Applying machine learning based on multiscale classifiers to detect remote phenology patterns in Cerrado savanna trees

Ecological Informatics

Volumn 23, Issue , 2014, Pages 49-61

  Almeida, Jurandy ^a   Dos Santos, Jefersson A ^a   Alberton, Bruna ^b   Torres, Ricardo da S ^a   Morellato, Leonor Patricia C ^b  

^a UNIVERSITY OF CAMPINAS   (Brazil)

^b SÃO PAULO STATE UNIVERSITY UNESP   (Brazil)

Author keywords

Digital cameras; Image analysis; Machine learning; Remote phenology; Tropical forests

Indexed keywords

CLIMATE EFFECT; COLOR MORPH; DIGITAL IMAGE; LEARNING; PHENOLOGY; SAVANNA; TEXTURE; TREE;

EID: 84905117659     PISSN: 15749541     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ecoinf.2013.06.011     Document Type: Article

References (44)

1. Ahrends H., Etzold S., Kutsch W., Stoeckli R., Bruegger R., Jeanneret F., Wanner H., Buchmann N., Eugster W. Tree phenology and carbon dioxide fluxes: use of digital photography for process-based interpretation at the ecosystem scale. Climate Research 2009, 39:261-274.
2. Alberton B., Almeida J., Henneken R., Torres R.da S., Menzel A., Morellato L.P.C. Near remote phenology: applying digital images to monitor leaf phenology in a Brazilian Cerrado savanna. International Conference on Phenology (Phenology'12) 2012, 2.
3. Almeida J., dos Santos J.A., Alberton B., Torres R.da S., Morellato L.P.C. Remote phenology: applying machine learning to detect phenological patterns in a Cerrado savanna. IEEE International Conference on eScience (eScience'12) 2012, 1-8.
4. Almeida J., dos Santos J.A., Alberton B., Morellato L.P.C., Torres R.da S. Visual rhythm-based time series analysis for phenology studies. IEEE International Conference on Image Processing (ICIP'13) 2013, 1-5.
5. Alpaydin E. Introduction to Machine Learning. Adaptive Computation and Machine Learning 2010, MIT Press.
6. Andrade F.S.P., Almeida J., Pedrini H., Torres R.da S. Fusion of local and global descriptors for content-based image and video retrieval. Iberoamerican Congress on, Pattern Recognition (CIARP'12) 2012, 845-853.
7. Cheng H.-D., Jiang X., Sun Y., Wang J. Color image segmentation: advances and prospects. Pattern Recognition 2001, 34(12):2259-2281.
8. Cope J.S., Corney D.P.A., Clark J.Y., Remagnino P., Wilkin P. Plant species identification using digital morphometrics: a review. Expert Systems with Applications 2012, 39(8):7562-7573.
9. Coutinho L.M. O conceito de cerrado. Brazilian Journal of Botany 1978, 1:17-23.
10. Culbert P.D., Pidgeon A.M., St.-Louis V., Bash D., Radeloff V.C. The impact of phenological variation on texture measures of remotely sensed imagery. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 2009, 2(4):299-309.
11. dos Santos J.A., Faria F.A., Torres R.da S., Rocha A., Gosselin P.-H., Philipp-Foliguet S., Falcão A.X. Descriptor correlation analysis for remote sensing image multiscale classification. IEEE International Conference on Pattern Recognition (ICPR'12) 2012, 3078-3081.
12. dos Santos J.A., Gosselin P.-H., Philipp-Foliguet S., Torres R.da S., Falcão A.X. Multiscale classification of remote sensing images. IEEE Transactions on Geoscience and Remote Sensing 2012, 50(10):3764-3775.
13. Grabner H., Bischof H. On-line boosting and vision. IEEE International Conference on Computer Vision and, Pattern Recognition (CVPR'06) 2006, 260-267.
14. Guigues L., Cocquerez J., Le Men H. Scale-sets image analysis. International Journal of Computer Vision 2006, 68:289-317.
15. Haralick R.M., Shanmugam K., Dinstein I. Textural features for image classification. IEEE Transaction on Systems, Man and Cybernetics 1973, 3(6):610-621.
16. Ide R., Oguma H. Use of digital cameras for phenological observations. Ecological Informatics 2010, 5:339-347.
17. Keeling C.D., Chin J.F.S., Whorf T.P. Increased activity of northern vegetation inferred from atmospheric co2 measurements. Nature 1996, 382:146-149.
18. Kumar N., Belhumeur P.N., Biswas A., Jacobs D.W., Kress W.J., Lopez I.C., Soares J.V.B. Leafsnap: a computer vision system for automatic plant species identification. European Conference on Computer Vision (ECCV'12) 2012, 502-516.
19. Kurc S., Benton L. Digital image-derived greenness links deep soil moisture to carbon uptake in a creosotebush-dominated shrubland. Journal of Arid Environments 2010, 74:585-594.
20. Lechervy A., Gosselin P.-H., Precioso F. Boosted Kernel for Image Categorization. Multimedia Tools and Applications 2013.
