Multispectral Thermal Imager Data Research Articles

Extending surface temperature and emissivity retrieval to the mid-infrared (3–5 μm) using the Multispectral Thermal Imager (MTI)

Surface-temperature ( T) and emissivity ( ε) estimation from remotely sensed mid-infrared (MIR: 3–5 μm) data requires modifications to existing long-wave infrared (LWIR: 8–12 μm) T/ ε separation algorithms because of the significantly different characteristics of Planck's function between the MIR and LWIR wavelength regions and the strong effects of reflected solar irradiance in the MIR. A modified version of the normalized emissivity method (NEM), utilizing independently scaled maximum emissivities in each channel, was applied to thermal data acquired by the Multispectral Thermal Imager (MTI) with two MIR channels, J (3.81 μm) and K (4.97 μm), and three LWIR channels, L (8.26 μm), M (8.65 μm), and N (10.51 μm). Atmosphere-free simulations of T and ε retrieval over a wide variety of terrestrial surfaces yielded T values within ± 0.75 K of ‘true T’ in the range of 270–330 K and ε values within ± 0.011 of true ε in channels L, M and N, and ± 0.019 and ± 0.023 in channels K and J, respectively. The algorithm was tested successfully using MTI data over the Mauna Loa caldera in Hawaii. Unconstrained effects of shading and unresolved shadows in channel J day time data, and the strong atmospheric effects in channel K limit the application of the algorithm, in its present form, to night-time data.

Evaluation of Environmental Data for Identification ofAnopheles(Diptera: Culicidae) Aquatic Larval Habitats in Kisumu and Malindi, Kenya

This research evaluates the extent to which use of environmental data acquired from field and satellite surveys enhances predictions of urban mosquito counts. Mosquito larval habitats were sampled, and multispectral thermal imager (MTI) satellite data in the visible spectrum at 5-m resolution were acquired for Kisumu and Malindi, Kenya, during February and March 2001. All entomological parameters were collected from January to May 2001, June to August 2002, and June to August 2003. In a Poisson model specification, for Anopheles funestus Giles, shade was the best predictor, whereas substrate was the best predictor for Anopheles gambiae, and vegetation for Anopheles arabensis Patton. The top predictors found with a logistic regression model specification were habitat size for An. gambiae Giles, pollution for An. arabensis, and shade for An. funestus. All other coefficients for canopy, debris, habitat nature, permanency, emergent plants, algae, pollution, turbidity, organic materials, all MTI waveband frequencies, distance to the nearest house, distance to the nearest domestic animal, and all land use land cover changes were nonsignificant. MTI data at 5-m spatial resolution do not have an additional predictive value for mosquito counts when adjusted for field-based ecological data.

Multispectral thermal imager: mission and applications overview

The Multispectral Thermal Imager (MTI) satellite is a research and development project sponsored by the U.S. Department of Energy. The primary mission is to demonstrate advanced multispectral and thermal imaging from a satellite, including new technologies, data processing, and analysis techniques and validation by reference to ground truth. The MTI builds on the efforts of a number of earlier efforts, including Landsat, National Aeronautics and Space Administration remote sensing missions, and others, but the MTI incorporates a unique combination of attributes designed to advance the state of the art. The MTI satellite was launched on March 12, 2000 into a 580 km/spl times/610 km, sun-synchronous orbit with nominal 1 a.m. and 1 p.m. equatorial crossing times. The Air Force Space Test Program provided the Orbital Sciences Taurus launch. The satellite-based sensors obtain radiance data that are subsequently processed into measurements of atmospheric and surface properties such as column water vapor, atmospheric aerosol loading, surface temperatures, material composition, and others. This paper provides an overview of the MTI research objectives, design, operations, data products, and data processing and analysis. Several other papers provide greater detail on selected topics.

