Master of Science

thesisHyperspectral remote sensing of wildfires combines principles of emitted radiation with advanced spectrometry to model wildfire area and temperature, as well as background land cover classification, at the subpixel level. Yet airborne hyperspectral sensors face problems of inconsistent spatial resolutions and have limited spatial and temporal coverage. A proposed hyperspectral/thermal infrared satellite, the Hyperspectral InfraRed Imager (HyspIRI), will provide hyperspectral data over a spectral range of 350- 2500 nm at a spatial resolution of 60.0 m. Hyperspectral radiance data have previously been shown to allow fire detection and retrieval of fire temperature, although these abilities have not been demonstrated at spatial resolutions coarser than 16.1 m. For this study, four hyperspectral images containing active fires were acquired by the Airborne Visible-Infrared Imaging Spectrometer (AVIRIS), with spatial resolutions ranging from 3.8 to 16.1 m. By resampling these AVIRIS images to coarser spatial resolutions and by modeling fire area, fire temperatures and background land cover, the impacts of spatial resolution on fire detection and temperature retrieval were simulated. Multiple endmember spectral mixture analysis (MESMA) methods were used to model fire temperature and background land cover types. Modeling at coarser spatial resolutions produced larger areas of low fire temperatures with lower modeling error than modeling at finer spatial resolutions. Modeling results comparing 60.0 m data with and without a Gaussian point spread function validated pixel aggregation resampling as a suitable approximation of coarser spatial resolution imagery. Coarser spatial resolution hyperspectral data, such as that collected by the future HyspIRI sensor, are likely to model more fire area and lower temperatures when compared against simultaneously acquired higher spatial resolution data. Increasing the saturation thresholds of SWIR channels could greatly improve the fire detection and temperature modeling capabilities of a HyspIRI-like sensor

HyspIRI High-Temperature Saturation Study

As part of the precursor activities for the HyspIRI mission, a small team was assembled to determine the optimum saturation level for the mid-infrared (4-?m) channel, which is dedicated to the measurement of hot targets. Examples of hot targets include wildland fires and active lava flows. This determination took into account both the temperature expected for the natural phenomena and the expected performance of the mid-infrared channel as well as its overlap with the other channels in the thermal infrared (7.5-12 ?m) designed to measure the temperature of lower temperature targets. Based on this work, the hot target saturation group recommends a saturation temperature of 1200 K for the mid-infrared channel. The saturation temperature of 1200 K represents a good compromise between the prevention of saturation and sensitivity to ambient temperature

Spaceborne monitoring of high temperature volcanic thermal features: studies using the ERS Along Track Scanning Radiometer

Satellite-based instruments have long been suggested as suitable for monitoring thermal phenomena occurring at the surface of active volcanoes. Past studies using data from high spatial resolution instruments indicated the effectiveness of this technique, but such data are expensive, time-consuming to obtain, and offer a poor temporal resolution. This thesis uses data from the European Remote Sensing satellites’ Along Track Scanning Radiometer (ATSR) to analyse infrared thermal emittance from a variety of volcanic thermal features at low spatial resolution (1 km2) but high temporal resolution (~ 3 days), with data from vegetation fires also being investigated. I calibrate the (previously uncalibrated) 1.6 μm channel of ATSR-1, and go onto show how nighttime data in this waveband can be used to characterise emittance from high temperature surfaces, even if these are significantly smaller than the ATSR pixel size. Procedures are developed to detect hotspots in ATSR data, filter out cloud contaminated observations, and quantitatively analyse the measurements of infrared thermal flux. ATSR time-series datasets are then used to study thermal emittance from active lava domes at Lascar Volcano (Chile) and Unzen Volcano (Japan), with volcanological interpretations being made from the observed variations in radiance. At both volcanoes the dominant source of nighttime shortwave infrared thermal flux is found to be high temperature surfaces heated by fumarolic degassing. During the monitoring period, decreases in shortwave infrared flux indicate an increased hazard at Lascar, such a change indicating blockage of the degassing system and an increased likelihood of a major pressure-driven explosive event. The reverse is found to be true at Unzen, where increases in shortwave infrared flux are found to be generally related to increases in magma supply (both being positively correlated with the flux rate of magmatic gas) and so to an increased frequency of hazardous pyroclastic flow from the growing dome. ATSR time-series studies of active lava flows at Fernandina Volcano (Galápagos Islands) and Mount Etna (Sicily) indicate that such data can also be used to document the thermal evolution of a developing lava flow field. Though necessitating assumptions regarding the flow-field thermal structure, ATSR-based estimates of the area of emplaced lava compare favourably with those obtained using higher spatial resolution imagery. For the 1991 - 1993 Etna flow, the estimates of flow surface temperature and area are used to investigate the importance of the various heat loss mechanisms. Results indicate that radiative losses dominate, but that basal conduction is also highly significant. The Moderate Resolution Imaging Spectrometer (MODIS) of NASA’s Earth Observing System (EOS) will soon provide a new source of multi-waveband, high temporal resolution data, available to the general volcanological and remote sensing community via the EOSDIS data network. I recommend that consideration be given to nighttime operation of the MODIS shortwave infrared channels, since studies using ATSR suggest that these data have considerable potential for the thermal monitoring of active volcanoes

