Knowledge Resource Center for Ecological Environment in Arid Area
| DOI | 10.3390/rs15174298 |
| Remotely Sensed Agriculture Drought Indices for Assessing the Impact on Cereal Yield | |
| Khlif, Manel; Escorihuela, Maria Jose; Bellakanji, Aicha Chahbi; Paolini, Giovanni; Chabaane, Zohra Lili | |
| 通讯作者 | Khlif, M |
| 来源期刊 | REMOTE SENSING
 |
| EISSN | 2072-4292 |
| 出版年 | 2023 |
| 卷号 | 15期号:17 |
| 英文摘要 | This study aims to analyze the potential of different drought indices for identifying drought periods and predicting cereal yield in two semi-arid regions, Lleida in Catalonia and Kairouan in Tunisia, which have similar Mediterranean climates but different agricultural practices. Four drought indices, namely the Soil Moisture Anomaly Index (SMAI), the Vegetation Anomaly Index (VAI), the Evapotranspiration Anomaly Index (EAI), and the Inverse Temperature Anomaly Index (ITAI), were calculated from remote sensing data. Drought periods were identified from 2010/2011 to 2021/2022 based on the aforementioned indices. A correlation study between drought indices and wheat and barley yields was performed in order to select the most informative index and month for yield prediction. In the rainfed cereal area of Lleida, the strongest correlation was found between the EAI and VAI with barley yield (0.91 and 0.83, respectively) at the time of cereal maturity in June. For wheat, the strongest correlation was found between the EAI and VAI (0.75 and 0.72, respectively) at the time of cereal maturity in July. However, the VAI, EAI, and SMAI showed the best performance as an earlier indicator in March with a correlation with barley yield of 0.72, 0.67, and 0.64, respectively; the lowest standard deviation was for the SMAI. For wheat yield, the best earlier indicator was the SMAI in March, showing the highest correlation (0.6) and the lowest standard deviation. For the irrigated cereal zone of Kairouan, the strongest correlation (0.9) and the lowest standard deviation are found between the EAI and cereal yield in April. In terms of advanced prediction, the VAI shows a high correlation in March (0.79) while the SMAI shows a slightly lower correlation in February (0.67) and a lower standard deviation. The results highlight the importance of the EAI and SMAI as key indicators for the estimation and early estimation (respectively) of cereal yield. |
| 英文关键词 | drought cereal yield remote sensing SMAI VAI EAI ITAI |
| 类型 | Article |
| 语种 | 英语 |
| 开放获取类型 | gold, Green Published |
| 收录类别 | SCI-E |
| WOS记录号 | WOS:001062576000001 |
| WOS关键词 | SMOS SOIL-MOISTURE ; SEMIARID REGION ; SEVERITY INDEX ; GLOBAL YIELDS ; TEMPERATURE ; VEGETATION ; STRESS ; GROWTH ; WHEAT ; EVAPOTRANSPIRATION |
| WOS类目 | Environmental Sciences ; Geosciences, Multidisciplinary ; Remote Sensing ; Imaging Science & Photographic Technology |
| WOS研究方向 | Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology |
| 资源类型 | 期刊论文 |
| 条目标识符 | http://119.78.100.177/qdio/handle/2XILL650/398315 |
| 推荐引用方式 GB/T 7714 | Khlif, Manel,Escorihuela, Maria Jose,Bellakanji, Aicha Chahbi,et al. Remotely Sensed Agriculture Drought Indices for Assessing the Impact on Cereal Yield[J],2023,15(17). |
| APA | Khlif, Manel,Escorihuela, Maria Jose,Bellakanji, Aicha Chahbi,Paolini, Giovanni,&Chabaane, Zohra Lili.(2023).Remotely Sensed Agriculture Drought Indices for Assessing the Impact on Cereal Yield.REMOTE SENSING,15(17). |
| MLA | Khlif, Manel,et al."Remotely Sensed Agriculture Drought Indices for Assessing the Impact on Cereal Yield".REMOTE SENSING 15.17(2023). |
| 条目包含的文件 | 条目无相关文件。 | |||||
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