@Article{JesusKupBarHilRos:2023:EsAbBi,
               author = "Jesus, Janisson B. de and Kuplich, Tatiana Mora and Barreto, 
                         {\'{\I}}karo D. de C. and Hillebrand, Fernando L. and Rosa, 
                         Cristiano N. da",
          affiliation = "{Universidade Federal do Rio Grande do Sul (UFRGS)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {Universidade Federal 
                         Rural de Pernanbuco (UFRPE)} and Instituto Federal de 
                         Educa{\c{c}}{\~a}o, Ci{\^e}ncia e Tecnologia do Rio Grande do 
                         Sul (IFRS) and {Universidade Federal do Rio Grande do Sul 
                         (UFRGS)}",
                title = "Estimation of aboveground biomass of arboreal species in the 
                         semi-arid region of Brazil using SAR (synthetic aperture radar) 
                         images",
              journal = "Journal of Arid Land",
                 year = "2023",
               volume = "15",
               number = "6",
                pages = "695--709",
                month = "June",
             keywords = "C-band, Caatinga, coherent and incoherent attributes, Sentinel-1, 
                         tropical dry forest.",
             abstract = "The Caatinga biome is an important ecosystem in the semi-arid 
                         region of Brazil. It has significantly degraded due to human 
                         activities and is currently a region undergoing desertification. 
                         Thus, monitoring the variation in the Caatinga biome has become 
                         essential for its sustainable development. However, traditional 
                         methods for estimating aboveground biomass (AGB) are 
                         time-consuming and destructive. Remote sensing, such as optical 
                         and radar imaging, can estimate and correlate with vegetation. 
                         Nevertheless, radar imaging is still a novelty to be applied in 
                         estimating the AGB of this biome, which is an area with little 
                         research. Therefore, this study aimed to use Sentinel-1 images to 
                         estimate the AGB of the Caatinga biome in Sergipe State 
                         (northeastern Brazil) and to verify its influencing factors. 
                         Nineteen sample plots (30 m×30 m) were selected, and the stems of 
                         individuals with a circumference at breast height (1.3 m above the 
                         ground) equal to or greater than 6.0 cm were measured, and the AGB 
                         through an allometric equation was estimated. The Sentinel-1 
                         images from 3 different periods (green, intermediate, and dry 
                         periods) were used to consider the phenological conditions of the 
                         Caatinga biome. All the pre-processing and extraction of 
                         attributes (co-polarized VV (vertical transmit and vertical 
                         receive), cross-polarized VH (vertical transmit and horizontal 
                         receive), and band ratio VH/VV backscatter, radar vegetation 
                         index, dual polarization synthetic aperture radar (SAR) vegetation 
                         index (DPSVI), entropy (H), and alpha angle (\α)) were 
                         performed with Sentinels Application Platform. These attributes 
                         were used to estimate the AGB through simple and multiple linear 
                         regressions and evaluated by the coefficients of determination (R 
                         2), correlation (r), and root mean squared error (RMSE). The 
                         results showed that the attributes individually had little ability 
                         to estimate the AGB of the Caatinga biome in the three periods. 
                         Combined with multiple regression, we found that the intermediate 
                         period presented the equation with the best results among the 
                         observed and estimated variables (R 2=0.73; r=0.85; RMSE=8.33 
                         Mg/hm2), followed by the greenness period (R 2=0.72; r=0.85; 
                         RMSE=8.40 Mg/hm2). The attributes contributing to these equations 
                         were VH/VV, DPSVI, H, \α, and co-polarized VV for the green 
                         period and cross-polarized VH for the intermediate period. The 
                         study showed that the Sentinel-1 images could be used to estimate 
                         the AGB of the Caatinga biome in the green and intermediate 
                         phenological periods since the SAR attributes highly correlated 
                         with the estimated variable (i.e., AGB) through multiple linear 
                         equations. ©.",
                  doi = "10.1007/s40333-023-0017-4",
                  url = "http://dx.doi.org/10.1007/s40333-023-0017-4",
                 issn = "1674-6767",
             language = "en",
           targetfile = "s40333-023-0017-4.pdf",
        urlaccessdate = "21 maio 2024"
}