Monitoring of the vegetation composition in rewetted peatland with iterative decision tree classifcation of satellite imagery

Photogrammetrie, Fernerkundung, Geoinformation

Volumn 2011, Issue 3, 2011, Pages 109-122

  Frick, Annett ^a   Steffenhagen, Peggy ^b   Zerbe, Stefan ^c   Timmermann, Tiemo ^b   Schulz, Karsten ^b  

^a LUP GmbH   (Germany)

^b FREE UNIVERSITY OF BOZEN BOLZANO   (Italy)

^c UNIVERSITY OF GREIFSWALD   (Germany)

Author keywords

Biomass; Carbon stock; Decision trees; Rewetted peatland; Vegetation monitoring; VHR

Indexed keywords

EID: 79958858290     PISSN: 14328364     EISSN: None     Source Type: Journal    
DOI: 10.1127/1432-8364/2011/0076     Document Type: Article

References (52)

1. BECKER, B.L., LUSCH, D.P. & QI, J., 2007: A classification-based assessment of the optimal spectral and spatial resolutions for Great Lakes coastal wetland imagery. - Remote Sensing of Environment 108: 111-120. (Pubitemid 46552024)
2. BERNHARD, J.M. & HANKINSON, G., 1979: Seasonal changes in standing crop, primary production and nutrient levels in a Carex rostrata wetland. - Oikos 32: 328-336.
3. BREIMAN, L., 1996: Bagging predictors. - Machine Learning 24 (2): 123-140. (Pubitemid 126724382)
4. BREIMAN, L., 2001: Random forests. - Machine Learning 45 (1): 5-32. (Pubitemid 32933532)
5. BREIMAN, L., FRIEDMAN, J., OLSHEN, R. & STONE, C., 1984: Classification and Regression Trees. - Chapman and Hall, New York, USA.
6. BRIX, H., SORRELL, B.K. & LORENZEN, B., 2001: Are Phragmites-dominated wetlands a net source or net sink of greenhouse gases? - Aquatic Botany 69 (2-4): 313-324. (Pubitemid 32319045)
7. BÜHLMANN, P. & HOTHORN, T., 2007: Boosting algorithms: regularization, prediction and modelfitting. - Statistical Science 22 (4): 477-505.
8. DYKYJOVÁ, D. & KVÉT, J., 1978: Pond Littoral Ecosystems - Structure and Functioning. - Springer, Berlin.
9. CHAN, J.C.-W. & PAELINCKX, D., 2008: Evaluation of Random Forest and Adaboost tree-based ensemble classification and spectral band selection for ecotope mapping using airborne hyperspectral imagery. - Remote Sensing of Environment 112: 2999-3011.
10. ELLENBERG, H., 1996: Vegetation Mitteleuropas mit den Alpen in ökologischer, dynamischer und historischer Sicht. - 5th ed., Ulmer, Stuttgart.
11. FISCHER, U., 2005: Entwicklung der Kulturlandschaft im Peene-Talmoor seit 1700. Historisch-landschaftsökologische Untersuchung eines nordostdeutschen Flußtalmoores unter besonderer Berücksichtigung des frühneuzeitlichen Zustandes. - Dissertation, Greifswald University.
12. FREUND, Y. & SCHAPIRE, R.E., 1996: Experiments with a new boosting algorithm. - Machine Learning: Thirteenth International Conference: 148-156.
13. FRIEDL, M.A. & BRODLEY, C.E., 1997: Decision tree classification of land cover from remotely sensed data. - Remote Sensing of Environment 61.
14. GELBRECHT, J., ZAK, D. & AUGUSTIN, J. (Eds.), 2008: Phosphor- und Kohlenstoffdynamik und Vegetationsentwicklung in wiedervernässten Mooren des Peenetals in Mecklenburg-Vorpommern. - Berichte des IGB (Leibniz-Institut für Gewässerökologie und Binnenfischerei) 26.
15. GROSSE-BRAUCKMANN, G., 1990: Ablagerungen der Moore. - Moor- und Torfkunde: 175-236; Sch-weizerbartsche Verlagsbuchhandlung, Stuttgart.
16. HARALICK, R.M., SHANMUGAN, K. & DINSTEIN, I., 1973: Textural Features for Image Classification. - IEEE Transactions on Systems, Man, and Cybernetics 3 (6): 610-621.
