remotesensing-logo

Journal Browser

Journal Browser

Cross-Calibration and Interoperability of Remote Sensing Instruments

A special issue of Remote Sensing (ISSN 2072-4292).

Deadline for manuscript submissions: closed (31 July 2020) | Viewed by 84891

Special Issue Editors


E-Mail Website
Guest Editor
Stinger Ghaffarian Technologies (SGT), Technical Support Services Contractor to USGS EROS, NASA/GSFC Mail Code 618, Greenbelt , MD 20771, USA
Interests: geometric calibration; satellite photogrammetry; remote sensing model simulations

E-Mail
Guest Editor
Stinger Ghaffarian Technologies (SGT), Technical Support Services Contractor to USGS EROS, 47914 252nd Street, Sioux Falls, SD 57198, USA
Interests: sensor characterization; feature extraction and modeling; Bayesian sensor/data fusion; lidar sensor analysis

E-Mail Website
Guest Editor
Earth Resources Observation and Science (EROS) Center, U.S. Geological Survey, 47914 252nd Street, Sioux Falls, SD 57198, USA
Interests: Cal/Val of sensors; CEOS; interoperability of sensors

Special Issue Information

Dear Colleagues,

The growing number of government and commercial sources of remotely sensed data offers users more choices than ever before, especially with the advent of CubeSats. The key to using data from these sources is to understand their capabilities, characteristics, and operational performance, as well as the quality of the data they produce. In addition to the characterization of the performance of individual sensors over time, it is equally important to understand the interoperability between similar sensors. This Special Issue aims to provide the user community with a good understanding of the radiometric, geometric, and spatial characteristics of the large and small satellite sensors that work in the optical domain with high to medium spatial resolution. The comparative analysis and understanding of the remotely sensed data and products will provide a measure of the data quality and awareness to Earth scientists and other users.

For this Special Issue, we would like to encourage papers on the following topics:

  • Design and pre-launch calibration of sensors
  • In-orbit calibration and characterization of satellite-borne optical sensors
  • Cross-calibration of sensors
  • Evaluation and cross-comparison of the geometric, radiometric, and spatial performance of sensors
  • Validation of higher level data products, such as surface reflectance or surface temperature products
  • Methodologies and reference datasets employed to improve the geometric and radiometric accuracy of products
  • Interoperability of data products from multiple sensors from a single constellation or across missions
  • Sensor and mission design trade-offs for applications using multiple sensors (for example: temporal resolution vs spatial resolution, radiometric accuracy vs. spectral coverage)

Dr. Rajagopalan Rengarajan
Dr. Ajit Sampath
Mr. Greg Stensaas
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Calibration
  • Characterization
  • Validation 
  • Cross-calibration 
  • Data interoperability

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

Further information on MDPI's Special Issue polices can be found here.

Published Papers (18 papers)

Order results
Result details
Select all
Export citation of selected articles as:

Research

Jump to: Other

15 pages, 4708 KiB  
Article
Landsat 8 Thermal Infrared Sensor Scene Select Mechanism Open Loop Operations
by Michael J. Choate, Rajagopalan Rengarajan, James C. Storey and Tim Beckmann
Remote Sens. 2021, 13(4), 617; https://doi.org/10.3390/rs13040617 - 9 Feb 2021
Cited by 2 | Viewed by 2752
Abstract
The Landsat 8 (L8) spacecraft and its two instruments, the operational land imager (OLI) and thermal infrared sensor (TIRS), have been consistently characterized and calibrated since its launch in February 2013. These performance metrics and calibration updates are determined through the U.S. Geological [...] Read more.
The Landsat 8 (L8) spacecraft and its two instruments, the operational land imager (OLI) and thermal infrared sensor (TIRS), have been consistently characterized and calibrated since its launch in February 2013. These performance metrics and calibration updates are determined through the U.S. Geological Survey (USGS) Landsat image assessment system (IAS), which has been performing this function since its launch. The TIRS on-orbit geometric calibration procedures include TIRS-to-OLI alignment, TIRS sensor chip assembly (SCA) alignment, and TIRS band alignment. In December 2014, the TIRS instrument experienced an anomalous condition related to the instrument’s ability to accurately measure the location of the scene select mechanism (SSM). The SSM is a rotating mirror that allows the instrument’s field of view to be pointed at the Earth, for normal imaging, or at either deep space or an onboard black body, for radiometric calibration purposes. This anomalous condition in the SSM’s position sensor made it necessary to implement a new mode of operation for this mirror, termed mode-0. Mode-0 involves operating the mirror in an open-loop control state during normal mission operations when acquiring Earth data. Closed-loop mode-4 is needed for directing the mirror towards the radiometric calibration targets and is used approximately once every two weeks to collect radiometric calibration data. Mode-0 is used for most operational imaging because it does not require SSM encoder data, thereby allowing the SSM encoder electronics to remain unpowered most of the time, reducing its use throughout the lifetime of the TIRS instrument, thus helping to preserve its nominal behavior during it use. This paper discusses the geometric calibration of the SSM mirror during its current normal mode-0 set of image operations, as its open-loop control allows the mirror to drift over time in its uncontrolled state and its effects on products. The results shown in this paper demonstrate that the ability to have ongoing updates to the modeling of the TIRS SSM mirror model, in both an automated fashion and with a set of more manual operations, allows accuracy that approaches mode-4 results within days from the start of a mode-0 event. Full article
(This article belongs to the Special Issue Cross-Calibration and Interoperability of Remote Sensing Instruments)
Show Figures

