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
                                            Gao, Fengitem
                                            Kustas, William

                                                         - *Bill*item
                                            Anderson, Martha
  Submitted to: Meeting Abstract
                                    Publication Type: Abstract Only
                                    Publication Acceptance Date: 9/4/2012
                                    Publication  Date: 10/25/2012
                                    Citation: Gao, F.N., Kustas, W.P., Anderson, M.C. 2012. Sharpening landsat thermal infrared imagery for mapping evapotranspiration at field scale[abstract]. 2012 Western States Remote Sensing of ET Workshop. 2012 CDROM.Interpretive Summary:
                                Technical Abstract: Thermal infrared (TIR) imagery provides estimates of land-surface temperature (LST) that can be used for mapping land surface energy fluxes and evapotranspiration (ET). For the ET mapping at the field scale, TIR data are required at relatively fine pixel resolution similar to the resolution of  Landsat shortwave sensors (30 m). To improve spatial resolution in LST retrievals (60 m for ETM+ and 120 m for TM), a new data mining sharpener (DMS) has been recently developed. The DMS approach sharpens TIR imagery using relationships between LST and shortwave spectral band reflectance built from a data mining technique (regression tree technique). The DMS approach has been compared to the classic thermal sharpening technique (TsHARP) that related LST to fractional vegetation cover. A comparison of sharpening techniques was applied over a rainfed agricultural area in central Iowa, an irrigated agricultural region in the Texas High Plains, and a heterogeneous naturally vegetated landscape in Alaska. In general, the DMS model provides better estimates of the sharpened LST in applications using Landsat TM, ETM+ and airborne data from the different locations and seasons. The artificial box-like patterns in LST generated by the TsHARP approach are greatly reduced using the DMS scheme, especially for areas containing irrigated crops, water, thin clouds or complex terrain. While the DMS technique can provide fine resolution Landsat TIR imagery, there are limitations to the sharpening ratios that can be reasonably implemented. Furthermore, subpixel variability in LST that are uncorrelated with signals captured in the shortwave bands will not be recovered (e.g., due to sub-pixel variations in surface moisture conditions). Consequently, sharpening approaches need to be further evaluated for ET mapping at field scale especially for the complex regions containing a patchwork of irrigated and non-irrigated fields and crop types. In this presentation, we will provide a detailed evaluation of the sharpening results using simulated Landsat TM and ETM+ data. The potential for the DMS approach to be used operationally will be discussed.


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