@Article{CayoBEMCAHYS:2022:MaThDe,
               author = "Cayo, Efrain Yury Turpo and Borja, Maria Olga and Espinoza-Villar, 
                         Raul and Moreno, Nicole and Camargo, Rodney and Almeida, 
                         Cl{\'a}udia Maria de and Hopfgartner, Kathrin and Yalerque, 
                         Christian and Souza J{\'u}nior, Carlos M.",
          affiliation = "{Instituto del Bien Com{\'u}n (IBC)} and {Fundaci{\'o}n 
                         EcoCiencia} and {Universidad Nacional Agraria La Molina} and 
                         {Instituto del Bien Com{\'u}n (IBC)} and {Fundaci{\'o}n Amigos 
                         de la Naturaleza (FAN)} and {Instituto Nacional de Pesquisas 
                         Espaciais (INPE)} and {Instituto del Bien Com{\'u}n (IBC)} and 
                         {Instituto de Investigaci{\'o}n en Glaciares y Ecosistemas de 
                         Montaņa (INAIGEM)} and {Instituto do Homem e Meio Ambiente da 
                         Amaz{\^o}nia (Imazon)}",
                title = "Mapping Three Decades of Changes in the Tropical Andean Glaciers 
                         Using Landsat Data Processed in the Earth Engine",
              journal = "Remote Sensing",
                 year = "2022",
               volume = "14",
               number = "9",
                pages = "e1974",
                month = "May",
             keywords = "Andean, glacier retreat, climate change, MapBiomas, Google Earth 
                         Engine.",
             abstract = "The fast retreat of the tropical Andean glaciers (TAGs) is 
                         considered an important indicator of climate change impact on the 
                         tropics, since the TAGs provide resources to highly vulnerable 
                         mountain populations. This study aims to reconstruct the glacier 
                         coverage of the TAGs, using Landsat time-series images from 1985 
                         to 2020, by digitally processing and classifying satellite images 
                         in the Google Earth Engine platform. We used annual reductions of 
                         the Normalized Difference Snow Index (NDSI) and spectral bands to 
                         capture the pixels with minimum snow cover. We also implemented 
                         temporal and spatial filters to have comparable maps at a 
                         multitemporal level and reduce noise and temporal inconsistencies. 
                         The results of the multitemporal analysis of this study confirm 
                         the recent and dramatic recession of the TAGs in the last three 
                         decades, in base to physical and statistical significance. The 
                         TAGs reduced from 2429.38 km(2) to 1409.11 km(2) between 1990 and 
                         2020, representing a loss of 42% of the total glacier area. In 
                         addition, the time-series analysis showed more significant losses 
                         at altitudes below 5000 masl, and differentiated changes by slope, 
                         latitude, and longitude. We found a more significant percentage 
                         loss of glacier areas in countries with less coverage. The 
                         multiannual validation showed accuracy values of 92.81%, 96.32%, 
                         90.32%, 97.56%, and 88.54% for the metrics F1 score, accuracy, 
                         kappa, precision, and recall, respectively. The results are an 
                         essential contribution to understanding the TAGs and guiding 
                         policies to mitigate climate change and the potential negative 
                         impact of freshwater shortage on the inhabitants and food 
                         production in the Andean region.",
                  doi = "10.3390/rs14091974",
                  url = "http://dx.doi.org/10.3390/rs14091974",
                 issn = "2072-4292",
             language = "en",
           targetfile = "remotesensing-14-01974-v2.pdf",
        urlaccessdate = "09 maio 2024"
}