Graphical abstract

24 pages, 8154 KiB  
Article
The New Landsat Collection-2 Digital Elevation Model
by Shannon Franks, James Storey and Rajagopalan Rengarajan
Remote Sens. 2020, 12(23), 3909; https://doi.org/10.3390/rs12233909 - 28 Nov 2020
Cited by 14 | Viewed by 5446
Abstract
The Landsat Collection-2 distribution introduces a new global Digital Elevation Model (DEM) for scene orthorectification. The new global DEM is a composite of the latest and most accurate freely available DEM sources and will include reprocessed Shuttle Radar Topographic Mission (SRTM) data (called [...] Read more.
The Landsat Collection-2 distribution introduces a new global Digital Elevation Model (DEM) for scene orthorectification. The new global DEM is a composite of the latest and most accurate freely available DEM sources and will include reprocessed Shuttle Radar Topographic Mission (SRTM) data (called NASADEM), high-resolution stereo optical data (ArcticDEM), a new National Elevation Dataset (NED) and various publicly available national datasets including the Canadian Digital Elevation Model (CDEM) and DEMs for Sweden, Norway and Finland (SNF). The new DEM will be available world-wide with few exceptions. It is anticipated that the transition from the Collection-1 DEM at 3 arcsecond to the new DEM will be seamless because processing methods to maintain a seamless transition were employed, void filling techniques were used, where persistent gaps were found, and the pixel spacing is the same between the two collections. Improvements to the vertical accuracy were realized by differencing accuracies of other elevation datasets to the new DEM. The greatest improvement occurred where ArcticDEM data were used, where an improvement of 35 m was measured. By using theses improved vertical values in a line of sight algorithm, horizontal improvements were noted in some of the most mountainous regions over multiple 30-m Landsat pixels. This new DEM will be used to process all of the scenes from Landsat 1-8 in Collection-2 processing and will be made available to the public by the end of 2020. Full article
(This article belongs to the Special Issue Cross-Calibration and Interoperability of Remote Sensing Instruments)
Show Figures

Graphical abstract

26 pages, 4516 KiB  
Article
Harmonizing the Landsat Ground Reference with the Sentinel-2 Global Reference Image Using Space-Based Bundle Adjustment
by Rajagopalan Rengarajan, James C. Storey and Michael J. Choate
Remote Sens. 2020, 12(19), 3132; https://doi.org/10.3390/rs12193132 - 24 Sep 2020
Cited by 23 | Viewed by 5550
Abstract
There is an ever-increasing need to use an accurate and consistent geometric ground reference in the processing of remotely sensed data products, as this reduces the burden on the end-users to account for the differences between the data products from different missions. In [...] Read more.
There is an ever-increasing need to use an accurate and consistent geometric ground reference in the processing of remotely sensed data products, as this reduces the burden on the end-users to account for the differences between the data products from different missions. In this regard, the U.S. Geological Survey (USGS) initiated an effort to harmonize the Landsat ground reference with the Sentinel-2 Global Reference Image (GRI) to improve the co-registration between the data products of the two global medium-resolution missions. In this paper, we discuss the process, results, and the improvements expected from this harmonization of two ground references using space-triangulation-based bundle adjustment techniques. The ground coordinates of the Landsat reference library, consisting of five million Ground Control Points (GCPs) were adjusted in a series of four simultaneous bundle block adjustments using thousands of Landsat-8 (L8) scenes anchored with more than 300,000 control points extracted from the GRI dataset. The net adjustments to each of the four blocks, namely, Australia, Americas, Eurasia, and Islands, varied anywhere from 1 to 13 m, depending on the accuracy of the GCPs in these blocks. The use of the GRI dataset in our bundle adjustment not only improved the absolute accuracy of the Landsat ground reference, but will also improve the co-registration between Sentinel-2 and Landsat terrain corrected products, as the European Space Agency plans to process the Sentinel-2 products using the GRI dataset. Independent validation of the Landsat products processed using harmonized GCPs with the GRI dataset indicated a global misregistration error of less than 8 m Circular Error Probable at 90 % (CE90), an improvement from the 25 m prior to harmonization. The improvements to the Landsat products using the harmonized GCPs are expected to be available to the public as part of Landsat Collection-2 processing by the end of 2020. Full article
(This article belongs to the Special Issue Cross-Calibration and Interoperability of Remote Sensing Instruments)
Show Figures

