Deriving vegetation indices for phenology analysis using genetic programming

Ecological Informatics

Volumn 26, Issue P3, 2015, Pages 61-69

  Almeida, Jurandy ^a,d   dos Santos, Jefersson A ^b   Miranda, Waner O ^b   Alberton, Bruna ^c   Morellato, Leonor Patricia C ^c   da S Torres, Ricardo ^d  

^a FEDERAL UNIVERSITY OF SÃO PAULO   (Brazil)

^b FEDERAL UNIVERSITY OF MINAS GERAIS   (Brazil)

^c SÃO PAULO STATE UNIVERSITY UNESP   (Brazil)

^d UNIVERSITY OF CAMPINAS   (Brazil)

Author keywords

Digital cameras; Genetic programming; Image analysis; Remote phenology; Vegetation indices

Indexed keywords

ACCURACY ASSESSMENT; BIOINFORMATICS; CERRADO; CLIMATE CHANGE; DIGITAL IMAGE; GENETIC ALGORITHM; IMAGE ANALYSIS; PHENOLOGY; SAVANNA; VEGETATION INDEX;

EID: 84922719400     PISSN: 15749541     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ecoinf.2015.01.003     Document Type: Article

References (39)

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. Clim. Res. 2009, 39:261-274.
2. Alberton B., Almeida J., Henneken R., da S.Torres R., Menzel A., Morellato L.P.C. Using phenological cameras to track the green up in a cerrado savanna and its on-the-ground validation. Ecol. Inform. 2014, 19:62-70.
3. Almeida J., dos Santos J.A., Alberton B., da S.Torres R., 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., da S.Torres R. Plant species identification with phenological visual rhythms. IEEE International Conference on eScience (eScience'13) 2013 a, 148-154.
5. Almeida J., dos Santos J.A., Alberton B., Morellato L.P.C., da S.Torres R. Visual rhythm-based time series analysis for phenology studies. IEEE International Conference on Image Processing (ICIP'13) 2013 b, 4412-4416.
6. Almeida J., dos Santos J.A., Alberton B., da S.Torres R., Morellato L.P.C. Applying machine learning based on multiscale classifiers to detect remote phenology patterns in cerrado savanna trees. Ecol. Inform. 2014, 23:49-61.
7. Andrade F.S.P., Almeida J., Pedrini H., da S.Torres R. Fusion of local and global descriptors for content-based image and video retrieval. Iberoamerican Congress on, Pattern Recognition (CIARP'12) 2012, 845-853.
8. Baeza-Yates R.A., Ribeiro-Neto B.A. Modern Information Retrieval 1999, Addison-Wesley Longman Publishing Co., Inc., Boston, MA, USA.
9. Bimbo A. Visual Information Retrieval 1999, Morgan Kaufmann Publishers Inc., San Francisco, CA, USA.
10. Calumby R.T., da S.Torres R., Gonçalves M.A. Multimodal retrieval with relevance feedback based on genetic programming. Multimed. Tools Appl. 2014, 69(3):991-1019.
11. Conti J.C., Faria F.A., Almeida J., Alberton B., Morellato L.P.C., Camolesi L., da S.Torres R. Evaluation of time series distance functions in the task of detecting remote phenology patterns. IEEE International Conference on Pattern Recognition (ICPR'14) 2014, 1-6.
12. da S.Torres R., Falcão A.X., Gonçalves M.A., Papa J.P., Zhang B., Fan W., Fox E.A. A genetic programming framework for content-based image retrieval. Pattern Recogn. 2009, 42(2):283-292.
13. Davis J., Goadrich M. The relationship between precision-recall and roc curves. ACM International Conference on, Machine Learning (ICML'06) 2006, 233-240.
14. Fan W., Fox E.A., Pathak P., Wu H. The effects of fitness functions on genetic programming-based ranking discovery forweb search. J. Am. Soc. Inf. Sci. Technol. 2004, 55(7):628-636.
15. Faria F.A., Veloso A., Almeida H.M., Valle E., da S.Torres R., Gonçalves M.A., Meira W. Learning to rank for content-based image retrieval. ACM International Conference on Multimedia Information Retrieval (MIR'10) 2010, 285-294.
