Calibration Of Satellite Sensors Research Articles

Identification of Global Extended Pseudo Invariant Calibration Sites (EPICS) and Their Validation Using Radiometric Calibration Network (RadCalNet)

This study introduces a global land cover clustering using an unsupervised algorithm, incorporating the novel step of filtering data to retain only temporally stable pixels before applying K-means clustering. Unlike previous approaches that did not assess the pixel-level temporal stability, this method provides more reliable clustering results. The K-means identified 160 distinct clusters, with Cluster 13 Global Temporally Stable (Cluster 13-GTS) showing significant improvements in temporal stability. Compared to Cluster 13 Global (Cluster 13-G) from earlier research, Cluster 13-GTS reduced the coefficient of variation by up to 1% and increased the number of calibration locations from 23 to over 50. This study also validated these clusters using TOA reflectance from ground-truth measurements collected at the Radiometric Calibration Network (RadCalNet) Gobabeb (RCN-GONA) site, incorporating data from Landsat 8, Landsat 9, Sentinel-2A, and Sentinel-2B. The GONA Extended Pseudo Invariant Calibration Sites (EPICS) GONA-EPICS cluster used for the validation provided statistically comparable mean TOA reflectance to RCN-GONA, with a reduced chi-square test indicating minimal differences within the cluster’s uncertainty range. Notably, the difference in reflectance between RCN-GONA and GONA-EPICS was less than 0.023 units across all the bands. Although GONA-EPICS exhibited slightly higher uncertainty (6.4% to 10.3%) compared to RCN-GONA site (<5%), it offered advantages such as 80 potential calibration points per Landsat cycle and reduced temporal instability, and it provided alternatives to reduce the reliance on single sites like traditional PICS or RCN-GONA, making it a valuable tool for calibration efforts. These findings highlight the potential of the newly developed EPICS for radiometric calibration and stability monitoring of optical satellite sensors. Distributed across diverse regions, these global targets increase the number of calibration points available for any sensor in any orbital cycle, reducing the reliance on traditional PICS and offering more robust targets for radiometric calibration efforts.

A GEO-GEO Stereo Observation of Diurnal Cloud Variations over the Eastern Pacific

Fast atmospheric processes such as deep convection and severe storms are challenging to observe and understand without adequate spatiotemporal sampling. Geostationary (GEO) imaging has the advantage of tracking these fast processes continuously at a cadence of the 10 min global and 1 min mesoscale from thermal infrared (TIR) channels. More importantly, the newly-available GEO-GEO stereo observations from our 3D-Wind algorithm provide more accurate height assignment for atmospheric motion vectors (AMVs) than those from conventional TIR methods. Unlike the radiometric methods, the stereo height is insensitive to radiometric TIR calibration of satellite sensors and can assign the feature height correctly under complex situation (e.g., multi-layer clouds and atmospheric inversion). This paper shows a case study from continuous GEO-GEO stereo observations over the Eastern Pacific during 1–5 February 2023, to highlight diurnal variations of clouds and dynamics in the planetary boundary layer (PBL), altocumulus/congestus, convective outflow and tropical tropopause layer (TTL). Because of their good vertical resolution, the stereo observations often show a wind shear in these cloud layers. As an example, the stereo winds reveal the classic Ekman spiral in marine PBL dynamics with a clockwise (counterclockwise) wind direction change with height in the Northern (Southern) Hemisphere subtropics. Over the Southeastern Pacific, the stereo cloud observations show a clear diurnal variation in the closed-to-open cell transition in the PBL and evidence of precipitation at a lower level from broken stratocumulus clouds.

Implementing a Dual-Spectrometer Approach for Improved Surface Reflectance Estimation

