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Junchang Ju - One of the best experts on this subject based on the ideXlab platform.
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a general method to normalize Landsat reflectance data to nadir brdf adjusted reflectance
Remote Sensing of Environment, 2016Co-Authors: Hankui K Zhang, Junchang Ju, Jose Gomezdans, P Lewis, Crystal B Schaaf, Jian Li, Haiyan Huang, Valeriy KovalskyyAbstract:Abstract The Landsat satellites have been providing spectacular imagery of the Earth's surface for over 40 years. However, they acquire images at view angles ± 7.5° from nadir that cause small directional effects in the surface reflectance. There are also variations with solar zenith angle over the year that can cause apparent change in reflectance even if the surface properties remain constant. When Landsat data from adjoining paths, or from long time series are used, a model of the surface anisotropy is required to adjust all Landsat observations to a uniform nadir view (primarily for visual consistency, vegetation monitoring, or detection of subtle surface changes). Here a generalized approach is developed to provide consistent view angle corrections across the Landsat archive. While this approach is not applicable for generation of Landsat surface albedo, which requires a full characterization of the surface bidirectional reflectance distribution function (BRDF), or for correction to a constant solar illumination angle across a wide range of sun angles, it provides Landsat nadir BRDF-adjusted reflectance (NBAR) for a range of terrestrial monitoring applications. The Landsat NBAR is derived as the product of the observed Landsat reflectance and the ratio of the reflectances modeled using MODIS BRDF spectral model parameters for the observed Landsat and for a nadir view and fixed solar zenith geometry. In this study, a total of 567 conterminous United States (CONUS) January and July 2010 Landsat 5 Thematic Mapper (TM) and Landsat 7 Enhanced Thematic Mapper (ETM +) images that have swath edge overlapping paths sensed in alternating backscatter and forward scattering orientations were used. The average difference between Landsat 5 TM and Landsat 7 ETM + surface reflectance in the forward and backward scatter directions at the overlapping Landsat scan edges was quantified. The CONUS July view zenith BRDF effects were about 0.02 in the Landsat visible bands, and about 0.03, 0.05 and 0.06, in the 2.1 μm, 1.6 μm and near-infrared bands respectively. Comparisons of Landsat 5 TM and Landsat 7 ETM + NBAR derived using MODIS BRDF spectral model parameters defined with respect to different spatial and temporal scales, and defined with respect to different land cover types, were undertaken. The results suggest that, because the BRDF shapes of different terrestrial surfaces are sufficiently similar over the narrow 15° Landsat field of view, a fixed set of MODIS BRDF spectral model parameters may be adequate for Landsat NBAR derivation with little sensitivity to the land cover type, condition, or surface disturbance. A fixed set of BRDF spectral model parameters, derived from a global year of highest quality snow-free MODIS BRDF product values, are provided so users may implement the described Landsat NBAR generation method.
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continental scale validation of modis based and ledaps Landsat etm atmospheric correction methods
Remote Sensing of Environment, 2012Co-Authors: Junchang Ju, Jeffrey G. Masek, Eric Vermote, Valeriy KovalskyyAbstract:Abstract The potential of Landsat data processing to provide systematic continental scale products has been demonstrated by several projects including the NASA Web-enabled Landsat Data (WELD) project. The recent free availability of Landsat data increases the need for robust and efficient atmospheric correction algorithms applicable to large volume Landsat data sets. This paper compares the accuracy of two Landsat atmospheric correction methods: a MODIS-based method and the Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) method. Both methods are based on the 6SV radiative transfer code but have different atmospheric characterization approaches. The MODIS-based method uses the MODIS Terra derived dynamic aerosol type, aerosol optical thickness, and water vapor to atmospherically correct ETM+ acquisitions in each coincident orbit. The LEDAPS method uses aerosol characterizations derived independently from each Landsat acquisition and assumes a fixed continental aerosol type and uses ancillary water vapor. Validation results are presented comparing ETM+ atmospherically corrected data generated using these two methods with AERONET corrected ETM+ data for 95 10 km × 10 km 30 m subsets, a total of nearly 8 million 30 m pixels, located across the conterminous United States. The results indicate that the MODIS-based method has better accuracy than the LEDAPS method for the ETM+ red and longer wavelength bands.
