Abstract

Land Surface Temperature (ST) represents the radiative temperature of the Earth’s surface and is used as an input for hydrological, agricultural, and meteorological science applications. Due to the synoptic nature of satellite imaging systems, ST products derived from spaceborne platforms are invaluable for estimating ST at the local, regional, and global scale. Over the past two decades, an emphasis has been placed on the need to develop algorithms necessary to deliver accurate ST products to support the needs of science users. However, corresponding efforts to validate these products are hindered by the availability of quality ground based reference measurements. NOAA’s Surface Radiation Budget Network (SURFRAD) is commonly used to support ST-validation efforts, but SURFAD’s instrumentation is broadband (4-50 micrometer) and several of their sites lack spatial uniformity, which can lead to large ST calculation errors. To address the apparent deficiencies within existing validation networks, this work discusses a prototype instrument developed to provide ST estimates to support validation efforts for spaceborne thermal sensor products. Specifically, a prototype radiometer was designed, built, calibrated, and utilized to acquire ground reference data to validate ST product(s) derived from Landsat 8 imagery. Field based efforts indicate these radiometers demonstrate agreement to Landsat-derived ST products to within 1.37 K over grass targets. This is an improvement of over 2 K when comparing to the SURFRAD validation network.

Additionally, the radiometers proposed in this research were designed to calculate the largest unknown variable used to create Landsat 8 derived ST products: the target emissivity. Algorithms have been developed with the purpose of using Landsat 8’s two thermal bands to calculate the ST of a given scene. One popular method is the split window algorithm, which uses at sensor apparent temperatures collected by band 10 and 11 of Landsat, along with atmospheric data to calculate the surface leaving temperatures. A key input into the split window algorithm is the emissivity of the target, which is currently calculated using data from another spaceborne sensor; the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data from EOS-1 (Terra). This emissivity calculation is not ideal because, like the ST calculation, the emissivity is also propagated through the atmosphere before being calculated. An ideal approach is to measure and calculate the emissivity close to the surface, thus eliminating any atmospheric compensation errors. To eliminate the reliance on ASTER data and calculate the emissivity of the target before atmospheric effects, four additional response bands in the 8 – 9 micrometer range are added to the radiometer resulting in a six band instrument capable of calculating the ST and emissivity of a ground target. Through a validation effort using a commercial Fourier Transform Infrared Spectrometer (FTIR) the six-band radiometer's ability to calculate the emissivity of a target is in agreement to the FTIR derived emissivity values to within 0.025 for Landsat-like band 10 and 0.022 for Landsat-like band 11 over grass targets. More accurate target emissivity values can decrease the error in the split window ST calculation by as much as 2.4 K over grass targets.

The proposed instruments in this research can provide a more accurate validation of the Landsat 8 ST product when comparing to current validation networks, and therefore more accurate target emissivity values. Combining the two capabilities of this proposed radiometer allows the delivery of trusted data to the scientific community for their use in multiple applications.

Library of Congress Subject Headings

Radiometers--Design and construction; Earth temperature--Remote sensing; Earth temperature--Measurement; Landsat satellites

Publication Date

11-6-2020

Document Type

Dissertation

Student Type

Graduate

Degree Name

Imaging Science (Ph.D.)

Department, Program, or Center

Chester F. Carlson Center for Imaging Science (COS)

Advisor

Aaron Gerace

Advisor/Committee Member

Dan Phillips

Advisor/Committee Member

Matthew Montanaro

Campus

RIT – Main Campus

Plan Codes

IMGS-PHD

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