Radiometric Calibration

The Deep Blue (DB) algorithm's primary data product is midvisible aerosol optical depth (AOD). DB applied to Moderate Resolution Imaging Spectroradiometer (MODIS) measurements provides a data record since early 2000 for MODIS Terra and mid-2002 for MODIS Aqua. In the previous data version (Collection 5, C5), DB production from Terra was halted in 2007 due to sensor degradation; the new Collection 6 (C6) has both improved science algorithms and sensor radiometric calibration. This includes additional calibration corrections developed by the Ocean Biology Processing Group to address MODIS Terra's gain, polarization sensitivity, and detector response versus scan angle, meaning DB can now be applied to the whole Terra record. Through validation with Aerosol Robotic Network (AERONET) data, it is shown that the C6 DB Terra AOD quality is stable throughout the mission to date. Compared to the C5 calibration, in recent years the RMS error compared to AERONET is smaller by ∼0.04 over bright (e.g., desert) and ∼0.01-0.02 over darker (e.g., vegetated) land surfaces, and the fraction of points in agreement with AERONET within expected retrieval uncertainty higher by ∼10% and ∼5%, respectively. Comparisons to the Aqua C6 time series reveal a high level of correspondence between the two MODIS DB data records, with a small positive (Terra-Aqua) average AOD offset <0.01. The analysis demonstrates both the efficacy of the new radiometric calibration efforts and that the C6 MODIS Terra DB AOD data remain stable (to better than 0.01 AOD) throughout the mission to date, suitable for quantitative scientific analyses.

On August 22, 2002, a vicarious calibration (VC) experiment of MERIS, a pushbroom imaging spectrometer on ESA’s ENVISAT, was performed. The purpose of this experiment was the acquisition of in-situ measurements of surface and atmospheric conditions over a bright, uniform target. These data were then used to compute top-ofatmosphere (TOA) radiances, which were correlated with the MERIS TOA radiances (Level 1b product), to determine the in-flight radiometric response of the on-orbit sensor. The Rail Road Valley Playa, NV, was the primary target chosen by the Optical Sciences Center, University of Arizona, and the Remote Sensing Laboratories, University of Zurich, for this experiment. The in-situ estimations of top-of-atmosphere radiances lie within less than 6% of the MERIS measurements, except for band 11 (760 nm) and band 15 (900 nm). The absolute uncertainty of the vicarious calibration experiment is estimated to be less than 3.36%. Based on the uncertainties of the vicarious calib...

The launch of ESA's ENVISAT in March 2002 was followed by a commissioning phase for all ENVISAT instruments to verify the performance of ENVISAT instruments and recommend possible adjustments of the calibration or the product algorithms before the data was widely distributed. The focus of this paper is on the vicarious calibration of the Medium Resolution Imaging Spectrometer (MERIS) radiance product (Level 1b) over land. From August to October 2002, several vicarious calibration (VC) experiments for MERIS were performed by the Optical Sciences Center, University of Arizona, and the Remote Sensing Laboratories, University of Zürich. The purpose of these activities was the acquisition of in-situ measurements of surface and atmospheric conditions over a bright, uniform land target, preferably during the time of MERIS data acquisition. The experiment was performed on a dedicated desert site (Railroad Valley Playa, Nevada, USA), which has previously been used to calibrate most relevant satellite instruments (e.g., MODIS, ETM+, etc.). In-situ data were then used to compute top-of-atmosphere (TOA) radiances which were compared to the MERIS TOA radiances (Level 1b full resolution product) to determine the in-flight radiometric response of the on-orbit sensor. The absolute uncertainties of the vicarious calibration experiment are found between 3.36-7.15%, depending on the accuracies of the available ground truth data. Based on the uncertainties of the vicarious calibration method and the calibration accuracies of MERIS, no recommendation to update the MERIS calibration is given.

An intercomparison of radiance and irradiance ocean color radiometers (the second laboratory comparison exercise—LCE-2) was organized within the frame of the European Space Agency funded project Fiducial Reference Measurements for Satellite Ocean Color (FRM4SOC) May 8–13, 2017 at Tartu Observatory, Estonia. LCE-2 consisted of three sub-tasks: (1) SI-traceable radiometric calibration of all the participating radiance and irradiance radiometers at the Tartu Observatory just before the comparisons; (2) indoor, laboratory intercomparison using stable radiance and irradiance sources in a controlled environment; (3) outdoor, field intercomparison of natural radiation sources over a natural water surface. The aim of the experiment was to provide a link in the chain of traceability from field measurements of water reflectance to the uniform SI-traceable calibration, and after calibration to verify whether different instruments measuring the same object provide results consistent within the ...