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the availability of cloud free Landsat etm data over the conterminous united states and globally
Remote Sensing of Environment, 2008Co-Authors: Junchang JuAbstract:Abstract The U.S. Landsat satellite series provide the longest dedicated land remote sensing data record with a balance between requirements for localized high spatial resolution studies and global monitoring. As with any other optical wavelength satellite sensor, cloud contamination greatly compromises image usability for land surface studies. Additionally, selective scene acquisition due to payload, ground station and mission cost constraints further reduces Landsat image availability. Since the 1999 launch of the Landsat Enhanced Thematic Mapper Plus (ETM+) a Long-term Acquisition Plan (LTAP) has been used to anticipate user requests with the goal of annually refreshing a global daytime archive of cloud-free ETM+ data. This research evaluates the availability of cloud-free Landsat ETM+ data over the conterminous U.S. and globally using 3 years of ETM+ cloud fraction metadata archived by the U.S. Landsat project. Landsat application requirements including obtaining at least one cloud-free observation in a year, a season, and two different seasons, or at least a pair of cloud-free observations occurring no more than 16, 32, 48, 64, and 80 days apart within a year and season are considered. Probabilistic analyses indicate that over the conterminous U.S., land applications requiring at least one cloud-free observation in a year, a season, two different seasons, or at least two cloud-free observations occurring within any period of the year, are on average largely unaffected by cloud cover, except for certain Winter applications and cloudy scenes near the U.S.–Canada border and the Great Lakes. Cloud becomes a constraint when at least two cloud-free observations are required from the same season over the conterminous U.S., especially when the separation between observations is restricted to short time intervals. Global applications requiring at least one cloud-free observation in a season, in two different seasons, and applications requiring at least two cloud-free observations in a year, are all severely affected by cloud and data availability constraints; and globally it is generally not practical to consider land applications that require at least two cloud-free observations in any season. Globally, only land applications requiring at least one cloud-free observation per year are largely unaffected by cloud cover and the reduced global ETM+ data availability. These results are specific only to the U.S. Landsat ETM+ archive; they suggest the need for an increased global Landsat acquisition rate for the current and future Landsat missions and/or the development of new approaches to mitigating cloud contamination in the U.S. global Landsat ETM+ archive.
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The availability of cloud-free Landsat ETM+ data over the conterminous United States and globally
Remote Sensing of Environment, 2008Co-Authors: Junchang Ju, David P. RoyAbstract:The U.S. Landsat satellite series provide the longest dedicated land remote sensing data record with a balance between requirements for localized high spatial resolution studies and global monitoring. As with any other optical wavelength satellite sensor, cloud contamination greatly compromises image usability for land surface studies. Additionally, selective scene acquisition due to payload, ground station and mission cost constraints further reduces Landsat image availability. Since the 1999 launch of the Landsat Enhanced Thematic Mapper Plus (ETM+) a Long-term Acquisition Plan (LTAP) has been used to anticipate user requests with the goal of annually refreshing a global daytime archive of cloud-free ETM+ data. This research evaluates the availability of cloud-free Landsat ETM+ data over the conterminous U.S. and globally using 3 years of ETM+ cloud fraction metadata archived by the U.S. Landsat project. Landsat application requirements including obtaining at least one cloud-free observation in a year, a season, and two different seasons, or at least a pair of cloud-free observations occurring no more than 16, 32, 48, 64, and 80 days apart within a year and season are considered. Probabilistic analyses indicate that over the conterminous U.S., land applications requiring at least one cloud-free observation in a year, a season, two different seasons, or at least two cloud-free observations occurring within any period of the year, are on average largely unaffected by cloud cover, except for certain Winter applications and cloudy scenes near the U.S.-Canada border and the Great Lakes. Cloud becomes a constraint when at least two cloud-free observations are required from the same season over the conterminous U.S., especially when the separation between observations is restricted to short time intervals. Global applications requiring at least one cloud-free observation in a season, in two different seasons, and applications requiring at least two cloud-free observations in a year, are all severely affected by cloud and data availability constraints; and globally it is generally not practical to consider land applications that require at least two cloud-free observations in any season. Globally, only land applications requiring at least one cloud-free observation per year are largely unaffected by cloud cover and the reduced global ETM+ data availability. These results are specific only to the U.S. Landsat ETM+ archive; they suggest the need for an increased global Landsat acquisition rate for the current and future Landsat missions and/or the development of new approaches to mitigating cloud contamination in the U.S. global Landsat ETM+ archive. © 2007 Elsevier Inc. All rights reserved.
