## 5 Conclusions  
The use of the optical Sentinel-2 and SAR Sentinel-1 images proved that they complement each other, allowing for the creation of a new synthetic image with the characteristics of both sources through the implementation of image fusion methods, and obtaining more information on the study area compared with that obtained from these two sources of information separately. In addition, as observed in the histograms of the fused images compared with the optical image, except for the Brovey method (BR), the other methods did not present significant distortions in the values of the fused image, demonstrating that no significant alterations are experienced when linking the SAR information to the optical image.  
The coverage classification through the random forest (RF) algorithm presented the highest overall accuracy (OA) for the image formed by the compilation (stack) of optical and SAR bands, reaching 82.14%, being 11.66% higher compared with the SAR image and 7.85% higher compared with the optical image. It was evidenced that the user accuracies (UA) obtained in the stack of bands were higher than 70% in all the analyzed coverages. Regarding the fused images, the high-frequency modulation (HFM) method showed an increase in the overall accuracy (OA) of 3.8%, and 3.09% for the Brovey (BR) method compared with the Sentinel-2 optical image. These results demonstrate the potential of integrating optical images with Sentinel SAR images to increase the accuracy of coverage classification.  
The overall accuracy (OA) obtained by the SAR image was slightly low compared with that obtained by the optical image, being 3.81% lower. However, it showed very high accuracies in the classification of oil palm and forest coverages, reaching 94.29% and 90%, respectively. This demonstrates the capacity of synthetic aperture radar (SAR) systems in land cover mapping, capturing global information day and night without being affected by atmospheric conditions, which is a significant limitation in the use of optical satellites. On the other hand, the Gram-Schmidt (GS) and principal components (PC) methods presented an overall accuracy (OA) lower than the optical image by 3.81%, 8.1%, and 2.15%, respectively.  
A high increase in SAR image accuracy was evidenced by linking both SAR indices and textural indices through a GLCM gray level co-occurrence matrix. It is recommended that future research implements the use of SAR images containing other polarizations, such as \"HH\" and \"HV\", and different wavelengths, such as L and P bands, which can provide more information on the coverages, and thus improve the accuracy of the classification using only SAR images.  
Conceptualization, [PERSON]-T., [PERSON]-L. and Y.A.G.-G.; methodology, [PERSON]-T.; software, [PERSON]-T.; validation, [PERSON]-T. and [PERSON]-L; formal analysis, [PERSON]-T., [PERSON]-L and Y.A.G.-G.; investigation, [PERSON]-T., J.L.T.-L.- and Y.A.G.-G.; resources, [PERSON]-L.; data curation, [PERSON]-T.; writing--original draft preparation, [PERSON]-T.; writing--review and editing, [PERSON]-L. and [PERSON]; visualization, [PERSON]; supervision, [PERSON] and [PERSON]; project administration, [PERSON] and [PERSON]; funding acquisition, [PERSON] and [PERSON]. All authors have read and agreed to the published version of the manuscript.  
Not applicable.  
The data presented in this study are available on request from the corresponding author.  
Acknowledgements to the \"Universidad Catolica de Manizales\" and the Master's program in remote sensing for the support and guidance provided in the development of the project. Thanks to the \"Centro de Investigacion en Palma de Aceite--Cenipalma\" for the technical support and the financing of this research. Finally, thanks to the European Space Agency (ESA) for providing the free optical and SAR data from Sentinel. The authors declare no conflict of interest.