The current study sets out to develop an empirical line method (ELM) radiometric calibration framework for the reduction of atmospheric contributions in unmanned aerial systems (UAS) imagery and for the production of scaled remote sensing reflectance imagery. Using a MicaSense RedEdge camera flown on a custom-built octocopter, the research reported herein finds that atmospheric contributions have an important impact on UAS imagery. Data collected over the Lower Pearl River Estuary in Mississippi during five week-long missions covering a wide range of environmental conditions were used to develop and test an ELM radiometric calibration framework designed for the reduction of atmospheric contributions from UAS imagery in studies with limited site accessibility or data acquisition time constraints. The ELM radiometric calibration framework was developed specifically for water-based operations and the efficacy of using generalized study area calibration equations averaged across variable illumination and atmospheric conditions was assessed. The framework was effective in reducing atmospheric and other external contributions in UAS imagery. Unique to the proposed radiometric calibration framework is the radiance-to-reflectance conversion conducted externally from the calibration equations which allows for the normalization of illumination independent from the time of UAS image acquisition and from the time of calibration equation development. While image-by-image calibrations are still preferred for high accuracy applications, this paper provides an ELM radiometric calibration framework that can be used as a time-effective calibration technique to reduce errors in UAS imagery in situations with limited site accessibility or data acquisition constraints.

The spreading of the seafloor and the dates given by the secular community are in complete contrast to the Young Earth Creation (YEC) timeline. Very little of the seafloor itself is older than 150 million years based on radiometric dating and the assumed slow movement of the plates because of subduction. While there are places that date 200 million years, the oldest oceanic crust found on Earth is located in the Herodotus Basin in the eastern Mediterranean Sea, dated to be around 340 million years old. Not to mention that sometimes the sea floor does not subduct but makes its way onto land. Some of the seafloor is on the top of mount everest that dates 475-500 million years old. How can we as YEC answer this? Catastrophic Plate Tectonics (CPT) offers this explanation. So, what is going on? How do we as YEC answer this and what predictions can be made?

The central objective of the research was to carry through the urban and partner-ambient inquiry, of the quarter D´Areia Step, inserted in the city of Saint Maria -RS, through the use of systems of geographic information, for the elaboration of thematic maps aiming at to contribute as well as for the urban planning and the ambient awareness.

HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

This paper provides an update on the RAD9000 MWIR/LWIR spectral radiometer -a high-performance instrument supporting extremely accurate absolute and relative radiometric calibration of EO test systems. The system features an all-reflective optical system, internal and external thermal reference sources, a visible camera-based sighting/alignment capability, modular MWIR and LWIR detector/filter subassemblies, flexible control/display software, and a sophisticated graphical user interface (GUI). We present prototype performance data describing the instrument's thermal sensitivity, radiometric accuracy, spectral resolution, calibration, and other key parameters.

The need to understand and monitor climate change has led to proposed radiometric accuracy requirements for space-based remote sensing instruments that are very stringent and currently outside the capabilities of many Earth orbiting instruments. A major problem is quantifying changes in sensor performance that occur from launch and during the mission. To address this problem on-orbit calibrators and monitors have been developed, but they too can suffer changes from launch and the harsh space environment. One solution is to use the Moon as a calibration reference source. Already the Moon has been used to remove post-launch drift and to cross-calibrate different instruments, but further work is needed to develop a new model with low absolute uncertainties capable of climate-quality absolute calibration of Earth observing instruments on orbit. To this end, we are proposing an Earth-based instrument suite to measure the absolute lunar spectral irradiance to an uncertainty 1 of 0.5 % (k=1) over the spectral range from 320 nm to 2500 nm with a spectral resolution of approximately 0.3 %. Absolute measurements of lunar radiance will also be acquired to facilitate calibration of high spatial resolution sensors. The instruments will be deployed at high elevation astronomical observatories and flown on high-altitude balloons in order to mitigate the effects of the Earth's atmosphere on the lunar observations. Periodic calibrations using instrumentation and techniques available from NIST will ensure traceability to the International System of Units (SI) and low absolute radiometric uncertainties.

