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Remote Sensing Techniques for Classification and Mapping of Sugarcane Growth
2020
Engineering, Technology & Applied Science Research
This study aimed to apply remote sensing technologies in delineating sugarcane (Saccharum officinarum) plantations and in identifying its growth stages. Considering the growing demand for sugarcane in the local and global markets, the need for a science-based resource inventory emerges. In this sense, remote sensing techniques' unique ability is vital to monitor crop growth and estimate crop yield. Object-Based Image Analysis (OBIA) concept was employed by utilizing orthophotos and Light
doi:10.48084/etasr.3694
fatcat:zjq7b5z4q5gtxoy6yn4z3pnhgq