The satellite imagery of nighttime lights (NTLs) has been studied to understand human activities, economic development, and more recently, the ecological impact of brighter night skies. The Visible Infrared Imaging Radiometer Suite (VIIRS) Day–Night Band (DNB) offers perhaps the most advanced nighttime imaging capabilities to date, but its large pixel size and single band capture large-scale changes in NTL while missing granular but important details, such as lighting type and brightness. To better understand individual NTL sources in a region, the spectra of nighttime lights captured by the DLR Earth Sensing Imaging Spectrometer (DESIS) were extracted and compared against near-coincident VIIRS DNB imagery. The analysis shows that DESIS’s finer spatial and spectral resolutions can detect individual NTL locations and types beyond what is possible with the DNB. Extracted night light spectra, validated against ground truth measurements, demonstrate DESIS’s ability to accurately detect and identify narrow-band atomic emission lines that characterize the spectra of high-intensity discharge (HID) light sources and the broader spectral features associated with different light-emitting diode (LED) lights. These results suggest the possible application of using hyperspectral data from moderate-resolution sensors to identify lamp construction details, such as illumination source type and light quality in low-light contexts. NTL data from DESIS and other hyperspectral sensors may improve the scientific understanding of light pollution, lighting quality, and energy efficiency by identifying, evaluating, and mapping individual and small groups of light sources.

The satellite Earth observation (EO) sector is burgeoning with hundreds of commercial satellites being launched each year, delivering a rich source of data that could be exploited for societal benefit. Data streams from the growing number of commercial satellites are of variable quality, limiting the potential for their combined use in science applications that need long time-series data from multiple sources. The quality of calibration performed on optical sensors onboard many satellite systems is highly variable due to calibration methods, sensor design, mission objective, budget, or other operational constraints. A small number of currently operating well-characterised satellite systems with onboard calibration, such as Landsat-8/9 and Sentinel-2, and planned future missions, like the NASA Climate Absolute Radiance and Refractivity Observatory (CLARREO) Pathfinder, the European Space Agency (ESA)’s Traceable Radiometry Underpinning Terrestrial and Helio Studies (TRUTHS), and LIBRA from China, are considered benchmarks for optical data quality due to their traceability to international measurement standards. This paper describes the concept of a space-based transfer calibration radiometer called the Satellite Cross-Calibration Radiometer (SCR) that would enable the calibration parameters from satellites such as Landsat-8/9, Sentinel-2, or other benchmark systems to be transferred to a range of commercial optical EO satellite systems while in orbit. A description of the key characteristics of the SCR to successfully operate in orbit and transfer calibration from reference systems to client systems is presented. A system like the SCR in orbit could complement SI-Traceable satellites (SITSats) to improve data quality and consistency and facilitate the interoperable use of data from multiple optical sensor systems for delivering higher returns on the global investment in EO.

First posted June 6, 2023 For additional information, contact: Director, Earth Resources Observation and Science CenterU.S. Geological Survey47914 252nd StreetSioux Falls, SD 57198Contact Pubs Warehouse This report addresses system characterization of the BlackSky Global satellites and is part of a series of system characterization reports produced and delivered by the U.S. Geological Survey Earth Resources Observation and Science Cal/Val Center of Excellence. These reports present and detail the methodology and procedures for characterization; present technical and operational information about the specific sensing system being evaluated; and provide a summary of test measurements, data retention practices, data analysis results, and conclusions.The BlackSky Global satellites are three-band multispectral imagers (red, green, and blue multispectral bands plus a panchromatic band) with a 0.8- to 0.9-meter (m) pixel ground sample distance for the assessed satellites. BlackSky Global satellites 9 and 12–17 were launched in March and December 2021, respectively, into a Sun-synchronous orbit of 430–450 kilometers with an inclination of 42–53 degrees and a swath width of 6 kilometers at nadir. Each Global satellite has an expected lifetime of about 3 years. More information on the BlackSky Global satellites is available in the "Land Remote Sensing Satellites Online Compendium" (https://calval.cr.usgs.gov/apps/compendium) and from BlackSky at www.BlackSky.com.The Earth Resources Observation and Science Cal/Val Center of Excellence system characterization team completed data analyses to characterize the geometric (interior and exterior) and spatial performances. Results of these analyses indicate that the assessed BlackSky Global satellites have an interior geometric performance in the range of −0.011 m (−0.012 pixel) to 0.007 m (0.008 pixel) in easting and −0.018 m (−0.020 pixel) to 0.012 m (0.013 pixel) in northing in band-to-band registration; an exterior geometric performance using ground control points of 8.0-m circular error (95-percent certainty) for orthorectified products and 10.7- to 17.4-m circular error (95-percent certainty) for nonorthorectified products, depending on the geolocation metadata used; and a spatial performance in the range of 1.70 to 2.43 pixels for full width at half maximum, with a modulation transfer function at a Nyquist frequency in the range of 0.032 to 0.084.