Surface reflectance measurement is an integral part of the vicarious calibration of satellite sensors and the validation of satellite-derived top-of-atmosphere (TOA) and surface reflectance products. A well-known practice for estimating surface reflectance is to conduct a field campaign with a spectrometer and a calibration panel, which is labor-intensive and expensive. To address this issue, the Radiometric Calibration Network, RadCalNet, has been developed, which automatically collects surface reflectance over several selected sites. Neither of these approaches can continuously track the atmosphere, which limits their ability to compensate for atmospheric transmittance change during target measurement. This paper presents the dual-spectrometer approach that uses a stationary spectrometer dedicated to continuously tracking changes in atmospheric transmittance by staring at a calibrated reference panel while the mobile spectrometer measures the target. Simultaneous measurement of the reflectance panel and target help to transfer calibration from the stationary spectrometer to the mobile spectrometer and synchronize the measurements. In this manner, atmospheric transmittance changes during target measurement can be tracked and used to reduce the variability of the target surface reflectance. This paper uses field measurement data from combined field campaigns between different calibration groups at Brookings, South Dakota, and Landsat 8 and Landsat 9 underfly efforts over Coconino National Forest, Arizona, and Guymon, Oklahoma. Preliminary results show that even in a clear sky condition, where atmospheric transmittance changes are minimal, the precision of target surface reflectance estimated using the dual-spectrometer approach is 2–6% better than the single-spectrometer approach. The dual-spectrometer approach shows the potential for a substantial improvement in the precision of the target spectral profile when the atmospheric transmittance is changing rapidly during field measurement. Results show that during non-optimal atmospheric conditions, the dual-spectrometer approach improved the precision of the surface reflectance by 50–60% compared to the single-spectrometer approach across most spectral regions. The ability to estimate surface reflectance more precisely using the dual-spectrometer approach in different atmospheric conditions improves the vicarious calibration of optical satellite sensors and the validation of both TOA and surface reflectance products.

Exploitation of the SoilPRO® (SP) apparatus to measure soil surface reflectance in the field: Five case studies

The SoilPRO® (SP) is an assembly designed to acquire soil reflectance information in the field without disturbing the soil surface, and regardless of atmospheric and solar radiation conditions. This paper summarizes five case studies in which the SP assembly was used for different applications. The case studies consisted of: (1) generating surface spectral measurements under any atmospheric condition; (2) comparing the performance of the SP to the traditional bare fiber method for vicarious calibration of hyperspectral satellite sensors; (3) assessing water repellency of a soil surface governed by organic matter hydrophobicity; (4) spatial prediction of the rate of water infiltration into the soil profile as governed by the soil surface seal; and (5) using the SP apparatus to measure soil surface reflectance in South Shetland Island, Antartica under severe weather conditions. The case studies included calculation of spectral quality, prediction accuracy and measurement stability. The paper discusses each of the cases in detail and concludes that the SP (or similar assembly) is the best way to measure the reflectance of the original soil surface in the field. In the first case study, the spectrum collected by the SP under daily changing illumination was shown to be stable relative to the traditional measurement methods of contact probe or bare fiber. The second case study indicated that use of the SP for vicarious calibration is much more efficient (in terms of time and stability) than ground-truth practice over a large area, and in the third case study, the SP was able to assess a soil surface property governed by organic matter hydrophobicity better than the contact probe, which destroys the soil surface organic seal. A similar achievement was gained in the fourth case study, providing a better assessment of the water-infiltration rate into the soil. In the fifth case study, the SP demonstrated impressive high-quality acquisition of soil surface reflectance with a very low sun angle over the South Pole. Based on these case studies and the high quality of the data generated by the SP in the field, we suggest building, in parallel to the classical soil spectral libraries generated in the laboratory, field soil spectral libraries that will preserve the soil surface properties scanned in the field. We anticipate the development of more applications for the SP assembly based on the capabilities shown in this paper.

In-Flight Relative Radiometric Calibration of a Wide Field of View Directional Polarimetric Camera Based on the Rayleigh Scattering over Ocean