Graphical abstract

36 pages, 22908 KiB  
Article
An Empirical Radiometric Intercomparison Methodology Based on Global Simultaneous Nadir Overpasses Applied to Landsat 8 and Sentinel-2
by Jorge Gil, Juan Fernando Rodrigo, Pablo Salvador, Diego Gómez, Julia Sanz and Jose Luis Casanova
Remote Sens. 2020, 12(17), 2736; https://doi.org/10.3390/rs12172736 - 24 Aug 2020
Cited by 5 | Viewed by 3776
Abstract
The Simultaneous Nadir Overpass (SNO) method was developed by the NOAA/NESDIS to improve the consistency and quality of climate data acquired by different meteorological satellites. Taking advantage of the reduced impact induced by the Bidirectional Reflectance Distribution Function (BRDF), atmospheric effects, illumination and [...] Read more.
The Simultaneous Nadir Overpass (SNO) method was developed by the NOAA/NESDIS to improve the consistency and quality of climate data acquired by different meteorological satellites. Taking advantage of the reduced impact induced by the Bidirectional Reflectance Distribution Function (BRDF), atmospheric effects, illumination and viewing geometries during an SNO, we created a sensor comparison methodology for all spectral targets. The method is illustrated by applying it to the assessment of data acquired by the Landsat 8 (L8), Sentinel-2A (S2A), and Sentinel-2B (S2B) optical sensors. Multiple SNOs were identified and selected without the need for orbit propagators. Then, by locating spatially homogeneous areas, it was possible to assess, for a wide range of Top-of-Atmosphere reflectance values, the relationship between the L8 bands and the corresponding ones of S2A and S2B. The results yield high coefficients of determination for S2 A/B with respect to L8. All are higher than 0.980 for S2A and 0.984 for S2B. If the S2 band 8 (wide near-infrared, NIR) is excluded then the lowest coefficients of determination become 0.997 and 0.999 from S2A and S2B, respectively. This methodology can be complementary to those based on Pseudo-Invariant Calibration Sites (PICS) due to its simplicity, highly correlated results and the wide range of compared reflectances and spectral targets. Full article
(This article belongs to the Special Issue Cross-Calibration and Interoperability of Remote Sensing Instruments)
Show Figures

Graphical abstract

20 pages, 7278 KiB  
Article
Benefits and Lessons Learned from the Sentinel-3 Tandem Phase
by Sébastien Clerc, Craig Donlon, Franck Borde, Nicolas Lamquin, Samuel E. Hunt, Dave Smith, Malcolm McMillan, Jonathan Mittaz, Emma Woolliams, Matthew Hammond, Christopher Banks, Thomas Moreau, Bruno Picard, Matthias Raynal, Pierre Rieu and Adrien Guérou
Remote Sens. 2020, 12(17), 2668; https://doi.org/10.3390/rs12172668 - 19 Aug 2020
Cited by 20 | Viewed by 4610
Abstract
During its commissioning phase, the Copernicus Sentinel-3B satellite has been placed in a tandem formation with Sentinel-3A for a period of 6 months. This configuration allowed a direct comparison of measurements obtained by the two satellites. The purpose of this paper was to [...] Read more.
During its commissioning phase, the Copernicus Sentinel-3B satellite has been placed in a tandem formation with Sentinel-3A for a period of 6 months. This configuration allowed a direct comparison of measurements obtained by the two satellites. The purpose of this paper was to present the range of analyses that can be performed from this dataset, highlighting methodology aspects and the main outcomes for each instrument. We examined, in turn, the benefit of the tandem in understanding instrument operational modes differences, in assessing inter-satellite differences, and in validating measurement uncertainties. The results highlighted the very good consistency of the Sentinel-3A and B instruments, ensuring the complete inter-operability of the constellation. Tandem comparisons also pave the way for further improvements through harmonization of the sensors (OLCI), correction of internal stray-light sources (SLSTR), or high-frequency processing of SRAL SARM data. This paper provided a comprehensive overview of the main results obtained, as well as insights into some of the results. Finally, we drew the main lessons learned from the Sentinel-3 tandem phase and provided recommendations for future missions. Full article
(This article belongs to the Special Issue Cross-Calibration and Interoperability of Remote Sensing Instruments)
Show Figures

Graphical abstract

17 pages, 6107 KiB  
Article
Orbital Lifetime (2008–2017) Radiometric Calibration and Evaluation of the HJ-1B IRS Thermal Infrared Band
by Wanyue Liu, Jiaguo Li, Qijin Han, Li Zhu, Hongyan Yang and Qiuming Cheng
Remote Sens. 2020, 12(15), 2362; https://doi.org/10.3390/rs12152362 - 23 Jul 2020
Cited by 6 | Viewed by 2168
Abstract
The infrared sensor (IRS) is a payload on the HJ-1B satellite and includes a thermal infrared band (B08). In order to obtain radiometric calibration coefficients and evaluate annual change, this study performed an analysis covering its 10-year orbital lifetime (2008–2017). The cross-calibration of [...] Read more.
The infrared sensor (IRS) is a payload on the HJ-1B satellite and includes a thermal infrared band (B08). In order to obtain radiometric calibration coefficients and evaluate annual change, this study performed an analysis covering its 10-year orbital lifetime (2008–2017). The cross-calibration of IRS B08 with MODIS was performed using near-simultaneous images over Lake Qinghai, China. The results reveal that the radiometric response of IRS B08 notably changed during its orbital lifetime from year-to-year. The offsets fluctuated more than the gain. The top-of-atmosphere (TOA) radiance obtained by calibration coefficients in this study was generally in agreement with those obtained by onboard calibrator, within an error range of ±4.00% from 2008 to 2012. The percent difference compared with field validation was within 1.63%. The difference between IRS and MODIS radiance over field validation sites was within ±5%. Approximately a 1% difference occurred between the TOA temperature of IRS and MODIS. The radiometric response of IRS B08 continuously decreased from 2008 to 2013, whereas it fluctuated from 2014 to 2017. Moreover, the DN fluctuated more when the at-aperture radiance was low, although it was more stable at higher radiance. Full article
(This article belongs to the Special Issue Cross-Calibration and Interoperability of Remote Sensing Instruments)
Show Figures