1 This report is based on the experiences of the past and present staff at NIST Optical Technology Division and NASA Goddard Space Flight Center who worked on NASA/ EOS and experts at NOAA on radiometric calibrations for remote sensing for the last two decades. Therefore, the information provided and discussed happened to be specific to these organizations. However, the best practice guidelines are generally applicable for all organizations towards climate quality data from satellite sensors. Cloud cover (Fraction of sky Feedback 0.01 0.003 covered)

The radiometric calibration equations for the thermal emissive bands (TEB) and the reflective solar bands (RSB) measurements of the earth scenes by the polar satellite sensors, (Terra and Aqua) MODIS and Suomi NPP (VIIRS), and geostationary sensors, GOES Imager and the GOES-R Advanced Baseline Imager (ABI) are analyzed towards calibration algorithm harmonization on the basis of SI traceability which is one of the goals of the NOAA National Calibration Center (NCC). One of the overarching goals of NCC is to provide knowledge base on the NOAA operational satellite sensors and recommend best practices for achieving SI traceability for the radiance measurements on-orbit. As such, the calibration methodologies of these satellite optical sensors are reviewed in light of the recommended practice for radiometric calibration at the National Institute of Standards and Technology (NIST). The equivalence of some of the spectral bands in these sensors for their end products is presented. The operational and calibration features of the sensors for on-orbit observation of radiance are also compared in tabular form. This review is also to serve as a quick cross reference to researchers and analysts on how the observed signals from these sensors in space are converted to radiances.

A one-day workshop was held on December 10, 2009 at the National Institute of Standards and Technology to address the issue of data gaps in the time series of satellite measurements. Such gaps can occur due to launch delay, launch failure, inconsistencies, or data jumps in radiometric scales between satellites. The presence of such gaps limit the ability of using measurements to detect the small changes in key environmental variables that result from climate change. Leading experts in the Earth Observation community from the National Aeronautics and Space Administration (NASA), National Oceanic and Atmospheric Adminstration (NOAA), United States Geological Survey (USGS), and academia attended the meeting to prioritize the calibration strategies for bridging and mitigating satellite data gaps for climate change detection. These strategies include establishing SI traceability for satellite sensor calibration and measurements; continuing improvements in prelaunch, onboard, and vicarious calibrations and transfer standards; establishing celestial standards and procedures for intercomparisons; establishing SI traceability for alternative measurement strategies, such as in-situ networks and airborne sensor campaigns; and leveraging international satellite assets. This paper summarizes the workshop and recommendations.

Survey (USGS), and other government and non-government organizations to discuss strategies for overcoming data gaps that may occur in satellite sensor observations. Developing and implementing effective strategies requires considerable forethought because the requirements of high accuracy for observing climate change are applicable through any data gap and are critical for maintaining irrefutable climate records. Drs. Raju Datla of the Optical Technology Division at NIST, Changyong Cao of the Center for Satellite Applications and Research (STAR) of NOAA, and James Butler of NASA Goddard Space Flight Center organized the workshop on behalf of their respective agencies to address the problem and recommend strategies for future planning. The one-day workshop began with invited talks in the morning session and concluded in the afternoon with discussions and consensus recommendations.

The Low Background Infrared (LBIR) facility at the National Institute of Standards and Technology (NIST) is responsible for absolute IR radiometric calibrations (SI traceable) in low-background temperature (below 80 K) environments. IR radiometric test hardware that needs to be operated in cryogenic environments is calibrated in cryogenic vacuum chambers maintained by the facility to create environments that simulate the low-temperature background of space. Transfer radiometers have also been developed to calibrate IR radiometric test hardware that is too large to ship to NIST from their own IR test facilities. The first generation transfer radiometer, the BXR, is a filter-based radiometer that utilizes an As-doped Si blocked impurity band detector, and can calibrate IR test chambers to a total uncertainty of less than 3 % (1 σ) at irradiance as low as 10 -14 W/cm 2 . The BXR has evaluated 9 chambers and the performance of a subset of these chambers will be discussed to a limited extent to demonstrate the need for calibrating IR test chambers. The second generation transfer radiometer, the MDXR, and new primary standards allowing absolute calibrations as low as 10 -15 W/cm 2 are in the final stages of development. The MDXR will have all the functionality of the BXR and it will have a cryogenic Fourier transform spectrometer (FTS) for high resolution spectral capability. Performance specifications and test results from development activity on the new primary standards will be discussed.

To deliver sample estimates provided with the necessary probability foundation to permit generalization from the sample data subset to the whole target population being sampled, probability sampling strategies are required to satisfy three necessary not sufficient conditions: (i) All inclusion probabilities be greater than zero in the target population to be sampled. If some sampling units have an inclusion probability of zero, then a map accuracy assessment does not represent the entire target region depicted in the map to be assessed. (ii) The inclusion probabilities must be: (a) knowable for nonsampled units and (b) known for those units selected in the sample: since the inclusion probability determines the weight attached to each sampling unit in the accuracy estimation formulas, if the inclusion probabilities are unknown, so are the estimation weights. This original work presents a novel (to the best of these authors&#39; knowledge, the first) probability sampling protocol for ...