The directional polarimetric camera (DPC) is a Chinese satellite sensor with a large field of view (FOV) (±50° both along-track and cross-track) and a high spatial resolution (about 3.3 km at nadir) that operates in a sun-synchronous orbit. It is a difficult task to calibrate the in-flight relative radiometric variation of the sensors with such a wide FOV. In this study, a new method based on Rayleigh scattering over the ocean is developed to estimate the radiometric sensitivity variation over the whole FOV of DPC. Firstly, the theoretical uncertainty of the method is analyzed to calibrate the relative radiometric response. The calibration uncertainties are about 2–6.9% (depending on the wavelength) when the view zenith angle (VZA) is 0° and decrease to about 1–3.8% when VZA increases to 70°. Then, the method is applied to evaluate the long-term radiometric drift of the DPC. It is found that the radiometric response of DPC/GaoFen-5 over the whole FOV is progressively drifting over time. The sensitivity at shorter bands decreases more strongly than longer bands, and at the central part of the optics decreases more strongly than the marginal part. During the 14 months (from March 2019 to April 2020) of operational running in-orbit, the DPC radiometric responses of 443 nm, 490 nm, 565 nm, and 670 nm bands drifted by about 4.44–23.08%, 4.75–16.22%, 3.86–9.81%, and 4.7–16.86%, respectively, from the marginal to the central part of the FOV. The radiometric sensitivity has become more stable since January 2020. The monthly radiometric drift is separated into the relative radiometric part and the absolute radiometric part. The relative radiometric drift of DPC is found to be smoothly varying with VZA, which can be parameterized as a polynomial function via VZA. At last, the temporal radiometric drift of DPC/GaoFen-5 is corrected by combining the relative and absolute radiometric coefficients. The correction is convincing by cross calibration with MODIS/Aqua observation over the desert sites and improving the aerosol retrievals. The Rayleigh method in this study is efficient for the radiometric sensitivity calibration of wide FOV satellite sensors.

CALVAL EVALUATION OF DESIS PRODUCTS IN AMIAZ PLAIN AND MAKHTESH RAMON TEST SITES, SOUTHERN ISRAEL

Abstract. The new era of hyperspectral remote (HSR) sensors in orbit is approaching. Missions such as CHIME of the European Space Agency (ESA), EMIT/SBG of NASA, EnMAP of the German Aerospace Center (DLR), and SHALOM of the Israel Space Agency (ISA) will launch in the near future, while other HSR sensors are already in orbit, such as DESIS of DLR, PRISMA of the Italian Space Agency (ASI), and HISUI of the Japan Aerospace Exploration Agency (JAXA). Vicarious calibration (VC) of satellite sensors is vital to tracking a sensor's performance during its lifetime and is a routine procedure in any satellite mission. Accordingly, searching for ideal sites for CAL/VAL operation is an important task that should be part of the mission planning. This study demonstrates two areas in southern Israel that can be acquired in one overpass as VC sites: Amiaz Plain (AP) and Makhtesh Ramon (MR), which were evaluated for their fulfillment of all VC requirements for HSR sensors. AP (5 km2 of homogeneous bright target) was found suitable for radiometric calibration, and MR (200 km2) for spectral and thematic validations. We checked the applicability of these sites using a high-end airborne HRS sensor (AisaFENIX 1K sensor with 420 bands, 375–2500 nm spectral range, and 1.5-m spatial resolution) along with comprehensive field studies and ground measurements. Accordingly, we developed an operational VC protocol to use these sites for both radiometric and spectral quality inspection of HRS satellites. We demonstrated this capability on recent PRISMA and DESIS reflectance products. Here we provide these analyses and recommend how to use these areas to further examine DESIS data's performance. We call for collaborations with individuals and space agencies in using these VC sites, where we will provide ground-truth information and fulfill any other requirements for VC.

Classification and Evaluation of Extended PICS (EPICS) on a Global Scale for Calibration and Stability Monitoring of Optical Satellite Sensors

Historically stable areas across North Africa, known as pseudo invariant calibration sites (PICS), have been used as targets for the calibration and monitoring of optical satellite sensors. However, two major drawbacks exist for these sites: first is the dependency on a single location to be always invariant, and second is the limited amount of observation achieved using these sites. As a result, longer time periods are necessary to construct a dense dataset to assess the radiometric performance of on-orbit optical sensors and confirm that the change detected is sensor-specific rather than site-specific. This work presents a global land cover classification to obtain an extended pseudo invariant calibration site (EPICS) on a global scale using Landsat-8 Operational Land Imager (OLI) data. This technique provides multiple calibration sites across the globe, allowing for the building of richer datasets in a shorter time frame compared to the traditional approach (PICS), with the advantage of assessing the calibration and stability of the sensors faster, detecting possible changes sooner and correcting them accordingly. This work identified 23 World Reference System two (WRS-2) path/row locations around the globe as part of the global EPICS. These EPICS have the advantage of achieving multiple observations per day, with similar spectral characteristics compared to traditional PICS, while still producing a temporal coefficient of variation (ratio of temporal standard deviation and temporal mean) less than 4% for all bands, with some as low as 2.7%.

