@Article{AtzbergerFoShUdMaSaAr:2014:UsUnAp,
               author = "Atzberger, Clement and Formaggio, Antonio Roberto and Shimabukuro, 
                         Yosio Edemir and Udelhoven, T. and Mattiuzzi, M. and Sanchez, 
                         Gildardo Arango and Arai, Egidio",
          affiliation = "Institute of Surveying, Remote Sensing and Land Information, 
                         University of Natural Resources and Life Sciences (BOKU), 1190 
                         Vienna, Austria and {Instituto Nacional de Pesquisas Espaciais 
                         (INPE)} and {Instituto Nacional de Pesquisas Espaciais (INPE)} and 
                         Remote Sensing and Geoinformatics Department, University of Trier, 
                         54296 Trier, Germany and Institute of Surveying, Remote Sensing 
                         and Land Information, University of Natural Resources and Life 
                         Sciences (BOKU), 1190 Vienna, Austria and {Instituto Nacional de 
                         Pesquisas Espaciais (INPE)} and {Instituto Nacional de Pesquisas 
                         Espaciais (INPE)}",
                title = "Obtaining crop-specific time profiles of NDVI: the use of unmixing 
                         approaches for serving the continuity between SPOT-VGT and PROBA-V 
                         time series",
              journal = "International Journal of Remote Sensing",
                 year = "2014",
               volume = "35",
               number = "7",
                pages = "2615--2638",
             keywords = "crops, image resolution, radiometers, vegetation, Landsat thematic 
                         mapper images, moderate resolution imaging spectroradiometer, Ndvi 
                         temporal profiles, normalized difference vegetation index, project 
                         for on-board autonomies, retrieval accuracy, Satellite Pour 
                         l'Observation de la Terre, Unmixing algorithms, Satellite imagery, 
                         algorithm, crop plant, data set, land cover, Landsat thematic 
                         mapper, MODIS, NDVI, sensor, spatial resolution, SPOT, time 
                         series, Brazil, Sao Paulo [Brazil].",
             abstract = "The study examined the potential of two unmixing approaches for 
                         deriving crop-specific normalized difference vegetation index 
                         (NDVI) profiles so that upon availability of Project for On-Board 
                         Autonomy - Vegetation (PROBA-V) imagery in winter 2013, this new 
                         data set can be combined with existing Satellite Pour 
                         l'Observation de la Terre - VEGETATION (SPOT-VGT) data despite the 
                         differences in spatial resolution (300 m of PROBA-V versus 1 km of 
                         SPOT-VGT). To study the problem, two data sets were analysed: (1) 
                         a set of 10 temporal NDVI images, with 300 and 1000 m spatial 
                         resolution, from the state of S{\~a}o Paulo (Brazil) synthesized 
                         from 30 m Landsat Thematic Mapper (TM) images, and (2) a 
                         corresponding set of 10 observed Moderate Resolution Imaging 
                         Spectroradiometer (MODIS) images (250 m spatial resolution). To 
                         mimic the influence of noise on the retrieval accuracy, different 
                         sensor/atmospheric noise levels were applied to the first data 
                         set. For the unmixing analysis, a high-resolution land-cover (LC) 
                         map was used. The LC map was derived beforehand using a different 
                         set of Landsat TM images. The map distinguishes nine classes, with 
                         four different sugarcane stages, two agricultural sub-classes, 
                         plus forest, pasture, and urban/water. Unmixing aiming at the 
                         retrieval of crop-specific NDVI profiles was done at 
                         administrative level. For the synthesized data set it was 
                         demonstrated that the 'true' NDVI temporal profiles of different 
                         land-cover classes (from 30 m TM data) can generally be retrieved 
                         with high accuracy. The two simulated sensors (PROBA-V and 
                         SPOT-VGT) and the two unmixing algorithms gave similar results. 
                         Analysing the MODIS data set, we also found a good correspondence 
                         between the modelled NDVI profiles (both approaches) and the 
                         (true) Landsat temporal endmembers.",
                  doi = "10.1080/01431161.2014.883106",
                  url = "http://dx.doi.org/10.1080/01431161.2014.883106",
                 issn = "0143-1161",
                label = "scopus 2014-05 AtzbergerFoShUdMaSaAr:2014:UsUnAp",
             language = "en",
        urlaccessdate = "28 abr. 2024"
}