170 research outputs found

    Absolute Calibration of Optical Satellite Sensors Using Libya 4 Pseudo Invariant Calibration Site

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    The objective of this paper is to report the improvements in an empirical absolute calibration model developed at South Dakota State University using Libya 4 (+28.55 deg, +23.39 deg) pseudo invariant calibration site (PICS). The approach was based on use of the Terra MODIS as the radiometer to develop an absolute calibration model for the spectral channels covered by this instrument from visible to shortwave infrared. Earth Observing One (EO-1) Hyperion, with a spectral resolution of 10 nm, was used to extend the model to cover visible and near-infrared regions. A simple Bidirectional Reflectance Distribution function (BRDF) model was generated using Terra Moderate Resolution Imaging Spectroradiometer (MODIS) observations over Libya 4 and the resulting model was validated with nadir data acquired from satellite sensors such as Aqua MODIS and Landsat 7 (L7) Enhanced Thematic Mapper (ETM+). The improvements in the absolute calibration model to account for the BRDF due to off-nadir measurements and annual variations in the atmosphere are summarized. BRDF models due to off-nadir viewing angles have been derived using the measurements from EO-1 Hyperion. In addition to L7 ETM+, measurements from other sensors such as Aqua MODIS, UK-2 Disaster Monitoring Constellation (DMC), ENVISAT Medium Resolution Imaging Spectrometer (MERIS) and Operational Land Imager (OLI) onboard Landsat 8 (L8), which was launched in February 2013, were employed to validate the model. These satellite sensors differ in terms of the width of their spectral bandpasses, overpass time, off-nadir-viewing capabilities, spatial resolution and temporal revisit time, etc. The results demonstrate that the proposed empirical calibration model has accuracy of the order of 3% with an uncertainty of about 2% for the sensors used in the study

    New Approach for Temporal Stability Evaluation of Pseudo-Invariant Calibration Sites (PICS)

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    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 (Students 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

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

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    An increasing number of Earth-observing satellite sensors are being launched to meet the insatiable demand for timely and accurate data to help the understanding of the Earth’s complex systems and to monitor significant changes to them. The quality of data recorded by these sensors is a primary concern, as it critically depends on accurate radiometric calibration for each sensor. Pseudo Invariant Calibration Sites (PICS) have been extensively used for 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; 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. In addition, this work proposes a technique to generate a representative hyperspectral profile for these clusters, as the hyperspectral profile of these identified clusters are mandatory in order to utilize them for performing cross-calibration of optical satellite sensors. 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. Furthermore, 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 crosscalibration. Eventually, North Africa can be used a continental scale PICS

    Vicarious Methodologies to Assess and Improve the Quality of the Optical Remote Sensing Images: A Critical Review

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    Over the past decade, number of optical Earth observing satellites performing remote sensing has increased substantially, dramatically increasing the capability to monitor the Earth. The quantity of remote sensing satellite increase is primarily driven by improved technology, miniaturization of components, reduced manufacturing, and launch cost. These satellites often lack on-board calibrators that a large satellite utilizes to ensure high quality (e.g., radiometric, geometric, spatial quality, etc.) scientific measurement. To address this issue, this work presents “best” vicarious image quality assessment and improvement techniques for those kinds of optical satellites which lacks on-board calibration system. In this article, image quality categories have been explored, and essential quality parameters (e.g., absolute and relative calibration, aliasing, etc.) have been identified. For each of the parameters, appropriate characterization methods are identified along with its specifications or requirements. In cases of multiple methods, recommendation has been made based-on the strengths and weaknesses of each method. Furthermore, processing steps have been presented, including examples. Essentially, this paper provides a comprehensive study of the criteria that needs to be assessed to evaluate remote sensing satellite data quality, and best vicarious methodologies to evaluate identified quality parameters such as coherent noise, ground sample distance, etc

    Extended Pseudo Invariant Calibration Site-Based Trend-To-Trend Cross-Calibration of Optical Satellite Sensors

