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Radiometric correction is a prerequisite for generating high-quality scientific data, making it possible to discriminate between product artefacts and real changes in Earth processes as well as accurately produce land cover maps and detect changes. This work contributes to the automatic generation of surface reflectance products for Landsat satellite series. Surface reflectances are generated by a new approach developed from a previous simplified radiometric (atmospheric + topographic) correction model. The proposed model keeps the core of the old model (incidence angles and cast-shadows through a digital elevation model [DEM], Earth–Sun distance, etc.) and adds new characteristics to enhance and automatize ground reflectance retrieval. The new model includes the following new features: (1) A fitting model based on reference values from pseudoinvariant areas that have been automatically extracted from existing reflectance products (Terra MODIS MOD09GA) that were selected also automatically by applying quality criteria that include a geostatistical pattern model. This guarantees the consistency of the internal and external series, making it unnecessary to provide extra atmospheric data for the acquisition date and time, dark objects or dense vegetation. (2) A spatial model for atmospheric optical depth that uses detailed DEM and MODTRAN simulations. (3) It is designed so that large time-series of images can be processed automatically to produce consistent Landsat surface reflectance time-series. (4) The approach can handle most images, acquired now or in the past, regardless of the processing system, with the exception of those with extremely high cloud coverage. The new methodology has been successfully applied to a series of near 300 images of the same area including MSS, TM and ETM+ imagery as well as to different formats and processing systems (LPGS and NLAPS from the USGS; CEOS from ESA) for different degrees of cloud coverage (up to 60%) and SLC-off. Reflectance products have been validated with some example applications: time series robustness (for a pixel in a pseudoinvariant area, deviations are only 1.04% on average along the series), spectral signatures generation (visually coherent with the MODIS ones, but more similar between dates), and classification (up to 4 percent points better than those obtained with the original manual method or the CDR products). In conclusion, this new approach, that could also be applied to other sensors with similar band configurations, offers a fully automatic and reasonably good procedure for the new era of long time-series of spatially detailed global remote sensing data.

The Laser Communications Lab (LCL) of the Wright Laboratory Avionics Directorate is heavily involved in designing optical communications systems to meet our current and future military communications requirements. Due to the reluctance of many DOD agencies to adopt laser communications because of the potential eye-safety hazards associated with lasers, work is being accomplished in the LCL to develop an eye-safe laser communications system which will be powerful enough to provide communications over an extended range. This paper summarizes a system which has been designed, built and tested in the LCL using a prototype one watt continuous wave, two micron wavelength, laser diode. Also summarized is the work accomplished using the Moderate Resolution Atmospheric Transmittance and Radiance Model, MODTRAN to choose the wavelength for the design.

Remotely sensed data, recorded by means of the MIVIS hyperspectral scanner in the framework of the research activity of the CNR Institutes IIA-LARA and IMAA, have been calibrated to reflectance values and then quan- titatively compared with ground data. A new procedure for radiometric calibration has been defined by utilizing the MIVIS test-bench and applying a wider radiance range with respect to the one provided by the manufactur- ing company. New calibration curves have been determined and applied in the pre-processing chain. For valida- tion purpose ground spectra were measured during the campaign by means of a portable spectroradiometer. The atmospheric correction has been carried out by implementing an IDL procedure to manage MODTRAN4 input and output cards. MIVIS test data acquired over Passo Corese (Roma) have shown how the new calibration co- efficients significantly improve the radiometric accuracy. In particular, in the VIS spectral region the percentage error, with respect to a ground truth spectrum, is about half of that occurring if the standard calibration coeffi- cients are used.

The estimation of sea and land surface temperature using multi-angular algorithms with Advanced Along Track Scanning Radiometer (AATSR) data require an accurate knowledge of the angular variation of surface emissivity in the thermal infrared. A range of operative and accurate multiangle algorithms for estimating surface temperature has been developed using MODTRAN 3.5 simulations of the AATSR data at 11 and 12 /spl mu/m wavelengths, making use of the dual-angle viewing capability of the AATSR. To build the simulated database, emissivity values have been used. An experimental investigation has been made in order to determine the angular variation of the infrared emissivity as a well-known parameter to estimate ST in multiangular methods. The results show a general decrease of the emissivity with increasing viewing angles. Finally, the proposed algorithms have been applied to a series of satellite images acquired by the CSIRO in Australia, retrieving LST with a standard deviation less than 0.6 K if the satellite data are error free; in this case, the emissivity and temperature values necessary to retrieve the ST have been acquired from CSIRO in situ data.