Jeffrey G. Masek - One of the best experts on this subject based on the ideXlab platform.
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Current status of Landsat program, science, and applications
Remote Sensing of Environment, 2019Co-Authors: Michael A Wulder, Thomas R. Loveland, Curtis E. Woodcock, Jeffrey G. Masek, Richard G Allen, Martha C Anderson, A S Belward, Christopher J. Crawford, Warren B. CohenAbstract:Abstract Formal planning and development of what became the first Landsat satellite commenced over 50 years ago in 1967. Now, having collected earth observation data for well over four decades since the 1972 launch of Landsat-1, the Landsat program is increasingly complex and vibrant. Critical programmatic elements are ensuring the continuity of high quality measurements for scientific and operational investigations, including ground systems, acquisition planning, data archiving and management, and provision of analysis ready data products. Free and open access to archival and new imagery has resulted in a myriad of innovative applications and novel scientific insights. The planning of future compatible satellites in the Landsat series, which maintain continuity while incorporating technological advancements, has resulted in an increased operational use of Landsat data. Governments and international agencies, among others, can now build an expectation of Landsat data into a given operational data stream. International programs and conventions (e.g., deforestation monitoring, climate change mitigation) are empowered by access to systematically collected and calibrated data with expected future continuity further contributing to the existing multi-decadal record. The increased breadth and depth of Landsat science and applications have accelerated following the launch of Landsat-8, with significant improvements in data quality. Herein, we describe the programmatic developments and institutional context for the Landsat program and the unique ability of Landsat to meet the needs of national and international programs. We then present the key trends in Landsat science that underpin many of the recent scientific and application developments and follow-up with more detailed thematically organized summaries. The historical context offered by archival imagery combined with new imagery allows for the development of time series algorithms that can produce information on trends and dynamics. Landsat-8 has figured prominently in these recent developments, as has the improved understanding and calibration of historical data. Following the communication of the state of Landsat science, an outlook for future launches and envisioned programmatic developments are presented. Increased linkages between satellite programs are also made possible through an expectation of future mission continuity, such as developing a virtual constellation with Sentinel-2. Successful science and applications developments create a positive feedback loop—justifying and encouraging current and future programmatic support for Landsat.
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the global Landsat archive status consolidation and direction
Remote Sensing of Environment, 2016Co-Authors: Michael A Wulder, Thomas R. Loveland, Curtis E. Woodcock, Warren B. Cohen, Joanne C. White, A S Belward, Eugene A Fosnight, Jerad Shaw, Jeffrey G. MasekAbstract:ABSTRACT New and previously unimaginable Landsat applications have been fostered by a policy change in 2008 that made analysis-ready Landsat data free and open access. Since 1972, Landsat has been collecting images of the Earth, with the early years of the program constrained by onboard satellite and ground systems, as well as limitations across the range of required computing, networking, and storage capabilities. Rather than robust on-satellite storage for transmission via high bandwidth downlink to a centralized storage and distribution facility as with Landsat-8, a network of receiving stations, one operated by the U.S. government, the other operated by a community of International Cooperators (ICs), were utilized. ICs paid a fee for the right to receive and distribute Landsat data and over time, more Landsat data was held outside the archive of the United State Geological Survey (USGS) than was held inside, much of it unique. Recognizing the critical value of these data, the USGS began a Landsat Global Archive Consolidation (LGAC) initiative in 2010 to bring these data into a single, universally accessible, centralized global archive, housed at the Earth Resources Observation and Science (EROS) Center in Sioux Falls, South Dakota. The primary LGAC goals are to inventory the data held by ICs, acquire the data, and ingest and apply standard ground station processing to generate an L1T analysis-ready product. As of January 1, 2015 there were 5,532,454 images in the USGS archive. LGAC has contributed approximately 3.2 million of those images, more than doubling the original USGS archive holdings. Moreover, an additional 2.3 million images have been identified to date through the LGAC initiative and are in the process of being added to the archive. The impact of LGAC is significant and, in terms of images in the collection, analogous to that of having had two additional Landsat-5 missions. As a result of LGAC, there are regions of the globe that now have markedly improved Landsat data coverage, resulting in an enhanced capacity for mapping, monitoring change, and capturing historic conditions. Although future missions can be planned and implemented, the past cannot be revisited, underscoring the value and enhanced significance of historical Landsat data and the LGAC initiative. The aim of this paper is to report the current status of the global USGS Landsat archive, document the existing and anticipated contributions of LGAC to the archive, and characterize the current acquisitions of Landsat-7 and Landsat-8. Landsat-8 is adding data to the archive at an unprecedented rate as nearly all terrestrial images are now collected. We also offer key lessons learned so far from the LGAC initiative, plus insights regarding other critical elements of the Landsat program looking forward, such as acquisition, continuity, temporal revisit, and the importance of continuing to operationalize the Landsat program.