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    Satellite sensors have been extremely useful and are in massive demand in the understanding of the Earth’s surface and monitoring of changes. For quantitative analysis and acquiring consistent measurements, absolute radiometric calibration is necessary. The most common vicarious approach of radiometric calibration is cross-calibration, which helps to tie all the sensors to a common radiometric scale for consistent measurement. One of the traditional methods of cross-calibration is performed using temporally and spectrally stable pseudo-invariant calibration sites (PICS). This technique is limited by adequate cloud-free acquisitions for cross-calibration which would require a longer time to study the differences in sensor measurements. To address the limitation of traditional PICS-based approaches and to increase the cross-calibration opportunity for quickly achieving highquality results, the approach is based on using extended pseudo invariant calibration sites (EPICS) over North Africa. With the EPICS-based approach, the area of extent of the cross-calibration site covers a large portion of the North African continent. With targets this large, any sensor should overpass some portion of PICS near-daily, allowing for evaluation of sensor-to-sensor performance with much greater frequency. By using these near-daily measurements, trends of the sensor’s performance are then used to evaluate sensor-to-sensor daily cross-calibration. With the use of the proposed methodology, the dataset for cross-calibration is increased by an order of magnitude compared to traditional approaches, resulting in the differences between any two sensors being detected within a much shorter time. Using this new trend in trend cross-calibration approaches, gains were evaluated for Landsat 7/8 and Sentinel 2A/B, with the results showing that the sensors are calibrated within 2.5% (within less than 8% uncertainty) or better for all sensor pairs, which is consistent with what the traditional PICS-based approach detects. The proposed crosscalibration technique is useful to cross-calibrate any two sensors without the requirement of any coincident or near-coincident scene pairs, while still achieving results similar to traditional approaches in a short time

    Hyperspectral Empirical Absolute Calibration Model Using Libya 4 Pseudo-Invariant Calibration Site

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    The objective of this paper is to find an empirical hyperspectral absolute calibration model using Libya 4 pseudo-invariant calibration site (PICS). The approach involves using the Landsat 8 (L8) Operational Land Imager (OLI) as the reference radiometer and using Earth Observing One (EO-1) Hyperion, with a spectral resolution of 10 nm as a hyperspectral source. This model utilizes data from a region of interest (ROI) in an “optimal region” of 3% temporal, spatial, and spectral stability within the Libya 4 PICS. It uses an improved, simple, empirical, hyperspectral Bidirectional Reflectance Distribution function (BRDF) model accounting for four angles: solar zenith and azimuth, and view zenith and azimuth angles. This model can perform absolute calibration in 1 nm spectral resolution by predicting TOA reflectance in all existing spectral bands of the sensors. The resultant model was validated with image data acquired from satellite sensors such as Landsat 7, Sentinel 2A, and Sentinel 2B, Terra MODIS, Aqua MODIS, from their launch date to 2020. These satellite sensors differ in terms of the width of their spectral band-pass, overpass time, off-nadir viewing capabilities, spatial resolution, and temporal revisit time, etc. The result demonstrates the efficacy of the proposed model has an accuracy of the order of 3% with a precision of about 3% for the nadir viewing sensors (with view zenith angle up to 5°) used in the study. For the off-nadir viewing satellites with view zenith angle up to 20°, it can have an estimated accuracy of 6% and precision of 4%

    The Development of Dark Hyperspectral Absolute Calibration Model Using Extended Pseudo Invariant Calibration Sites at a Global Scale: Dark EPICS-Global

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    This research aimed to develop a novel dark hyperspectral absolute calibration (DAHAC) model using stable dark targets of Global Cluster - 36 (GC-36), one of the clusters from 300 Class Global Classification. The stable dark sites were identified from GC-36 called Dark EPICS-Global covering the surface types viz; dark rock, volcanic area, and dark sand. The Dark EPICS-Global shows a temporal variation of 0.02 unit reflectance. This work uses the Landsat-8 (L8) Operational Land Imager (OLI) , Sentinel-2A (S2A) Multispectral Instrument (MSI) , and Earth Observing One (EO-1) Hyperion data for the DAHAC model development, where well-calibrated L8 and S2A are used as the reference sensors while EO-1 Hyperion with 10 nm spectral resolution is used as a hyperspectral library. The dark hyperspectral dataset (DaHD) is generated by combining the normalized hyperspectral profile of L8 and S2A for the DAHAC model development. The DAHAC model developed in this study takes into account the solar zenith and azimuth angles as well as the view zenith and azimuth angles in Cartesian coordinates form. This model is capable of predicting TOA reflectance in all existing spectral bands of any sensor. The DAHAC model was then validated with Landsat-7 (L7) , Landsat-9 (L9) , and Sentinel-2B (S2B) satellites from their launch dates to March 2022. These satellite sensors vary in terms of their spectral resolution, equatorial crossing time, spatial resolution, etc. The comparison between the DAHAC model and satellite measurements shows accuracy within 0.01 unit reflectance across overall spectral bands. The proposed DAHAC model uncertainty level is determined using Monte Carlo Simulation and found to be 0.04 and 0.05 unit reflectance for VNIR and SWIR channels, respectively. The DAHAC model double ratio is used as a tool to perform the inter-comparison between two satellites. The sensor inter-comparison results for L8 and L9 shows a 2% difference and 1% for S2A and S2B across all spectral bands