In-flight validation of mid- and thermal infrared data from the Multispectral Thermal Imager (MTI) using an automated high-altitude validation site at Lake Tahoe CA/NV, USA

The Multispectral Thermal Imager (MTI) is a 15-band satellite-based imaging system. Two of the bands (J, K) are located in the mid-infrared (3-5 /spl mu/m) wavelength region: J, 3.5-4.1 /spl mu/m and K, 4.9-5.1 /spl mu/m, and three of the bands (L, M, N) are located in the thermal infrared (8-12 /spl mu/m) wavelength region: L, 8.0-8.4 /spl mu/m; M, 8.4-8.8 /spl mu/m; and N, 10.2-10.7 /spl mu/m. The absolute radiometric accuracy of the MTI data acquired in bands J-N was assessed over a period of approximately three years using data from the Lake Tahoe, CA/NV, automated validation site. Assessment involved using a radiative transfer model to propagate surface skin temperature measurements made at the time of the MTI overpass to predict the vicarious at-sensor radiance. The vicarious at-sensor radiance was convolved with the MTI system response functions to obtain the vicarious at-sensor MTI radiance in bands J-N. The vicarious radiances were then compared with the instrument measured radiances. In order to avoid any reflected solar contribution in the mid-infrared bands, only nighttime scenes were used in the analysis of bands J and K. Twelve cloud-free scenes were used in the analysis of the data from the mid-infrared bands (J, K), and 23 cloud-free scenes were used in the analysis of the thermal infrared bands (L, M, N). The scenes had skin temperatures ranging between 4.4 and 18.6/spl deg/C. The skin temperature was found to be, on average, 0.18/spl plusmn/0.36 degC cooler than the bulk temperature during the day and 0.65/spl plusmn/0.31 degC cooler than the bulk temperature at night. The smaller skin effect during the day was attributed to solar heating. The mean and standard deviation of the percent differences between the vicarious (predicted) at-sensor radiance convolved to the MTI bandpasses and the MTI measured radiances were -1.38/spl plusmn/2.32, -2.46/spl plusmn/1.96, -0.04/spl plusmn/0.78, -1.97/spl plusmn/0.62, -1.59/spl plusmn/0.55 for bands J-N, respectively. The results indicate that, with the exception of band L, the instrument measured radiances are warmer than expected.

Linking field-based ecological data with remotely sensed data using a geographic information system in two malaria endemic urban areas of Kenya

BackgroundRemote sensing technology provides detailed spectral and thermal images of the earth's surface from which surrogate ecological indicators of complex processes can be measured.MethodsRemote sensing data were overlaid onto georeferenced entomological and human ecological data randomly sampled during April and May 2001 in the cities of Kisumu (population ≈ 320,000) and Malindi (population ≈ 81,000), Kenya. Grid cells of 270 meters × 270 meters were used to generate spatial sampling units for each city for the collection of entomological and human ecological field-based data. Multispectral Thermal Imager (MTI) satellite data in the visible spectrum at five meter resolution were acquired for Kisumu and Malindi during February and March 2001, respectively. The MTI data were fit and aggregated to the 270 meter × 270 meter grid cells used in field-based sampling using a geographic information system. The normalized difference vegetation index (NDVI) was calculated and scaled from MTI data for selected grid cells. Regression analysis was used to assess associations between NDVI values and entomological and human ecological variables at the grid cell level.ResultsMultivariate linear regression showed that as household density increased, mean grid cell NDVI decreased (global F-test = 9.81, df 3,72, P-value = <0.01; adjusted R2 = 0.26). Given household density, the number of potential anopheline larval habitats per grid cell also increased with increasing values of mean grid cell NDVI (global F-test = 14.29, df 3,36, P-value = <0.01; adjusted R2 = 0.51).ConclusionsNDVI values obtained from MTI data were successfully overlaid onto georeferenced entomological and human ecological data spatially sampled at a scale of 270 meters × 270 meters. Results demonstrate that NDVI at such a scale was sufficient to describe variations in entomological and human ecological parameters across both cities.