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Evaluation of the Landsat-5 TM and Landsat-7 ETM + surface reflectance products
Remote Sensing of Environment, 2015Co-Authors: Martin Claverie, B. Franch, Eric Vermote, Jeffrey G. MasekAbstract:Abstract Maintaining consistent datasets of Surface Reflectance (SR) is an important challenge to ensure long-term quality of Climate Data Records. The Landsat 5 and 7 archives offer a unique data source to monitor globally the land surface at high spatial resolution. The Landsat-5 TM and Landsat-7 ETM + SR products, derived from the on-demand processing Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS), require periodic evaluation to check the data consistency. Two evaluation approaches are presented in this paper. The first approach used the Aerosol Robotic Network (AERONET) data set for the period 2000 to 2013 over 489 sites with 3600 Landsat-5 TM and Landsat-7 ETM + scenes selected. For each scene, 10 × 10 km subsets of LEDAPS-derived Landsat SR and AERONET-derived SR are compared. The latter are computed using Landsat top of atmosphere reflectance, AERONET measurements of atmospheric parameters, and the 6S radiative transfer model. Second, we introduce a methodology to cross-compare Landsat data and MODIS data acquired on the same day. The analysis is based on 4000 random Landsat scenes globally distributed from 2000 to 2013. This method includes: (i) a surface anisotropy adjustment, based on the VJB Bidirectional Reflectance Distribution Function (BRDF) method, to adjust Terra and Aqua MODIS data to Landsat 5 and 7 sun-view geometry, (ii) a spectral adjustment based on an artificial neural network trained with the PROSAIL vegetation radiative transfer model, to adjust MODIS data to TM and ETM + spectral responses. The overall results of both approaches show a good match in over 80% of the scenes, i.e. the TM and ETM + SR uncertainty remained within the SR specification, defined as 0.05 × SR + 0.005. The worst results are found in the blue band used in LEDAPS to adjust the Aerosol Optical Thickness (AOT). The MODIS-Landsat SR cross-comparison confirms the utility of a BRDF adjustment method to decrease the scattering between Landsat sensors and MODIS sensors (Terra and Aqua). The spectral adjustment removes part of the biases related to spectral response differences. Global analysis is used to identify AOT retrieval issues over specific scenes, mostly over bright surfaces. From 2000 to 2013, no significant temporal variation of the performance is detected, which enhanced the consistency of LEDAPS-derived surface reflectance data set.
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Evaluation of the Landsat-5 TM and Landsat-7 ETM+ surface reflectance products
Remote Sensing of Environment, 2015Co-Authors: Martin Claverie, B. Franch, E.f. Vermote, Jeffrey G. MasekAbstract:Maintaining consistent datasets of Surface Reflectance (SR) is an important challenge to ensure long-term quality of Climate Data Records. The Landsat 5 and 7 archives offer a unique data source to monitor globally the land surface at high spatial resolution. The Landsat-5 TM and Landsat-7 ETM. + SR products, derived from the on-demand processing Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS), require periodic evaluation to check the data consistency. Two evaluation approaches are presented in this paper. The first approach used the Aerosol Robotic Network (AERONET) data set for the period 2000 to 2013 over 489 sites with 3600 Landsat-5 TM and Landsat-7 ETM. + scenes selected. For each scene, 10. ×. 10. km subsets of LEDAPS-derived Landsat SR and AERONET-derived SR are compared. The latter are computed using Landsat top of atmosphere reflectance, AERONET measurements of atmospheric parameters, and the 6S radiative transfer model. Second, we introduce a methodology to cross-compare Landsat data and MODIS data acquired on the same day. The analysis is based on 4000 random Landsat scenes globally distributed from 2000 to 2013. This method includes: (i) a surface anisotropy adjustment, based on the VJB Bidirectional Reflectance Distribution Function (BRDF) method, to adjust Terra and Aqua MODIS data to Landsat 5 and 7 sun-view geometry, (ii) a spectral adjustment based on an artificial neural network trained with the PROSAIL vegetation radiative transfer model, to adjust MODIS data to TM and ETM. + spectral responses.The overall results of both approaches show a good match in over 80% of the scenes, i.e. the TM and ETM. + SR uncertainty remained within the SR specification, defined as 0.05. × SR + 0.005. The worst results are found in the blue band used in LEDAPS to adjust the Aerosol Optical Thickness (AOT). The MODIS-Landsat SR cross-comparison confirms the utility of a BRDF adjustment method to decrease the scattering between Landsat sensors and MODIS sensors (Terra and Aqua). The spectral adjustment removes part of the biases related to spectral response differences. Global analysis is used to identify AOT retrieval issues over specific scenes, mostly over bright surfaces. From 2000 to 2013, no significant temporal variation of the performance is detected, which enhanced the consistency of LEDAPS-derived surface reflectance data set.
