@InProceedings{OliveiraEpipRenn:2012:UsSpAn,
               author = "Oliveira, Julio Cesar de and Epiphanio, Jos{\'e} Carlos Neves and 
                         Renn{\'o}, Camilo Daleles",
          affiliation = "{Universidade Federal de Vi{\c{c}}osa (UFV)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de 
                         Pesquisas Espaciais (INPE)}",
                title = "The use of spatial-temporal analysis for noise reduction in MODIS 
                         NDVI time series data",
            booktitle = "Proceedings...",
                 year = "2012",
               editor = "Aquino A. R., Vieira C. A. O., Bogorny V",
                pages = "49--54",
         organization = "International Symposium on Spatial Accuracy Assessment in Natural 
                         Resources and Environmental Sciences, 10.",
             keywords = "Environmental engineering, Image processing, Natural resources, 
                         Noise abatement, Pixels, Quality control, Radiometers, Regression 
                         analysis, Reliability, Reliability analysis, Spatial variables 
                         measurement, Time series, Atmospheric variability, Cloud 
                         contamination, Modis ndvi, Production chain, Quality of product, 
                         Satellite data, Spatial temporal analysis, Spatial temporals, Time 
                         series analysis.",
             abstract = "Time series of satellite data can be employed for mapping the 
                         development of vegetation in space and time. However, noise 
                         induced by cloud contamination and atmospheric variability affects 
                         data quality. Science Datasets is an integral part of the MODIS 
                         Land production chain that focuses on evaluating and documenting 
                         the scientific quality of products. This study aims at the 
                         reconstruction of time series of MODIS NDVI data based on the 
                         reliability of the science data sets and on a spatial-temporal 
                         analysis of the low quality pixels. The MOD13Q1 product was 
                         analyzed over a period of one year. After identifying the pixel 
                         with the lowest guarantee of quality, it is estimated by 
                         regression analysis among neighboring pixels classified as 
                         high-quality. The combination of the per-pixel quality and 
                         spatial-temporal information is a promising method for 
                         reconstructing high-quality MODIS NDVI time series.",
  conference-location = "Florian{\'o}polis",
      conference-year = "10 - 13 July 2012",
                label = "lattes: 7176155601161528 1 OliveiraEpipRenn:2012:USSPAN",
             language = "en",
         organisation = "International Spatial Accuracy Research Association (ISARA)",
           targetfile = "OliveiraAccuracy2012.pdf",
        urlaccessdate = "30 abr. 2024"
}