High-resolution methods for fluorescence retrieval from space

The retrieval from space of a very weak fluorescence signal was studied in the O2A and O2B oxygen atmospheric absorption bands. The accuracy of the method was tested for the retrieval of the chlorophyll fluorescence and reflectance terms contributing to the sensor signal. The radiance at the top of the atmosphere was simulated by means of a commercial radiative-transfer program at a high resolution (0.1 cm-1). A test data set was generated in order to simulate sun-induced chlorophyll fluorescence at the top of the canopy. Reflectance terms were spectrally modeled using cubic splines and fluorescence by means of the sum of two Voigt functions. Sensor radiance residual minimization was performed in the presence of a multiplicative noise, thus ensuring that the sensor simulations were realistic. The study, which focused on the possibility of retrieving fluorescence with an accuracy better than 10%, was performed for instrument resolutions ranging from about 0.4 cm-1 to 2 cm-1 in order to test the algorithm for the characteristics of existing and planned hyper-spectral sensors. The algorithm was also used to retrieve fluorescence in the single O2A band at the OCO and TANSO-FTS instrument spectral resolution

Fundamental remote sensing science research program. Part 1: Scene radiation and atmospheric effects characterization project

Brief articles summarizing the status of research in the scene radiation and atmospheric effect characterization (SRAEC) project are presented. Research conducted within the SRAEC program is focused on the development of empirical characterizations and mathematical process models which relate the electromagnetic energy reflected or emitted from a scene to the biophysical parameters of interest

Uncertainty Analysis for Input Parameters of the Atmospheric Compensation Process in Airborne Imaging Spectroscopy.

In airborne imaging spectroscopy for the Visible Shortwave Infrared (VSWIR) wavelength range the state of the atmosphere can have a large influence on the values detected by optical sensors like APEX or AVIRIS NG. Since the value of interest is the reflectance property of the surface, atmospheric effects need to be compensated for. Atmospheric compensation algorithms like ATCOR-4 use radiance images as input data. In theory, the algorithm would then estimates the hemispherical-directional reflectance factor as a function of radiance intensity minus the influence of atmospheric particles and processes. Assuming the atmospheric parameters to be independent of the radiance intensity, a higher obtained radiance would necessarily lead to a higher estimated reflectance factor. The atmospheric compensation, however, is not a linear function and therefore the resulting images might show errors. This thesis presents an uncertainty analysis for the radiance intensity as one of several independent and non-independent input parameters and variables of ATCOR-4. The analysis is done by modelling the radiance images with factors drawn from a normal probability distribution and simulating the corresponding reflectance factor images with consideration of various other parameters and variables. Generally, the resulting HDRF can be found to have a wavelength dependent standard uncertainty of 0 to 0.15% associated with the radiance intensity. The uncertainty values are put into perspective by showing how other factors like a) the solar reference spectrum, b) the solar azimuth and zenith angle, c) the sensor uncertainty, d) different steps within the atmospheric compensation process, e) the choice of terrain mode in ATCOR-4 and f) the adjacency effect do all have an influence on the HDRF as well

Variability of adjacency effects in sky reflectance measurements

Sky reflectance Rsky(l) is used to correct in situ reflectance measurements in the remote detection of water colour. We analysed the directional and spectral variability in Rsky(l) due to adjacency effects against an atmospheric radiance model. The analysis is based on one year of semi-continuous Rsky(l) observations that were recorded in two azimuth directions. Adjacency effects contributed to Rsky(l) dependent on season and viewing angle, and predominantly in the near-infrared (NIR). For our test area, adjacency effects spectrally resembled a generic vegetation spectrum. The adjacency effect was weakly dependent on the magnitude of Rayleigh- and aerosol-scattered radiance. Reflectance differed between viewing directions 5.4 +/- 6.3% for adjacency effects and 21.0 +/- 19.8% for Rayleigh- and aerosol-scattered Rsky(l), in the NIR. It is discussed under which conditions in situ water reflectance observations require dedicated correction for adjacency effects. We provide an open source implementation of our method to aid identification of such conditions. Copyright 2017 Optical Society of America

Exploring Aerosols near Clouds with High-Spatial-Resolution Aircraft Remote Sensing During SEAC4RS