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Preface to Landsat Legacy Special Issue: Continuing the Landsat Legacy
Remote Sensing of Environment, 2012Co-Authors: Michael A Wulder, Jeffrey G. MasekAbstract:Since the launch of its first satellite in 1972, the Landsat program has demonstrated the insights that can be obtained through Earth observation at a resolution sensitive to both natural and human drivers. As a result, both scientific debate and environmental policy development are increasingly aided by information from the Landsat satellites. The scientific and operational uses of Landsat data are innumerable and exhibit increasing rigor and sophistication. The US Geological Survey's (USGS) decision in 2008 to make standard data products freely available through the internet was a watershed event in the history of the program, and has led to ambitious analyses previously precluded by data costs and processing requirements. In this Special Issue of Remote Sensing of Environment, “Continuing the Landsat Legacy,” we capture the current status of the Landsat program, present information regarding the forthcoming Landsat Data Continuity Mission (Landsat-8), and document new research programs and projects that rely on Landsat data. A special emphasis is placed on the burgeoning scientific and applications opportunities enabled by free access to the US archive, including use of dense time-series data to characterize inter- and intra-annual land cover changes, new capabilities for continental-scale mapping, and applications focused upon particular information needs. The importance of free and open access to the Landsat image archive cannot be overstated. The geometric and radiometricqualityof thestandard Landsatproducts has enabled new applications. Furthermore, the ability to leverage the complete archive to track four decades of environmental and resource change on Earth has ultimatelyresultedinthefulfillmentof theoriginal visionof theLandsat program, which was first articulated in the 1960's.
Valeriy Kovalskyy - One of the best experts on this subject based on the ideXlab platform.
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characterization of Landsat 7 to Landsat 8 reflective wavelength and normalized difference vegetation index continuity
Remote Sensing of Environment, 2016Co-Authors: Valeriy Kovalskyy, Hankui K Zhang, Eric Vermote, Sanath Sathyachandran Kumar, Alexey EgorovAbstract:Abstract At over 40 years, the Landsat satellites provide the longest temporal record of space-based land surface observations, and the successful 2013 launch of the Landsat-8 is continuing this legacy. Ideally, the Landsat data record should be consistent over the Landsat sensor series. The Landsat-8 Operational Land Imager (OLI) has improved calibration, signal to noise characteristics, higher 12-bit radiometric resolution, and spectrally narrower wavebands than the previous Landsat-7 Enhanced Thematic Mapper (ETM +). Reflective wavelength differences between the two Landsat sensors depend also on the surface reflectance and atmospheric state which are difficult to model comprehensively. The orbit and sensing geometries of the Landsat-8 OLI and Landsat-7 ETM + provide swath edge overlapping paths sensed only one day apart. The overlap regions are sensed in alternating backscatter and forward scattering orientations so Landsat bi-directional reflectance effects are evident but approximately balanced between the two sensors when large amounts of time series data are considered. Taking advantage of this configuration a total of 59 million 30 m corresponding sensor observations extracted from 6317 Landsat-7 ETM + and Landsat-8 OLI images acquired over three winter and three summer months for all the conterminous United States (CONUS) are compared. Results considering different stages of cloud and saturation filtering, and filtering to reduce one day surface state differences, demonstrate the importance of appropriate per-pixel data screening. Top of atmosphere (TOA) and atmospherically corrected surface reflectance for the spectrally corresponding visible, near infrared and shortwave infrared bands, and derived normalized difference vegetation index (NDVI), are compared and their