Evaluation of VIIRS Nightfire Product and Comparison with MODIS and VIIRS Active Fire Products in a Russian Gas Flaring Region.

Gas flaring is a commonly used practice for disposing of waste gases emerging from industrial oil drilling and production processes. It is a serious environmental and economic hazard with adverse impacts on air quality, climate, and the public health. Accurate determination of flare locations and estimation of associated emissions are therefore of prime importance. Recently developed Visible Infrared Imaging Radiometer Suite (VIIRS) Nightfire product (VNF) has shown remarkable efficiency in detecting gas flares globally, owing primarily to its use of Shortwave Infrared (SWIR) band in its detection algorithm. This study compares and contrast nocturnal hot source detection by VNF to detections by other established fire detection products (i.e., Moderate Resolution Imaging Spectroradiometer (MODIS) Terra Thermal Anomalies product (MOD14), MODIS Aqua Thermal Anomalies product (MYD14) and VIIRS Applications Related Active Fire Product (VAFP)) over an extensive gas flaring region in Russia ‑ Khanty Mansiysk Autonomous Okrug, for the time period of April - August 2013. The surface hotspots detected by VNF were found to be much higher in magnitude than detected by other products. An attempt to replicate VNF algorithm locally for better comprehension, revealed threshold related discrepancies in VNF V1.0 in multiple spectral bands. Case studies for reconciliation between VNF‑R (VNF replicated product) and VAFP hotspots showed that convergence in hotspot detection between two products is possible by scaling up VNF-R thresholds, and, VAFP can detect large flares having strong spectral signature in SWIR bands. The efficacy of VNF hotspot detection was evaluated for 10 previously identified flare locations with varying hot source sizes over the period of April‑August 2013. VNF was able to detect all the test sites with frequency of detection varying between 20% to 42% of the days tested. Mean areas of tested gas flares estimated by VNF showed good agreement with areas of flares computed using Google Earth with a linear correlation of 0.91; however, VNF estimated areas were found to be somewhat underestimated. Overall the results indicate significant potential of VNF in characterizing gas flaring from space. Advisor: Mark R. Anderso

Comparison of MODIS and VIIRS Snow Cover Products for the 2016 Hydrological Year

The VIIRS (Visible Infrared Imaging Radiometer Suite) on board the Suomi-NPP (National Polar-orbiting Partnership) satellite aims to provide long-term continuity of several environmental data series including snow cover initiated with the MODIS (Moderate Resolution Imaging Spectroradiometer) instrument carried aboard Aqua and Terra satellites. There are speculations concerning differences between MODIS and VIIRS snow cover products because of different spatial resolution and spectral coverage. However, the quantitative comparisons between VIIRS and MODIS snow products are currently limited. Consequently, this study intercompares MODIS and VIIRS snow products during the 2016 hydrological year. To accomplish its research objectives, 244 swath snow products from MODIS/Aqua (MYD10L2) and the VIIRS EDR (VSCMO/binary) were intercompared for the 2016 hydrological year from October 1, 2015 to May 31, 2016 using confusion matrices, comparison maps and false color imagery. The current VIIRS snow product is binary, therefore to produce MODIS binary snow maps, the MODIS snow cover fraction threshold value of 30% was determined by examining snow cover area at four different thresholds (20%, 30%, 40% and 50%) and comparing them with the VIIRS binary snow map. Overall VIIRS appears to map more snow and less clouds than MODIS. On average, MODIS snow maps mapped snow but VIIRS in 1% of cloud free pixels, whereas 2% of the time VIIRS mapped snow but MODIS did not. The average agreement between MODIS and VIIRS was approximately 98% indicating good agreement between them. Agreement between MODIS and VIIRS was high during the winter but lower during late fall and spring, mostly over dense forest. Both MODIS and VIIRS often mapped snow/no-snow transition zones as cloud. The visual comparison depicts good qualitative agreement between snow cover area visible in MODIS and VIIRS false color imagery and mapped in their respective snow cover products

