 4.0 International License.
© CSIC. Manuscripts published in both the printed and online versions of this Journal are the property of Consejo Superior de Investigaciones Científicas, and quoting this source is a requirement for any partial or full reproduction.All contents of this electronic edition, except where otherwise noted, are distributed under a “Creative Commons Attribution 4.0 International” (CC BY 4.0) License. You may read here the basic information and the legal text of the license. The indication of the CC BY 4.0 License must be expressly stated in this way when necessary.
Self-archiving in repositories, personal webpages or similar, of any version other than the published by the Editor, is not allowed.
