Automated training sample extraction for global land cover mapping

Remote Sensing

Volumn 6, Issue 5, 2014, Pages 3965-3987

  Radoux, Julien ^a   Lamarche, Céline ^a   Van Bogaert, Eric ^a   Bontemps, Sophie ^a   Brockmann, Carsten ^b   Defourny, Pierre ^a  

^a UNIVERSITÉ CATHOLIQUE DE LOUVAIN   (Belgium)

^b GITZ   (Germany)

Author keywords

Automated classification; Global land cover; Local training; MERIS; Morphological filtering; Trimming

Indexed keywords

AUTOMATION; CLIMATE CHANGE; GEOMETRICAL OPTICS; TRIMMING;

AUTOMATED CLASSIFICATION; LAND COVER; LOCAL TRAINING; MERIS; MORPHOLOGICAL FILTERING;

SAMPLING;

EID: 84901482913     PISSN: None     EISSN: 20724292     Source Type: Journal    
DOI: 10.3390/rs6053965     Document Type: Article

References (37)

1. Hollmann, R.; Merchant, C.; Saunders, R.; Downy, C.; Buchwitz, M.; Cazenave, A.; Chuvieco, E.; Defourny, P.; de Leeuw, G.; Forsberg, R.; et al. The ESA climate change initiative: Satellite data records for essential climate variables. Bull. Am. Meteorol. Soc. 2013, 94, 1541-1552.
2. Herold, M.; Achard, F.; deFries, R.; Mollicone, D. Earth Observation and Political Negotiations: Linking Requirements and Capabilities in the Context of the UNFCCC/REDD Process. In Proceedings of the 33rd International Symposium on Remote Sensing of Environment (ISRSE 2009), Stresa, Italy, 4-8 May 2009; pp. 1-4.
3. Defries, R.; Townshend, J. NDVI-derived land cover classifications at a global scale. Int. J. Remote Sens. 1994, 15, 3567-3586.
4. DeFries, R.; Hansen, M.; Townshend, J.; Sohlberg, R. Global land cover classifications at 8 km spatial resolution: The use of training data derived from Landsat imagery in decision tree classifiers. Int. J. Remote Sens. 1998, 19, 3141-3168.
5. Loveland, T.; Reed, B.; Brown, J.; Ohlen, D.; Zhu, Z.; Yang, L.; Merchant, J. Development of a global land cover characteristics database and IGBP DISCover from 1 km AVHRR data. Int. J. Remote Sens. 2000, 21, 1303-1330.
6. Arino, O.; Gross, D.; Ranera, F.; Leroy, M.; Bicheron, P.; Brockman, C.; Defourny, P.; Vancutsem, C.; Achard, F.; Durieux, L.; et al. GlobCover: ESA Service for Global Land Cover from MERIS. In Proceedings of IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2007), Barcelona, Spain, 23-28 July 2007; pp. 2412-2415.
7. Friedl, M.; Sulla-Menashe, D.; Tan, B.; Schneider, A.; Ramankutty, N.; Sibley, A.; Huang, X. MODIS Collection 5 global land cover: Algorithm refinements and characterization of new datasets. Remote Sens. Environ. 2010, 114, 168-182.
8. Bontemps, S.; Arino, O.; Bicheron, P.; Brockmann, C.; Leroy, M.; Vancutsem, C.; Defourny, P. Operational Service Demonstration for Global Land Cover Mapping. In Remote Sensing of Land Use and Land Cover: Principles and Applications, 1st ed.; Remote Sensing Applications Series; Giri, C.P., Ed.; CRC Press-Taylor & Francis: Boca Raton, FL, USA, 2012; Chapter 16, pp. 243-264.
9. Colditz, R.; Schmidt, M.; Conrad, C.; Hansen, M.; Dech, S. Land cover classification with coarse spatial resolution data to derive continuous and discrete maps for complex regions. Remote Sens. Environ. 2011, 115, 3264-3275.
10. Hansen, M.; Defries, R.; Townshend, J.; Sohlberg, R. Global land cover classification at 1 km spatial resolution using a classification tree approach. Int. J. Remote Sens. 2000, 21, 1331-1364.
11. Muchoney, D.; Strahler, A.; Hodges, J.; LoCastro, J. The IGBP DISCover confidence sites and the system for terrestrial ecosystem parameterization: Tools for validating global land-cover data. Photogramm. Eng. Remote Sens. 1999, 65, 1061-1067.
12. Pal, M.; Mather, P. Some issues in the classification of DAIS hyperspectral data. Int. J. Remote Sens. 2006, 27, 2895-2916.
13. Foody, G.; Arora, M. An evaluation of some factors affecting the accuracy of classification by an artificial neural network. Int. J. Remote Sens. 1997, 18, 799-810.
14. Tuia, D.; Pasolli, E.; Emery, W. Using active learning to adapt remote sensing image classifiers. Remote Sens. Environ. 2011, 115, 2232-2242.
15. Brodley, C.E.; Friedl, M.A. Identifying and Eliminating Mislabeled Training Instances. In AAAI; AAAI Press: Menlo Park, CA, USA, 1996; Volume 1, pp. 799-805.