Sharpening ECOSTRESS and VIIRS Land Surface Temperature Using Harmonized Landsat-Sentinel Surface Reflectances

Land surface temperature (LST) is a key diagnostic indicator of agricultural water use and crop stress. LST data retrieved from thermal infrared (TIR) band imagery, however, tend to have a coarser spatial resolution (e.g., 100 m for Landsat 8) than surface reflectance (SR) data collected from shortwave bands on the same instrument (e.g., 30 m for Landsat). Spatial sharpening of LST data using the higher resolution multi-band SR data provides an important path for improved agricultural monitoring at sub-field scales. A previously developed Data Mining Sharpener (DMS) approach has shown great potential in the sharpening of Landsat LST using Landsat SR data co-collected over various landscapes. This work evaluates DMS performance for sharpening ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) LST (~70 m native resolution) and Visible Infrared Imaging Radiometer Suite (VIIRS) LST (375 m) data using Harmonized Landsat and Sentinel-2 (HLS) SR data, providing the basis for generating 30-m LST data at a higher temporal frequency than afforded by Landsat alone. To account for the misalignment between ECOSTRESS/VIIRS and Landsat/HLS caused by errors in registration and orthorectification, we propose a modified version of the DMS approach that employs a relaxed box size for energy conservation (EC). Sharpening experiments were conducted over three study sites in California, and results were evaluated visually and quantitatively against LST data from unmanned aerial vehicles (UAV) flights and from Landsat 8. Over the three sites, the modified DMS technique showed improved sharpening accuracy over the standard DMS for both ECOSTRESS and VIIRS, suggesting the effectiveness of relaxing EC box in relieving misalignment-induced errors. To achieve reasonable accuracy while minimizing loss of spatial detail due to the EC box size increase, an optimal EC box size of 180–270 m was identified for ECOSTRESS and about 780 m for VIIRS data based on experiments from the three sites. Results from this work will facilitate the development of a prototype system that generates high spatiotemporal resolution LST products for improved agricultural water use monitoring by synthesizing multi-source remote sensing data

Land Surface Temperature Product Validation Best Practice Protocol Version 1.0 - October, 2017

The Global Climate Observing System (GCOS) has specified the need to systematically generate andvalidate Land Surface Temperature (LST) products. This document provides recommendations on goodpractices for the validation of LST products. Internationally accepted definitions of LST, emissivity andassociated quantities are provided to ensure the compatibility across products and reference data sets. Asurvey of current validation capabilities indicates that progress is being made in terms of up-scaling and insitu measurement methods, but there is insufficient standardization with respect to performing andreporting statistically robust comparisons.Four LST validation approaches are identified: (1) Ground-based validation, which involvescomparisons with LST obtained from ground-based radiance measurements; (2) Scene-based intercomparisonof current satellite LST products with a heritage LST products; (3) Radiance-based validation,which is based on radiative transfer calculations for known atmospheric profiles and land surface emissivity;(4) Time series comparisons, which are particularly useful for detecting problems that can occur during aninstrument's life, e.g. calibration drift or unrealistic outliers due to undetected clouds. Finally, the need foran open access facility for performing LST product validation as well as accessing reference LST datasets isidentified

Suomi NPP VIIRS Prelaunch and On-orbit Geometric Calibration and Characterization