Normalization Method and Application for MODIS TEB Assessments Using Earth Scene Measurements

AbstractSelected Earth targets are commonly used for satellite sensor calibration assessments (e.g., sensor stability and inter‐comparisons). Moreover, typical scenes used for the calibration assessment of the thermal emissive bands (TEBs) include Dome Concordia (Dome‐C), ocean, desert, and deep convective clouds (DCC). Reference data used for these calibration assessments can come from another band, another instrument, or ground measurements. The Dome‐C site, covered with uniformly distributed permanent snow, is normally used for the assessment of the TEBs at cold temperatures. Furthermore, ocean and desert measurements prove useful for scenes with higher temperatures. The DCC, one of the most consistent and coldest targets, can be used for the TEBs calibration and product stability assessments. Moderate Resolution Imaging Spectroradiometer (MODIS) band 31 (∼11 μm) can be used as a reference for these scenes. However, measurements over these scenes have seasonal variations, and the DCC brightness temperatures (BTs) have asymmetrical distributions. These features can introduce additional uncertainty to the stability assessments. A normalization method is applied by using an empirical model to derive reference‐dependent BTs. Using the developed empirical model, measurements can be normalized to a reference BT in order to enhance the calibration assessment's accuracy. This method is evaluated using all four scene types (i.e., ocean, desert, snow (Dome‐C), and DCC) and applied to all the Terra and Aqua MODIS TEBs. Stability assessments over the instruments' entire data records are presented and discussed. The technique can be applied in future efforts to support MODIS TEBs calibration assessments.

Evaluation of regions suitable for vicarious calibration of ocean color satellite sensors in the South China Sea.

Accurate retrieval of biogeochemical components of the ocean at a global scale from space requires accurately calibrated top-of-atmosphere (TOA) radiance, which is usually achieved by deriving a vicarious gain coefficient (g-factor) through a process called system vicarious calibration (SVC). Currently, only two SVC sites, Marine Optical Buoy (MOBY) and BOUée pour l'acquiSition d'une Série Optique à Long termE (BOUSSOLE), are routinely operated to support the SVC process for all on-orbit ocean color satellite payloads. However, high-quality matchups between satellite observations and in situ measurements are rare because of the strict requirements of the SVC process. Meanwhile, a stable g-factor is usually computed by averaging sufficient gain measurements. Therefore, more SVC sites are required to derive a stable g-factor in a short duration, particularly for the initial calibration of newly launched satellite sensors. In this study, nearly twenty years of well-calibrated ocean color satellite data were used to calculate the mean and standard deviation of physical and optical properties of waters and the atmosphere in the South China Sea (SCS) to evaluate the feasibility of establishing a SVC site. A region was identified that meets all requirements that were used to evaluate the MOBY and BOUSSOLE sites. Two in situ measurements within this region were used to derive a g-factor for MODIS-Terra and MODIS-Aqua and were compared with the g-factor derived using MOBY data. The consistence of the two g-factors indicates that the identified region in the SCS could be a potential area for establishing a long-term moored SVC site.

Geolocation Correction for Geostationary Satellite Observations by a Phase-Only Correlation Method Using a Visible Channel

This study describes a high-speed correction method for geolocation information of geostationary satellite data for accurate physical analysis. Geostationary satellite observations with high temporal resolution provide instantaneous analysis and prompt reports. We have previously reported the quasi real-time analysis of solar radiation at the surface and top of the atmosphere using geostationary satellite data. Estimating atmospheric parameters and surface albedo requires accurate geolocation information to estimate the solar radiation accurately. The physical analysis algorithm for Earth observations is verified by the ground truth. In particular, downward solar radiation at the surface is validated by pyranometers installed at ground observation sites. The ground truth requires that the satellite observation data pixels be accurately linked to the location of the observation equipment on the ground. Thus, inaccurate geolocation information disrupts verification and causes complex problems. It is difficult to determine whether error in the validation of physical quantities arises from the estimation algorithm, satellite sensor calibration, or a geolocation problem. Geolocation error hinders the development of accurate analysis algorithms; therefore, accurate observational information with geolocation information based on latitude and longitude is crucial in atmosphere and land target analysis. This method provides the basic data underlying physical analysis, parallax correction, etc. Because the processing speed is important in geolocation correction, we used the phase-only correlation (POC) method, which is fast and maintains the accuracy of geolocation information in geostationary satellite observation data. Furthermore, two-dimensional fast Fourier transform allowed the accurate correction of multiple target points, which improved the overall accuracy. The reference dataset was created using NASA’s Shuttle Radar Topography Mission 1-s mesh data. We used HIMAWARI-8/Advanced HIMAWARI Imager data to demonstrate our method, with 22,709 target points for every 10-min observation and 5826 points for every 2.5 min observation. Despite the presence of disturbances, the POC method maintained its accuracy. Column offset and line offset statistics showed stability and characteristic error trends in the raw HIMAWARI standard data. Our method was sufficiently fast to apply to quasi real-time analysis of solar radiation every 10 and 2.5 min. Although HIMAWARI-8 is used as an example here, our method is applicable to all geostationary satellites. The corrected HIMAWARI 16 channel gridded dataset is available from the open database of the Center for Environmental Remote Sensing (CEReS), Chiba University, Japan. The total download count was 50,352,443 on 8 July 2020. Our method has already been applied to NASA GeoNEX geostationary satellite products.