[1] Measurement and modeling of downward longwave irradiance are a special challenge in arctic winter due to its low water vapor content and the extreme meteorological conditions. There are questions about the representativeness of the instrument calibration, the consistency and unfcertainty of measurements and models in these environments. The Second International Pyrgeometer and Absolute Sky-scanning Radiometer Comparison (IPASRC-II), which was conducted at Atmospheric Radiation Measurement (ARM) program's North Slope of Alaska (NSA) site in Barrow provided a unique opportunity to compare high accuracy downward longwave irradiance measurements and radiative transfer model computations during arctic winter. Participants from 11 international institutions deployed 14 pyrgeometers, which were field-calibrated against the Absolute Sky-scanning Radiometer (ASR). Continuous measurements over a 10-day period in early March 2001 with frequent clear-sky conditions yielded downward longwave irradiances between 120 and 240 W m−2. The small average difference between ASR irradiances, pyrgeometer measurements, MODTRAN and LBLRTM radiative transfer computations indicates that the absolute uncertainty of measured downward longwave irradiance under arctic winter conditions is within ±2 W m−2.

A flexible and inexpensive remote sensing tool for albedo estimation using conventional terrestrial photography and its validation on an Alpine glacier are described. The proposed technique involves georeferencing oblique photographs to a digital elevation model (DEM), defining a mapping function between the information contained on a given pixel of the image and the corresponding cell of the DEM. This is attained by performing a perspective projection of the DEM after a viewing transformation into the camera coordinate system. Once the image is georeferenced, the reflectance values recorded by the film or digital camera are corrected for topographic and atmospheric influences and for the effect of the photographic process (lens-film- developing-scanning). Atmospheric transmittance is evaluated using the MODTRAN radiative transfer model. Diffuse and direct irradiation are estimated using a parametric solar irradiation model. The solar-ground geometry, anisotropy of reflected radiation, the effect of surrounding topography and the portion of visible sky are evaluated using terrain algorithms applied to the DEM. The response of the camera-film-scanner system is evaluated using an empirical approach. The result is a geographically correct map of normalized reflectance values. By comparing these to a surface of known albedo, the spatial distribution of albedos is calculated. Comparisons to in situ measurements on the Mer de Glace glacier, French Alps, show good agreement. Sources of error are identified and ways of improvement addressed. The georeferencing algorithm, implemented into the Interactive Data Language (IDL) is available from the author and at the user contributed IDL library at www.rsinc.com.

We describe a model to evaluate the volcanic SO2 emission using images acquired by the airborne multispectral infrared and visible imaging spectrometer (MIVIS) in the thermal infrared spectral region. The estimating procedure consists of mapping of the SO2 columnar content and evaluation of the total SO2 flux emitted by the volcano. All the atmospheric radiative effects, including the SO2 plume emission/absorption, are computed by the MODTRAN 3.5 radiative transfer code. We apply the model to two MIVIS images acquired over Mount Etna, located on the east coast of Sicily, Italy, during the “Sicilia-94” remote sensing campaign on July 24 and 25, 1994. The June 25 image was acquired during the night; this is the first attempt to estimate the SO2 content in volcanic plume using nocturnal thermal infrared images. The total flux estimates range from 20.9 kg s−1 (1810 t d−1) to 82.2 kg s−1 (7100 t d−1) depending on the plume geometry used in the procedure. These results, except one case (82.2 kg s−1), are in agreement with the estimates derived from correlation spectrometer (COSPEC) measurements collected during the same period. We also evaluate the dependencies of the results on several parameters such as plume geometry, surface emissivity, water vapor content, and wind speed.