Subpixel temperature estimation from single-band thermal infrared imagery

Target temperature estimation from thermal infrared (TIR) imagery is a complex task that becomes increasingly more difficult as the target size approaches the size of a projected pixel. At that point the assumption of pixel homogeneity is invalid as the radiance value recorded at the sensor is the result of energy contributions from the target material and any other background material that falls within a pixel boundary. More often than not, thermal infrared pixels are heterogeneous and therefore subpixel temperature extraction becomes an important capability. Typical subpixel estimation approaches make use of multispectral or hyperspectral sensors. These technologies are expensive and multispectral or hyperspectral thermal imagery might not be readily available for a target of interest. A methodology was developed to retrieve the temperature of an object that is smaller than a projected pixel of a single-band TIR image using physics-based modeling. Physics-based refers to the utilization of the Multi-Service Electro-optic Signature (MuSES) heat transfer model, the MODerate spectral resolution atmospheric TRANsmission (MODTRAN) atmospheric propagation algorithm, and the Digital Imaging and Remote Sensing Image Generation (DIRSIG) synthetic image generation model to reproduce a collected thermal image under a number of user-supplied conditions. A target space is created and searched to determine the temperature of the subpixel target of interest from a collected TIR image. The methodology was tested by applying it to single-band thermal imagery collected during an airborne campaign. The emissivity of the targets of interest ranged from 0.02 to 0.91 and the temperature extraction error for the high emissivity targets were similar to the temperature extraction errors found in published papers that employed multi-band techniques

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

NASA's surface biology and geology designated observable: A perspective on surface imaging algorithms

The 2017–2027 National Academies' Decadal Survey, Thriving on Our Changing Planet, recommended Surface Biology and Geology (SBG) as a “Designated Targeted Observable” (DO). The SBG DO is based on the need for capabilities to acquire global, high spatial resolution, visible to shortwave infrared (VSWIR; 380–2500 nm; ~30 m pixel resolution) hyperspectral (imaging spectroscopy) and multispectral midwave and thermal infrared (MWIR: 3–5 μm; TIR: 8–12 μm; ~60 m pixel resolution) measurements with sub-monthly temporal revisits over terrestrial, freshwater, and coastal marine habitats. To address the various mission design needs, an SBG Algorithms Working Group of multidisciplinary researchers has been formed to review and evaluate the algorithms applicable to the SBG DO across a wide range of Earth science disciplines, including terrestrial and aquatic ecology, atmospheric science, geology, and hydrology. Here, we summarize current state-of-the-practice VSWIR and TIR algorithms that use airborne or orbital spectral imaging observations to address the SBG DO priorities identified by the Decadal Survey: (i) terrestrial vegetation physiology, functional traits, and health; (ii) inland and coastal aquatic ecosystems physiology, functional traits, and health; (iii) snow and ice accumulation, melting, and albedo; (iv) active surface composition (eruptions, landslides, evolving landscapes, hazard risks); (v) effects of changing land use on surface energy, water, momentum, and carbon fluxes; and (vi) managing agriculture, natural habitats, water use/quality, and urban development. We review existing algorithms in the following categories: snow/ice, aquatic environments, geology, and terrestrial vegetation, and summarize the community-state-of-practice in each category. This effort synthesizes the findings of more than 130 scientists

