A Comparison of Different Data Fusion Strategies' Effects on Maize Leaf Area Index Prediction Using Multisource Data from Unmanned Aerial Vehicles (UAVs)
文献类型：期刊论文
| 作者 | Ma, Junwei2,3; Chen, Pengfei1,3; Wang, Lijuan2 |
| 刊名 | DRONES
 |
| 出版日期 | 2023-10-01 |
| 卷号 | 7期号:10页码:16 |
| 关键词 | multisource remote sensing images leaf area index UAV maize |
| DOI | 10.3390/drones7100605 |
| 通讯作者 | Chen, Pengfei(pengfeichen@igsnrr.ac.cn) |
| 英文摘要 | The leaf area index (LAI) is an important indicator for crop growth monitoring. This study aims to analyze the effects of different data fusion strategies on the performance of LAI prediction models, using multisource images from unmanned aerial vehicles (UAVs). For this purpose, maize field experiments were conducted to obtain plants with different growth status. LAI and corresponding multispectral (MS) and RGB images were collected at different maize growth stages. Based on these data, different model design scenarios, including single-source image scenarios, pixel-level multisource data fusion scenarios, and feature-level multisource data fusion scenarios, were created. Then, stepwise multiple linear regression (SMLR) was used to design LAI prediction models. The performance of models were compared and the results showed that (i) combining spectral and texture features to predict LAI performs better than using only spectral or texture information; (ii) compared with using single-source images, using a multisource data fusion strategy can improve the performance of the model to predict LAI; and (iii) among the different multisource data fusion strategies, the feature-level data fusion strategy performed better than the pixel-level fusion strategy in the LAI prediction models. Thus, a feature-level data fusion strategy is recommended for the creation of maize LAI prediction models using multisource UAV images. |
| WOS关键词 | CROP CHLOROPHYLL CONTENT ; SUPPORT VECTOR MACHINES ; VEGETATION INDEXES ; REMOTE ESTIMATION ; SOIL ; REFLECTANCE ; CANOPY ; IDENTIFICATION ; YIELD ; LAI |
| 资助项目 | We thank Jian Gu and Yi Sun for providing the experimental field and Ke Zhou for his assistance during the field data campaign and help in making pixel-level fused images. |
| WOS研究方向 | Remote Sensing |
| 语种 | 英语 |
| WOS记录号 | WOS:001092402800001 |
| 出版者 | MDPI |
| 资助机构 | We thank Jian Gu and Yi Sun for providing the experimental field and Ke Zhou for his assistance during the field data campaign and help in making pixel-level fused images. |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/199237]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Chen, Pengfei |
| 作者单位 | 1.Jiangsu Ctr Collaborat Innovat Geog Informat Resou, Nanjing 210023, Peoples R China 2.Jiangsu Normal Univ, Sch Geog Geomat & Planning, Xuzhou 221116, Peoples R China 3.Chinese Acad Sci, State Key Lab Resources & Environm Informat Syst, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China |
| 推荐引用方式 GB/T 7714 | Ma, Junwei,Chen, Pengfei,Wang, Lijuan. A Comparison of Different Data Fusion Strategies' Effects on Maize Leaf Area Index Prediction Using Multisource Data from Unmanned Aerial Vehicles (UAVs)[J]. DRONES,2023,7(10):16. |
| APA | Ma, Junwei,Chen, Pengfei,&Wang, Lijuan.(2023).A Comparison of Different Data Fusion Strategies' Effects on Maize Leaf Area Index Prediction Using Multisource Data from Unmanned Aerial Vehicles (UAVs).DRONES,7(10),16. |
| MLA | Ma, Junwei,et al."A Comparison of Different Data Fusion Strategies' Effects on Maize Leaf Area Index Prediction Using Multisource Data from Unmanned Aerial Vehicles (UAVs)".DRONES 7.10(2023):16. |
入库方式： OAI收割
来源：地理科学与资源研究所
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