Satellite Image Price Prediction Based on Machine Learning

This study develops a comprehensive, data-driven framework for predicting satellite imagery prices using four state-of-the-art ensemble learning algorithms: XGBoost, LightGBM, AdaBoost, and CatBoost. Two distinct datasets—optical and Synthetic Aperture Radar (SAR) imagery—were assembled, each charac...

詳細記述

書誌詳細

出版年:	Remote Sensing
主要な著者:	Linhan Yang, Zugang Chen, Guoqing Li
フォーマット:	論文
言語:	英語
出版事項:	MDPI AG 2025-06-01
主題:	satellite imagery pricing ensemble learning Bayesian optimization SHAP analysis
オンライン･アクセス:	https://www.mdpi.com/2072-4292/17/12/1960