Relative radiometric calibration of yaw data without calibration field of hyperspectral images based on harmonic analysis

ABSTRACT Radiometric calibration of satellite sensor could be divided into absolute radiometric calibration and relative radiometric calibration. Relative radiometric calibration can greatly reduce the impact of the sensor’s instability due to many factors like failure to perform calibration experiments or satellite post-operative attenuation. One of the methods is to use the 90° yaw data for relative radiation calibration, where the camera or satellite rotates by 90° so that the linear charge-coupled device (CCD) detector is parallel to the flight direction and sequentially passes through the ground uniform field to obtain the same radiance to achieve the satellite in order to achieve relative radiometric calibration of satellite sensor and eliminate stripe phenomenon in image. The orbita hyperspectral satellites (OHS) are commercial hyperspectral remote sensing satellites with the largest image width and the highest spatial resolution in China. It has realized the operation of multiple hyperspectral satellites network for the first time. However, there are still problems such as inaccurate calculation of radiation calibration parameters, difficulty in realizing uniform field ground, and difficulty in achieving full dynamic calibration of the sensor. In this study, the hyperspectral images acquired by OHS satellites were taken as the research object to propose a method to achieve field-free relative radiometric calibration based on harmonic analysis of yaw data. This method combines the advantages of harmonic analysis technology and the least squares theory and is applied to the relative radiation calibration of hyperspectral yaw data. It is called the harmonic analysis radiometric calibration (HARC) algorithm. First, HARC algorithm performed the first-order forward and reverses harmonic analysis on the 86° yaw data of OHS satellites which were pre-processed into the data of the conventional image mode to obtain the theoretical value of the pre-processed yaw data. Then, the actual radiance value of yaw data in column direction would be fitted to the theoretical value using the least squares theory to calculate the offset and gain of radiometric calibration parameter after eliminating the high and low radiance values in yaw data. Finally, the offset and gain parameters were used to carry out relative radiometric calibration on conventional push-broom satellite image. The comparative analysis of the test showed that relative radiometric calibration of all band images of six pieces of CCD arrays in the hyperspectral sensor of OHS satellites was realized based on yaw data without uniform ground calibration field. The HARC algorithm proposed in this paper can overcome the inaccurate calculation of calibration parameters caused by the yaw angle less than 90°. It not only retains the image detail information but also effectively removes various types of thick and thin stripe noise in the sweep direction, and is not limited by the different bands. The algorithm has good universality in applications on various bands. Qualitative and quantitative comparison analyses were conducted between HARC algorithm and classical relative radiometric calibration methods, and the corrected image has a great improvement in image quality and sharpness compared with the original image. The effect of stripe removal and the accuracy of radiation correction of the HARC algorithm are superior to the classical relative radiation calibration method.