Trace Gas Emissions from Biomass Burning inferred from Aerosol Optical Depth

We have observed strong correlations between simultaneous and co-located measurements of aerosol optical depth and column amounts of carbon monoxide, hydrogen cyanide, formaldehyde and ammonia in bushfire smoke plumes over SE Australia during the Austral summers of 2001/2002 and 2002/2003. We show how satellite-derived aerosol optical depth maps may be used in conjunction with these correlations to determine the total amounts of these gases present in a fire-affected region. This provides the basis of a method for estimating total emissions of trace gases from biomass burning episodes using visible radiances measured by satellite

Modeling wildland fire radiance in synthetic remote sensing scenes

This thesis develops a framework for implementing radiometric modeling and visualization of wildland fire. The ability to accurately model physical and op- tical properties of wildfire and burn area in an infrared remote sensing system will assist efforts in phenomenology studies, algorithm development, and sensor evaluation. Synthetic scenes are also needed for a Wildland Fire Dynamic Data Driven Applications Systems (DDDAS) for model feedback and update. A fast approach is presented to predict 3D flame geometry based on real time measured heat flux, fuel loading, and wind speed. 3D flame geometry could realize more realistic radiometry simulation. A Coupled Atmosphere-Fire Model is used to de- rive the parameters of the motion field and simulate fire dynamics and evolution. Broad band target (fire, smoke, and burn scar) spectra are synthesized based on ground measurements and MODTRAN runs. Combining the temporal and spa- tial distribution of fire parameters, along with the target spectra, a physics based model is used to generate radiance scenes depicting what the target might look like as seen by the airborne sensor. Radiance scene rendering of the 3D flame includes 2D hot ground and burn scar cooling, 3D flame direct radiation, and 3D indirect reflected radiation. Fire Radiative Energy (FRE) is a parameter defined from infrared remote sensing data that is applied to determine the radiative energy released during a wildland fire. FRE derived with the Bi-spectral method and the MIR radiance method are applied to verify the fire radiance scene synthesized in this research. The results for the synthetic scenes agree well with published values derived from wildland fire images

A review of approaches to estimate wildfire plume injection height within large-scale atmospheric chemical transport models

Landscape fires produce smoke containing a very wide variety of chemical species, both gases and aerosols. For larger, more intense fires that produce the greatest amounts of emissions per unit time, the smoke tends initially to be transported vertically or semi-vertically close by the source region, driven by the intense heat and convective energy released by the burning vegetation. The column of hot smoke rapidly entrains cooler ambient air, forming a rising plume within which the fire emissions are transported. The characteristics of this plume, and in particular the height to which it rises before releasing the majority of the smoke burden into the wider atmosphere, are important in terms of how the fire emissions are ultimately transported, since for example winds at different altitudes may be quite different. This difference in atmospheric transport then may also affect the longevity, chemical conversion, and fate of the plumes chemical constituents, with for example very high plume injection heights being associated with extreme long-range atmospheric transport. Here we review how such landscape-scale fire smoke plume injection heights are represented in larger-scale atmospheric transport models aiming to represent the impacts of wildfire emissions on component of the Earth system. In particular we detail (i) satellite Earth observation data sets capable of being used to remotely assess wildfire plume height distributions and (ii) the driving characteristics of the causal fires. We also discuss both the physical mechanisms and dynamics taking place in fire plumes and investigate the efficiency and limitations of currently available injection height parameterizations. Finally, we conclude by suggesting some future parameterization developments and ideas on Earth observation data selection that may be relevant to the instigation of enhanced methodologies aimed at injection height representation