鉴定(生物学)
植被(病理学)
时间序列
遥感
环境科学
计算机科学
生物
地理
植物
机器学习
医学
病理
作者
Yan Guo,Haoming Xia,Xiaoyang Zhao,Longxin Qiao,Yaochen Qin
出处
期刊:Remote Sensing
[MDPI AG]
日期:2022-09-08
卷期号:14 (18): 4476-4476
被引量:5
摘要
Garlic is the major economic crop in China. Timely and accurate identification and mapping of garlic are significant for garlic yield prediction and garlic market management. Previous studies on garlic mapping were mainly based on all observations of the entire growing season, so the resulting maps have a hysteresis. Here, we determined the optimal identification strategy and the earliest identifiable phenophase for garlic based on all available Landsat 8/9 time series imagery in Google Earth Engine. Specifically, we evaluated the performance of different vegetation indices for each phenophase to determine the optimal classification metrics for garlic. Secondly, we identified garlic using random forest algorithm and classification metrics of different time series lengths. Finally, we determined the earliest identifiable phenophase of garlic and generated an early-season garlic distribution map. Garlic could be identified as early as March (bud differentiation period) with an F1 of 0.91. Our study demonstrates the differences in the performance of vegetation indices at different phenophases, and these differences provide a new idea for mapping crops. The generated early-season garlic distribution map provides timely data support for various stakeholders.
科研通智能强力驱动
Strongly Powered by AbleSci AI