differences quantified. On average the OLI TOA reflectance is greater than the ETM + TOA reflectance for all bands, with greatest differences in the near-infrared (NIR) and the shortwave infrared bands due to the quite different spectral response functions between the sensors. The atmospheric correction reduces the mean difference in the NIR and shortwave infrared but increases the mean difference in the visible bands. Regardless of whether TOA or surface reflectance are used to generate NDVI, on average, for vegetated soil and vegetation surfaces (0 ≤ NDVI ≤ 1), the OLI NDVI is greater than the ETM + NDVI. Statistical functions to transform between the comparable sensor bands and sensor NDVI values are presented so that the user community may apply them in their own research to improve temporal continuity between the Landsat-7 ETM + and Landsat-8 OLI sensor data. The transformation functions were developed using ordinary least squares (OLS) regression and were fit quite reliably ( r 2 values > 0.7 for the reflectance data and > 0.9 for the NDVI data, p-values
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a general method to normalize Landsat reflectance data to nadir brdf adjusted reflectance
Remote Sensing of Environment, 2016Co-Authors: Hankui K Zhang, Junchang Ju, Jose Gomezdans, P Lewis, Crystal B Schaaf, Jian Li, Haiyan Huang, Valeriy KovalskyyAbstract:Abstract The Landsat satellites have been providing spectacular imagery of the Earth's surface for over 40 years. However, they acquire images at view angles ± 7.5° from nadir that cause small directional effects in the surface reflectance. There are also variations with solar zenith angle over the year that can cause apparent change in reflectance even if the surface properties remain constant. When Landsat data from adjoining paths, or from long time series are used, a model of the surface anisotropy is required to adjust all Landsat observations to a uniform nadir view (primarily for visual consistency, vegetation monitoring, or detection of subtle surface changes). Here a generalized approach is developed to provide consistent view angle corrections across the Landsat archive. While this approach is not applicable for generation of Landsat surface albedo, which requires a full characterization of the surface bidirectional reflectance distribution function (BRDF), or for correction to a constant solar illumination angle across a wide range of sun angles, it provides Landsat nadir BRDF-adjusted reflectance (NBAR) for a range of terrestrial monitoring applications. The Landsat NBAR is derived as the product of the observed Landsat reflectance and the ratio of the reflectances modeled using MODIS BRDF spectral model parameters for the observed Landsat and for a nadir view and fixed solar zenith geometry. In this study, a total of 567 conterminous United States (CONUS) January and July 2010 Landsat 5 Thematic Mapper (TM) and Landsat 7 Enhanced Thematic Mapper (ETM +) images that have swath edge overlapping paths sensed in alternating backscatter and forward scattering orientations were used. The average difference between Landsat 5 TM and Landsat 7 ETM + surface reflectance in the forward and backward scatter directions at the overlapping Landsat scan edges was quantified. The CONUS July view zenith BRDF effects were about 0.02 in the Landsat visible bands, and about 0.03, 0.05 and 0.06, in the 2.1 μm, 1.6 μm and near-infrared bands respectively. Comparisons of Landsat 5 TM and Landsat 7 ETM + NBAR derived using MODIS BRDF spectral model parameters defined with respect to different spatial and temporal scales, and defined with respect to different land cover types, were undertaken. The results suggest that, because the BRDF shapes of different terrestrial surfaces are sufficiently similar over the narrow 15° Landsat field of view, a fixed set of MODIS BRDF spectral model parameters may be adequate for Landsat NBAR derivation with little sensitivity to the land cover type, condition, or surface disturbance. A fixed set of BRDF spectral model parameters, derived from a global year of highest quality snow-free MODIS BRDF product values, are provided so users may implement the described Landsat NBAR generation method.