According to existing literature and despite their commercial success, state-of-the-art two-stage non-iterative geographic object-based image analysis (GEOBIA) systems and three-stage iterative geographic object-oriented image analysis (GEOOIA) systems, where GEOOIA  GEOBIA, remain affected by a lack of productivity, general consensus and research. To outperform the degree of automation, accuracy, efficiency, robustness, scalability and timeliness of existing GEOBIA/GEOOIA systems in compliance with the Quality Assurance Framework for Earth Observation (QA4EO) guidelines, this methodological work is split into two parts. The present first paper provides a multi-disciplinary Strengths, Weaknesses, Opportunities and Threats (SWOT) analysis of the GEOBIA/GEOOIA approaches that augments similar analyses proposed in recent years. In line with constraints stemming from human vision, this SWOT analysis promotes a shift of learning paradigm in the pre-attentive vision first stage of a remote sensing (RS) image understanding system (RS-IUS), from sub-symbolic statistical model-based (inductive) image segmentation to symbolic physical model-based (deductive) image preliminary classification. Hence, a symbolic deductive pre-attentive vision first stage accomplishes image sub-symbolic segmentation and image symbolic pre-classification simultaneously. In the second part of this work a novel hybrid (combined deductive and inductive) RS-IUS architecture featuring a symbolic deductive pre-attentive vision first stage is proposed and discussed in terms of: (a) computational theory (system design); (b) information/knowledge representation; (c) algorithm design; and

JAXA has developed the Advanced Optical Satellite (ALOS-3) as a successor to the optical mission of the Advanced Land Observing Satellite (ALOS) "Daichi" (2006 -2011) since FY 2016. The wide-swath and high-resolution optical imager (WISH) is the main instrument of ALOS-3 and equipped with a panchromatic (Pa) band and 6 multispectral (MS) bands. For the optics of WISH, a large off-axis four mirror anastigmat type has been selected to achieve both highresolution (0.8 m Pa, 3.2 m MS) and wide-swath (70 km). The proto-flight model (PFM) of all mirrors has already in the precision polishing process, and highly accurate measurements of large off-axis aspherical surfaces (primary and tertiary mirror) are carried out both in a contact and a non-contact method. The verification concerning the high precision assembly of the large off-axis optical system was also carried out using the structural model which is manufactured with the same design for the PFM. Manufacture and test of the PFM of WISH would be conducted over the next one year and the PFM would be delivered to the ALOS-3 satellite system within FY 2019. ALOS-3 is scheduled to be launch from Tanegashima Space Center in FY 2020.

Using high-resolution Panchromatic (Pan) imagery to sharpen Multi-Spectral Imagery (MSI) has been an active area of research for a number of years. The primary innovations of our approach is casting the problem as a superresolution of the MSI to the sampling geometry of the Pan, using the Pan as a template for object boundaries and cross-calibrating the Pan/MSI spatially and spectrally. This perspective leads us to a fused image with the sampling geometry (high spatial resolution) of the Pan which preserves the radiometric calibration (high spectral resolution) of the MSI. The Pan and MSI do not provide sufficient information for this fused product; additional constrains must be imposed to obtain a unique solution. Preserving the radiometric calibration of the MSI, and our choice of additional constraints are motivated by our ultimate goal of material classification of the MSI at the Pan resolution.

A water bath blackbody has been built under contract for the Electromag- netic Metrology Engineering Branch at Newark Air Force Station. The per- formance goal Wcis a large-area, self-calibrating, high-accuracy blackbody covering the majority of the liquid water temperature range. With the ex- ception of self-calibration, these goals were met. This report describes both the conceptual design of the water bath blackbody and the results of the tests that were carried out to characterize the performance of the actual water bath blackbody that was built for Newark Air Force Station. The details of the construction and operation of that water bath blackbody are described in a companion report.

This study presents a modeling approach to improve solar diffuser (SD) degradation determination from SD stability monitor (SDSM) measurements. The MODIS instrument uses a SD to calibrate its reflective solar bands (RSBs) on-orbit. Due to the imperfectly designed SDSM sun view screen, the SD reflectance tracked by SDSM has large noise. The SDSM measurements noise is spectrally coherent and can be minimized by normalizing measurements to the least degraded detector 9 (936 nm). In this study, a SD degradation model is used to determine the SD degradation's wavelength dependency and the detector 9 degradation is estimated by the model solution. The results show the SD degradations measured at 6 SDSM detectors (554 -936 nm) have stable relationships, where the degradation is inversely proportion to 1/wavelength^4. The model estimated SD degradation at SDSM detector 9 wavelength (936 nm) is ~0.9% from 2002 to 2018. Based on the SD degradation model solution, the SD degradation at short/mid wave bands are estimated to improve short/mid wave bands calibration. The model can also be used to improve interpolating SD degradation at SDSM detectors to RSB wavelengths. Compared to linear interpolation, bands 9 and 10 show the largest differences of up to 0.3 and 0.4% respectively. These differences directly impact the calibration coefficients of these bands.