GOES-16 Advanced Baseline Imager instrument performance monitor

Time series generated from NOAA operational satellite sensor temperature, noise, and calibration parameter statistics is a critical science analysis tool to trend instrument performance and detect and resolve on-orbit anomalies. Establishing this capability entails ingesting instrument engineering, housekeeping, and calibration data; performing statistics on them; and then storing and providing the resultant data and/or plots. For instruments with relatively small amounts of input and output data, this is a relatively easy task. For the NOAA Geostationary Operational Environmental Satellite R-Series Advanced Baseline Imager (ABI)—with three times more spectral information, four times the spatial resolution, and more than five times faster temporal coverage than previous GOES—instrument performance monitoring can be extremely complex because of the relatively large data volumes and number of parameters. Also of difficulty is that software and computing architecture needed to build such a system is usually proprietary and not openly documented. In order to fill this gap, we focus on the concept of operations and the results associated with the ABI instrument performance monitor. This monitoring system has proven to be extremely valuable in tracking instrument stability and detecting and performing initial diagnosis of ABI anomalies.

SITE SELECTION AND EVALUATION OF CHINA'S NEW RADIOMETRIC CALIBRATION TEST SITES

Abstract. The ideal radiometric calibration site is the basis for achieving on-orbit radiometric calibration. At present, China mainly uses the Dunhuang national test site for on-orbit radiometric calibration. However, the Dunhuang national test site has a shortage of ground objects and surface damage, and it is urgent to select and evaluate the new calibration sites. By analyzing the calibration site selection requirements, three new radiometric calibration sites were selected in Dunhuang and Golmud. Obtaining high-resolution satellite image data of each calibration site and evaluating the spatial uniformity of the site on different spatial scales. The radiometric stability of the sites is evaluated using the long-term sequence of Landsat8 image data from 2013 to 2019. Atmospheric and surface tests were carried out at various sites in August 2019, and atmospheric information and ground spectral data were obtained to evaluate the spectral characteristics of the sites. The surface directional characteristics of the sites are evaluated by using MODIS images at different angles in sunny weather on adjacent dates. Obtaining MOD05 water vapor products from 2013 to 2019 of each calibration site and conducting monthly statistics. The number of sunny days at each calibration site is counted and the drought conditions of the site are evaluated. The results show that the three new radiometric calibration sites have uniform and stable surface characteristics and atmospheric characteristics, and are suitable for on-orbit radiometric calibration of satellite sensors, which provides a reference for the location and evaluation of future calibration sites.

The Influence of Heterogeneity on Lunar Irradiance Based on Multiscale Analysis

The Moon is a stable light source for the radiometric calibration of satellite sensors. It acts as a diffuse panel that reflects sunlight in all directions, however, the lunar surface is heterogeneous due to its topography and different mineral content and chemical composition at different locations, resulting in different optical properties. In order to perform radiometric calibration using the Moon, a lunar irradiance model using different observation geometry is required. Currently, two lunar irradiance models exist, namely, the Robotic Lunar Observatory (ROLO) and the Miller and Turner 2009 (MT2009). The ROLO lunar irradiance model is widely used as the radiometric standard for on-orbit sensors. The MT2009 lunar irradiance model is popular for remote sensing at night, however, the original version of the MT2009 lunar irradiance model takes less consideration of the heterogeneous lunar surface and lunar topography. Since the heterogeneity embedded in the lunar surface is the key to the improvement of the lunar irradiance model, this study analyzes the influence of the heterogeneous surface on the irradiance of moonlight based on model data at different scales. A heterogeneous correction factor is defined to describe the impact of the heterogeneous lunar surface on lunar irradiance. On the basis of the analysis, the following conclusions can be made. First, the influence of heterogeneity in the waning hemisphere is greater than that in waxing hemisphere under all 32 wavelengths of the ROLO filters. Second, the influence of heterogeneity embedded in the lunar surface exerts less impact on lunar irradiance at lower resolution. Third, the heterogeneous correction factor is scale independent. Finally, the lunar irradiance uncertainty introduced by topography is very small and decreases as the resolution of model data decreases due to the loss of topographic information.