16. Ferreira C.D., dos Santos J.A., da S.Torres R., Gonçalves M.A., Rezende R.C., Fan W. Relevance feedback based on genetic programming for image retrieval. Pattern Recogn. Lett. 2011, 32(1):27-37.
17. Fishburn P.C. Nonlinear Preference and Utility Theory 1988, Johns Hopkins University Press.
18. Gillespie A.R., Kahle A.B., Walker R.E. Color enhancement of highly correlated images. II. Channel ratio and "chromaticity" transformation techniques. Remote Sens. Environ. 1987, 22(3):343-365.
19. Gonzalez R.C., Woods R.E. Digital Image Processing 2007, Prentice-Hall Inc., Upper Saddle River, NJ, USA. 3rd Edition.
20. Guigues L., Cocquerez J., Le Men H. Scale-sets image analysis. Int. J. Comput. Vis. 2006, 68:289-317.
21. Henneken R., Dose V., Schleip C., Menzel A. Detecting plant seasonality from webcams using bayesian multiple change point analysis. Agric. For. Meteorol. 2013, 168:177-185.
22. Ide R., Oguma H. Use of digital cameras for phenological observations. Ecol. Inform. 2010, 5(5):339-347.
23. Ide R., Oguma H. A cost-effective monitoring method using digital time-lapse cameras for detecting temporal and spatial variations of snowmelt and vegetation phenology in alpine ecosystems. Ecol. Inform. 2013, 16:25-34.
24. Koza J.R. Genetic Programming: on the Programming of Computers by Means of Natural Selection 1992, MIT Press.
25. Kurc S., Benton L. Digital image-derived greenness links deep soil moisture to carbon uptake in a creosotebush-dominated shrubland. J. Arid Environ. 2010, 74:585-594.
26. 2 uptake. Agric. For. Meteorol. 2011, 151(10):1325-1337.
27. 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. Braz. J. Bot. 1989, 12:85-98.
28. Morellato L.P.C., Camargo M.G.G., Gressler E. A review of plant phenology in south and central america. Phenology: An Integrative Environmental Science 2013, 91-113. Springer, (chapter 6). M.D. Schwartz (Ed.).
29. Morisette J.T., Richardson A.D., Knapp A.K., Fisher J.I., Graham E.A., Abatzoglou J., Wilson B.E., Breshears D.D., Henebry G.M., Hanes J.M., Liang L. Tracking the rhythm of the seasons in the face of global change: phenological research in the 21st century. Front. Ecol. Environ. 2009, 7(5):253-260.
30. Muttil N., Lee J.H.W. Genetic programming for analysis and real-time prediction of coastal algal blooms. Ecol. Model. 2005, 189(3-4):363-376.
31. 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 Ecol. Divers. 2011, 4:79-89.
32. 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.
33. 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. Ecol. Appl. 2009, 19:1417-1428.
34. Rocha A., Almeida J., Nascimento M.A., da S., Torres R., Goldenstein S. Efficient and flexible cluster-and-search approach for CBIR. Advanced Concepts for Intelligent Vision Systems (ACIVS'08) 2008, 77-88.
35. Schwartz M.D. Phenology: An Integrative Environmental Science 2013, Springer. 2nd Edition.
36. Sonnentag O., Hufkens K., Teshera-Sterne C., Young A.M., Friedl M., Braswell B.H., Milliman T.O., Keefe J., Richardson A.D. Digital repeat photography for phenological research in forest ecosystems. Agric. For. Meteorol. 2012, 152:159-177.
37. Woebbecke D.M., Meyer G.E., Von-Bargen K., Mortensen A.D. Color indices for weed identification under various soil, residue, and lighting conditions. Trans. ASAE 1995, 38(1):259-269.
38. Zhao J., Zhang Y., Tan Z., Song Q., Liang N., Yu L., Zhao J. Using digital cameras for comparative phenological monitoring in an evergreen broad-leaved forest and a seasonal rain forest. Ecol. Inform. 2012, 10:65-72.
39. Zhou L., He H., Sun X., Zhang L., Yu G., Ren X.-L., Wang J.-Y., Zhao F.-H. Modeling winter wheat phenology and carbon dioxide fluxes at the ecosystem scale based on digital photography and eddy covariance data. Ecol. Inform. 2013, 18:69-78.