2025/01/07 by Kuchkorov, Temurbek, Saydullayev, Humoyun, Khamzaev, Jamshid
paper · doi:10.34920/icdgpdt.42
This thesis evaluates various change detection algorithms for land cover analysis using remote sensing data, aiming to enhance accuracy and efficiency in environmental monitoring. It reviews algebra-based, classification-based, and advanced statistical techniques, highlighting their applications, strengths, and limitations. The study emphasizes the integration of machine learning and multi-sensor data fusion to address current challenges in the field, advocating for hybrid models that improve detection capabilities across diverse landscapes.