Graphical abstract

20 pages, 4930 KiB  
Article
Radiometric Cross Calibration and Validation Using 4 Angle BRDF Model between Landsat 8 and Sentinel 2A
by M M Farhad, Morakot Kaewmanee, Larry Leigh and Dennis Helder
Remote Sens. 2020, 12(5), 806; https://doi.org/10.3390/rs12050806 - 2 Mar 2020
Cited by 20 | Viewed by 4658
Abstract
This work describes a proposed radiometric cross calibration between the Landsat 8 Operational Land Imager (OLI) and Sentinel 2A Multispectral Instrument (MSI) sensors. The cross-calibration procedure involves (i) correction of the MSI data to account for spectral band differences with OLI and (ii) [...] Read more.
This work describes a proposed radiometric cross calibration between the Landsat 8 Operational Land Imager (OLI) and Sentinel 2A Multispectral Instrument (MSI) sensors. The cross-calibration procedure involves (i) correction of the MSI data to account for spectral band differences with OLI and (ii) normalization of Bidirectional Reflectance Distribution Function (BRDF) effects in the data from both sensors using a new model accounting for the view zenith/azimuth angles in addition to the solar zenith/view angles. Following application of the spectral and BRDF normalization, standard least-squares linear regression is used to determine the cross-calibration gain and offset in each band. Uncertainties related to each step in the proposed process are determined, as is the overall uncertainty associated with the complete processing sequence. Validation of the proposed cross-calibration gains and offsets is performed on image data acquired over the Algodones Dunes site. The results of this work indicate that the blue band has the most significant offset, requiring use of the estimated cross-calibration offset in addition to the estimated gain. The highest difference was observed in the blue and red bands, which are 2.6% and 1.4%, respectively, while other bands shows no significant difference. Overall, the net uncertainty in the proposed process was estimated to be on the order of 6.76%, with the largest uncertainty component due to each sensor’s calibration uncertainty on the order of 5% and 3% for the MSI and OLI, respectively. Other significant contributions to the uncertainty include seasonal changes in solar zenith and azimuth angles, target site nonuniformity, variability in atmospheric water vapor, and/or aerosol concentration. Full article
(This article belongs to the Special Issue Cross-Calibration and Interoperability of Remote Sensing Instruments)
Show Figures

Graphical abstract

21 pages, 8355 KiB  
Article
In-Flight Radiometric Calibration of Compact Infrared Camera (CIRC) Instruments Onboard ALOS-2 Satellite and International Space Station
by Hideyuki Tonooka, Michito Sakai, Ayaka Kumeta and Koji Nakau
Remote Sens. 2020, 12(1), 58; https://doi.org/10.3390/rs12010058 - 22 Dec 2019
Cited by 4 | Viewed by 4107
Abstract
The Compact Infrared Camera (CIRC) instruments onboard the Advanced Land Observing Satellite-2 (ALOS-2) and the Calorimetric Electron Telescope (CALET) attached to the International Space Station are satellite-borne 2D-array thermal infrared cameras for technical demonstrations in fields such as forest fire monitoring, volcano monitoring, [...] Read more.
The Compact Infrared Camera (CIRC) instruments onboard the Advanced Land Observing Satellite-2 (ALOS-2) and the Calorimetric Electron Telescope (CALET) attached to the International Space Station are satellite-borne 2D-array thermal infrared cameras for technical demonstrations in fields such as forest fire monitoring, volcano monitoring, and heat island analysis. Since they have the characteristics of low cost and low power consumption and have no onboard calibrator such as a blackbody or shutter, in-flight calibration should be performed by vicarious calibration (VC) and cross-calibration (CC). In this study, we determined the recalibration coefficients for both of the CIRC instruments as a function of time based on VC experiments in Lake Kasumigaura (Japan) and Railroad Valley Playa (USA), VC with telemetry data from three lakes in Japan and the USA, and CC with imagers onboard two geostationary satellites (MTSAT-2 and Himawari-8). As a result, the derived recalibration coefficients improved the accuracy of the ground-testing-based radiance remarkably in both of the CIRC instruments, suggesting that the recalibrated radiance can satisfy the target accuracy of CIRC, given as 2 K at 300 K. These coefficients, as a function of time, will be applied to all CIRC images by reprocessing planned in the near future. Full article
(This article belongs to the Special Issue Cross-Calibration and Interoperability of Remote Sensing Instruments)
Show Figures