The Visible Infrared Imager Radiometer Suite (VIIRS) sensor was launched 28 October 2011 on the Suomi National Polarorbiting Partnership (SNPP) satellite. VIIRS has 22 spectral bands covering the spectrum between 0.412 m and 12.01 m, including 16 moderate resolution bands (M-bands) with a spatial resolution of 750 m at nadir, 5 imaging resolution bands (I-bands) with a spatial resolution of 375 m at nadir, and 1 day-night band (DNB) with a near-constant 750 m spatial resolution throughout the scan. These bands are located in a visible and near infrared (VisNIR) focal plane assembly (FPA), a short- and mid-wave infrared (SWMWIR) FPA and a long-wave infrared (LWIR) FPA. All bands, except the DNB, are co-registered for proper environmental data records (EDRs) retrievals. Observations from VIIRS instrument provide long-term measurements of biogeophysical variables for climate research and polar satellite data stream for the operational communitys use in weather forecasting and disaster relief and other applications. Well Earth-located (geolocated) instrument data is important to retrieving accurate biogeophysical variables. This paper describes prelaunch pointing and alignment measurements, and the two sets of on-orbit correction of geolocation errors, the first of which corrected error from 1,300 m to within 75 m (20 I-band pixel size), and the second of which fine tuned scan angle dependent errors, bringing VIIRS geolocation products to high maturity in one and a half years of the SNPP VIIRS on-orbit operations. Prelaunch calibration and the on-orbit characterization of sensor spatial impulse responses and band-to-band co-registration (BBR) are also described

Comparison of MODIS and VIIRS Snow Cover Products for the 2016 Hydrological Year

The VIIRS (Visible Infrared Imaging Radiometer Suite) on board the Suomi-NPP (National Polar-orbiting Partnership) satellite aims to provide long-term continuity of several environmental data series including snow cover initiated with the MODIS (Moderate Resolution Imaging Spectroradiometer) instrument carried aboard Aqua and Terra satellites. There are speculations concerning differences between MODIS and VIIRS snow cover products because of different spatial resolution and spectral coverage. However, the quantitative comparisons between VIIRS and MODIS snow products are currently limited. Consequently, this study intercompares MODIS and VIIRS snow products during the 2016 hydrological year. To accomplish its research objectives, 244 swath snow products from MODIS/Aqua (MYD10L2) and the VIIRS EDR (VSCMO/binary) were intercompared for the 2016 hydrological year from October 1, 2015 to May 31, 2016 using confusion matrices, comparison maps and false color imagery. The current VIIRS snow product is binary, therefore to produce MODIS binary snow maps, the MODIS snow cover fraction threshold value of 30% was determined by examining snow cover area at four different thresholds (20%, 30%, 40% and 50%) and comparing them with the VIIRS binary snow map. Overall VIIRS appears to map more snow and less clouds than MODIS. On average, MODIS snow maps mapped snow but VIIRS in 1% of cloud free pixels, whereas 2% of the time VIIRS mapped snow but MODIS did not. The average agreement between MODIS and VIIRS was approximately 98% indicating good agreement between them. Agreement between MODIS and VIIRS was high during the winter but lower during late fall and spring, mostly over dense forest. Both MODIS and VIIRS often mapped snow/no-snow transition zones as cloud. The visual comparison depicts good qualitative agreement between snow cover area visible in MODIS and VIIRS false color imagery and mapped in their respective snow cover products

Land and cryosphere products from Suomi NPP VIIRS: overview and status

[1] The Visible Infrared Imaging Radiometer Suite (VIIRS) instrument was launched in October 2011 as part of the Suomi National Polar-Orbiting Partnership (S-NPP). The VIIRS instrument was designed to improve upon the capabilities of the operational Advanced Very High Resolution Radiometer and provide observation continuity with NASA's Earth Observing System's Moderate Resolution Imaging Spectroradiometer (MODIS). Since the VIIRS first-light images were received in November 2011, NASA- and NOAA-funded scientists have been working to evaluate the instrument performance and generate land and cryosphere products to meet the needs of the NOAA operational users and the NASA science community. NOAA's focus has been on refining a suite of operational products known as Environmental Data Records (EDRs), which were developed according to project specifications under the National Polar-Orbiting Environmental Satellite System. The NASA S-NPP Science Team has focused on evaluating the EDRs for science use, developing and testing additional products to meet science data needs, and providing MODIS data product continuity. This paper presents to-date findings of the NASA Science Team's evaluation of the VIIRS land and cryosphere EDRs, specifically Surface Reflectance, Land Surface Temperature, Surface Albedo, Vegetation Indices, Surface Type, Active Fires, Snow Cover, Ice Surface Temperature, and Sea Ice Characterization. The study concludes that, for MODIS data product continuity and earth system science, an enhanced suite of land and cryosphere products and associated data system capabilities are needed beyond the EDRs currently available from the VIIRS

