J. Moncet - Academia.edu (original) (raw)
Papers by J. Moncet
IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium, 2008
Journal of Geophysical Research: Atmospheres, 2015
ABSTRACT Modeled land surface microwave emissivity compared to satellite‐based estimateOver snow‐... more ABSTRACT Modeled land surface microwave emissivity compared to satellite‐based estimateOver snow‐free vegetated areas, the emissivities agree reasonably wellFurther evaluation is provided by direct comparison with satellite observationsModeled land surface microwave emissivity compared to satellite‐based estimateOver snow‐free vegetated areas, the emissivities agree reasonably wellFurther evaluation is provided by direct comparison with satellite observations
2006 IEEE International Symposium on Geoscience and Remote Sensing, 2006
ABSTRACT Accurate knowledge of local surface emissivity is required for lower troposphere microwa... more ABSTRACT Accurate knowledge of local surface emissivity is required for lower troposphere microwave remote sensing over land and for land surface parameter retrievals. Ideally, for a stand-alone microwave system (i.e., without an external source of surface temperature), a priori emissivity accuracies of 0.01 or less are needed to minimize the impact of cloud liquid water on temperature and water vapor retrievals and to improve surface temperature retrievals to 2 K or better. We are developing a system for land surface microwave emissivity retrieval and using it to derive emissivities in the AMSR-E channels over a full year. The system now incorporates both AMSR-E and SSM/I brightness temperatures and MODIS-derived land surface temperature (LST) products. We have examined the temporal variability of retrieved local surface emissivities and describe approaches developed to identify and minimize sources of error in the retrieval. The emissivity retrieval system is a precursor for a dynamic emissivity database to be fully implemented for NPOESS CMIS with coincident VIIRS LST observations available up to six times per day.
IEEE Transactions on Communications, 1986
ABSTRACT Coding schemes suitable for progressive transmission of still pictures in NTSC composite... more ABSTRACT Coding schemes suitable for progressive transmission of still pictures in NTSC composite format are studied. Transform coding methods based on the discrete cosine transform (DCT) and the WalshHadamard transform (WHT) are used. The transform coefficients are segmented into groups having similar properties. Variable blocklength to variable length codes are used to encode the quantized coefficients for each of the groups. Progressive transmission is achieved by sending the coefficients belonging to particular groups in successive passes over the image. Results are presented for coding the NTSC signal sampled at four times the color subcarrier frequency with an orthogonal structure, and at twice the subcarrier frequency with a hexagonal structure.
IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium, 2008
Atmospheric and Environmental Remote Sensing Data Processing and Utilization: an End-to-End System Perspective, 2004
Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery X, 2004
This report has described the results of a study undertaken at AER to identify and implement a st... more This report has described the results of a study undertaken at AER to identify and implement a state of the art nonlinear retrieval approach to characterize line of sight variability of atmospheric thermal and constituent environments. This path characterization capability was designed to interface with the existing Geophysics Laboratory (GL) line-by-line radiance/transmittance code, FASCODE. Accomplishments of the study include: (a) a review of the relevant literature concerning potential path characterization retrieval algorithms, selection of a physical least squares (PLS) nonlinear retrieval approach for implementation based on criteria including flexibility within the context of FASCODE and a certain degree of robustness in application; (b) development of a stand alone, preprocessing screening procedure to identify potential channels for path characterization based on user requirements; (c) formulation and implementation of the path characterization retrieval algorithm includin...
The large volume of existing and planned infrared observations of Mars have prompted the developm... more The large volume of existing and planned infrared observations of Mars have prompted the development of a new martian radiative transfer model that could be used in the retrievals of atmospheric and surface properties. The model is based on the Optimal Spectral Sampling (OSS) method [1]. The method is a fast and accurate monochromatic technique applicable to a wide range of remote sensing platforms (from microwave to UV) and was originally developed for the real-time processing of infrared and microwave data acquired by instruments aboard the satellites forming part of the next-generation global weather satellite system NPOESS (National Polarorbiting Operational Satellite System) [2]. As part of our on-going research related to the radiative properties of the martian polar caps, we have begun the development of a martian OSS model with the goal of using it to perform self-consistent atmospheric corrections necessary to retrieve caps emissivity from the Thermal Emission Spectrometer ...
Abstract,Introduction The ,U.S. Department ,of Energy ,(DOE) Atmospheric,FASCODE for the Environm... more Abstract,Introduction The ,U.S. Department ,of Energy ,(DOE) Atmospheric,FASCODE for the Environment (FASE) was developed by
We have developed the Integrated Algorithm Testbed (IATB) to address the development and validati... more We have developed the Integrated Algorithm Testbed (IATB) to address the development and validation needs of current and future remote sensing platforms. The core of the IATB is the Optimal Spectral Sampling (OSS) radiative transfer model. OSS is a robust approach to radiative transfer modeling which addresses the need for algorithm speed, accuracy, and flexibility. The OSS technique allows for the rapid calculation of radiance for any class of multispectral, hyperspectral, or ultraspectral sensors at any spectral resolution operating in any region from microwave through UV wavelengths by selecting and appropriately weighting the monochromatic points that contribute over the sensor bandwidth. This allows for the calculation to be performed at a small number of spectral points while retaining the advantages of a monochromatic calculation such as exact treatment of multiple scattering and/or polarization. The OSS method is well suited for remote sensing applications which require extr...
