1,721,018 research outputs found
Deriving Vegetation Indices For Phenology Analysis Using Genetic Programming
No full textPlant phenology studies recurrent plant life cycle events and is a key component for understanding the impact of climate change. To increase accuracy of observations, new technologies have been applied for phenological observation, and one of the most successful strategies relies on the use of digital cameras, which are used as multi-channel imaging sensors to estimate color changes that are related to phenological events. We monitor leaf-changing patterns of a cerrado-savanna vegetation by taking daily digital images. We extract individual plant color information and correlate with leaf phenological changes. For that, several vegetation indices associated with plant species are exploited for both pattern analysis and knowledge extraction. In this paper, we present a novel approach for deriving appropriate vegetation indices from vegetation digital images. The proposed method is based on learning phenological patterns from plant species through a genetic programming framework. A comparative analysis of different vegetation indices is conducted and discussed. Experimental results show that our approach presents higher accuracy on characterizing plant species phenology.26P36169Ahrends, 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) Clim. Res., 39, pp. 261-274Alberton, 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) Ecol. Inform., 19, pp. 62-70Almeida, 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., Morellato, L.P.C., da S.Torres, R., Plant species identification with phenological visual rhythms (2013) IEEE International Conference on eScience (eScience'13), pp. 148-154Almeida, 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. 4412-4416Almeida, 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) Ecol. Inform., 23, pp. 49-61Andrade, F.S.P., Almeida, J., Pedrini, H., da S.Torres, R., Fusion of local and global descriptors for content-based image and video retrieval (2012) Iberoamerican Congress on, Pattern Recognition (CIARP'12), pp. 845-853Baeza-Yates, R.A., Ribeiro-Neto, B.A., (1999) Modern Information Retrieval, , Addison-Wesley Longman Publishing Co., Inc., Boston, MA, USABimbo, A., (1999) Visual Information Retrieval, , Morgan Kaufmann Publishers Inc., San Francisco, CA, USACalumby, R.T., da S.Torres, R., Gonçalves, M.A., Multimodal retrieval with relevance feedback based on genetic programming (2014) Multimed. Tools Appl., 69 (3), pp. 991-1019Conti, 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 (2014) IEEE International Conference on Pattern Recognition (ICPR'14), pp. 1-6da 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 (2009) Pattern Recogn., 42 (2), pp. 283-292Davis, J., Goadrich, M., The relationship between precision-recall and roc curves (2006) ACM International Conference on, Machine Learning (ICML'06), pp. 233-240Fan, W., Fox, E.A., Pathak, P., Wu, H., The effects of fitness functions on genetic programming-based ranking discovery forweb search (2004) J. Am. Soc. Inf. Sci. Technol., 55 (7), pp. 628-636Faria, 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 (2010) ACM International Conference on Multimedia Information Retrieval (MIR'10), pp. 285-294Ferreira, 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 (2011) Pattern Recogn. Lett., 32 (1), pp. 27-37Fishburn, P.C., (1988) Nonlinear Preference and Utility Theory, , Johns Hopkins University PressGillespie, A.R., Kahle, A.B., Walker, R.E., Color enhancement of highly correlated images. II. Channel ratio and "chromaticity" transformation techniques (1987) Remote Sens. Environ., 22 (3), pp. 343-365Gonzalez, R.C., Woods, R.E., (2007) Digital Image Processing, , Prentice-Hall Inc., Upper Saddle River, NJ, USAGuigues, L., Cocquerez, J., Le Men, H., Scale-sets image analysis (2006) Int. J. Comput. Vis., 68, pp. 289-317Henneken, R., Dose, V., Schleip, C., Menzel, A., Detecting plant seasonality from webcams using bayesian multiple change point analysis (2013) Agric. For. Meteorol., 168, pp. 177-185Ide, R., Oguma, H., Use of digital cameras for phenological observations (2010) Ecol. Inform., 5 (5), pp. 339-347Ide, 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 (2013) Ecol. Inform., 16, pp. 25-34Koza, J.R., (1992) Genetic Programming: on the Programming of Computers by Means of Natural Selection, , MIT PressKurc, S., Benton, L., Digital image-derived greenness links deep soil moisture to carbon uptake in a creosotebush-dominated shrubland (2010) J. 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Bot., 12, pp. 85-98Morellato, L.P.C., Camargo, M.G.G., Gressler, E., A review of plant phenology in south and central america (2013) Phenology: An Integrative Environmental Science, pp. 91-113. , Springer, (chapter 6), M.D. Schwartz (Ed.)Morisette, J.T., Richardson, A.D., Knapp, A.K., Fisher, J.I., Graham, E.A., Abatzoglou, J., Wilson, B.E., Liang, L., Tracking the rhythm of the seasons in the face of global change: phenological research in the 21st century (2009) Front. Ecol. Environ., 7 (5), pp. 253-260Muttil, N., Lee, J.H.W., Genetic programming for analysis and real-time prediction of coastal algal blooms (2005) Ecol. Model., 189 (3-4), pp. 363-376Nagai, 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 Ecol. 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Phenological Event Detection By Visual Rhythms Dissimilarity Analysis