The satellite cross-calibration radiometer (SCR) is a conceptual on-orbit hyperspectral imaging radiometer that transfers the radiometric calibration from a “gold-standard” reference instrument such as the Landsat 8/9 Operational Land Imager (OLI) to other civil, international, or commercial “client” multispectral satellite systems via near-simultaneous cross-calibration acquisitions. The spectral resolution, spectral range, spatial resolution, and signal-to-noise ratio (SNR) all significantly impact the complexity and cost of hyperspectral SCRs, so it is important to understand their effect on cross-calibration quality. This paper discusses the results of a trade study to quantify the effects of varying ground sample distance (GSD), number of independent samples, and instrument/scene noise on cross-calibration gain uncertainties. The trade study used a simulated SCR cross-calibration with near-simultaneous nadir overpasses (SNOs) of the Landsat 8 OLI acting as the reference instrument and the DLR Earth Sensing Imaging Spectrometer (DESIS) acting as a surrogate SCR hyperspectral instrument. Results demonstrate that cross-calibration uncertainty is only minimally affected by spatial resolution and SNR, which may allow SCR instruments to be developed at a lower cost.

Imaging spectrometry provides densely sampled and finely structured spectral information for each image pixel over large areas, enabling the characterization of materials on the Earth's surface by measuring and analyzing quantitative parameters allowing the user to identify and characterize Earth surface materials such as minerals in rocks and soils, vegetation types and stress indicators, and water constituents. The recently launched DLR Earth Sensing Imaging Spectrometer (DESIS) installed on the International Space Station (ISS) closes the long-term gap of sparsely available spaceborne imaging spectrometry data and will be part of the upcoming fleet of such new instruments in orbit. DESIS measures in the spectral range from 400 and 1000 nm with a spectral sampling distance of 2.55 nm and a Full Width Half Maximum (FWHM) of about 3.5 nm. The various DESIS data products available for users are described with the focus on specific processing steps. A summary of the data quality results are given. The product validation studies show that top-of-atmosphere radiance, geometrically corrected, and bottom-of-atmosphere reflectance products meet the mission requirements.

A fully automated, National Institute of Standards and Technology (NIST)-traceable artificial light source called Terra Vega has been developed to radiometrically calibrate the Visible Infrared Imaging Radiometer (VIIRS) Day Night Band (DNB) working in high gain stage (HGS) mode. The Terra Vega active point source is a calibrated integrating sphere that is only a fraction in size of a VIIRS DNB pixel. As such, it can be considered analogous to a ground-based photometric reference star. Vicarious calibrations that employ active point sources are different than those that make use of traditional extended sources and can be applyed to quantify the brightness of artificial light sources. The active source is successfully fielded, and early results indicate that it can be used to augment and validate the radiometric calibration of the VIIRS DNB HGS sensor on both the Suomi National Polar-orbiting Partnership (NPP) and NOAA-20 satellites. The VIIRS DNB HGS sensor can benefit from this technology as on-board calibration is challenging and hinges on transferring low gain stage (LGS) calibration using a solar diffuser to the medium gain stage (MGS) and HGS via regions of overlap. Current vicarious calibration methods that use a lunar-illuminated extended source estimate the HGS radiometric accuracy to within 8-15%. By comparison, early results and analysis showed that Terra Vega is stable to about 1%. Under clear dark night conditions, predicted top-of-atmosphere radiance from Terra Vega ranged between 1–11% of VIIRS measured values. Terra Vega’s excellent stability opens up new opportunities to validate and develop nighttime imaging applications based on point sources.

