Phenological Event Detection By Visual Rhythms Dissimilarity Analysis

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Plant phenology has been exploited as an important research venue for assessing the impact of climate changes. One common approach for monitoring vegetation relies on the use of digital cameras. The employment of imaging techniques for phenological observation allows the extraction and analysis of visual characteristics based on color and texture information with the objective of determining plant life cycle changes, such as the beginning of the leaf flushing or the senescence period. This paper presents a novel approach for detecting phenological changes by analyzing image temporal series. Our method is based on the use of visual rhythm analysis and the adoption of a dissimilarity measure to detect visual changes in the time line. Experiments were conducted on a three-year data set composed of 3,538 vegetation images and 21 samples of 6 different species of interest. Results demonstrate that the proposed change detection approach is able to effectively identify phenological events.12632702007/59779-6; CAPES; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior; 2010/51307-0; FAPESP; Coordenação de Aperfeiçoamento de Pessoal de Nível SuperiorFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Walther, G.R., Post, E., Convey, P., Menzel, A., Parmesan, C., Beebee, T.J.C., Fromentin, J.M., Bairlein, F., Ecological responses to recent climate change (2002) Nature, 416, pp. 389-395Parmesan, C., Yohe, G.A., A globally coherent fingerprint to climate change impacts accross natural systems (2003) Nature, 421, pp. 37-42Walther, G.R., Plants in a warmer world (2004) Perspectives in Plant Ecology Evolution and Systematics, 6, pp. 169-185Rosenzweig, C., Karoly, D., Vicarelli, M., Neofotis, P., Wu, Q., Casassa, G., Menzel, A., Imeson, A., Attributing physical and biological impacts to anthropogenic climate change (2008) Nature, 453, pp. 353-357Richardson, 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 (2009) Ecological Applications, 19, pp. 1417-1428Richardson, 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 (2007) Oecologia, 152, pp. 323-334Ahrends, H., Etzold, S., Kutsch, W., Stoeckli, R., Bruegger, R., Jeanneret, F., Wanner, H., Eugster, W., Tree phenology and carbon dioxide fluxes: Use of digital photography for process-based interpretation at the ecosystem scale (2009) Climate Research, 39, pp. 261-274Ide, R., Oguma, H., Use of digital cameras for phenological observations (2010) Ecological Informatics, 5, pp. 339-347Kurc, S., Benton, L., Digital image-derived greenness links deep soil moisture to carbon uptake in a creosotebush-dominated shrubland (2010) Journal of Arid Environments, 74, pp. 585-594Nagai, 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 (2011) Plant Ecology and Diversity, 4, pp. 79-89Alberton, 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 (2014) Ecological Informatics, 19, pp. 62-70Almeida, J., Dos Santos, J.A., Alberton, B., Morellato, L.P.C., Da S Torres, R., Visual rhythm-based time series analysis for phenology studies (2013) IEEE International Conference on Image Processing (ICIP'13), pp. 4412-4416Forster, M., Schmidt, T., Schuster, C., Kleinschmit, B., Multitemporal detection of grassland vegetation with rapideye imagery and a spectral-temporal library (2012) IEEE International Symposium on Geoscience and Remote Sensing (IGARSS'12), pp. 4930-4933Rodrigues, A., Marcal, A.R.S., Cunha, M., Phenology parameter extraction from time-series of satellite vegetation index data using phenosat (2012) IEEE International Symposium on Geoscience and Remote Sensing (IGARSS'12), pp. 4926-4929Brooks, E.B., Thomas, V.A., Wynne, R.H., Coulston, J.W., Fitting the multitemporal curve: A fourier series approach to the missing data problem in remote sensing analysis (2012) IEEE Transactions on Geoscience and Remote Sensing, 50 (9), pp. 3340-3353Almeida, J., Dos Santos, J.A., Alberton, B., Morellato, L.P.C., Da S Torres, R., Plant species identification with phenological visual rhythms (2013) IEEE International Conference on EScience (eScience'13), pp. 148-154Priya, G.L., Domnic, S., Shot based keyframe extraction for ecological video indexing and retrieval (2013) Ecological Informatics, , to appearJiang, X., Sun, T., Liu, J., Chao, J., Zhang, W., An adaptive video shot segmentation scheme based on dual-detection model (2013) Neurocomputing, 116, pp. 102-111. , advanced Theory and Methodology in Intelligent Computing Selected Papers from the Seventh International Conference on Intelligent Computing (ICIC 2011)Ngo, C.W., Pong, T.C., Chin, R.T., Detection of gradual transitions through temporal slice analysis (1999) IEEE International Conference on Computer Vision and Pattern Recognition (CVPR'99), pp. 1036-1041Guimaraes, S.J.F., Couprie, M., ArÁujo, A.A., Leite, N.J., Video segmentation based on 2d image analysis (2003) Pattern Recognition Letters, 24 (7), pp. 947-957Guimaraes, S., Do Patrocinio, Z., Souza, K., De Paula, H., Gradual transition detection based on bipartite graph matching approach (2009) MMSP, pp. 1-6. , OctMorellato, L.P.C., Rodrigues, R.R., Leitao Filho, H.F., Joly, C.A., Estudo comparativo da fenologia de espécies arbóreas de floresta de altitude e floresta mesófila semidećdua na serra do iap, jundiÁ?, sao paulo (1989) Brazilian Journal of Botany, 12, pp. 85-98Serra, J., (1983) Image Analysis and Mathematical Morphology, , Orlando, FL, USA: Academic Press, IncLeite, N.J., Guimaraes, S.J.F., Morphological residues and a general framework for image filtering and segmentation (2001) EURASIP Journal on Advances in Signal Processing, 2001 (4), pp. 219-229Sonnentag, O., Hufkens, K., Teshera-Sterne, C., Young, A.M., Friedl, M., Braswell, B.H., Milliman, T., Richardson, A.D., Digital repeat photography for phenological research in forest ecosystems (2012) Agricultural and Forest Meteorology, 152, pp. 159-177Almeida, 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 (2012) IEEE International Conference on EScience (eScience'12), pp. 1-8Almeida, 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 (2014) Ecological Informatics, 23, pp. 49-6