21. Loustau D., Bosc A., Colin A., Davi H., François C., Dufrêne E., Équé M., Cloppet E., Arrouays D., Le Bas C., Saby N., Pignard G., Hamza N., Granier A., Breda N., Ciais P., Viovy N., Ogée J., Delage J. Modeling the climate change effects on the potential reduction of french plains forests at the sub regional level. Tree Physiology 2005, 25:813-823.
22. Morellato L.P.C., Rodrigues R.R., Leitão Filho H.F., Joly C.A. Estudo comparativo da fenologia de espécies arbóreas de floresta de altitude e floresta mesófila semidecídua na serra do iapí, jundiaí, são paulo. Brazilian Journal of Botany 1989, 12:85-98.
23. Nagai S., Maeda T., Gamo M., Muraoka H., Suzuki R., Nasahara K.N. Using digital camera images to detect canopy condition of deciduous broad-leaved trees. Plant Ecology and Diversity 2011, 4:79-89.
24. Negi G.C.S. Leaf and bud demography and shoot growth in evergreen and deciduous trees of Central Himalaya, India. Trees 2006, 20:416-429.
25. Parmesan C., Yohe G.A. A globally coherent fingerprint to climate change impacts accross natural systems. Nature 2003, 421:37-42.
26. Reich P.B. Phenology of tropical forests: patterns, causes and consequences. Canadian Journal of Botany 1995, 73:164-174.
27. Reys P. Estrutura e fenologia da vegetação de borda e interior em um fragmento de cerrado Sensu Stricto no sudeste do brasil (itirapina, são paulo) 2008, (Ph.D. thesis), Bioscience Institute, Sao Paulo State University, Rio Claro, SP, Brazil.
28. Richardson A.D., Jenkins J.P., Braswell B.H., Hollinger D.Y., Ollinger S.V., Smith M.L. Use of digital webcam images to track spring greep-up in a deciduous broadleaf forest. Oecologia 2007, 152:323-334.
29. Richardson A.D., Braswell B.H., Hollinger D.Y., Jenkins J.P., Ollinger S.V. Near-surface remote sensing of spatial and temporal variation in canopy phenology. Ecological Applications 2009, 19:1417-1428.
30. Rosenzweig C., Karoly D., Vicarelli M., Neofotis P., Wu Q., Casassa G., Menzel A., Root T.L., Estrella N., Seguin B., Tryjanowski P., Liu C., Rawlins S., Imeson A. Attributing physical and biological impacts to anthropogenic climate change. Nature 2008, 453:353-357.
31. Rostamizadeh A., Talwalker A. Foundations of Machine Learning. Adaptive Computation and Machine Learning Series 2012, University Press Group Limited.
32. Rotzer T., Grote R., Pretzsch H. The timing of bud burst and its effect on tree growth. International Journal of Biometeorology 2004, 48:109-118.
33. Schapire R.E. A brief introduction to boosting. International Joint Conference on, Artificial Intelligence (IJCAI'99) 1999, 1401-1406. T. Dean (Ed.).
34. Schwartz M.D. Phenology: An Integrative Environmental Science 2003, Academic Publishers.
35. Schwartz M.D., Reed B.C., White M.A. Assessing satellite derived start-of-season measures in the coterminous. International Journal of Climatology 2002, 22:1793-1805.
36. Staggemeier V.G., Diniz-Filho J.F., Morellato L.P.C. The shared influence of phylogeny and ecology on the reproductive patterns of Myrteae (Myrtaceae). Journal of Ecology 2010, 98:1409-1421.
37. Tan P.-N., Steinbach M., Kumar V. Introduction to Data Mining 2005, Addison-Wesley.
38. Torres R.da S., Falcão A.X. Content-based image retrieval: theory and applications. Revista de Informática Teórica e Aplicada 2006, 13(2):161-185.
39. Torres R.da S., Hasegawa M., Tabbone S., Almeida J., dos Santos J.A., Alberton B., Morellato L.P.C. Shape-based time series analysis for remote phenology studies. IEEE International Geoscience and Remote Sensing Symposium (IGARSS'13) 2013, 1-4.
40. Unser M. Sum and difference histograms for texture classification. IEEE Transactions on Pattern Analysis and Machine Intelligence 1986, 8(1):118-125.
41. Viola P., Jones M. Rapid object detection using a boosted cascade of simple features. IEEE International Conference on Computer Vision and, Pattern Recognition (CVPR'01) 2001, 511-518.
42. Walther G.R. Plants in a warmer world. Perspectives in Plant Ecology Evolution and Systematics 2004, 6:169-185.
43. Walther G.R., Post E., Convey P., Menzel A., Parmesan C., Beebee T.J.C., Fromentin J.M., Hoegh-Guldberg O., Bairlein F. Ecological responses to recent climate change. Nature 2002, 416:389-395.
44. White M.A., Running S.W., Thornton P.E. The impact of growing-season length variability on carbon assimilation and evapotranspiration over 88years in the eastern us deciduous forest. International Journal of Biometeorology 1999, 42:139-145.