    Detection of Change Points in Pseudo-Invariant Calibration Sites Time Series Using Multi-Sensor Satellite Imagery

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    The remote sensing community has extensively used Pseudo-Invariant Calibration Sites (PICS) to monitor the long-term in-flight radiometric calibration of Earth-observing satellites. The use of the PICS has an underlying assumption that these sites are invariant over time. However, the site’s temporal stability has not been assured in the past. This work evaluates the temporal stability of PICS by not only detecting the trend but also locating significant shifts (change points) lying behind the time series. A single time series was formed using the virtual constellation approach in which multiple sensors data were combined for each site to achieve denser temporal coverage and overcome the limitation of dependence related to a specific sensor. The sensors used for this work were selected based on radiometric calibration uncertainty and availability of the data: operational land imager (Landsat-8), enhanced thematic mapper (Landsat-7), moderate resolution imaging spectroradiometer (Terra and Aqua), and multispectral instrument (Sentinel-2A). An inverse variance weighting method was applied to the Top-of- Atmosphere (TOA) reflectance time series to reveal the underlying trend. The sequential Mann–Kendall test was employed upon the weighted TOA reflectance time-series recorded over 20 years to detect abrupt changes for six reflective bands. Statistically significant trends and abrupt changes have been detected for all sites, but the magnitude of the trends (maximum of 0.215% change in TOA reflectance per year) suggest that these sites are not changing substantially over time. Hence, it can be stated that despite minor changes in all evaluated PICS, they can be used for radiometric calibration of optical remote sensing sensors. The new approach provides useful results by revealing underlying trends and providing a better understanding of PICS\u27 stability

    Empirical Absolute Calibration Model for Multiple Pseudo-Invariant Calibration Sites

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    This work extends an empirical absolute calibration model initially developed for the Libya 4 Pseudo-Invariant Calibration Site (PICS) to five additional Saharan Desert PICS (Egypt 1, Libya 1, Niger 1, Niger 2, and Sudan 1), and demonstrates the efficacy of the resulting models at predicting sensor top-of-atmosphere (TOA) reflectance. It attempts to generate absolute calibration models for these PICS that have an accuracy and precision comparable to or better than the current Libya 4 model, with the intent of providing additional opportunities for sensor calibration. In addition, this work attempts to validate the general applicability of the model to other sites. The method uses Terra Moderate Resolution Imaging Spectroradiometer (MODIS) as the reference radiometer and Earth Observing-1 (EO-1) Hyperion image data to provide a representative hyperspectral reflectance profile of the PICS. Data from a region of interest (ROI) in an “optimal region” of 3% temporal, spatial, and spectral stability within the PICS are used for developing the model. The developed models were used to simulate observations of the Landsat 7 (L7) Enhanced Thematic Mapper Plus (ETM+), Landsat 8 (L8) Operational Land Imager (OLI), Sentinel 2A (S2A) Multispectral Instrument (MSI) and Sentinel 2B (S2B) Multispectral Instrument (MSI) from their respective launch date through 2018

    Validation of Expanded Trend-To-Trend Cross-Calibration Technique and its Application to Global Scale

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    The expanded Trend-to-Trend (T2T) cross-calibration technique has the potential to calibrate two sensors in much less time and provides trends on daily assessment basis. The trend obtained from the expanded technique aids in evaluating the differences between satellite sensors. Therefore, this technique was validated with several trusted cross-calibration techniques to evaluate its accuracy. Initially, the expanded T2T technique was validated with three independent RadcaTS RRV, DIMITRI-PICS, and APICS models, and results show a 1% average difference with other models over all bands. Further, this technique was validated with other SDSU techniques to calibrate the newly launched satellite Landsat 9 with 8, demonstrating good agreement in all bands within 0.5%. This technique was also validated for Terra MODIS and ETM+, showing consistency within 1% for all bands compared to four PICS sites. Additionally, the T2T technique was applied to a global scale using EPICS Global sites. The expanded T2T cross-calibration gain result obtained for Landsat 8 versus Landsat 7/9, Sentinel 2A/2B, and Terra/Aqua MODIS presented that the difference between these pairs was within 0.5- 1% for most of the spectral bands. Total uncertainty obtained for these pairs of sensors using Monte Carlo Simulation varies from 2.5-4% for all bands except for SWIR2 bands, which vary up to 5%. The difference between EPICS Global and EPICS North Africa was calculated using the ratio of trend gain; the difference among them was within 0.5-1% difference on average for all the sensors and bands within a 0.5% uncertainty level difference
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