Graphical abstract

19 pages, 8542 KiB  
Article
Analysis of Spatial and Temporal Variability in Libya-4 with Landsat 8 and Sentinel-2 Data for Optimized Ground Target Location
by Juan Fernando Rodrigo, Jorge Gil, Pablo Salvador, Diego Gómez, Julia Sanz and Jose Luis Casanova
Remote Sens. 2019, 11(24), 2909; https://doi.org/10.3390/rs11242909 - 5 Dec 2019
Cited by 3 | Viewed by 3726
Abstract
Pseudo-Invariant Calibration Sites (PICS) have been widely used by the remote sensing community in recent decades for post-launch absolute calibration, cross-calibration, and the monitoring of radiometric stability. The Committee on Earth Observation Satellites (CEOS) has established several official PICS for these purposes. Of [...] Read more.
Pseudo-Invariant Calibration Sites (PICS) have been widely used by the remote sensing community in recent decades for post-launch absolute calibration, cross-calibration, and the monitoring of radiometric stability. The Committee on Earth Observation Satellites (CEOS) has established several official PICS for these purposes. Of these, Libya-4 is the most commonly used, due to its high uniformity and stability. The site was chosen as a large-area site for medium resolution sensors, and with high-resolution sensors now common, smaller sites are being identified. This work has identified an improved area of interest (AOI) within Libya-4 by using combined Landsat 8 and Sentinel 2 data. The Optimized Ground Target (OGT) was determined by calculating the coefficient of variation along with the use of a quasi-Newton optimization algorithm combined with the Basin–Hopping global optimization technique to constrain a search area small enough to perform a final brute-force refinement. The Coefficient of Variation CV of the proposed OGT is significantly lower than that in the original CEOS area, with differences between the CV of both zones in the order of 1% in the visible near-infrared (VNIR) bands. This new AOI has the potential to improve the cross-calibration between high-resolution sensors using the PICS methodology through an OGT with more homogeneous and stable characteristics. Full article
(This article belongs to the Special Issue Cross-Calibration and Interoperability of Remote Sensing Instruments)
Show Figures

Graphical abstract

33 pages, 67626 KiB  
Article
Derivation of Hyperspectral Profile of Extended Pseudo Invariant Calibration Sites (EPICS) for Use in Sensor Calibration
by Mahesh Shrestha, Nahid Hasan, Larry Leigh and Dennis Helder
Remote Sens. 2019, 11(19), 2279; https://doi.org/10.3390/rs11192279 - 29 Sep 2019
Cited by 9 | Viewed by 3136
Abstract
Reference of Earth-observing satellite sensor data to a common, consistent radiometric scale is an increasingly critical issue as more of these sensors are launched; such consistency can be achieved through radiometric cross-calibration of the sensors. A common cross-calibration approach uses a small set [...] Read more.
Reference of Earth-observing satellite sensor data to a common, consistent radiometric scale is an increasingly critical issue as more of these sensors are launched; such consistency can be achieved through radiometric cross-calibration of the sensors. A common cross-calibration approach uses a small set of regions of interest (ROIs) in established Pseudo-Invariant Calibration Sites (PICS) mainly located throughout North Africa. The number of available cloud-free coincident scene pairs available for these regions limits the usefulness of this approach; furthermore, the temporal stability of most regions throughout North Africa is not known, and limited hyperspectral information exists for these regions. As a result, it takes more time to construct an appropriate cross-calibration dataset. In a previous work, Shrestha et al. presented an analysis identifying 19 distinct “clusters” of spectrally similar surface cover that are widely distributed across North Africa, with the potential to provide near-daily cloud-free imaging for most sensors. This paper proposes a technique to generate a representative hyperspectral profile for these clusters. The technique was used to generate the profile for the cluster containing the largest number of aggregated pixels. The resulting profile was found to have temporal uncertainties within 5% across all the spectral regions. Overall, this technique shows great potential for generation of representative hyperspectral profiles for any North African cluster, which could allow the use of the entire North Africa Saharan region as an extended PICS (EPICS) dataset for sensor cross-calibration. This should result in the increased temporal resolution of cross-calibration datasets and should help to achieve a cross-calibration quality similar to that of individual PICS in a significantly shorter time interval. It also facilitates the development of an EPICS based absolute calibration model, which can improve the accuracy and consistency in simulating any sensor’s top of atmosphere (TOA) reflectance. Full article
(This article belongs to the Special Issue Cross-Calibration and Interoperability of Remote Sensing Instruments)
Show Figures

Graphical abstract

24 pages, 6067 KiB  
Article
Evaluation of an Extended PICS (EPICS) for Calibration and Stability Monitoring of Optical Satellite Sensors
by Md Nahid Hasan, Mahesh Shrestha, Larry Leigh and Dennis Helder
Remote Sens. 2019, 11(15), 1755; https://doi.org/10.3390/rs11151755 - 25 Jul 2019
Cited by 12 | Viewed by 3395
Abstract
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 [...] Read more.
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. Full article
(This article belongs to the Special Issue Cross-Calibration and Interoperability of Remote Sensing Instruments)
Show Figures

