Name
Title | ||
|---|---|---|
Developing an integrated indicator for monitoring maize growth condition using remotely sensed vegetation temperature condition index and leaf area index. |
Abstract | ||
|---|---|---|
•The developed index is very reliable and promising for estimating the growth conditions of maize.•Integrating more growth-correlated variables improves the maize growth monitoring accuracy.•GRA and AHP as useful weighting methods to acquire priorities of indicators at different stages.•Classification standards established to improve precision and quantification of regional monitoring results. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1016/j.compag.2018.07.026 | Computers and Electronics in Agriculture |
Keywords | Field | DocType |
Maize growth,Integrated monitoring,Grey relational analysis,Analytic hierarchy process,Vegetation temperature condition index,Leaf area index | Computer vision,Agronomy,Leaf area index,Vegetation,Grey relational analysis,Water stress,Weight coefficient,Artificial intelligence,Engineering,Condition index,Linear regression | Journal |
Volume | ISSN | Citations |
152 | 0168-1699 | 0 |
PageRank | References | Authors |
0.34 | 5 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lei Wang | 1 | 65 | 54.21 |
| Peng Xin Wang | 2 | 14 | 6.53 |
| Li Li | 3 | 6 | 2.22 |
| Lan Xun | 4 | 0 | 0.34 |
| Qingling Kong | 5 | 0 | 0.34 |
| Shunlin Liang | 6 | 611 | 116.22 |