No full textFundação 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
Applying Machine Learning Based On Multiscale Classifiers To Detect Remote Phenology Patterns In Cerrado Savanna Trees
No full textPlant phenology is one of the most reliable indicators of species responses to global climate change, motivating the development of new technologies for phenological monitoring. Digital cameras or near remote systems have been efficiently applied as multi-channel imaging sensors, where leaf color information is extracted from the RGB (Red, Green, and Blue) color channels, and the changes in green levels are used to infer leafing patterns of plant species. In this scenario, texture information is a great ally for image analysis that has been little used in phenology studies. We monitored leaf-changing patterns of Cerrado savanna vegetation by taking daily digital images. We extract RGB channels from the digital images and correlate them with phenological changes. Additionally, we benefit from the inclusion of textural metrics for quantifying spatial heterogeneity. Our first goals are: (1) to test if color change information is able to characterize the phenological pattern of a group of species; (2) to test if the temporal variation in image texture is useful to distinguish plant species; and (3) to test if individuals from the same species may be automatically identified using digital images. In this paper, we present a machine learning approach based on multiscale classifiers to detect phenological patterns in the digital images. Our results indicate that: (1) extreme hours (morning and afternoon) are the best for identifying plant species; (2) different plant species present a different behavior with respect to the color change information; and (3) texture variation along temporal images is promising information for capturing phenological patterns. Based on those results, we suggest that individuals from the same species and functional group might be identified using digital images, and introduce a new tool to help phenology experts in the identification of new individuals from the same species in the image and their location on the ground. © 2013 Elsevier B.V.234961Ahrends, 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. 261-274Alberton, B., Almeida, J., Henneken, R., Torres, R.D.S., Menzel, A., Morellato, L.P.C., Near remote phenology: applying digital images to monitor leaf phenology in a Brazilian Cerrado savanna (2012) International Conference on Phenology (Phenology'12), p. 2Almeida, J., dos Santos, J.A., Alberton, B., Torres, R.D.S., 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., Morellato, L.P.C., Torres, R.D.S., Visual rhythm-based time series analysis for phenology studies (2013) IEEE International Conference on Image Processing (ICIP'13), pp. 1-5Alpaydin, E., (2010) Introduction to Machine Learning. Adaptive Computation and Machine Learning, , MIT PressAndrade, F.S.P., Almeida, J., Pedrini, H., Torres, R.D.S., Fusion of local and global descriptors for content-based image and video retrieval (2012) Iberoamerican Congress on, Pattern Recognition (CIARP'12), pp. 845-853Cheng, H.-D., Jiang, X., Sun, Y., Wang, J., Color image segmentation: advances and prospects (2001) Pattern Recognition, 34 (12), pp. 2259-2281Cope, J.S., Corney, D.P.A., Clark, J.Y., Remagnino, P., Wilkin, P., Plant species identification using digital morphometrics: a review (2012) Expert Systems with Applications, 39 (8), pp. 7562-7573Coutinho, L.M., O conceito de cerrado (1978) Brazilian Journal of Botany, 1, pp. 17-23Culbert, 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 (2009) IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2 (4), pp. 299-309dos Santos, J.A., Faria, F.A., Torres, R.D.S., Rocha, A., Gosselin, P.-H., Philipp-Foliguet, S., Falcão, A.X., Descriptor correlation analysis for remote sensing image multiscale classification (2012) IEEE International Conference on Pattern Recognition (ICPR'12), pp. 3078-3081dos Santos, J.A., Gosselin, P.-H., Philipp-Foliguet, S., Torres, R.D.S., Falcão, A.X., Multiscale classification of remote sensing images (2012) IEEE Transactions on Geoscience and Remote Sensing, 50 (10), pp. 3764-3775Grabner, H., Bischof, H., On-line boosting and vision (2006) IEEE International Conference on Computer Vision and, Pattern Recognition (CVPR'06), pp. 260-267Guigues, L., Cocquerez, J., Le Men, H., Scale-sets image analysis (2006) International Journal of Computer Vision, 68, pp. 289-317Haralick, R.M., Shanmugam, K., Dinstein, I., Textural features for image classification (1973) IEEE Transaction on Systems, Man and Cybernetics, 3 (6), pp. 610-621Ide, R., Oguma, H., Use of digital cameras for phenological observations (2010) Ecological Informatics, 5, pp. 339-347Keeling, C.D., Chin, J.F.S., Whorf, T.P., Increased activity of northern vegetation inferred from atmospheric co2 measurements (1996) Nature, 382, pp. 146-149Kumar, 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 (2012) European Conference on Computer Vision (ECCV'12), pp. 502-516Kurc, 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. 585-594Lechervy, A., Gosselin, P.