This paper summarizes the results from the system level test campaign of the Engineering Test Unit (ETU) of the ‘Ocean Color Instrument’ (OCI), the primary payload of NASA’s ‘Plankton, Aerosol, Cloud and ocean Ecosystem’ (PACE) mission. The main goals of the test campaign were to optimize characterization procedures and evaluate system level performance relative to model predictions. Critical performance parameters such as radiometric gain, signal-to-noise ratio, polarization, instantaneous field-of-view, temperature sensitivity, relative spectral response and stability were evaluated for wavelengths from 600 to 2,260 nm and are in line with expectations. We expect the OCI flight unit to meet the PACE mission performance requirements. Building and testing the ETU has been extremely important for the development of the OCI flight unit (e.g. improved SNR by increasing the aperture, optimized thermal design), and we strongly recommend the inclusion of an ETU in the development of futur...

Positions System (GPS) satellites) are used to constrain the model of atmospheric water vapor absorption in the 20 to 32 GHz band. A differential approach is presented in which the slope of opacity-versus-wet delay data is used as the absorption model constraint. This technique minimizes the effects of radiometric calibration errors and oxygen model uncertainties in the derivation of a best-fit vapor absorption model. A total of approximately 5 months of data were obtained from two experiment sites. At the Cloud and Radiation Testbed (CART) site near Lamont, Oklahoma, three independent WVRs provided near-continuous opacity measurements over the interval from July through September 1998. At NASA's Goldstone tracking station in the California desert, two WVRs obtained opacity data over the September through October 1997 interval. At both sites, a GPS receiver and surface barometer obtained the data required for deriving the zenith wet delays over the same time frames. Measured values of the opacity-versus-wet delay slope parameter were obtained at four WVR frequencies (20.7, 22.2, 23.8, and 31.4 GHz) and compared with predictions of three candidate absorption models referenced in the recent literature. With one exception, all three models provide agreement within approximately 5 percent of the opacity-versus-wet delay slope measurements at all WVR frequencies at both sites. One model provides agreement for all channels at both sites to the 2 to 3 percent level. This accuracy is sufficient to meet the requirements of the tropospheric calibration system now being deployed at Goldstone to support the Cassini Gravitational Wave Experiment.

The NASA STI Program Office is operated by Langley Research Center, the lead center for NASA's scientific and technical information. The NASA STI Program Office provides access to the NASA STI Database, the largest collection of aeronautical and space science STI in the world. The Program Office is also NASA's institutional mechanism for disseminating the results of its research and development activities. These results are published by NASA in the NASA STI Report Series, which includes the following report types:

The second sIMBIOs (sensor Intercomparison and Merger for Biological and Interdisciplinary Oceanic studies) Radiometric Intercomparison (sIMRIc-2) was carried out in 2002. The purpose of the sIMRIcs is to ensure a common radiometric scale among the ...

The NIST anechoic chamber is used to generate standard (known) EM fields for frequencies from 200 MHz to 40 GHz. The transmitting antennas used are open-ended rectangular waveguides from 200 to 500 MHz and pyramidal horns from 450 MHz to 40 GHz. The uncertainty in the electric field is currently estimated to be ± 1 . dB . A number of changes and additions are planned to improve the accuracy, repeatability, and efficiency of the system.

Detailed radiometric calibration tracking of the vacuum-ultraviolet spectrometer SUMER ͑from solar ultraviolet measurements of emitted radiation͒ was performed during the first year of the Solar and Heliospheric Observatory ͑SOHO͒ mission and will continue. In view of the flight history of many previous solar UV instruments, the stability of calibration of the extreme-ultraviolet instruments on SOHO has been a major concern. Results obtained during the first year of operation show that excellent radiometric stability has been achieved with SUMER. These results were accomplished by stringent cleanliness and contamination-control procedures during all phases of the project. We describe the strategy and results of the in-flight calibration tracking program performed with SUMER.

