U.S. flagAn official website of the United States government
                    Here's how you know **Official websites use .gov**
                            
                            A **.gov** website belongs to an official government organization in the United States.
 **Secure .gov websites use HTTPS**
                            
                            A **lock** (                            
                              A locked padlock                                                      
                            
                            ) or **https://** means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.


Menu Agricultural Research Service
						
                    U.S. DEPARTMENT OF AGRICULTURE
 Hydrology and Remote Sensing Laboratory: Beltsville, MD
 close



    Research

                    Research Projects
                                    Publications
                                    Collaborations
                                    News
                                    Software
                People

                    Staff Listing
                                    CareersSearch small
                    Search
            
            ARS Home
                                About ARS
                                Contact Us




ARS Home Northeast Area Beltsville, Maryland (BARC) Beltsville Agricultural Research Center Hydrology and Remote Sensing Laboratory Research Publications at this Location





- ARS National Programs
- Search for a scientific manuscript
- Search for a research project
- ARS Software
- Programs and Projects
- Collaborations
- Subjects of Investigation
- Publications
- People
- Research Sites
- Pesticide Volatilization
- Watershed Modeling
- Climate Change
- Soil Moisture
- Drought and ET
- HRSL Brochure

Title:   Author  item
                                            SUN, LIANG - Collaboratoritem
                                            Gao, Fengitem
                                            Anderson, Marthaitem
                                            Dulaney, Wayneitem
                                            ALSINA, MIMAR - E & J Gallo Wineryitem
                                            SANCHEZ, L. - E & J Gallo Wineryitem
                                            SAMS, BRENT - E & J Gallo Wineryitem
                                            McKee, Lynnitem
                                            White, William

                                                         - *Alex*item
                                            Kustas, William

                                                         - *Bill*item
                                            Alfieri, Josephitem
                                            Prueger, John
  Submitted to: Geoscience and Remote Sensing Symposium Proceedings
                                    Publication Type: Proceedings
                                    Publication Acceptance Date: 1/14/2016
                                    Publication  Date: 7/10/2016
                                    Citation: Sun, L., Gao, F.N., Anderson, M.C., Dulaney, W.P., Alsina, M., Sanchez, L., Sams, B., Mckee, L.G., White, W.A., Kustas, W.P., Alfieri, J.G., Prueger, J.H. 2016. Daily mapping of Landsat-like LAI and correlation to grape yield. Meeting Abstract. 2016 CDROM.Interpretive Summary:
                                Technical Abstract: Wine grape quality and quantity are affected by vine growing condition during some critical growing stages. In this paper, MODIS and Landsat were used to map daily LAI in the two Grape Remote sensing Atmospheric Profiling and Evapotranspiration eXperiment (GRAPEX) experiment fields near Lodi, Californiain 2013. Data fusion approach was applied to map daily LAI at 30m spatial resolution. The LAI data from two fields were validated using the in-situ measurements. The cumulative LAI from two fields were compared to the grape yields from 2013. High correlations are found between yield and the cumulative LAI. The within-season yield predictability was examined using daily LAI map. Results show that the grape yields are highly correlated with the cumulative LAI after June which suggests that the grape yields are predictable using remote sensing data 2-3 months prior to harvest under the normal condition.


Return to top


Connect with ARS Sign up


ARS Home
                            USDA.gov
                            Plain Writing
                            Policies & Links
                            Civil Rights Statements
                            FOIA
                            Accessibility Statement
                            Privacy Policy
                            Non-Discrimination Statement
                            Quality of Information
                            USA.gov
                            WhiteHouse.gov