Animal Molecular Breeding 2024, Vol.14, No.1, 130-140 http://animalscipublisher.com/index.php/amb 135 the model achieves high precision, recall, and F1-scores for double crop and pasture. The confusion matrix for SS2 highlights effective discrimination between these classes, although minor overlaps exist. Overall, the research underscores the effectiveness of remote sensing techniques in accurately mapping LULC, crucial for monitoring and managing ICLS. Figure 2 More suitable method specifications for ICLS (sensor, algorithm, and time window) for each study site, confusion matrices, and the respective values of precision, recall, and the F1 score for all classes (Adopted from Toro et al., 2023) The combination of genomic data and remote sensing technologies holds great promise for the future of wildlife monitoring. By leveraging these advanced data analysis and modeling techniques, conservationists can develop more informed and targeted strategies to protect and preserve endangered species and their habitats (Kerr and Ostrovsky, 2003; Marvin et al., 2016; Drakshayini et al., 2023).
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