We investigate uncertainties in the Atmospheric Infrared Sounder (AIRS) radiances based on in-flight and preflight calibration algorithms and observations. The global coverage and spectra1 resolution (X/AX --1200) of AIRS enable it to produce a data set that can be used as a climate data record over the lifetime of the instrument. Therefore, we examine the effects of the uncertainties in the calibration and the detector stability on future climate studies. The uncertainties of the parameters that go into the AIRS radiometric calibration are propagated to estimate the accuracy of the radiances and any climate data record created from AIRS measurements. The calculated radiance uncertainties are consistent with observations. Algorithm enhancements may be able to reduce the radiance uncertainties by as much as 7%. We find that the orbital variation of the gain contributes a brightness temperature bias of < 0.01 K. Although this can be removed by algorithm enhancements, it is smaller than uncertainty of the gain for most channels.

The Atmospheric Infrared Sounder (AIRS) is a space based instrument developed for measurement of global atmospheric properties; primarily water vapor and temperature. AIRS is one of several instruments on board NASA's Earth Observing System Aqua spacecraft. AIRS operates in the 3.7 -15.4 micron region and has 2378 infrared channels. AIRS spatial resolution is 13.5 km from the orbit of 705 km and it scans +-49.5 degrees. AIRS has a set of on-board calibrators including a single infiared blackbody source, a parylene spectral calibration source, a space view and a Vis/NIR photometric calibrator. The on-board calibration subsystems are described along with a description of special test procedures for using them and results from several tests performed to date. Results are exceptional indicating that the instrument is performing better than expected.

With hyperspectral imaging, image content can be identified based on fine spectral details related to chemical composition. Immediate applications in smart agriculture and environmental monitoring have the potential for strong societal benefits. However, the technology struggles with the vast amount of data that it produces, in particular when deployed on satellites. The current movement towards increased use of lossy compression is highly risky, because even careful and tedious parameter tuning cannot guarantee that no applications are compromised. We implemented and validated a compression method that simultaneously provides a strong data reduction and preserves analysis results for all possible applications.

In precision agriculture detailed geoinformation on plant and soil properties plays an important role. Laser scanning already has been used to describe in-field variations of plant growth in 3D and over time and can serve as valuable complementary topographic data set for remote sensing, such as deriving soil properties from hyperspectral sensors. In this study full-waveform laser scanning data acquired with a Riegl VZ-400 instrument is used to classify 3D point clouds into post-harvest straw residues and bare soil. A workflow for point cloud based classification is presented using radiometric and geometric point features. A radiometric correction is performed by using a range-correction function f(r), which is derived from lab experiments with a reference target of known reflectance. Thereafter, the corrected signal amplitude and local height features are explored with respect to the target classes. The following procedure includes feature calculation, decision tree analysis, point cloud classification and finally result validation using detailed classified reference RGB images. The classification tree separates the classes of harvest residues and bare soil with an accuracy of 96% by using geometric and radiometric features. The LiDAR-derived harvest residue coverage value of 75% lies in accordance with the image-based reference (coverage of 68%). The results indicate the high potential of radiometric features for natural surface classification, particularly in combination with geometric features.

Prior research has shown that for specific periods, vegetation indices from PlanetScope and Sentinel-2 (used as a reference) must be aligned to benefit from the experience of Sentinel-2 and utilize techniques such as data fusion. Even during the worstcase scenario, it is possible through histogram matching to calibrate PlanetScope indices to achieve the same values as Sentinel-2 (useful also for proxy). Based on these findings, the authors examined the effectiveness of linear regression in aligning individual bands prior to computing indices to determine if the bands are shifted differently. The research was conducted on five important bands: Red, Green, Blue, NIR, and RedEdge. These bands allow for the computation of well-known vegetation indices like NDVI and NDRE, and soil indices like Iron Oxide Ratio and Coloration Index. Previous research showed that linear regression is not sufficient by itself to align indices in the worst-case scenario. However, this paper demonstrates its efficiency in achieving accurate band alignment. This finding highlights the importance of considering specific scaling requirements for bands obtained from different satellite sensors, such as PlanetScope and Sentinel-2. Contemporary images acquired by the two sensors during May and July demonstrated different behaviors in their bands; however, linear regression can align the datasets even during the problematic month of May.

This thesis deals with the potential of full-waveform airborne laser scanning for improved digital terrain model generation. The additional observables amplitude, echo width and backscatter cross section from this new scanning technique are separately analysed to assess their discriminatory power for classifying airborne laser scanner point clouds into terrain and off-terrain points. Based on the results of the exploratory data analysis, three different approaches for the extraction of terrain points are presented and tested in a practical application. On the one hand, hard thresholds for the full-waveform observables are applied on the single points to discriminate into terrain and off-terrain. On the other hand, the full-waveform information is used to derive weights for the single points, describing the probability for belonging to the class &quot;terrain&quot;. Proper probability and weight functions are introduced. The third method is segmentation-based. A seeded region growing...