In 2014, the German Aerospace Center (DLR) and the US company Teledyne Brown Engineering (TBE) decided to collaborate and develop the hyperspectral instrument Earth Imaging Spectrometer (DESIS) for integration into the Multi-User System for Earth Sensing (MUSES) installed on the International Space Station (ISS). Four years later, on 29 June 2018, the instrument was launched from Cape Canaveral with a SpaceX Dragon rocket. One month later, the instrument was robot-assisted integrated into MUSES and the commissioning phase started. First light images were available after 48 hours. The commissioning phase includes checkout for functional testing, End-to-End tests, processing parameter tuning, in-flight calibration tests and product validation. The operational phase of the mission has been entered several months later. From this point on, hyperspectral data will be available to the scientific and commercial user community. In this paper a summary of results from the commissioning phase will be presented including aspects of data quality, operational performance and first data evaluation results. The MUSES platform provides accommodations for two large and two small hosted payloads. MUSES is attached at the ELC-4 (EXPRESS Logistics Carriers) starboard of the ISS. It is a space-based, Earth-pointing platform providing position and attitude sensing, data downlink, and other core services common for each payload. DESIS has a mass of ~88 kg and is integrated in one of the large containers. Two gimbals allow a rotation of the whole MUSES platform around two axes resulting in ±25° forward / backward view, 45° backboard (port) view and 5° starboard view. The platform is equipped with a star tracker (sampling rate 10 Hz) and a MIMU (Miniature Inertial Measurement Unit) (sampling rate 50 Hz) providing a 10 Hz attitude measurement after filtering. ISS GPS data provide position and velocity vectors and time tags (sampling rate 1 Hz). The predicted viewing capability of MUSES, when operating at the ISS orbit inclination of 51.6°, will enable the DESIS instrument to scan greater than 90% of the populated Earth with an average cadence of about one week. The DESIS hyperspectral instrument is realized as a pushbroom imaging spectrometer and features 235 bands with 3.5-4.0 nm spectral resolution, covering a range from 400 nm to 1000 nm with 30 m spatial resolution employing a 2-dimensional back illuminated CMOS (Complementary Metal Oxide Semiconductor) detector array. The optical design is based on the Offner-type grating spectrometer widely used in hyperspectral imaging. DESIS is equipped with a Pointing Unit (POI) consisting of a rotating mirror in front of the entrance slit allowing a forward and backward viewing change up to ±15° w.r.t. the nominal (e.g. nadir) view. The POI can be operated in a static mode with 3° angle steps for the viewing direction and in a dynamic mode with up to 1.5° change in viewing direction per seconds. This allows, besides standard Earth data products, acquisition of Bidirectional Reflectance Distribution Function (BRDF) products and continuous observations of the same targets on ground (using forward motion compensation mode). DESIS has been characterized in laboratory and will be re-calibrated after launch employing measurements of internal light sources (bank of white and colored LED lamps) and globally distributed reference sites aiming to assess radiometric, spectrometric and geometric characteristics of the DESIS hyperspectral instrument in orbit. Vicarious validation activities will be performed at regular interval to ensure that a suitable data quality is met. This includes validation over well-known calibration sites, cross-comparisons with other simultaneous acquired data sets and analysis of homogenous areas. The Ground Segment at DLR has developed the operational processing chain to derive different types of DESIS products from tiled data takes of size 1024 x 1024 pixels (~30 x 30 km²). An identical processing chain is licensed to TBE running on a cloud based system (© Amazon Cloud) for commercial product generation. DESIS level 1A products (Earth image scenes, on-board calibration measurements, dark current measurements and experimental products) will be long-term archived together with the corresponding metadata, while level 1B products (systematically and radiometrically corrected data), level 1C products (geometrically corrected data employing global references) and level 2A products (atmospherically compensated data) will be processed on demand before being delivered to the user for further value-add product generation. For scientific purposes only, DLR can share DESIS scientific data with other scientific organizations. TBE distributes data on a commercial basis.

Imaging spectrometry from aerial or spaceborne platforms, also known as hyperspectral remote sensing, provides dense sampled and fine structured spectral information for each image pixel, allowing the user to identify and characterize Earth surface materials such as minerals in rocks and soils, vegetation types and stress indicators, and water constituents. The recently launched DLR Earth Sensing Imaging Spectrometer (DESIS) installed on the International Space Station (ISS) closes the long-term gap of sparsely available spaceborne imaging spectrometry data and will be part of the upcoming fleet of such new instruments in orbit. DESIS measures in the spectral range from 400 and 1000 nm with a spectral sampling distance of 2.55 nm and a Full Width Half Maximum (FWHM) of about 3.5 nm. The ground sample distance is 30 m with 1024 pixels across track. In this article, a detailed review is given on the applicability of DESIS data based on the specifics of the instrument, the characteristics of the ISS orbit, and the methods applied to generate products. The various DESIS data products available for users are described with the focus on specific processing steps. The results of the data quality and product validation studies show that top-of-atmosphere radiance, geometrically corrected, and bottom-of-atmosphere reflectance products meet the mission requirements. The limitations of the DESIS data products are also subject to a critical examination.

