التفاصيل البيبلوغرافية
| العنوان: |
Using the red-near infrared spectral to estimate ground cover based on vegetative indices. |
| المؤلفون: |
Asadi, Sara1, Bannayan, Mohammad1 Banayan@um.ac.ir, Jahan, Mohsen1, Farid Hosseini, Alireza1 |
| المصدر: |
International Journal of Remote Sensing. Sep2019, Vol. 40 Issue 18, p7153-7168. 16p. 2 Charts, 5 Graphs, 1 Map. |
| مصطلحات موضوعية: |
*GROUND cover plants, *REMOTE sensing, *NORMALIZED difference vegetation index, *PHOTOSYNTHESIS, *EVAPOTRANSPIRATION |
| مستخلص: |
Rapid and accurate estimation of Ground Cover (GC) at regional and global scales for agricultural management application is only possible by using remote sensing (RS). In this study, two Vegetation Indices (VIs) including the Perpendicular Vegetation Index (PVI) and Normalized Difference Vegetation Index (NDVI) were used for estimating GC. Since the parameters of the bare soil line have an important role in calculating GC based on PVI, this line was extracted based on the red-NIRmin (minimum near infrared) method with different intervals (0.0001, 0.0005, and 0.0010). In addition to traditional statistics such as Root Mean Square Error (RMSE), the sensitivity analysis (S) was also used to sharpen the accuracy of the models' estimations. The results indicated that the PVI-based method, in contrast to the NDVI-based approach, had a better performance in estimating GC of wheat. The highest correlation between the observed GC and the estimated GC based on PVI method was achieved in interval length of 0.0005 (R2 = 0.91) with RMSE equal to 8.82. This regression line (GCEST = -3.47 + 0.96 GCOBS) was not significantly different from the 1:1 line. As expected, the best estimation was achieved when the sensitivity of estimated GC based on PVI (length of the interval: 0.0005) was almost constant and low compared to the other models. [ABSTRACT FROM AUTHOR] |
| قاعدة البيانات: |
Academic Search Index |