-H., Precioso, F., (2013) Boosted Kernel for Image Categorization. Multimedia Tools and ApplicationsLoustau, D., Bosc, A., Colin, A., Davi, H., François, C., Dufrêne, E., Équé, M., Delage, J., Modeling the climate change effects on the potential reduction of french plains forests at the sub regional level (2005) Tree Physiology, 25, pp. 813-823Morellato, 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 (1989) Brazilian Journal of Botany, 12, pp. 85-98Nagai, 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. 79-89Negi, G.C.S., Leaf and bud demography and shoot growth in evergreen and deciduous trees of Central Himalaya, India (2006) Trees, 20, pp. 416-429Parmesan, C., Yohe, G.A., A globally coherent fingerprint to climate change impacts accross natural systems (2003) Nature, 421, pp. 37-42Reich, P.B., Phenology of tropical forests: patterns, causes and consequences (1995) Canadian Journal of Botany, 73, pp. 164-174Reys, P., (2008) Estrutura e fenologia da vegetação de borda e interior em um fragmento de cerrado Sensu Stricto no sudeste do brasil (itirapina, são paulo), , (Ph.D. thesis), Bioscience Institute, Sao Paulo State University, Rio Claro, SP, BrazilRichardson, 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. 323-334Richardson, 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. 1417-1428Rosenzweig, 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. 353-357Rostamizadeh, A., Talwalker, A., (2012) Foundations of Machine Learning. 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Using Phenological Cameras To Track The Green Up In A Cerrado Savanna And Its On-the-ground Validation
No full textPlant phenology has gained new importance in the context of global change research, stimulating the development of novel technologies for phenological observations. Regular digital cameras have been effectively used as three-channel imaging sensors, providing measures of leaf color change or phenological shifts in plants. We monitored a species rich Brazilian cerrado savanna to assess the reliability of digital images to detect leaf-changing patterns. Analysis was conducted by extracting color information from selected parts of the image named regions of interest (ROIs). We aimed to answer the following questions: (i) Do digital cameras capture leaf changes in cerrado savanna vegetation? (ii) Can we detect differences in phenological changes among species crowns and the cerrado community? (iii) Is the greening pattern detected for each species by digital camera validated by our on-the-ground leafing phenology (direct observation of tree leaf changes)? We analyzed daily sequences of five images per hour, taken from 6:00 to 18:00. h, recorded during the cerrado main leaf flushing season. We defined 24 ROIs in the original digital image, including total or partial regions and crowns of six plant species. Our results indicated that: (i) for the studied period, single plant species ROIs were more sensitive to changes in relative green values than the community ROIs, (ii) three leaf strategies could be depicted from the species' ROI patterns of green color change, and (iii) the greening patterns and leaf functional groups were validated by our on-the-ground phenology. 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Visual Rhythm-based Time Series Analysis For Phenology Studies
No full textPlant phenology has gained importance in the context of global change research, stimulating the development of new technologies for phenological observation. In this context, digital cameras have been successfully used as multi-channel imaging sensors, providing measures to estimate changes on phenological events, such as leaf flushing and senescence. We monitored leaf-changing patterns of a cerrado-savanna vegetation by taken daily digital images. For that, we extract leaf color information and correlated with phenological changes. In this way, time series associated with plant species are obtained, raising the need of using appropriate tools for mining patterns of interest. In this paper, we present a novel approach for representing phenological patterns of plant species. The proposed method is based on encoding time series as a visual rhythm, which is characterized by color description algorithms. A comparative analysis of different descriptors is conducted and discussed. Experimental results show that our approach presents high accuracy on identifying plant species. © 2013 IEEE.44124416The Institute of Electrical and Electronics Engineers (IEEE) Signal Processing SocietyWalther, 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 creosotebushdominated 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 Torres S, R., Menzel, A., Morellato, L.P.C., Near remote phenology: Applying digital images to monitor leaf phenology in a brazilian cerrado savanna (2012) Int. Conf. Phenology (Phenology'12), p. 2Forster, M., Schmidt, T., Schuster, C., Kleinschmit, B., Multi-temporal detection of grassland vegetation with rapideye imagery and a spectral-temporal library (2012) IEEE Int. Symp. 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 Int. Symp. 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Aspectos da autoecologia de Cecropia Glaziovii Snethl. (Cecropiaceae), fundamentos para o manejo e conservação de populações naturais da espécie
Get PDFDissertação (mestrado) - Universidade Federal de Santa Catarina, Centro de Ciências Biológicas. Programa de Pós-Graduação em Biologia Vegetal
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
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