The high sensitivity of the Visible Infrared Imaging Radiometer (VIIRS) Day Night Band (DNB) high gain stage (HGS) cannot directly use on-board calibration sources such as solar diffusers, so other calibration approaches are needed. A fully automated, NIST-traceable active point source called the Accurate Active Light Source (AALS) based on a 1-meter diameter integrating sphere illuminated with High Pressure Sodium (HPS) lamps has been developed to calibrate the VIIRS DNB HGS mode. This paper provides the theory and operation of the AALS. The AALS is housed in an environmentally controlled, moveable, enclosed trailer that protects the sphere and is being deployed in South Dakota during the summer and Mississippi during the winter. AALS Lambertian source radiance is measured by a NIST-traceable spectroradiometer. MODTRAN-based top of atmosphere (TOA) radiance is calculated using nighttime aerosol estimates and point source radiative transfer techniques that account for the VIIRS finite Point Spread Function (PSF). This new active point source complements current vicarious calibration techniques, which are based on lunar illumination of extended sources (clouds, playas, etc.), and helps improve our understanding of the point source radiative transfer needed to develop nighttime artificial light source applications. An uncertainty budget for TOA radiance indicates that accuracy under clear, moonless conditions should be comparable to daytime vicarious calibration methods. This paper shows that the major uncertainty is the ground-to-space atmospheric transmission and discusses approaches to reduce this error. Initial assessment of the VIIRS DNB HGS on the Suomi-NPP and NOAA-20 satellites are presented.

NASA's Black Marble nighttime lights product suite (VNP46) is available at 500 m resolution since January 2012 with data from the Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) onboard the Suomi National Polar-orbiting Platform (SNPP). The retrieval algorithm, developed and implemented for routine global processing at NASA's Land Science Investigator-led Processing System (SIPS), utilizes all high-quality, cloud-free, atmospheric-, terrain-, vegetation-, snow-, lunar-, and stray light-corrected radiances to estimate daily nighttime lights (NTL) and other intrinsic surface optical properties. Extensive benchmark tests at representative spatial and temporal scales were conducted on the VNP46 time series record to characterize the uncertainties stemming from upstream data sources. Current and planned validation activities under the Group on Earth Observations (GEO) Human Planet Initiative are aimed at evaluating the products at different geographic locations and time periods representing the full range of retrieval conditions.

A comprehensive radiometric characterization of raw-data format imagery acquired with the Raspberry Pi 3 and V2.1 camera module is presented. The Raspberry Pi is a high-performance single-board computer designed to educate and solve real-world problems. This small computer supports a camera module that uses a Sony IMX219 8 megapixel CMOS sensor. This paper shows that scientific and engineering-grade imagery can be produced with the Raspberry Pi 3 and its V2.1 camera module. Raw imagery is shown to be linear with exposure and gain (ISO), which is essential for scientific and engineering applications. Dark frame, noise, and exposure stability assessments along with flat fielding results, spectral response measurements, and absolute radiometric calibration results are described. This low-cost imaging sensor, when calibrated to produce scientific quality data, can be used in computer vision, biophotonics, remote sensing, astronomy, high dynamic range imaging, and security applications, to name a few. (C) The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its

We present and demonstrate an innovative and extremely low cost aerial monitoring and surveillance platform based on integrating open source and small unmanned aerial vehicles (UAV) with a highly capable compact, lightweight smart phone. We investigated sensors available within smart phones such as the camera, GPS, gyroscope and accelerometer, to integrate computing and sensing capabilities to the UAV in an extremely cost-effective way, which could fundamentally affect the way UAVs are used in emergency response and other applications.