Evaluation of an Extended PICS (EPICS) for Calibration and Stability Monitoring of Optical Satellite Sensors

Pseudo Invariant Calibration Sites (PICS) have been increasingly used as an independent data source for on-orbit radiometric calibration and stability monitoring of optical satellite sensors. Generally, this would be a small region of land that is extremely stable in time and space, predominantly found in North Africa. Use of these small regions, referred to as traditional PICS, can be limited by: (i) the spatial extent of an individual Region of Interest (ROI) and/or site; (ii) and the frequency of how often the site can be acquired, based on orbital patterns and cloud cover at the site, both impacting the time required to construct a richly populated temporal dataset. This paper uses a new class of continental scaled PICS clusters (also known as Extended PICS or EPICS), to demonstrate their capability in increasing temporal frequency of the calibration time series which ultimately allows calibration and stability assessment at a much finer scale compared to the traditional PICS-based method while also reducing any single location’s potential impact to the overall assessment. The use of EPICS as a calibration site was evaluated using data from Landsat-8 Operational Land Imager (OLI), Landsat 7 Enhanced Thematic Mapper Plus (ETM+), and Sentinel-2A&B Multispectral Instrument (MSI) images at their full spatial resolutions. Initial analysis suggests that EPICS, at its full potential and with nominal cloud consideration, can significantly decrease the temporal revisit interval of moderate resolution sensors to as much as of 0.33 day (3 collects/day). A traditional PICS is expected to have a temporal uncertainty (defined as the ratio of temporal standard deviation and temporal mean) of 2–5% for TOA reflectance. Over the same time period EPICS produced a temporal uncertainty of 3%. But the advantage to be leveraged is the ability to detect sensor change quicker due to the denser dataset and reduce the impact of any potential ‘local’ changes. Moreover, this approach can be extended to any on-orbit sensor. An initial attempt to quantify the minimum detectable change (a threshold slope value which must be exceeded by the reflectance trend to be considered statistically significant) suggests that the use of EPICS can decrease the time period up to approximately half of that found using traditional PICS-based approach.

Spatial inventory of selected atmospheric emissions from oil industry in Ecuadorian Amazon: Insights from comparisons among satellite and institutional datasets

Atmospheric emissions from oil activities impact human health, socioeconomic status and exacerbate global warming. This study was conducted in the North-eastern Ecuadorian Amazon, a rich biodiverse and cultural area. This study aimed to show the benefits of public institutional data to advance hazard mapping knowledge for comprehensible risk evaluation. A spatial inventory was built from publicly disclosed reports spanning ten years (2003–2012). Emissions were estimated for gas flaring, associated black carbon (BC) and greenhouse gases (i.e., CO2 and CH4). To assess the quality of publicly available data, the calculated emissions were compared with satellite observations and historical energy statistics from the United Nations (UN). Results indicate total gas flared for this period of 7.6 Gm3, corresponding to 782 Mm3 yr−1, and equivalent to a 3.7–4.5 kt yr−1 of BC. These values were in agreement with the UN estimates, suggesting that publicly available data are of acceptable quality. In contrast, the results from energy censuses diverged from satellite observation data, which might be explained by a poor calibration of satellite sensors. Study results enabled emissions mapping at a higher spatial scale than previous studies. Black carbon presented the highest results with 29.4–148.0 kg m−2 yr−1 in the cities of Shushufindi and Joya de Los Sachas. Greenhouse gases were up to twenty-fold higher than previous estimates. Publicly disclosed data estimates were discussed in terms of their potential on evaluations for climate, local health and economic impacts, to raise environmental monitoring and accountability in governmental institutions.

Classification of North Africa for Use as an Extended Pseudo Invariant Calibration Sites (EPICS) for Radiometric Calibration and Stability Monitoring of Optical Satellite Sensors

Pseudo invariant calibration sites (PICS) have been extensively used for the radiometric calibration and temporal stability monitoring of optical satellite sensors. Due to limited knowledge about the radiometric stability of North Africa, only a limited number of sites in the region are used for this purpose. This work presents an automated approach to classify North Africa for its potential use as an extended PICS (EPICS) covering vast portions of the continent. An unsupervised classification algorithm identified 19 “clusters” representing distinct land surface types was used; three clusters were identified with spatial uncertainties within approximately 5% in the shorter wavelength bands and 3% in the longer wavelength bands. A key advantage of the cluster approach is that large numbers of pixels are aggregated into contiguous homogeneous regions sufficiently distributed across the continent to allow multiple imaging opportunities per day, as opposed to imaging a typical PICS once during the sensor’s revisit period. This potential increase in temporal resolution could result in increased sensitivity for the quicker identification of changes in sensor response.