17. HARTMANN, M., 1999: Species dependent root decomposition in rewetted fen soils. - Plant and Soil 213: 93-98.
18. HEROLD, N.D., KOELN, G. & CUNNINGHAM, D., 2003: Mapping Impervious Surfaces and Forest Canopy Using Classification and Regression Tree (CART) Analysis. - ASPRS 2003 Annual Conference.
19. HÜTTICH, C., GESSNER, U., HEROLD, M., STROHBACH, B.J., SCHMIDT, M., KEIL, M. & DECH, S., 2009: On the Suitability of MODIS Time Series Metrics to Map Vegetation Types in Dry Savanna Ecosystems: A Case Study in the Kalahari of NE Namibia. - Remote Sensing 1 (4): 620-643.
20. JANSEN, F., ZERBE S. & SUCCOW, M., 2009: Changes in landscape naturalness derived from a historical land register - a case study from NE Germany. - Landscape Ecology 24 (2): 185-196.
21. KEARNS, M. & MANSOUR, Y., 1998: A fast, bottom-up decision tree pruning algorithm with near-optimal generalisation. - 15th International Conference on Machine Learning: 269-277.
22. KOWATSCH, A., 2007: Moorschutzkonzepte und -programme in Deutschland. - Naturschutz und Landschaftsplanung 39 (7): 197-204.
23. KÜHL, H. & KOHL, J.G., 1992: Nitrogen accumulation, productivity and stability of reed stands (Phragmites australis (Cav.) Trin. ex Steudel) at different lakes and sites of the lake districts Uckermark and Mark Brandenburg. - Internationale Revue der gesamten Hydrobiologie 77: 85-107.
24. LAWRENCE, R.L., WOOD, S.D. & SHELEY, R.L., 2006: Mapping invasive plants using hyperspectral imagery and Breiman Cutler classifications (RandomForest). - Remote Sensing of Environment 100: 356-362. (Pubitemid 43145876)
25. LENSCHOW, U., 1997: Landschaftsökologische Grundlagen und Ziele zum Moorschutz in Mecklenburg-Vorpommern. - Landesamt für Umwelt und Natur Mecklenburg-Vorpommern (Ed.) 3.
26. LI, Z., HAYWARD, R., ZHANG, J., JIN, H. & WALKER, R., 2010: Evaluation of spectral and texture features for object-based vegetation species classification using support vector machines. - ISPRS TC VII Symposium, IAPRS XXXVIII (7A).
27. LUNG, 1994-1997: Moorstandortkatalog Mecklenburg-Vorpommern. - Güstrow.
28. MANDER, U., LOHMUS, K., TEITER, S., MAURING, T., NURK, K. & AUGUSTIN, J., 2008: Gaseous fluxes in the nitrogen and carbon budgets of subsurface flow constructed wetlands. - Science of the Total Environment 404 (2-3): 343-353.
29. ODONK, J.P. & KVÉT, J., 1978: Selection of sampling areas in assessment of production. - Pond Littoral Ecosystems - Structure and Functioning: 163-174; Springer, Berlin.
30. OSTENDORP, W., 1988: Nährstoffkreisläufe und Nährstoffakkumulation in Seeufer-Schilfröhrichten - am Beispiel des Bodensee-Untersees. - Telma 18: 351-372. (Pubitemid 20421663)
31. OTUKEI, J. & BLASCHKE, T., 2010: Land cover change assessment using decision trees, support vector machines and maximum likelihood classification algorithms. - International Journal of Applied Earth Observation and Geoinformation 12: 27-31.
32. PÄTZOLT, J. & JANSEN, F., 2004: Molinio-Arrhenath-eretea Tx. 1937 - Wirtschaftsgrünland. - Die Pflanzengesellschaften Mecklenburg-Vorpommerns und ihre Gefährdung: 336-353; Weißdorn- Verlag, Jena.
33. PENGRA, B.W., JOHNSTON, C.A. & LOVELAND, T.R., 2007: Mapping an invasive plant, Phragmites australis, in coastal wetlands using the EO-1 Hyperion hyperspectral sensor. - Remote Sensing of Environment 108:74-81. (Pubitemid 46578133)