Improving Nocturnal Fire Detection with the VIIRS Day-Night Band

As an important component in the Earth-atmosphere system, wildfires are a serious threat to life and property that—despite improving warning systems—have exacted greater costs in recent years. In addition, they impact global atmospheric chemistry by releasing potent trace gasses and aerosols. Using the Visible Infrared Imaging Radiometer Suite (VIIRS), this study investigates the adjustment of fire pixel selection criteria to include visible light signatures at night, creating the Firelight Detection Algorithm (FILDA). This allows for greatly improved detection of smaller and cooler fires from satellite observations. VIIRS scenes with coincident Advanced Spaceborne Thermal Emission and Reflection (ASTER) overpasses are examined after applying the operational VIIRS fire product algorithm and including a modified candidate fire pixel selection approach, which lowers the 4 μm brightness temperature threshold from 305 K but includes a minimum day-night band (DNB) radiance. FILDA is tested by applying it to scenes in different environments, including large forest fires like the Rim Fire in California and High Park fire in Colorado, in addition to gas flares. A large increase in the number of detected fire pixels is observed with small non-agricultural wildfires, as verified with the finer-resolution ASTER data (90 m). Quantitative use of the DNB to improve detection of these smaller fires could lead to reduced warning and response times as well as provide more accurate quantification of biomass burning emissions at night. Adviser: Jun Wan

The Capabilities of FY-3D/MERSI-II Sensor to Detect and Quantify Thermal Volcanic Activity: The 2020–2023 Mount Etna Case Study

Satellite data provide crucial information to better understand volcanic processes and mitigate associated risks. In recent years, exploiting the growing number of spaceborne polar platforms, several automated volcanic monitoring systems have been developed. These, however, rely on good geometrical and meteorological conditions, as well as on the occurrence of thermally detectable activity at the time of acquisition. A multiplatform approach can thus increase the number of volcanological-suitable scenes, minimise the temporal gap between acquisitions, and provide crucial information on the onset, evolution, and conclusion of both transient and long-lasting volcanic episodes. In this work, we assessed the capabilities of the MEdium Resolution Spectral Imager-II (MERSI-II) sensor aboard the Fengyun-3D (FY-3D) platform to detect and quantify heat flux sourced from volcanic activity. Using the Middle Infrared Observation of Volcanic Activity (MIROVA) algorithm, we processed 3117 MERSI-II scenes of Mount Etna acquired between January 2020 and February 2023. We then compared the Volcanic Radiative Power (VRP, in Watt) timeseries against those obtained by MODIS and VIIRS sensors. The remarkable agreement between the timeseries, both in trends and magnitudes, was corroborated by correlation coefficients (ρ) between 0.93 and 0.95 and coefficients of determination (R2) ranging from 0.79 to 0.84. Integrating the datasets of the three sensors, we examined the effusive eruption of Mount Etna started on 27 November 2022, and estimated a total volume of erupted lava of 8.15 ± 2.44 × 106 m3 with a Mean Output Rate (MOR) of 1.35 ± 0.40 m3 s-1. The reduced temporal gaps between acquisitions revealed that rapid variations in cloud coverage as well as geometrically unfavourable conditions play a major role in thermal volcano monitoring. Evaluating the capabilities of MERSI-II, we also highlight how a multiplatform approach is essential to enhance the efficiency of satellite-based systems for volcanic surveillance