Since aerosols are important to our climate system, we seek to observe the variability of aerosol properties within cloud systems. When applied to the satelliteborne Moderateresolution Imaging Spectroradiometer (MODIS), the Dark Target retrieval algorithm provides global aerosol optical depth (AOD; at 0.55 m) in cloudfree scenes. Since MODIS' resolution (500m pixels, 3 or 10km product) is too coarse for studying nearcloud aerosol, we ported the Dark Target algorithm to the highresolution (~50m pixels) enhancedMODIS Airborne Simulator (eMAS), which flew on the highaltitude ER2 during the Studies of Emissions, Atmospheric Composition, Clouds, and Climate Coupling by Regional Surveys Airborne Science Campaign over the United States in 2013. We find that even with aggressive cloud screening, the ~0.5km eMAS retrievals show enhanced AOD, especially within 6 km of a detected cloud. To determine the cause of the enhanced AOD, we analyze additional eMAS products (cloud retrievals and degradedresolution AOD), coregistered Cloud Physics Lidar profiles, MODIS aerosol retrievals, and groundbased Aerosol Robotic Network observations. We also define spatial metrics to indicate local cloud distributions near each retrieval and then separate into nearcloud and farfromcloud environments. The comparisons show that low cloud masking is robust, and unscreened thin cirrus would have only a small impact on retrieved AOD. Some of the enhancement is consistent with clearcloud transition zone microphysics such as aerosol swelling. However, 3D radiation interaction between clouds and the surrounding clear air appears to be the primary cause of the high AOD near clouds

Atmospheric and Science Complexity Effects on Surface Bidirectional Reflectance

Among the tools used in passive remote sensing of Earth resources in the visible and near-infrared spectral regions are measurements of spectral signature and bidirectional reflectance functions (BDRFs). Determination of surface properties using these observables is complicated by a number of factors, including: (1) mixing of surface components, such as soil and vegetation, (2) multiple reflections of radiation due to complex geometry, such as in crop canopies, and (3) atmospheric effects. In order to bridge the diversity in these different approaches, there is a need for a fundamental physical understanding of the influence of the various effects and a quantiative measure of their relative importance. In particular, we consider scene complexity effects using the example of reflection by vegetative surfaces. The interaction of sunlight with a crop canopy and interpretation of the spectral and angular dependence of the emergent radiation is basically a multidimensional radiative transfer problem. The complex canopy geometry, underlying soil cover, and presence of diffuse as well as collimated illumination will modify the reflectance characteristics of the canopy relative to those of the individual elements

Soil moisture and evapotranspiration predictions using Skylab data

The author has identified the following significant results. Multispectral reflectance and emittance data from the Skylab workshop were evaluated for prediction of evapotranspiration and soil moisture for an irrigated region of southern Texas. Wavelengths greater than 2.1 microns were required to spectrally distinguish between wet and dry fallow surfaces. Thermal data provided a better estimate of soil moisture than did data from the reflective bands. Thermal data were dependent on soil moisture but not on the type of agricultural land use. The emittance map, when used in conjunction with existing models, did provide an estimate of evapotranspiration rates. Surveys of areas of high soil moisture can be accomplished with space altitude thermal data. Thermal data will provide a reliable input into irrigation scheduling

Atmospheric correction of Landsat-8/OLI and Sentinel-2/MSI data using iCOR algorithm: validation for coastal and inland waters

Image correction for atmospheric effects (iCOR) is an atmospheric correction tool that can process satellite data collected over coastal, inland or transitional waters and land. The tool is adaptable with minimal effort to hyper- or multi-spectral radiometric sensors. By using a single atmospheric correction implementation for land and water, discontinuities in reflectance within one scene are reduced. iCOR derives aerosol optical thickness from the image and allows for adjacency correction, which is SIMilarity Environmental Correction (SIMEC) over water. This paper illustrates the performance of iCOR for Landsat-8 OLI and Sentinel-2 MSI data acquired over water. An intercomparison of water leaving reflectance between iCOR and Aerosol Robotic Network – Ocean Color provided a quantitative assessment of performance and produced coefficient of determination (R2) higher than 0.88 in all wavebands except the 865 nm band. For inland waters, the SIMEC adjacency correction improved results in the red-edge and near-infrared region in relation to optical in situ measurements collected during field campaigns

Atmospheric correction of visible to middle-infrared EOS-MODIS data over land surfaces: Background, operational algorithm and validation

The NASA moderate resolution imaging spectroradiometer (MODIS) instrument will provide a global and improved source of information for the study of land surfaces with a spatial resolution of up to 250 m