ProVal: A New Autonomous Profiling Float for High Quality Radiometric Measurements

An efficient system to produce in situ high quality radiometric measurements is compulsory to rigorously perform the vicarious calibration of satellite sensors dedicated to Ocean Color Radiometry (OCR) and to validate their derived products. This requirement is especially needed during the early stages of an OCR satellite activity or for remote areas poorly covered by oceanographic cruises with possible bio-optical anomalies. Taking advantage of Argo’s profiling float, we present a new autonomous profiling float dedicated to in situ radiometric measurements. The float is based on the Provor CTS5 (manufacturer NKE) with an added novel two protruding arm design allowing for sensor redundancies, shading mitigation and near-surface data. Equipped with two identical radiometers on each arm that measure downward irradiance and upwelling radiance at seven wavelengths, the ProVal float generates both redundant radiometric profiles as well as an estimate of Remote Sensing Reflectance. Results from 449 profiles sampled obtained in the NW Mediterranean Sea and in the Indian sector of the Southern Ocean are presented to illustrate the ProVal float technical maturity. Analysis of the behavior of the profiling float, including tilting and ascent speeds, is presented. The vertical stability of the ProVal exhibits 85% of surface data of the Mediterranean Sea with a tilt smaller than 10 degrees. This percentage is 45% in the Southern Ocean due to rougher seas. Redundant sensors provide a characterization of the relative drift between sensors over the deployment which is found to be less than 0.15% per month over a year. Post-cruise calibration of a recovered float revealed no significant drift. As an example of the utility of ProVal floats, a match-up of Remote Sensing Reflectance measured with the European Space Agency Ocean and Land Color Imager (OLCI onboard Sentinel-3A & 3B) is shown. It follows that profiling floats, such as ProVal, could provide a significant contribution to an upcoming global System Vicarious Calibration of space-based radiometers.

An Automatic Recognition and Positioning Method for Point Source Targets on Satellite Images

Currently, the geometric and radiometric calibration of on-board satellite sensors utilizes different ground targets using some form of manual intervention. Point source targets provide high precision geometric and radiometric information and have the potential to become a new tool for joint geometric and radiometric calibration. In this paper, an automatic recognition and positioning method for point source target images is proposed. First, the template matching method was used to effectively reduce nonpoint source target image pixels in the satellite imagery. The point source target images were then identified using particular feature parameters. Using the template matching method, the weighted centroid method, and the Gaussian fitting method, the positions of the centroid of the point source target images were calculated. The maximum position detection error obtained using the three methods was 0.07 pixels, which is comparably better than artificial targets currently in use. The experimental results show point source targets provide high precision geometric information, which can become a suitable alternative for automatic joint geometric and radiometric calibration of spaceborne optical sensors.

Assessing the calibration differences in the reflective solar bands of Terra MODIS and Landsat-7 enhanced thematic mapper plus

Long-term data records obtained from Earth observing sensors depend not only on the calibration accuracy of individual sensors but also on the consistency across instruments and platforms. Hence, sensor calibration intercomparison plays a vital role for a better understanding of various science products. The Moderate Resolution Imaging Spectroradiometer (MODIS) and enhanced thematic mapper plus (ETM+) on the Terra and Landsat 7 platforms have operated successfully since their launch, collecting measurements in the reflective solar and infrared parts of the spectrum. Terra MODIS has employed a reflectance-based calibration since beginning its mission. In the case of ETM+, a radiance-based calibration was employed until recent years, when a reflectance-based calibration was introduced. Being in the AM constellation with less than 30 min difference in overpass times, near-simultaneous Earth scene measurements can be effectively used to assess the calibration differences between the spectrally matching bands of these two instruments. The pseudoinvariant calibration sites (PICS) in the North African desert are widely used for on-orbit calibration and validation of satellite sensors. Four PICS from this region have been employed to assess the multitemporal reflectance differences. Correction for bidirectional reflectance, spectral response function mismatch, and impacts of atmospheric water-vapor have been incorporated to provide an assessment of the long-term stability of each spectral band and reflectance differences amongst them. Results indicate that the spectral bands of both instruments show a long-term stability to within 2% from 2000 to 2017. The top-of-atmosphere reflectances between the two instruments postcorrection agree to within 4%. Also included in this paper is a detailed discussion of various parameters contributing to the uncertainties of this cross-calibration. The techniques presented in this paper can be further extended to perform similar intercomparison between Landsat 8 Operational Land Imager, Aqua MODIS, and Suomi-NPP VIIRS.