Kenta Ogawa

Mapping Surface Broadband Emissivity of the Sahara Desert Using ASTER and MODIS Data

Abstract Surface broadband emissivity in the thermal infrared region is an important parameter for the studies of the surface energy balance. This paper focuses on estimating a broadband window emissivity from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and Moderate Resolution Imaging Spectrometer (MODIS) data. Both sensors are on board the NASA Earth Observing System (EOS) Terra satellite, which was launched in 1999. First, several definitions of the broadband emissivity were investigated, and it was found that the emissivity integrated between 8 and 13.5 μm is the best for estimating the net longwave radiation under clear-sky conditions. Then, a method to estimate broadband emissivity at the continental scale was developed. The method uses two regressions. The first regression is to relate the broadband emissivity to the emissivities for the five ASTER channels using measured emissivities in the laboratory from spectral libraries. The second regression relates the broadban...

Estimating Broadband Emissivity of Arid Regions and Its Seasonal Variations Using Thermal Infrared Remote Sensing

Surface emissivity in the thermal infrared region is an important parameter for determining the surface radiation budget in climate, weather, and hydrological models. This paper focuses on estimating the spatial and temporal variations of the surface emissivities using thermal infrared remotely sensed data from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard NASAs Terra satellite. We developed a regression approach to use the ASTER and MODIS data for estimating the broadband emissivity (BBE; 8-13.5 mum). The regressions were calibrated using a library of spectral emissivity data for terrestrial materials. We applied these regressions to ASTER and MODIS data to obtain emissivity maps for several arid regions of the Earth. In the 8-9-mum band for sparsely or nonvegetated desert areas, emissivity values between 0.66 and 0.96 have been observed, which are due to the low emissivity of quartz-rich sands at these wavelengths. As a result, the range of BBE is between 0.86 and 0.96. The seasonal variation over a two-year period and the dependence on land cover/soil type were also investigated.

Modeling and Inversion in Thermal Infrared Remote Sensing over Vegetated Land Surfaces

Thermal Infra Red (TIR) Remote sensing allow spatializing various land surface temperatures: ensemble brightness, radiometric and aerodynamic temperatures, soil and vegetation temperatures optionally sunlit and shaded, and canopy temperature profile. These are of interest for monitoring vegetated land surface processes: heat and mass exchanges, soil respiration and vegetation physiological activity. TIR remote sensors collect information according to spectral, directional, temporal and spatial dimensions. Inferring temperatures from measurements relies on developing and inverting modeling tools. Simple radiative transfer equations directly link measurements and variables of interest, and can be analytically inverted. Simulation models allow linking radiative regime to measurements. They require indirect inversions by minimizing differences between simulations and observations, or by calibrating simple equations and inductive learning methods. In both cases, inversion consists of solving an ill posed problem, with several parameters to be constrained from few information. Brightness and radiometric temperatures have been inferred by inverting simulation models and simple radiative transfer equations, designed for atmosphere and land surfaces. Obtained accuracies suggest refining the use of spectral and temporal information, rather than innovative approaches. Forthcoming challenge is recovering more elaborated temperatures. Soil and vegetation components can replace aerodynamic temperature, which retrieval seems almost impossible. They can be inferred using multiangular measurements, via simple radiative transfer equations previously parameterized from simulation models. Retrieving sunlit and shaded components or canopy temperature profile requires inverting simulation models. Then, additional difficulties are the influence of thermal regime, and the limitations of spaceborne observations which have to be along track due to the temperature fluctuations. Finally, forefront investigations focus on adequately using TIR information with various spatial resolutions and temporal samplings, to monitor the considered processes with adequate spatial and temporal scales. 10.1 Introduction Using TIR remote sensing for environmental issues have been investigated the last three decades. This is motivated by the potential of the spatialized information for documenting the considered processes within and between the Earth system components: cryosphere [1–2], atmosphere [3–6], oceans [7–9], and land surfaces [10]. For the latter, TIR remote sensing is used to monitor forested areas [11–14], urban areas [15–17], and vegetated areas. We focus here on vegetated areas, natural and cultivated. The monitored processes are related to climatology, meteorology, hydrology and agronomy: (1) radiation, heat and water transfers at the soil–vegetation–atmosphere interface [18–24]; (2) interactions between land surface and atmospheric boundary layer [25]; (3) vegetation physiological processes such as transpiration and water consumption, photosynthetic activity and CO2 uptake, vegetation growth and

A comparison of thermal infrared emissivity spectra measured in situ, in the laboratory, and derived from thermal infrared multispectral scanner (TIMS) data in Cuprite, Nevada, U.S.A.

In order to obtain ground truth data for multispectral thermal infrared sensors such as TIMS and ASTER, in situ spectral emissivity measurements were made during field surveys. These spectral emissivity measurements and laboratory spectral reflectance measurements of field samples were compared to emissivity spectra extracted from TIMS data at the surveyed points. The results indicate that emissivity spectra derived from the TIMS data agree well in shape with the spectra measured in situ or in the laboratory.

