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@InProceedings{CasagrandeMaSaTuHaMo:2017:PrNeNe,
               author = "Casagrande, Luan and Machado, Gustavo Mello and Samiappan, 
                         Sathishkumar and Turnage, Gray and Hathcock, Lee and Moorhead, 
                         Robert",
          affiliation = "Department of Computer Engineering, Universidade Federal de Santa 
                         Catarina, Ararangua, SC, Brazil; and Department of Computer 
                         Engineering, Universidade Federal de Santa Catarina, Ararangua, 
                         SC, Brazil; and Geosystems Research Institute, Mississippi State 
                         University, Starkville, MS, USA and Geosystems Research Institute, 
                         Mississippi State University, Starkville, MS, USA and Geosystems 
                         Research Institute, Mississippi State University, Starkville, MS, 
                         USA and Geosystems Research Institute, Mississippi State 
                         University, Starkville, MS, USA",
                title = "Probabilistic Neural Network and Wavelet Transform for Mapping of 
                         Phragmites australis Using Low Altitude Remote Sensing",
            booktitle = "Proceedings...",
                 year = "2017",
               editor = "Torchelsen, Rafael Piccin and Nascimento, Erickson Rangel do and 
                         Panozzo, Daniele and Liu, Zicheng and Farias, Myl{\`e}ne and 
                         Viera, Thales and Sacht, Leonardo and Ferreira, Nivan and Comba, 
                         Jo{\~a}o Luiz Dihl and Hirata, Nina and Schiavon Porto, Marcelo 
                         and Vital, Creto and Pagot, Christian Azambuja and Petronetto, 
                         Fabiano and Clua, Esteban and Cardeal, Fl{\'a}vio",
         organization = "Conference on Graphics, Patterns and Images, 30. (SIBGRAPI)",
            publisher = "IEEE Computer Society",
              address = "Los Alamitos",
             keywords = "Probablistic neural networks, Wavelets, Image texture 
                         classification, Wetlands, Phragmites.",
             abstract = "Phragmites australis (common reed) commonly found in the coastal 
                         wetlands can rapidly alter the ecology of these systems by 
                         outcompeting native plant species for resources. Identifying and 
                         mapping Phragmites can help resource managers to restore affected 
                         wetlands. In this work, we use probabilistic neural network with 
                         wavelet texture features for mapping regions with Phragmites in 
                         visible spectrum imagery acquired at low altitude with small 
                         unmanned aerial system. Evaluation study was conducted with 
                         imagery acquired in the delta of the Pearl River located in 
                         southeastern Louisiana and southwestern Mississippi, United States 
                         of America. In comparison to state-of-the-art, our approach 
                         presented improvements in several statistical variables such as 
                         overall accuracy and kappa value. Furthermore, we show that the 
                         remaining omission and commission errors with this technique are 
                         generally located along boundaries of patches with Phragmites, 
                         which reduces unnecessary efforts for resource managers while 
                         searching for nonexistent patches.",
  conference-location = "Niter{\'o}i, RJ",
      conference-year = "Oct. 17-20, 2017",
             language = "en",
           targetfile = "paper.pdf",
        urlaccessdate = "2021, Jan. 21"
}


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