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
 close



Research
                Research Home
                            National Programs
                            Research Projects
                            Scientific Manuscripts
                            International Engagement
                            Scientific Software/Models
                            Databases and Datasets
                            Office of Scientific Quality Review
            Media
                News & Features
                            Multimedia
                            Briefing Room
                            Down on the Farm
                            Press Room
                            Science in Your Shopping Cart
                            Scientific Discoveries
                            Tellus
                            Under the Microscope
            About ARS
                About ARS Home
                            Staff Directory
                            Labs and Research Centers (Map)
                            Headquarter Offices
                            Organizational Chart
                            Employee Services (REE Employees Only)
                            Office of Outreach, Diversity, and Equal Opportunity
            Work With Us
                Work With Us Home
                            ARS Vacancies at USAJOBS
                            Careers at ARS Information
                            Scientific Collaborations
                            Extramural Agreements
                            1890 Faculty Research Sabbatical ProgramSearch small
                    Search
            
            ARS Home
                                About ARS
                                Contact Us




ARS Home 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

Title:   Author  item
                                            Cammalleri, Carmeloitem
                                            Anderson, Marthaitem
                                            Gao, Fengitem
                                            HOUBORG, RASMUS - Collaboratoritem
                                            Schull, Mitchellitem
                                            Kustas, William

                                                         - *Bill*
  Submitted to: Meeting Abstract
                                    Publication Type: Abstract Only
                                    Publication Acceptance Date: 5/8/2012
                                    Publication  Date: 5/9/2012
                                    Citation: Cammalleri, C.N., Anderson, M.C., Gao, F.N., Houborg, R., Schull, M.A., Kustas, W.P. 2012. Using satellites to provide reliable daily water use estimates at field scales [abstract]. Moderate Resolution Imaging Spectroradiometer Science Team Meeting, May 7-9, 2012, Silver Spring, MD.Interpretive Summary:
                                Technical Abstract: The ability to accurately map daily crop water use over agricultural landscapes at scales resolving individual farm fields is a significant challenge, but it is increasingly relevant in a future scenario of reduced water availability and increased atmospheric demand. Remote sensing provides a robust means to determine spatially distributed evapotranspiration (ET) over large areas in a cost effective manner, capitalizing the strong interconnection between remotely-observed land-surface temperature (LST) and ET fluxes. Nevertheless, there is an inherent trade-off in satellites collecting thermal infrared (TIR) imagery used to map LST. In fact, due to technical and budget limitations the currently available data are generally characterized by low spatial resolution (10^3-10^4 m) and high repeatability (1 day to 15 min), such as MODIS (MODerate resolution Imaging Spectroradiometer) and GOES (Geostationary Operational Environmental Satellite), or by moderate/high spatial resolution (10^1-10^2 m) and low temporal frequency (15 days), as for instance with the Landsat series. In order to obtain reliable daily ET estimates at field scale, the best characteristics of each dataset should be combined. With this aim, we developed a multi-scale, multi-sensor modeling framework. The Atmosphere-Land EXchange Inverse (ALEXI) model uses GOES data to obtain coarse (10-km) maps at the U.S. continental scale, while the Dis-ALEXI procedure disaggregates ALEXI ET to finer spatial scales using MODIS 1-km (daily) and Landsat 30-m (15 day) LST imagery. These latter estimates are combined by means of a data fusion algorithm to retrieve daily and seasonal 30-m ET maps over areas on the order of 100 km in dimension. In this work, ALEXI/DisALEXI was applied to GOES, MODIS and Landsat images acquired in 2002 over central Iowa, the site of the Soil Moisture Experiment of 2002 (SMEX02). The time series of 30-m maps obtained in the period May-August were validated by means of 7 micrometeorological flux towers, which provide a unique and extensive observational dataset of ET time series in corn and soybean fields during a period of rapid crop development. The MODIS-Landsat Fused results were also compared to a benchmark case, obtained using Landsat images only. The results indicate that significant improvement in agreement between modeled and observed ET can be obtained in some cases by fusing MODIS and Landsat data, particularly when a rainfall event occurs between Landsat image acquisitions. The fused ET maps had an accuracy of about 0.5 mm/d at daily timesteps (10% of the observed values) and 5% for seasonal total water use, which is suitable for detailed analysis and management of crop water consumption.


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