Loading...
Please wait, while we are loading the content...
Similar Documents
Estimation and Forecasting of Rice Yield Using Phenology-Based Algorithm and Linear Regression Model on Sentinel-II Satellite Data
| Content Provider | MDPI |
|---|---|
| Author | Nazir, Abid Ullah, Saleem Saqib, Zulfiqar Ahmad Abbas, Azhar Ali, Asad Iqbal, Muhammad Shahid Hussain, Khalid Shakir, Muhammad Shah, Munawar Butt, Muhammad Usman |
| Copyright Year | 2021 |
| Description | Rice is a primary food for more than three billion people worldwide and cultivated on about 12% of the world’s arable land. However, more than 88% production is observed in Asian countries, including Pakistan. Due to higher population growth and recent climate change scenarios, it is crucial to get timely and accurate rice yield estimates and production forecast of the growing season for governments, planners, and decision makers in formulating policies regarding import/export in the event of shortfall and/or surplus. This study aims to quantify the rice yield at various phenological stages from hyper-temporal satellite-derived-vegetation indices computed from time series Sentinel-II images. Different vegetation indices (viz. NDVI, EVI, SAVI, and REP) were used to predict paddy yield. The predicted yield was validated through RMSE and ME statistical techniques. The integration of PLSR and sequential time-stamped vegetation indices accurately predicted rice yield (i.e., maximum $R^{2}$ = 0.84 and minimum RMSE = 0.12 ton $ha^{−1}$ equal to 3% of the mean rice yield). Moreover, our results also established that optimal time spans for predicting rice yield are late vegetative and reproductive (flowering) stages. The output would be useful for the farmer and decision makers in addressing food security. |
| Starting Page | 1026 |
| e-ISSN | 20770472 |
| DOI | 10.3390/agriculture11101026 |
| Journal | Agriculture |
| Issue Number | 10 |
| Volume Number | 11 |
| Language | English |
| Publisher | MDPI |
| Publisher Date | 2021-10-19 |
| Access Restriction | Open |
| Subject Keyword | Agriculture Remote Sensing Rice Yield Vegetation Indices Hyper-temporal Data Plsr |
| Content Type | Text |
| Resource Type | Article |