Journal of Geophysical Research: Atmospheres, 2015
ABSTRACT Monthly-average estimates of latent heat flux have been derived from a combination of sa... more ABSTRACT Monthly-average estimates of latent heat flux have been derived from a combination of satellite-derived microwave emissivities, day-night differences in land surface temperature (from microwave AMSR-E), downward solar and infrared fluxes from ISCCP cloud analysis, and MODIS visible and near-infrared surface reflectances. The estimates, produced with a neural network, were compared with data from the Noah land surface model, as produced for GLDAS-2, and with two alternative estimates derived from different datasets and methods. Areas with extensive, persistent, substantial discrepancies between the satellite and land surface model fluxes have been analyzed with the aid of data from flux towers. The sources of discrepancies were found to include problems with the model surface roughness length and turbulent exchange coefficients for mid-latitude cropland areas in summer, inaccuracies in the precipitation data that were used as forcing for the land surface model, and model underestimation of transpiration in some forests during dry periods. At the tower sites analyzed, agreement with tower data was generally closer for our satellite-derived fluxes than for the land surface model fluxes, in terms of monthly averages.
Optical Remote Sensing, 2003
Optics InfoBase is the Optical Society's online library for flagship journals, partnered... more Optics InfoBase is the Optical Society's online library for flagship journals, partnered and copublished journals, and recent proceedings from OSA conferences.
Passive Infrared Remote Sensing of Clouds and the Atmosphere III, 1995
ABSTRACT The Support of Environmental Requirements for Cloud Analysis and Archives (SERCAA) progr... more ABSTRACT The Support of Environmental Requirements for Cloud Analysis and Archives (SERCAA) program is a two phase basic research program to develop techniques for analysis of multi-source multi-spectral satellite sensor data for the purpose of estimating cloud fractional amount, location, height, and type. In the first phase, cloud analysis algorithms were developed for each imaging sensor. A major innovation was an analysis integration approach to combine the separate algorithm results from the temporally, spatially, and spectrally inconsistent sources into a single logically consistent analysis. In the second phase, work includes algorithms for retrieval and estimation of the cloud physical and optical properties such as phase, drop size distribution, optical thickness, and emissivity. Also under investigation are cloud environment parameters including vertical profiles of temperature and moisture available from sounding sensors.
IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium, 2008
Journal of Geophysical Research: Atmospheres, 2015
ABSTRACT Modeled land surface microwave emissivity compared to satellite‐based estimateOver snow‐... more ABSTRACT Modeled land surface microwave emissivity compared to satellite‐based estimateOver snow‐free vegetated areas, the emissivities agree reasonably wellFurther evaluation is provided by direct comparison with satellite observationsModeled land surface microwave emissivity compared to satellite‐based estimateOver snow‐free vegetated areas, the emissivities agree reasonably wellFurther evaluation is provided by direct comparison with satellite observations
2006 IEEE International Symposium on Geoscience and Remote Sensing, 2006
ABSTRACT Accurate knowledge of local surface emissivity is required for lower troposphere microwa... more ABSTRACT Accurate knowledge of local surface emissivity is required for lower troposphere microwave remote sensing over land and for land surface parameter retrievals. Ideally, for a stand-alone microwave system (i.e., without an external source of surface temperature), a priori emissivity accuracies of 0.01 or less are needed to minimize the impact of cloud liquid water on temperature and water vapor retrievals and to improve surface temperature retrievals to 2 K or better. We are developing a system for land surface microwave emissivity retrieval and using it to derive emissivities in the AMSR-E channels over a full year. The system now incorporates both AMSR-E and SSM/I brightness temperatures and MODIS-derived land surface temperature (LST) products. We have examined the temporal variability of retrieved local surface emissivities and describe approaches developed to identify and minimize sources of error in the retrieval. The emissivity retrieval system is a precursor for a dynamic emissivity database to be fully implemented for NPOESS CMIS with coincident VIIRS LST observations available up to six times per day.
IEEE Transactions on Communications, 1986
ABSTRACT Coding schemes suitable for progressive transmission of still pictures in NTSC composite... more ABSTRACT Coding schemes suitable for progressive transmission of still pictures in NTSC composite format are studied. Transform coding methods based on the discrete cosine transform (DCT) and the WalshHadamard transform (WHT) are used. The transform coefficients are segmented into groups having similar properties. Variable blocklength to variable length codes are used to encode the quantized coefficients for each of the groups. Progressive transmission is achieved by sending the coefficients belonging to particular groups in successive passes over the image. Results are presented for coding the NTSC signal sampled at four times the color subcarrier frequency with an orthogonal structure, and at twice the subcarrier frequency with a hexagonal structure.
IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium, 2008
Atmospheric and Environmental Remote Sensing Data Processing and Utilization: an End-to-End System Perspective, 2004
Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery X, 2004
This report has described the results of a study undertaken at AER to identify and implement a st... more This report has described the results of a study undertaken at AER to identify and implement a state of the art nonlinear retrieval approach to characterize line of sight variability of atmospheric thermal and constituent environments. This path characterization capability was designed to interface with the existing Geophysics Laboratory (GL) line-by-line radiance/transmittance code, FASCODE. Accomplishments of the study include: (a) a review of the relevant literature concerning potential path characterization retrieval algorithms, selection of a physical least squares (PLS) nonlinear retrieval approach for implementation based on criteria including flexibility within the context of FASCODE and a certain degree of robustness in application; (b) development of a stand alone, preprocessing screening procedure to identify potential channels for path characterization based on user requirements; (c) formulation and implementation of the path characterization retrieval algorithm includin...
The large volume of existing and planned infrared observations of Mars have prompted the developm... more The large volume of existing and planned infrared observations of Mars have prompted the development of a new martian radiative transfer model that could be used in the retrievals of atmospheric and surface properties. The model is based on the Optimal Spectral Sampling (OSS) method [1]. The method is a fast and accurate monochromatic technique applicable to a wide range of remote sensing platforms (from microwave to UV) and was originally developed for the real-time processing of infrared and microwave data acquired by instruments aboard the satellites forming part of the next-generation global weather satellite system NPOESS (National Polarorbiting Operational Satellite System) [2]. As part of our on-going research related to the radiative properties of the martian polar caps, we have begun the development of a martian OSS model with the goal of using it to perform self-consistent atmospheric corrections necessary to retrieve caps emissivity from the Thermal Emission Spectrometer ...
Abstract,Introduction The ,U.S. Department ,of Energy ,(DOE) Atmospheric,FASCODE for the Environm... more Abstract,Introduction The ,U.S. Department ,of Energy ,(DOE) Atmospheric,FASCODE for the Environment (FASE) was developed by
We have developed the Integrated Algorithm Testbed (IATB) to address the development and validati... more We have developed the Integrated Algorithm Testbed (IATB) to address the development and validation needs of current and future remote sensing platforms. The core of the IATB is the Optimal Spectral Sampling (OSS) radiative transfer model. OSS is a robust approach to radiative transfer modeling which addresses the need for algorithm speed, accuracy, and flexibility. The OSS technique allows for the rapid calculation of radiance for any class of multispectral, hyperspectral, or ultraspectral sensors at any spectral resolution operating in any region from microwave through UV wavelengths by selecting and appropriately weighting the monochromatic points that contribute over the sensor bandwidth. This allows for the calculation to be performed at a small number of spectral points while retaining the advantages of a monochromatic calculation such as exact treatment of multiple scattering and/or polarization. The OSS method is well suited for remote sensing applications which require extr...
Journal of Geophysical Research: Atmospheres, 2015
ABSTRACT Monthly-average estimates of latent heat flux have been derived from a combination of sa... more ABSTRACT Monthly-average estimates of latent heat flux have been derived from a combination of satellite-derived microwave emissivities, day-night differences in land surface temperature (from microwave AMSR-E), downward solar and infrared fluxes from ISCCP cloud analysis, and MODIS visible and near-infrared surface reflectances. The estimates, produced with a neural network, were compared with data from the Noah land surface model, as produced for GLDAS-2, and with two alternative estimates derived from different datasets and methods. Areas with extensive, persistent, substantial discrepancies between the satellite and land surface model fluxes have been analyzed with the aid of data from flux towers. The sources of discrepancies were found to include problems with the model surface roughness length and turbulent exchange coefficients for mid-latitude cropland areas in summer, inaccuracies in the precipitation data that were used as forcing for the land surface model, and model underestimation of transpiration in some forests during dry periods. At the tower sites analyzed, agreement with tower data was generally closer for our satellite-derived fluxes than for the land surface model fluxes, in terms of monthly averages.
Optical Remote Sensing, 2003
Optics InfoBase is the Optical Society's online library for flagship journals, partnered... more Optics InfoBase is the Optical Society's online library for flagship journals, partnered and copublished journals, and recent proceedings from OSA conferences.
Passive Infrared Remote Sensing of Clouds and the Atmosphere III, 1995
ABSTRACT The Support of Environmental Requirements for Cloud Analysis and Archives (SERCAA) progr... more ABSTRACT The Support of Environmental Requirements for Cloud Analysis and Archives (SERCAA) program is a two phase basic research program to develop techniques for analysis of multi-source multi-spectral satellite sensor data for the purpose of estimating cloud fractional amount, location, height, and type. In the first phase, cloud analysis algorithms were developed for each imaging sensor. A major innovation was an analysis integration approach to combine the separate algorithm results from the temporally, spatially, and spectrally inconsistent sources into a single logically consistent analysis. In the second phase, work includes algorithms for retrieval and estimation of the cloud physical and optical properties such as phase, drop size distribution, optical thickness, and emissivity. Also under investigation are cloud environment parameters including vertical profiles of temperature and moisture available from sounding sensors.