This multidisciplinary paper reports on a research application-led study for predicting atmospheric attenuation, and tries to bridge the knowledge gap between applied engineering and atmospheric sciences. As a useful comparative baseline, this paper focuses specifically on atmospheric attenuation under pristine conditions, over the extended terahertz spectrum. Three well-known simulation software packages (`HITRAN on the Web', MODTRAN ® 4, and LBLRTM) are compared and contrasted. Techniques used for modeling atmospheric attenuation have been applied to investigate the resilience of (ultra-)wide fractional bandwidth applications to the effects of molecular absorption. Two extreme modeling scenarios are investigated: horizontal path links at sea level and Earth-space path links. It is shown by example that a basic software package (`HITRAN on the Web') can give good predictions with the former, whereas sophisticated simulation software (LBLRTM) is required for the latter. Finally, with molecular emission included, carrier-to-noise ratio fade margins can be calculated for the effects of line broadening due to changes in macroscopic atmospheric conditions with sub-1-THz ultra-narrow fractional bandwidth applications. Outdoors can be far from pristine, with additional atmospheric contributions only briefly introduced here; further discussion is beyond the scope of this paper, but relevant references have been cited.

A mid-infrared Normalized Difference Water Index (NDWI) is proposed for the estimation of vegetation water content (VWC). As part of a large-scale hydrology experiment (SMEX02) an extensive VWC data set was collected for corn and soybeans over a portion of the growth cycle. Landsat Thematic Mapper (TM) data for several dates were used to develop two indices, the well-known NDVI and the NDWI, for each ground sampling site. Since multiple dates and satellites were used, atmospheric correction and cross calibration was performed on each TM image. Two atmospheric correction models, 6S and MODTRAN, and an empirical method, produced comparable results. Comparisons of VWC and the indices showed that the NDVI saturated at a lower VWC than did the NDWI. This indicates that the NDWI is a better index for use in estimating the VWC over a full crop growing cycle. Relationships were developed between the VWC and NDWI for corn and soybeans. The error with this approach was approximately 0.5 kg/m/sup 2/ for corn and 0.2 kg/m/sup 2/ for soybeans.

Physically-based radiative transfer models (RTMs) help understand the interactions of radiation with vegetation and atmosphere. However, advanced RTMs can be computationally burdensome, which makes them impractical in many real applications, especially when many state conditions and model couplings need to be studied. To overcome this problem, it is proposed to substitute RTMs through surrogate meta-models also named emulators. Emulators approximate the functioning of RTMs through statistical learning regression methods, and can open many new applications because of their computational efficiency and outstanding accuracy. Emulators allow fast global sensitivity analysis (GSA) studies on advanced, computationally expensive RTMs. As a proof-of-concept, three machine learning regression algorithms (MLRAs) were tested to function as emulators for the leaf RTM PROSPECT-4, the canopy RTM PROSAIL, and the computationally expensive atmospheric RTM MODTRAN5. Selected MLRAs were: kernel ridge regression (KRR), neural networks (NN) and Gaussian processes regression (GPR). For each RTM, 500 simulations were generated for training and validation. The majority of MLRAs were excellently validated to function as emulators with relative errors well below 0.2%. The emulators were then put into a GSA scheme and compared against GSA results as generated by original PROSPECT-4 and PROSAIL runs. NN and GPR emulators delivered identical GSA results, while processing speed compared to the original RTMs doubled for PROSPECT-4 and tripled for PROSAIL. Having the emulator-GSA concept successfully tested, for six MODTRAN5 atmospheric transfer functions (outputs), i.e., direct and diffuse at-surface solar irradiance ( E d i f , E d i r ), direct and diffuse upward transmittance ( T d i r , T d i f ), spherical albedo (S) and path radiance ( L 0 ), the most accurate MLRA’s were subsequently applied as emulator into the GSA scheme. The sensitivity analysis along the 400–2500 nm spectral range took no more than a few minutes on a contemporary computer—in comparison, the same analysis in the original MODTRAN5 would have taken over a month. Key atmospheric drivers were identified, which are on the one hand aerosol optical properties, i.e., aerosol optical thickness (AOT), Angstrom coefficient (AMS) and scattering asymmetry variable (G), mostly driving diffuse atmospheric components, E d i f and T d i f ; and those affected by atmospheric scattering, L 0 and S. On the other hand, as expected, AOT, AMS and columnar water vapor (CWV) in the absorption regions mostly drive E d i r and T d i r atmospheric functions. The presented emulation schemes showed very promising results in replacing costly RTMs, and we think they can contribute to the adoption of machine learning techniques in remote sensing and environmental applications.