Synergistic Use of Multitemporal SAR and Optical Data with Random Forest Approach for Rice Mapping in Bangladesh
融合Sentinel-1 SAR与Sentinel-2光学影像，用随机森林在GEE上绘制孟加拉国Bo
← 主题
Landsat NDVI 水稻 机器学习
同时包含 Landsat NDVI、水稻、机器学习 的农业资讯，共 3 条。
Rice Cropping Pattern Mapping Using GEE-Based Sentinel-1/2 Time-Series Imagery and Machine Learning
基于GEE融合Sentinel-1/2时序与地形特征，用机器学习高精度制图长三角水稻种植模式。
Research on the optimal modeling path for inversion of Pb content in rice leaves based on hyperspectral data of ground objects and machine learning and cross-scale remote sensing monitoring
研究基于地面高光谱与机器学习反演水稻叶片铅含量，并探索跨尺度遥感监测的最优建模路径。