Name
Abstract | ||
|---|---|---|
Wine grape quality and quantity are affected by vine growing conditions during some critical growing stages. In this paper, MODIS and Landsat were used to map daily LAI in two Grape Remote sensing Atmospheric Profiling and Evapotranspiration eXperiment (GRAPEX) experimental fields near Lodi, California in 2013. A data fusion approach was applied to map daily LAI at 30 m spatial resolution. The LAI data from two fields were validated using insitu measurements. Cumulative LAI from two fields were compared to the 2013 grape yields. High correlations were found between yield and cumulative LAI. The within-season yield predictability was examined using daily LAI maps. Results show that the grape yields were highly correlated with the cumulative LAI after the month of June. This suggests that grape yields are predictable using remotely sensed data 2-3 months prior to harvest under normal conditions. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/IGARSS.2016.7730867 | 2016 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS) |
Keywords | Field | DocType |
MODIS, Landsat, LAI, grape, yield | Computer science,Remote sensing,Correlation,Evapotranspiration | Conference |
ISSN | Citations | PageRank |
2153-6996 | 1 | 0.41 |
References | Authors | |
1 | 9 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| liang sun | 1 | 25 | 5.83 |
| Feng Gao | 2 | 32 | 5.87 |
| Martha C. Anderson | 3 | 72 | 23.99 |
| Wayne P. Dulaney | 4 | 9 | 2.25 |
| Lynn McKee | 5 | 5 | 2.32 |
| Alex White | 6 | 1 | 0.75 |
| William P. Kustas | 7 | 54 | 16.67 |
| Joe Alfteri | 8 | 1 | 0.41 |
| John H. Prueger | 9 | 68 | 12.82 |