Graphical abstract

18 pages, 4813 KiB  
Article
Developing Transformation Functions for VENμS and Sentinel-2 Surface Reflectance over Israel
by V.S. Manivasagam, Gregoriy Kaplan and Offer Rozenstein
Remote Sens. 2019, 11(14), 1710; https://doi.org/10.3390/rs11141710 - 19 Jul 2019
Cited by 21 | Viewed by 6586
Abstract
Vegetation and Environmental New micro Spacecraft (VENμS) and Sentinel-2 are both ongoing earth observation missions that provide high-resolution multispectral imagery at 10 m (VENμS) and 10–20 m (Sentinel-2), at relatively high revisit frequencies (two days for VENμS and five days for Sentinel-2). Sentinel-2 [...] Read more.
Vegetation and Environmental New micro Spacecraft (VENμS) and Sentinel-2 are both ongoing earth observation missions that provide high-resolution multispectral imagery at 10 m (VENμS) and 10–20 m (Sentinel-2), at relatively high revisit frequencies (two days for VENμS and five days for Sentinel-2). Sentinel-2 provides global coverage, whereas VENμS covers selected regions, including parts of Israel. To facilitate the combination of these sensors into a unified time-series, a transformation model between them was developed using imagery from the region of interest. For this purpose, same-day acquisitions from both sensor types covering the surface reflectance over Israel, between April 2018 and November 2018, were used in this study. Transformation coefficients from VENμS to Sentinel-2 surface reflectance were produced for their overlapping spectral bands (i.e., visible, red-edge and near-infrared). The performance of these spectral transformation functions was assessed using several methods, including orthogonal distance regression (ODR), the mean absolute difference (MAD), and spectral angle mapper (SAM). Post-transformation, the value of the ODR slopes were close to unity for the transformed VENμS reflectance with Sentinel-2 reflectance, which indicates near-identity of the two datasets following the removal of systemic bias. In addition, the transformation outputs showed better spectral similarity compared to the original images, as indicated by the decrease in SAM from 0.093 to 0.071. Similarly, the MAD was reduced post-transformation in all bands (e.g., the blue band MAD decreased from 0.0238 to 0.0186, and in the NIR it decreased from 0.0491 to 0.0386). Thus, the model helps to combine the images from Sentinel-2 and VENμS into one time-series that facilitates continuous, temporally dense vegetation monitoring. Full article
(This article belongs to the Special Issue Cross-Calibration and Interoperability of Remote Sensing Instruments)
Show Figures

Graphical abstract

22 pages, 22058 KiB  
Article
Extended Pseudo Invariant Calibration Sites (EPICS) for the Cross-Calibration of Optical Satellite Sensors
by Mahesh Shrestha, Md. Nahid Hasan, Larry Leigh and Dennis Helder
Remote Sens. 2019, 11(14), 1676; https://doi.org/10.3390/rs11141676 - 14 Jul 2019
Cited by 11 | Viewed by 3619
Abstract
An increasing number of Earth-observing satellite sensors are being launched to meet the insatiable demand for timely and accurate data to aid the understanding of the Earth’s complex systems and to monitor significant changes to them. To make full use of the data [...] Read more.
An increasing number of Earth-observing satellite sensors are being launched to meet the insatiable demand for timely and accurate data to aid the understanding of the Earth’s complex systems and to monitor significant changes to them. To make full use of the data from these sensors, it is mandatory to bring them to a common radiometric scale through a cross-calibration approach. Commonly, cross-calibration data were acquired from selected pseudo-invariant calibration sites (PICS), located primarily throughout the Saharan desert in North Africa, determined to be temporally, spatially, and spectrally stable. The major limitation to this approach is that long periods of time are required to assemble sufficiently sampled cloud-free cross-calibration datasets. Recently, Shrestha et al. identified extended, cluster-based sites potentially suitable for PICS-based cross-calibration and estimated representative hyperspectral profiles for them. This work investigates the performance of extended pseudo-invariant calibration sites (EPICS) in cross-calibration for one of Shrestha’s clusters, Cluster 13, by comparing its results to those obtained from a traditional PICS-based cross-calibration. The use of EPICS clusters can significantly increase the number of cross-calibration opportunities within a much shorter time period. The cross-calibration gain ratio estimated using a cluster-based approach had a similar accuracy to the cross-calibration gain derived from region of interest (ROI)-based approaches. The cluster-based cross-calibration gain ratio is consistent within approximately 2% of the ROI-based cross-calibration gain ratio for all bands except for the coastal and shortwave-infrared (SWIR) 2 bands. These results show that image data from any region within Cluster 13 can be used for sensor cross-calibration. Full article
(This article belongs to the Special Issue Cross-Calibration and Interoperability of Remote Sensing Instruments)
Show Figures