A characterization software suite was developed to facilitate NASA's in-flight characterization of commercial remote sensing systems. Characterization of aerial and satellite systems requires knowledge of ground characteristics, or ground truth. This information is typically obtained with instruments taking measurements prior to or during a remote sensing system overpass. Acquired ground-truth data, which can consist of hundreds of measurements with different data formats, must be processed before it can be used in the characterization. Accurate in-flight characterization of remote sensing systems relies on multiple field data acquisitions that are efficiently processed, with minimal error. To address the need for timely, reproducible ground-truth data, a characterization software suite was developed to automate the data processing methods. The characterization software suite is engineering code, requiring some prior knowledge and expertise to run. The suite consists of component scripts for each of the three main in-flight characterization types: radiometric, geometric, and spatial. The component scripts for the radiometric characterization operate primarily by reading the raw data acquired by the field instruments, combining it with other applicable information, and then reducing it to a format that is appropriate for input into MODTRAN (MODerate resolution atmospheric TRANsmission), an Air Force Research Laboratory-developed radiative transport code used to predict at-sensor measurements. The geometric scripts operate by comparing identified target locations from the remote sensing image to known target locations, producing circular error statistics defined by the Federal Geographic Data Committee Standards. The spatial scripts analyze a target edge within the image, and produce estimates of Relative Edge Response and the value of the Modulation Transfer Function at the Nyquist frequency. The software suite enables rapid, efficient, automated processing of ground truth data, which has been used to provide reproducible characterizations on a number of commercial remote sensing systems. Overall, this characterization software suite improves the reliability of ground-truth data processing techniques that are required for remote sensing system in-flight characterizations.

Considerable interest has been given to forming an international collaboration to develop a virtual moderate spatial resolution land observation constellation through aggregation of data sets from comparable national observatories such as the US Landsat, the Indian ResourceSat and related systems. This study explores the complementarity of India's ResourceSat-1 Advanced Wide Field Sensor (AWiFS) with the Landsat 5 Thematic Mapper (TM) and Landsat 7 Enhanced Thematic Mapper Plus (ETM+). The analysis focuses on the comparative radiometry, geometry, and spectral properties of the two sensors. Two applied assessments of these data are also explored to examine the strengths and limitations of these alternate sources of moderate resolution land imagery with specific application domains. There are significant technical differences in these imaging systems including spectral band response, pixel dimensions, swath width, and radiometric resolution which produce differences in observation data sets. None of these differences was found to strongly limit comparable analyses in agricultural and forestry applications. Overall, we found that the AWiFS and Landsat TM/ETM+ imagery are comparable and in some ways complementary, particularly with respect to temporal repeat frequency. We have found that there are limits to our understanding of the AWiFS performance, for example, multi-camera design and stability of radiometric calibration over time, that leave some uncertainty that has been better addressed for Landsat through the Image Assessment System and related cross-sensor calibration studies. Such work still needs to be undertaken for AWiFS and similar observatories that may play roles in the Global Earth Observation System of Systems Land Surface Imaging Constellation.

Image spatial resolution characteristics can vary widely among sources. In the case of aerial-based imaging systems, the image spatial resolution characteristics can even vary between acquisitions. In these systems, aircraft altitude, speed, and sensor look angle all affect image spatial resolution. Image spatial resolution needs to be verified with estimators that include the ground sample distance (GSD), the modulation transfer function (MTF), and the relative edge response (RER), all of which are key components of image quality, along with signal-to-noise ratio (SNR) and dynamic range. Knowledge of spatial resolution parameters is important to determine if features of interest are distinguishable in imagery or associated products, and to develop image restoration algorithms. An automated Spatial Resolution Verification Tool (SRVT) was developed to rapidly determine the spatial resolution characteristics of remotely sensed aerial and satellite imagery. Most current methods for assessing spatial resolution characteristics of imagery rely on pre-deployed engineered targets and are performed only at selected times within preselected scenes. The SRVT addresses these insufficiencies by finding uniform, high-contrast edges from urban scenes and then using these edges to determine standard estimators of spatial resolution, such as the MTF and the RER. The SRVT was developed using the MATLAB programming language and environment. This automated software algorithm assesses every image in an acquired data set, using edges found within each image, and in many cases eliminating the need for dedicated edge targets. The SRVT automatically identifies high-contrast, uniform edges and calculates the MTF and RER of each image, and when possible, within sections of an image, so that the variation of spatial resolution characteristics across the image can be analyzed. The automated algorithm is capable of quickly verifying the spatial resolution quality of all images within a data set, enabling the appropriate use of those images in a number of applications.