16. Vancutsem, C.; Bicheron, P.; Cayrol, P.; Defourny, P. An assessment of three candidate compositing methods for global MERIS time series. Can. J. Remote Sens. 2007, 33, 492-502.
17. Di Gregorio, A.; Jansen, L. Land Cover Classification System (LCCS): Classification Concepts And User Manual. In GCP/RAF/287/ITA Africover-East Africa Project and Soil Resources, Management and Conservation Service; Food and Agriculture Organization: Rome, Italy, 2000; pp. 1-91
18. Herold, M.; Mayaux, P.; Woodcock, C.; Baccini, A.; Schmullius, C. Some challenges in global land cover mapping: An assessment of agreement and accuracy in existing 1 km datasets. Remote Sens. Environ. 2008, 112, 2538-2556.
19. Bontemps, S.; Bogaert, P.; Titeux, N.; Defourny, P. An object-based change detection method accounting for temporal dependencies in time series with medium to coarse spatial resolution. Remote Sens. Environ. 2008, 112, 3181-3191.
20. Hansen, M.; Loveland, T. A review of large area monitoring of land cover change using Landsat data. Remote Sens. Environ. 2012, 122, 66-74.
21. Vancutsem, C.; Defourny, P. A decision support tool for the optimization of compositing parameters. Int. J. Remote Sens. 2008, 30, 41-56.
22. Bruzzone, L.; Roli, F.; Serpico, S.B. Extension of the Jeffreys-Matusita distance to multiclass cases for feature selection. IEEE Trans. Geosci. Remote Sens. 1995, 33, 1318-1321.
23. Cortes, C.; Vapnik, V. Support vector network. Mach. Learn. 1995, 20, 273-297.
24. Hsu, C.W.; Lin, C.J. A comparison of methods for multi-class support vector machines. IEEE Trans. Neur. Netw. 2002, 13, 415-425.
25. Soille, P. Morphological Image Analysis; Springer-Verlag: Berlin, Germany, 1999.
26. Desclée, B.; Bogaert, P.; Defourny, P. Forest change detection by statistical object-based method. Remote Sens. Environ. 2006, 102, 1-11.
27. Radoux, J.; Defourny, P. Automated image-to-map discrepancy detection using iterative trimming. Photogramm. Eng. Remote Sens. 2010, 76, 173-181.
28. Colditz, R.; Lopez Saldana, G.; Maeda, P.; Argumedo Espinoza, J.; Meneses Tovar, C.; Victoria Hernandez, A.; Zermeno Benitez, C.; Cruz Lopez, I.; Ressl, R. Generation and analysis of the 2005 land cover map for Mexico using 250 m MODIS data. Remote Sens. Environ. 2012, 123, 541-552.
29. Defourny, P.; Mayaux, P.; Herold, M.; Bontemps, S. Global Land Cover Map Validation Experiences: Toward the Characterisation of Quantitative Uncertainty. In Remote Sensing of Land Use and Land Cover: Principles and Applications, 1st ed.; Remote Sensing Applications Series; Giri, C.P., Ed.; CPC Press-Taylor & Francis: Boca Raton, FL, USA, 2012; Chapter 14, pp. 207-222.
30. DeFries, R.S.; Chan, J.C.W. Development of a MODIS tree cover validation data set for Western Province, Zambia. Remote Sens. Environ. 2002, 74, 503-515.
31. Mayaux, P.; Eva, H.; Gallego, J.; Strahler, A.; Herold, M.; Agrawal, S.; Naumov, S.; de Miranda, E.; di Bella, C.; Ordoyne, C.; et al. Validation of the global land cover 2000 map. IEEE Trans. Geosci. Remote Sens. 2006, 44, 1728-1737.
32. Strahler, A.H.; Boschetti, L.; Foody, G.M.; Friedl, M.A.; Hansen, M.C.; Herold, M.; Mayaux, P.; Morisette, J.T.; Stehman, S.V.; Woodcock, C.E. Global land cover validation: Recommendations for evaluation and accuracy assessment of global land cover maps. GOFC-GOLD Rep. 2006, 25, 1-52.
33. Blanco, P.; Colditz, R.; Lopez Saldana, G.; Hardtke, L.; Llamas, R.; Mari, N.; Fischer, A.; Caride, C.; Acenolaza, P.; del Valle, H.; et al. A land cover map of Latin America and the Caribbean in the framework of the SERENA project. Remote Sens. Environ. 2013, 132, 13-31.
34. Schneider, A.; Friedl, M.; Potere, D. Mapping global urban areas using MODIS 500-m data: New methods and datasets based on "urban ecoregions". Remote Sens. Environ. 2010, 114, 1733-1746.
35. Pal, M.; Mather, P. Support vector machines for classification in remote sensing. Int. J. Remote Sens. 2005, 26, 1007-1011.
36. Mountrakis, G.; Im, J.; Ogole, C. Support vector machines in remote sensing: A review. ISPRS J. Photogramm. Remote Sens. 2011, 66, 247-259.
37. Foody, G.; Mathur, A. A relative evaluation of multiclass image classification by support vector machines. IEEE Trans. Geosci. Remote Sens. 2004, 42, 1335-1343.