@InProceedings{NevesJúniLuizSanc:2017:ÍnCoVe,
               author = "Neves, Marcos Corr{\^e}a and J{\'u}nior, Othon da Rocha Neves 
                         and Luiz, Alfredo Jos{\'e} Barreto and Sanches, Ieda Del Arco",
          affiliation = "{} and {} and {} and {Instituto Nacional de Pesquisas Espaciais 
                         (INPE)}",
                title = "{\'{\I}}ndice de cobertura verde para imagens de 
                         alt{\'{\i}}ssima resolu{\c{c}}{\~a}o",
            booktitle = "Anais...",
                 year = "2017",
               editor = "Gherardi, Douglas Francisco Marcolino and Arag{\~a}o, Luiz 
                         Eduardo Oliveira e Cruz de",
                pages = "1273--1280",
         organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 18. (SBSR)",
            publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
              address = "S{\~a}o Jos{\'e} dos Campos",
             abstract = "The low altitude aerial images are becoming more common every day 
                         due to low cost and ease of useof platforms such as remotely 
                         piloted aircraft. The potential application of this type of data 
                         is very high. Oneexample is the precision agriculture, a farming 
                         management concept based on observing, measuring andresponding to 
                         inter and intra-field variability in crops, an activity than can 
                         greatly benefit from this technology.The low altitude of image 
                         acquisition allows very high level of scene details but aggravates 
                         problems such aslighting variation and image deformation. In 
                         addition, often common cameras are used in different 
                         situationsaltitude, inclination, lighting and camera setup. These 
                         specific characteristics in relation to the orbital datarequire 
                         development of new methods and approaches to exploit the potential 
                         of data and to mitigate problemsand limitations. In this work we 
                         present a proposal for a method that provides a green coverage 
                         index. It reflectsthe green pixels density in an area. The 
                         proposed index has similar applicability to vegetation indices but 
                         doesnot require near-infrared data, not available in common 
                         cameras. We show problems especially related toagriculture 
                         applications, present initial test results discuss the 
                         possibilities and limitations of the method.",
  conference-location = "Santos",
      conference-year = "28-31 maio 2017",
                 isbn = "978-85-17-00088-1",
                label = "59957",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "8JMKD3MGP6W34M/3PS4GE7",
                  url = "http://urlib.net/ibi/8JMKD3MGP6W34M/3PS4GE7",
           targetfile = "59957.pdf",
                 type = "VANTs, videografia e alta resolu{\c{c}}{\~a}o",
        urlaccessdate = "27 abr. 2024"
}