As an active remote sensing technique airborne laser scanning (ALS) is able to capture the topography with high precision even for densely forested areas. Due to the high pulse repetition frequency of up to 400 kHz a high sampling rate on the ground can be achieved, which allows the description of the terrain surface in decimeter scale. In this contribution two approaches to characterize terrain roughness are described. In the first approach the standard deviation of detrended terrain points is calculated. To achieve a high spatial resolution of the derived roughness layer a high terrain point density is essential, which requires especially in dense forested areas a very high sampling rate. In addition to the 3D position of backscattering objects, full-waveform ALS systems provide the width of each detectable echo, which provides information on the range distribution of scatterers within the laser footprint that contribute to one echo. It is therefore, an indicator for surface roughness and the slope of the target. In comparison to the roughness layer derived from the first approach using high point densities, the derived echo width image shows similar spatial patterns of terrain roughness even for moderate point densities. The results show that both the echo widths and the vertical distribution of terrain echoes are useful to derive reliable geometric terrain roughness layers of large areas.

Surface, Space ENvironment, GEochemistry, and Ranging) is the first spacecraft to visit Mercury since the Mariner 10 flybys in 1974 and 1975 and will be the first spacecraft to orbit the innermost planet, beginning in March 2011. The science payload is designed to study all aspects of Mercury and its environment and consists of seven instruments and a radio science experiment. During the primary orbital phase of the mission, the MESSENGER team faces the challenge of scheduling science observations to meet all measurement objectives while operating in a thermally harsh environment in geometrically challenging orbits. An efficient, automated science planning and commanding system called MESSENGER SciBox has been developed to support orbital analysis and strategic planning activities prior to orbital insertion, and to schedule and command the instrument and spacecraft operation during the orbital phase. In this paper we present the architecture of MESSENGER SciBox and its application to pre-orbital simulation and inorbit operational usage.

A novel analytical model of the calibration error impact on the Earth radiance measurement from thermal emissive bands of sensors is developed. The goal is to assess the impact of calibration errors, to evaluate those errors and to perform correction. This model is applied in the correction of bias in Advanced Very High Resolution Radiometer (AVHRR) channels 4 and 5 observed from the intercomparison with Infrared Atmospheric Sounding Interferometer measurements. A two-step regression is used to separate the effects of calibration radiance errors from calibration coefficient errors. In the first step, the calibration radiance error, primarily due to internal calibration target (ICT) imperfections and temperature measurement error, is evaluated using the bias from selected Earth scenes with brightness temperatures close to the ICT temperature. The effects from the ICT imperfections and temperature measurement errors are analyzed collectively. The resulting estimation of the calibration radiance error is 0.30% for channel 4 and 0.33% for channel 5. After correcting the Earth scene radiance for these effects, the errors in the offset and nonlinear coefficient of instrument response are evaluated through the second step of the regression. A weighting function is used to account for the nonuniformity in the data distribution over the Earth radiance range. After the evaluation of the errors, removal of their effects can be achieved either through corrections of the calibration coefficients or correction of the measured radiance. The results are useful for the improvement of the AVHRR IR channel calibration algorithm. This model and two-step regression approach can also be applied to other similar broadband thermal infrared radiometric sensors. The infrared (IR) channels on AVHRR are calibrated using an onboard blackbody (BB) with reference to cold space, while the nonlinearity in instrument response was characterized at prelaunch using Thermal Vacuum (TV) test data. The imperfection in the BB emissivity, BB temperature measurement error, and errors in the calibration coefficients impact Earth scene radiance measurement. Assessing the impact of these errors on the retrieved radiance and correcting the resulting bias are essential to enhance product accuracy. This paper focuses on modeling the impact of these errors on Earth scene radiance measurements for the AVHRR IR channels and correcting the calibration coefficients.

The utilization of multi-sensor and constellation satellite data with appropriate geometric and radiometric calibration and validation is required for effective satellite data applications for various monitoring tasks. In this paper, we present the research and development of optical calibration sites using both natural surface and ground point-source-mirror reflectors constructed at The Center for Research and Application of Satellite Remote Sensing of Yamaguchi University (YUCARS), Japan. The YUCARS calibration sites experimented with GRUS-1A (Axelspace Corporation, Tokyo, Japan) and PlanetScope (Planet Lab, San Francisco, CA, USA) images for the verification of radiometric and geometric performance following the harmonized reflectance product. The top of atmosphere (TOA) radiance and reflectance of optical micro-satellite imageries were simulated by MODTRAN6 based on the in-situ data of the ground point-source-mirror reflector, ground surface and atmospheric measurements. The YUC...