Graphical abstract

25 pages, 2111 KiB  
Article
Bundle Adjustment Using Space-Based Triangulation Method for Improving the Landsat Global Ground Reference
by James C. Storey, Rajagopalan Rengarajan and Michael J. Choate
Remote Sens. 2019, 11(14), 1640; https://doi.org/10.3390/rs11141640 - 10 Jul 2019
Cited by 26 | Viewed by 8476
Abstract
There is an ever-increasing interest and need for accurate georegistration of remotely sensed data products to a common global geometric reference. Although georegistration has improved substantially in the last decade, the lack of an accurate global ground reference dataset poses serious issues for [...] Read more.
There is an ever-increasing interest and need for accurate georegistration of remotely sensed data products to a common global geometric reference. Although georegistration has improved substantially in the last decade, the lack of an accurate global ground reference dataset poses serious issues for data providers seeking to make geometrically stackable analysis-ready data. The existing Global Land Survey 2000 (GLS2000) dataset derived from Landsat 7 images provides global coverage and can be used as a reference dataset, but its accuracy is much lower than what can be attained using the agile and precise pointing capability of the new spacecrafts. The improved position and pointing knowledge of the new spacecrafts such as Landsat 8 can be used to improve the accuracy of the existing global ground control points using a space-based triangulation method. This paper discusses the theoretical basis, formulation, and application of the space-based triangulation method at a continental scale to improve the accuracy of the GLS-derived ground control points. Our triangulation method involves adjusting the spacecraft position, velocity, attitude, attitude rate, and ground control point locations, iteratively, by linearizing the non-linear viewing geometry, such that the residual errors in the measured image points are minimized. The complexity of the numerical inversion and processing is dealt with in our approach by processing and eliminating the ground points one at a time. This helps to reduce the size of the normal matrix significantly, thereby making the triangulation of a continent-wide scale block feasible and efficient. One of the unique characteristics of our method is the use of a correlation model linking the attitude corrections between images of the same pass, which promotes consistency in the attitude corrections. We evaluated the performance of our triangulation method over the Australian continent using the Australian Geographic Reference Image (AGRI) dataset as a reference. Both a free adjustment, using only the pointing information of the Landsat 8 spacecraft, and a constrained adjustment using the AGRI as external control were performed and the results compared. The Australian block’s horizontal accuracy improved from 15.4 m to 3.6 m with the use of AGRI controls and from 15.4 m to 8.8 m without the use of AGRI controls. Full article
(This article belongs to the Special Issue Cross-Calibration and Interoperability of Remote Sensing Instruments)
Show Figures

Figure 1

26 pages, 10113 KiB  
Article
Methods for Earth-Observing Satellite Surface Reflectance Validation
by Moe Badawi, Dennis Helder, Larry Leigh and Xin Jing
Remote Sens. 2019, 11(13), 1543; https://doi.org/10.3390/rs11131543 - 28 Jun 2019
Cited by 23 | Viewed by 6516
Abstract
In this study an initial validation of the Landsat 8 (L8) Operational Land Imager (OLI) Surface Reflectance (SR) product was performed. The OLI SR product is derived from the L8 Top-of-Atmosphere product via the Landsat Surface Reflectance Code (LaSRC) software and generated by [...] Read more.
In this study an initial validation of the Landsat 8 (L8) Operational Land Imager (OLI) Surface Reflectance (SR) product was performed. The OLI SR product is derived from the L8 Top-of-Atmosphere product via the Landsat Surface Reflectance Code (LaSRC) software and generated by the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center. The goal of this study is to develop and evaluate proper validation methodology for the OLI L2 SR product. Validation was performed using near-simultaneous ground truth SR measurements during Landsat 8 overpasses at 13 sites located in the U.S., Brazil, Chile and France. The ground truth measurements consisted of field spectrometer measurements, automated hyperspectral ground measurements operated by the Radiometric Calibration Network (RadCalNet) and derived SR measurements from Airborne Observation Platforms (AOP) operated by the National Ecological Observatory Network (NEON). The 13 sites cover a broad range of 0–0.5 surface reflectance units across the reflective solar spectrum. Results show that the mean reflectance difference between OLI L2 SR products and ground truth measurements for the 13 validation sites and all bands was under 2.5%. The largest uncertainties of 11% and 8% were found in the CA and Blue bands, respectively; whereas, the longer wavelength bands were within 4% or less. Results consistently indicated similarity between the OLI L2 SR product and ground truth data, especially in longer wavelengths over dark and bright targets, while less reliable performance was observed in shorter wavelengths and sparsely vegetated targets. Full article
(This article belongs to the Special Issue Cross-Calibration and Interoperability of Remote Sensing Instruments)
Show Figures

Graphical abstract

23 pages, 5353 KiB  
Article
New Approach for Temporal Stability Evaluation of Pseudo-Invariant Calibration Sites (PICS)
by Fatima Tuz Zafrin Tuli, Cibele Teixeira Pinto, Amit Angal, Xiaoxiong Xiong and Dennis Helder
Remote Sens. 2019, 11(12), 1502; https://doi.org/10.3390/rs11121502 - 25 Jun 2019
Cited by 17 | Viewed by 4820
Abstract
Pseudo-Invariant Calibration Sites (PICS) are one of the most popular methods for in-flight vicarious radiometric calibration of Earth remote sensing satellites. The fundamental question of PICS temporal stability has not been adequately addressed. However, the main purpose of this work is to evaluate [...] Read more.
Pseudo-Invariant Calibration Sites (PICS) are one of the most popular methods for in-flight vicarious radiometric calibration of Earth remote sensing satellites. The fundamental question of PICS temporal stability has not been adequately addressed. However, the main purpose of this work is to evaluate the temporal stability of a few PICS using a new approach. The analysis was performed over six PICS (Libya 1, Libya 4, Niger 1, Niger 2, Egypt 1 and Sudan 1). The concept of a “Virtual Constellation” was developed to provide greater temporal coverage and also to overcome the dependence limitation of any specific characteristic derived from one particular sensor. TOA reflectance data from four sensors consistently demonstrating “stable” calibration to within 5%—the Landsat 7 ETM+ (Enhanced Thematic Mapper Plus), Landsat 8 OLI (Operational Land Imager), Terra MODIS (Moderate Resolution Imaging Spectroradiometer) and Sentinel-2A MSI (Multispectral Instrument)–were merged into a seamless dataset. Instead of using the traditional method of trend analysis (Student’s T test), a nonparametric Seasonal Mann-Kendall test was used for determining the PICS stability. The analysis results indicate that Libya 4 and Egypt 1 do not exhibit any monotonic trend in six reflective solar bands common to all of the studied sensors, indicating temporal stability. A decreasing monotonic trend was statistically detected in all bands, except SWIR 2, for Sudan 1 and the Green and Red bands for Niger 1. An increasing trend was detected in the Blue band for Niger 2 and the NIR band for Libya 1. These results do not suggest abandoning PICS as a viable calibration source. Rather, they indicate that PICS temporal stability cannot be assumed and should be regularly monitored as part of the sensor calibration process. Full article
(This article belongs to the Special Issue Cross-Calibration and Interoperability of Remote Sensing Instruments)
Show Figures