This technology exploits the organic decomposition capability and hydrophilic properties of the photocatalytic material titanium dioxide (TiO2), a nontoxic and non-hazardous substance, to address contamination and biofouling issues in field-deployed optical sensor systems. Specifically, this technology incorporates TiO2 coatings and materials applied to, or integrated as a part of, the optical surfaces of sensors and calibration sources, including lenses, windows, and mirrors that are used in remote, unattended, ground-based (land or maritime) optical sensor systems. Current methods used to address contamination or biofouling of these optical surfaces in deployed systems are costly, toxic, labor intensive, and non-preventative. By implementing this novel technology, many of these negative aspects can be reduced. The functionality of this innovative self-cleaning solution to address the problem of contamination or biofouling depends on the availability of a sufficient light source with the appropriate spectral properties, which can be attained naturally via sunlight or supplemented using artificial illumination such as UV LEDs (light emitting diodes). In land-based or above-water systems, the TiO2 optical surface is exposed to sunlight, which catalyzes the photocatalytic reaction, facilitating both the decomposition of inorganic and organic compounds, and the activation of superhydrophilic properties. Since underwater optical surfaces are submerged and have limited sunlight exposure, supplementary UV light sources would be required to activate the TiO2 on these optical surfaces. Nighttime operation of land-based or above-water systems would require this addition as well. For most superhydrophilic self-cleaning purposes, a rainwater wash will suffice; however, for some applications an attached rainwater collector/ dispenser or other fresh water dispensing system may be required to wash the optical surface and initiate the removal of contaminates. Deployment of this non-toxic,non-hazardous-technology will take advantage of environmental elements (i.e. rain and sunlight), increase the longevity of unattended optical systems, increase the amount of time between required maintenance, and improve the long-term accuracy of sensor measurements.

The spatial resolution of a digital, electro-optical remote sensing imaging system or product is an important image quality characteristic that helps determine the utility of an imaging source. Although spatial resolution is often described by a single image quality parameter, the ground sample distance, there are several other parameters that affect image sharpness and need to be considered. These other parameters are associated with the point-spread function, signal-to-noise ratio, and dynamic range of the image product. This review paper covers the various approaches to in-flight measurement of spatial resolution parameters, including ground sample distance, point spread function, optical transfer function, modulation transfer function, far field response, and edge response and their significance, as well as target types and methods to determine these spatial resolution parameters. To this end, the paper lists and describes various targets found across the world, as well as astronomical ones. These targets are appropriate for evaluating a wide range of image scale products. For high spatial resolution imaging systems, the types of targets range from engineered fixed and deployable targets to agricultural and urban features, allowing almost any site to be used for determining spatial resolution. Independent, comprehensive image product evaluation sites that are currently in use in the US and Europe are also described.

A simple method to estimate the photocatalytic reactivity performance of spray-on titanium dioxide coatings for transmissive glass surfaces was developed. This novel technique provides a standardized method to evaluate the efficiency of photocatalytic material systems over a variety of illumination levels. To date, photocatalysis assessments have generally been conducted using mercury black light lamps. Illumination levels for these types of lamps are difficult to vary, consequently limiting their use for assessing material performance under a diverse range of simulated environmental conditions. This new technique uses an ultraviolet (UV) gallium nitride (GaN) light emitting diode (LED) array instead of a traditional black light to initiate and sustain photocatalytic breakdown. This method was tested with a UV-resistant dye (crystal violet) applied to a titanium dioxide coated glass slide. Experimental control is accomplished by applying crystal violet to both titanium dioxide coated slides and uncoated control slides. A slide is illuminated by the UV LED array, at various light levels representative of outdoor and indoor conditions, from the dye side of the slide. To monitor degradation of the dye over time, a temperature-stabilized white light LED, whose emission spectrum overlaps with the dye absorption spectrum, is used to illuminate the opposite side of the slide. Using a spectrometer, the amount of light from the white light LED transmitted through the slide as the dye degrades is monitored as a function of wavelength and time and is subsequently analyzed. In this way, the rate of degradation for photocatalytically coated versus uncoated slide surfaces can be compared. Results demonstrate that the dye absorption decreased much more rapidly on the photocatalytically coated slides than on the control uncoated slides, and that dye degradation is dependent on illumination level. For photocatalytic activity assessment purposes, this experimental configuration and methodology minimizes many external variable effects and enables small changes in absorption to be measured. This research also compares the advantages of this innovative LED light source design over traditional mercury black light systems and non- LED lamp approaches. This novel technology begins to address the growing need for a standard method that can assess the performance of photocatalytic materials before deployment for large scale, real world use.