New sensors exhibiting advanced technical specifications motivate the development of improved algorithms to take advantage of the enhanced performances of these sensors. In the particular case of the Multiangle Imaging Spectroradiometer (MISR) instrument, the angular sampling of the scattered radiance field, coupled with high spatial resolution and accurate radiometric calibration, justifies the implementation of physically based algorithms to optimally interpret the data and extract high-level information. This paper proposes a new approach to the reliable and accurate characterization of vegetated areas on the basis of data gathered in space and to the delivery of improved products to meet increasingly demanding user requests. An exploratory study based on advanced very high-resolution radiometer (AVHRR) data shows the potential of approaches based on advanced models but also points out the limitations associated with the use of data from monodirectional instruments. By contrast, a preliminary investigation conducted with synthetic MISR-like multiangular data illustrates the potential of analyzing data of high radiometric quality with advanced models to move toward a more complete characterization of terrestrial surfaces. Over the past decades, significant advances have taken place in the understanding of the scattering of light by the atmosphere, plant canopies, and soil surfaces [e.g.,

Multi-spectral (ms) airborne lidar data are enriched relative to traditional lidar due to the multiple channels of intensity digital numbers (DNs), which offer the potential for active Spectral Vegetation Indices (SVIs), enhanced classification, and change monitoring. However, in case of SVIs, indices should be calculated from spectral reflectance values derived from intensity DNs after calibration. In this paper, radiometric calibration of multi-spectral airborne lidar data is presented. A novel low-cost diffuse reflectance coating was adopted for creating radiometric targets. Comparability of spectral reflectance values derived from ms lidar data for coniferous stand (2.5% for 532 nm, 17.6% for 1064 nm, and 8.4% for 1550 nm) to available spectral libraries is shown. Active vertical profiles of SVIs were constructed and compared to modeled results available in the literature. The potential for a new landscape-level active 3D SVI voxel approach is demonstrated. Results of a field ex...

The thermal emission of the dark side of Venus is used to investigate the distribution of CO above the clouds using the VIRTIS-H instrument aboard Venus Express. The objective is to study the latitudinal variations of CO, in particular in the polar regions.

ESA's Soil Moisture and Ocean Salinity (SMOS) mission, launched 2-Nov-2009, has been in orbit for over 5 years, and its Microwave Imaging Radiometer with Aperture Synthesis (MIRAS) in two dimensions keeps working well. The calibration strategy remains overall as established after the commissioning phase, with a few improvements. The data for this whole period has been reprocessed with a new fully polarimetric version of the Level-1 processor which includes a refined calibration schema for the antenna losses. This reprocessing has allowed the assessment of an improved performance benchmark. An overview of the results and the progress achieved in both calibration and image reconstruction is presented in this contribution. With an experience of over 5 years of in-orbit operation, much has been learnt on how MIRAS works and how its observations can be improved through better calibration and image reconstruction techniques. The purpose of this paper is to update the reader with the latest results on the payload performance and data processing of the SMOS mission . SMOS is currently delivering several products, some of them used by operational systems, others only for scientific research (Mecklenburg et al., in press). MIRAS is a Microwave Imaging Radiometer with twodimensional Aperture Synthesis, which remains being the first and so far, the only one of its kind, in space. The main feature of MIRAS is that it obtains two-dimensional images at every snapshot without needing any mechanical scanning of its antenna, a very distinct capability when compared with traditional scanners or push-broom radiometers. A detailed description of the instrumental aspects of MIRAS can be found in while the on-board Calibration System and respective in-flight calibration strategy are described in . One year after launch the calibration approach was slightly modified with the initial flight experience, and the first SMOS instrument in-orbit performance was assessed in , including the effect of the unexpectedly severe Radio Frequency Interference from ground transmitters . The present paper will then follow the same structure as , with important

The Hyperion instrument mounted on the EO-1 spacecraft was launched November 21, 2000 into an orbit following LANDSAT-7 by 1 minute. Hyperion has a 7.5 km swath width, a 30 meter ground resolution and 10 nm spectral resolution extending from 400 nm to 2500 nm. The first portion of the mission was used to measure and characterize the on-orbit radiometric, spectral, image quality and geometric performance of the instrument. Lake Frome, a dry salt lake in South Australia was chosen as a calibration site for Hyperion. Surface spectral data were collected along a transect through the center of the lake prior to the Hyperion overpass. This paper discusses the incorporation of the Lake Frome ground measurements and analysis into the performance verification of the instrument.