An artificial neural network model for estimating crop yields using remotely sensed information
文献类型：SCI/SSCI论文
| 作者 | Jiang D. ; Yang X.; Clinton N.; Wang N.
|
| 发表日期 | 2004 |
| 关键词 | Vegetation Indexes Red |
| 英文摘要 | Crop yield forecasting is a very important task for researchers in remote sensing. Problems exist with traditional statistical modelling (especially regression models) of nonlinear functions with multiple factors in the cropland ecosystem. This paper describes the successful application of an artificial neural network in developing a model for crop yield forecasting using back-propagation algorithms. The model has been adapted and calibrated using on the ground survey and statistical data, and it has proven to be stable and highly accurate. |
| 出处 | International Journal of Remote Sensing |
| 卷 | 25 |
| 期 | 9 |
| 页 | 1723-1732 |
| 语种 | 英语 |
| ISSN号 | 0143-1161 |
| 源URL | [http://159.226.115.200/handle/311030/23764]  |
| 专题 | 资源利用与环境修复重点实验室_外文论文 |
| 推荐引用方式 GB/T 7714 | Jiang D.,Yang X.,Clinton N.,et al. An artificial neural network model for estimating crop yields using remotely sensed information. 2004. |
入库方式： OAI收割
来源：地理科学与资源研究所
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