@InProceedings{MarianoFoscMore:2014:MaLaUs,
               author = "Mariano, Denis Araujo and Foschiera, William and Moreira, 
                         Maur{\'{\i}}cio Alves",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de 
                         Pesquisas Espaciais (INPE)}",
                title = "Mapping land use classes by analyzing MODIS LST time-series / 
                         Mapeamento de classes de uso do solo por meio de an{\'a}lise de 
                         s{\'e}ries temporais de dados MODIS-LST",
            booktitle = "Anais...",
                 year = "2014",
                pages = "561--568",
         organization = "Semin{\'a}rio de Atualiza{\c{c}}{\~a}o em Sensoriamento Remoto 
                         e Sistemas de Informa{\c{c}}{\~o}es Geogr{\'a}ficas Aplicados 
                         {\`a} Engenharia Florestal, 11. (SenGeF).",
            publisher = "IEP",
              address = "Curitiba",
             keywords = "Land surface temperature, MODIS, time-series, Python, agriculture, 
                         thermal.",
             abstract = "The current paper presents a method to discriminate land use 
                         classes (LCCs) by analysing Land Surface Temperature (LST) 
                         time-series derived from the Moderate Resolution Imaging Spectro 
                         radiometer (MODIS). We used Terra and Aqua LST daytime and night 
                         time data (M_D11A2) with 8-day temporal and 1km spatial 
                         resolution. The physical basis behind the method is the heat 
                         transfer between soil, plant and atmosphere over time. There are 
                         two approaches, inter-daily and intra-daily LST variation. We 
                         tested daytime and day-night difference time-series, being the 
                         latter more efficient on discriminating classes. Regarding the 
                         satellites, Aqua proves on being more efficient due the passage 
                         hour for daytime. In sense, the couple Aqua/Difference yielded 
                         better results. However, the performance is strongly dependent 
                         upon the targets' acreage due to the high thermal mixing effect. 
                         Despite the limitations, this approach shows potential on being 
                         coupled to traditional vegetation indices (VI) based methods for 
                         furthering the biophysical meaning and relationships between 
                         vegetation and the electromagnetic spectrum. It also brings new 
                         findings about vegetation thermal behaviour throughout the time.",
  conference-location = "Curitiba",
      conference-year = "14-16 out. 2014",
                 issn = "2178-8634",
                label = "lattes: 4721908858063120 1 MarianoFoscMore:2014:MaLaUs",
             language = "en",
           targetfile = "Mariano, Denis 2014.pdf",
                  url = "http://www.11sengef.com.br/arquivos/documentos/anaisonline/SENGEF2014.pdf",
        urlaccessdate = "27 abr. 2024"
}