Validation of Emissivity Estimates from ASTER and MODIS Data

Two distinctly different approaches are used to extract emissivity information from ASTER and MODIS data. ASTER uses an intuitive empirical relationship between the range of emissivities in the 5 ASTER bands and their minimum value. With its greater swath MODIS is able to uses the day / night pair of observations to obtain the emissivities. The combination of the two approaches should provide robust estimation of the land surface emissivity.

Application of Interactive Deformation to Assembled Mesh Models for CAE Analysis

Mesh deformation, which is sometimes referred to as mesh morphing in CAE, is useful for providing various shapes of meshes for CAE tools. This paper proposes a new framework for interactively and consistently deforming assembly models of sheet structure for mechanical parts. This framework is based on a surface-based deformation, which calculates the vertex positions so that the mean curvature normal is preserved at each vertex in a least squares sense. While existing surface-based deformation techniques cannot simultaneously deform assembly mesh models, our method allows us to smoothly deform disconnected meshes by propagating the rotations and translations through disconnected vertices. In addition, we extend our deformation technique to handle non-manifold conditions, because shell structure models may include non-manifold edges. We have applied our method to assembly mesh models of automobile parts. Our experimental results have shown that our method requires almost the same pre-processing time as existing methods and can deform practical assembly models interactively.Copyright

Validation of emissivity estimates from ASTER data

The multispectral thermal infrared data obtained from the Advanced Spaceborne Thermal Emission and Reflection (ASTER) radiometer have been shown to be of good quality. ASTER is on NASAs Terra satellite. It has 5 bands in the 8 to 12 micrometer waveband with 90 m spatial resolution, when the data are combined with the Temperature Emissivity Separation (TES) algorithm the surface emissivity over this wavelength region can be determined. This paper will present some quantitative emissivity results obtained over test sites in southern New Mexico, USA; the Jornada Experimental Range and the White Sands National Monument which are compared with ground measurements. The Jornada site is typical of a desert grassland where the main vegetation components are grass and shrubs with a large fraction of exposed soil. While the White Sands site is mainly dunes of gypsum sand which provides relatively good homogenous emissivity target. More than a dozen ASTER scenes over these New Mexico test sites have been acquired since the launch of Terra in December 1999. There were simultaneous field campaigns in May of 2000, 2001 and 2002 and September/October 2001 and 2002. Also, simultaneous MASTER (MODIS-ASTER airborne simulator) coverage was obtained for several of the dates. In spite of the 90 m resolution, the results appear to be in good quantitative agreement with laboratory measurements of the emissivity for the quartz rich soils of the Jornada with values < 0.85 for the 8 - 9 micrometer channels. For the longest wavelength channels little spatial variation of the emissivity was observed with values of 0.96 +/- 0.005 over large areas. Emissivity values derived from several ASTER scenes for the gypsum at White Sands were in good agreement with field measurements and values calculated from the lab spectra for gypsum and with each other. Gypsum has a strong emissivity minimum centered on the ASTER 8.63 micrometer band, and the satellite results for this band agree within 0.01 of the value calculated from the laboratory spectra.

Effective observation planning and its simulation of a Japanese spaceborne sensor: Hyperspectral imager suite (HISUI)

Hyperspectral Imager Suite (HISUI) is a Japanese future spaceborne hyperspectral instrument being developed by Ministry of Economy, Trade, and Industry (METI) and will be launched in 2017 or later. In HISUI project, observation strategy is important especially for hyperspectral sensor, and relationship between the limitations of sensor operation and the planned observation scenarios have to be studied. Using observation coverage simulation program and we estimate progress of observation coverage of image with days after launch. We found that HISUI can make 4 times repeated observations for protected area (20 million km2 in the world). And about 70 % of land surface can be observed over 5 years. We also found that the developed rules to avoid cloudy are will improve the area coverage up to 2.4 %.

Observation planning and its coverage simulation of a Japanese spaceborne sensor: Hyperspectral Imager Suite (HISUI)

As mentioned above, the simulation program is useful to investigate observation-planning strategy and rules for improving efficiency of observations.

Operation planning for Japanese future hyperspectral and multispectral senor: HISUI and usage of cloud climate data

Hyperspectral Imager Suite (HISUI) is a Japanese future spaceborne hyperspectral instrument being developed by Ministry of Economy, Trade, and Industry (METI) and will be launched in 2015 or later. HISUIs operation strategic study is described in this paper. In HISUI project, Operation Mission Planning (OMP) team has responsibility to make long term and short term strategy of the observation and sensor operation plan. The OMP is important for HISUI to archive both global mapping and monitoring of specific sites. Major factors of the HISUI operation limitations are downlink rate, observation time (15 minutes per orbit) and the swath of the sensor (30 km). The OMP plans to use detailed climate data generated from MODIS data for observation simulation. The workflow to deal cloud climate data is described in this paper.