Graphical abstract

Other

Jump to: Research

22 pages, 4864 KiB  
Technical Note
Calibrating Geosynchronous and Polar Orbiting Satellites: Sharing Best Practices
by Dennis Helder, David Doelling, Rajendra Bhatt, Taeyoung Choi and Julia Barsi
Remote Sens. 2020, 12(17), 2786; https://doi.org/10.3390/rs12172786 - 27 Aug 2020
Cited by 6 | Viewed by 4535
Abstract
Earth remote sensing optical satellite systems are often divided into two categories—geosynchronous and sun-synchronous. Geosynchronous systems essentially rotate with the Earth and continuously observe the same region of the Earth. Sun-synchronous systems are generally in a polar orbit and view differing regions of [...] Read more.
Earth remote sensing optical satellite systems are often divided into two categories—geosynchronous and sun-synchronous. Geosynchronous systems essentially rotate with the Earth and continuously observe the same region of the Earth. Sun-synchronous systems are generally in a polar orbit and view differing regions of the Earth at the same local time. Although similar in instrument design, there are enough differences in these two types of missions that often the calibration of the instruments can be substantially different. Thus, respective calibration teams develop independent methods and do not interact regularly or often. Yet, there are numerous areas of overlap and much to learn from one another. To address this issue, a panel of experts from both types of systems was convened to discover common areas of concern, areas where improvements can be made, and recommendations for the future. As a result of the panelist’s efforts, a set of eight recommendations were developed. Those that are related to improvements of current technologies include maintaining sun-synchronous orbits (not allowing orbital decay), standardization of spectral bandpasses, and expanded use of well-developed calibration techniques such as deep convective clouds, pseudo invariant calibration sites, and lunar methodologies. New techniques for expanded calibration capability include using geosynchronous instruments as transfer radiometers, continued development of ground-based prelaunch calibration technologies, expansion of RadCalNet, and development of space-based calibration radiometer systems. Full article
(This article belongs to the Special Issue Cross-Calibration and Interoperability of Remote Sensing Instruments)
Show Figures

Graphical abstract

17 pages, 3352 KiB  
Technical Note
Observations and Recommendations for Coordinated Calibration Activities of Government and Commercial Optical Satellite Systems
by Dennis Helder, Cody Anderson, Keith Beckett, Rasmus Houborg, Ignacio Zuleta, Valentina Boccia, Sebastien Clerc, Michele Kuester, Brian Markham and Mary Pagnutti
Remote Sens. 2020, 12(15), 2468; https://doi.org/10.3390/rs12152468 - 31 Jul 2020
Cited by 14 | Viewed by 4176
Abstract
One of the biggest changes in the world of optical remote sensing over the last several years is the sheer increase in the number of sensors that are imaging the Earth in moderate to high spatial resolution. With respect to the calibration of [...] Read more.
One of the biggest changes in the world of optical remote sensing over the last several years is the sheer increase in the number of sensors that are imaging the Earth in moderate to high spatial resolution. With respect to the calibration of these sensors, they are broadly classified into two types, namely government systems and commercial systems. Because of the differences in the design and mission of these sensor types, calibration approaches are often substantially different. Thus, an opportunity exists to foster discussion between calibration teams for these sensors with the goal of improving overall sensor calibration and data interoperability. The approach used to accomplish this task was a one-day workshop where team members from both government and commercial sensors could share best practices, discuss methods for collaboration and improvement, and make recommendations for continuing activities. Five major recommendations were developed from the event that focused on coordinated activities using pseudo invariant calibration sites (PICS), broader and more consistent communication, collaboration on specific cross-calibration opportunities, developing a reference sensor for all optical systems, and encouraging the coordinated development of surface reflectance products. Workshop participants concluded that regular interactions between these teams could foster a better calibration of all sensor systems and accelerate the improved interoperability of surface products. Full article
(This article belongs to the Special Issue Cross-Calibration and Interoperability of Remote Sensing Instruments)
Show Figures

Graphical abstract

Back to TopTop