34. PERROW, M.R. & DAV Y, A.J. (eds.), 2002: Handbook of Ecological Restoration. - Cambridge University Press, Vol. 1 and 2; Cambridge, UK.
35. PFADENHAUER, J. & KLÖTZLI, F., 1996: Restoration experiments in middle European wet terrestrial ecosystems: An overview. - Vegetatio 126 (1): 101-115.
36. QUINLAN, J.R., 1993: C4.5: Programs for Machine Learning. - Morgan Kaufmann Publishers, San Mateo, USA.
37. RICHERT, M., DIETRICH, O., KOPPISCH, D. & ROTH, S., 2000: The influence of rewetting on vegetation development and decomposition in a degraded fen. - Restoration ecology 8 (2): 186-195. (Pubitemid 30419241)
38. ROTH, S., 2000: Etablierung von Schilfröhrichten und Seggenriedern auf wiedervernässten Niedermoor. - Dissertation, Greifswald University.
39. RUIZ, L.A., FDEZ-SARRÍA, A. & RECIO, J.A., 2004: Text ure Feature Extraction for Classification of Remote Sensing Data Using Wavelet Decomposition: A Comparative Study. - 20th ISPRS Congress, IAPSR XXXV (B4): 1109-1114.
40. SCHAPIRE, R.E., 1999: A brief introduction to boosting. - Sixteenth International Joint Conference on Artificial Intelligence 2: 1401-1406.
41. STEFFENHAGEN, P., FRICK, A., TIMMERMANN, T., ZER-BE, S. & SCHULZ, K., 2008: Vegetationsentwicklung sowie Kohlenstoff- und Nährstoffspeich-erung in der pflanzlichen Biomasse wieder-vernässter Niedermoore. - Phosphor- und Kohlenstoff-Dynamik und Vegetationsentwicklung in wiedervernässten Mooren des Peenetals in Mecklenburg-Vorpommern - Status, Steuergrößen und Handlungsmöglichkeiten, Berichte des IGB 26: 142-160.
42. SUCCOW, M., 2001: Revitalisierung von Moorökosystemen - Beispiele in Nordostdeutschland. Grundsätze. - Landschaftsökologische Moorkunde: 496-497; Schweizerbartsche Verlagsbuchhandlung, Stuttgart.
43. SUCCOW, M. & JOOSTEN, H. (Eds.), 2001: Landschaftsökologische Moorkunde. - 2nd ed., Schweizer-bartsche Verlagsbuchhandlung, Stuttgart.
44. TASSETTI, A.N., MALINVERNI, E.S. & HAHN, M., 2010: Texture Analysis to improve supervised classification in Ikonos Imagery. - ISPRS TC VII Symposium, IAPRS XXXVIII (7A).
45. TEMPERTON, V.M., HOBBS, R.J., NUTTLE, T. & HALLE, S., 2004: Assembly rules and restoration ecology: Bridging the gap between theory and practice. - Island Press, Washington, USA.
46. THEVS, N., ZERBE, S., GAHLERT, F., MIJIT, M. & SUCCOW, M., 2007: Productivity of reed (Phragmites australis Trin. ex Steud.) in continental-arid NW China in relation to soil, groundwater, and land-use. - Journal of Applied Botany and Food Quality 81: 62-68. (Pubitemid 47324815)
47. TIMMERMANN, T., JOOSTEN, H. & SUCCOW, M., 2009: Renaturierung von Mooren. - Renaturierung von Ökosystemen in Mitteleuropa: 55-93; Schweizerbartsche Verlagsbuchhandlung, Stuttgart.
48. TIMMERMANN, T., MARGÖCZI, K., TAKÁCS, G. & VEGELIN, K., 2006: Restoring peat forming vegetation by rewetting species-poor fen grasslands: the role of water level for early succession. -Applied Vegetation Science 9: 241-250.
49. TOU, J. & GONZALEZ, R., 1974: Pattern Recognition Principles. - Sensing of Environment 61: 399-409.
50. VAN ANDEL, J. & ARONSON, J., 2006: Restoration ecology. The new frontier. - Blackwell Publ., Oxford, UK.
51. WILCOX, D.A. & WHILLANS, T.H., 1999: Techniques for restoration of disturbed coastal wetlands of the Great Lakes. - Wetlands 19 (4): 835-857. (Pubitemid 30199669)
52. ZERBE, S. & WIEGLEB, G. (eds.), 2009: Renaturierung von Ökosystemen in Mitteleuropa. - Spektrum Akademischer Verlag, Heidelberg.