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the global availability of Landsat 5 tm and Landsat 7 etm land surface observations and implications for global 30m Landsat data product generation
Remote Sensing of Environment, 2013Co-Authors: Valeriy Kovalskyy, David P. RoyAbstract:Abstract With the advent of the free U.S. Landsat data policy it is now feasible to consider the generation of global coverage 30 m Landsat data sets with temporal reporting frequency similar to that provided by the monthly Web Enabled Landsat (WELD) products. A statistical Landsat metadata analysis is reported considering more than 800,000 Landsat 5 TM and Landsat 7 ETM + acquisitions obtained from the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center archive. The global monthly probabilities of acquiring a cloud-free land surface observation for December 1998 to November 2001 (2000 epoch) and from December 2008 to November 2011 (2010 epoch) are reported to assess the availability of the Landsat data in the USGS Landsat archive for global multi-temporal land remote sensing applications. The global probabilities of acquiring a cloud-free land surface observation in each of three different seasons with the highest seasonal probabilities of cloud-free land surface observation are reported, considering one, two and three years of Landsat data, to assess the availability of Landsat data for global land cover mapping. The probabilities are derived considering Landsat 5 TM only, Landsat 7 ETM + only, and both sensors combined, to examine the relative benefits of using one or both Landsat sensors. The results demonstrate the utility of combing both Landsat 5 TM and Landsat 7 ETM + data streams to take advantage of their different acquisition patterns and to mitigate the deleterious impact of the Landsat 7 ETM + 2003 scan line failure. Sensor combination provided a greater global acquisition coverage with a 1.7% to 14.4% higher percentage of land locations acquired monthly compared to considering Landsat 7 ETM + data alone. The mean global monthly probability of a cloud-free land surface observation for the combined sensors was up to nearly 1.4 and 6.7 times greater than for ETM + and TM alone respectively. The probability of acquiring a cloud-free Landsat land surface observation in different seasons was greater when more years of data were considered and when both Landsat sensor data were combined. Considering combined sensors and 36 months of data, 86.4% and 84.2% of the global land locations had probabilities ≥ 0.95 for the 2000 and 2010 epochs respectively, with a global mean probability of 0.92 (σ 0.24) for the 2000 epoch and 0.90 (σ 0.28) for the 2010 epoch. These results indicate that 36 months of combined Landsat sensor data will provide sufficient land surface observations for 30 m global land cover mapping using a multi-temporal supervised classification scheme.
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continental scale validation of modis based and ledaps Landsat etm atmospheric correction methods
Remote Sensing of Environment, 2012Co-Authors: Junchang Ju, Jeffrey G. Masek, Eric Vermote, Valeriy KovalskyyAbstract:Abstract The potential of Landsat data processing to provide systematic continental scale products has been demonstrated by several projects including the NASA Web-enabled Landsat Data (WELD) project. The recent free availability of Landsat data increases the need for robust and efficient atmospheric correction algorithms applicable to large volume Landsat data sets. This paper compares the accuracy of two Landsat atmospheric correction methods: a MODIS-based method and the Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) method. Both methods are based on the 6SV radiative transfer code but have different atmospheric characterization approaches. The MODIS-based method uses the MODIS Terra derived dynamic aerosol type, aerosol optical thickness, and water vapor to atmospherically correct ETM+ acquisitions in each coincident orbit. The LEDAPS method uses aerosol characterizations derived independently from each Landsat acquisition and assumes a fixed continental aerosol type and uses ancillary water vapor. Validation results are presented comparing ETM+ atmospherically corrected data generated using these two methods with AERONET corrected ETM+ data for 95 10 km × 10 km 30 m subsets, a total of nearly 8 million 30 m pixels, located across the conterminous United States. The results indicate that the MODIS-based method has better accuracy than the LEDAPS method for the ETM+ red and longer wavelength bands.
David P. Roy - One of the best experts on this subject based on the ideXlab platform.
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the global availability of Landsat 5 tm and Landsat 7 etm land surface observations and implications for global 30m Landsat data product generation
Remote Sensing of Environment, 2013Co-Authors: Valeriy Kovalskyy, David P. RoyAbstract:Abstract With the advent of the free U.S. Landsat data policy it is now feasible to consider the generation of global coverage 30 m Landsat data sets with temporal reporting frequency similar to that provided by the monthly Web Enabled Landsat (WELD) products. A statistical Landsat metadata analysis is reported considering more than 800,000 Landsat 5 TM and Landsat 7 ETM + acquisitions obtained from the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center archive. The global monthly probabilities of acquiring a cloud-free land surface observation for December 1998 to November 2001 (2000 epoch) and from December 2008 to November 2011 (2010 epoch) are reported to assess the availability of the Landsat data in the USGS Landsat archive for global multi-temporal land remote sensing applications. The global probabilities of acquiring a cloud-free land surface observation in each of three different seasons with the highest seasonal probabilities of cloud-free land surface observation are reported, considering one, two and three years of Landsat data, to assess the availability of Landsat data for global land cover mapping. The probabilities are derived considering Landsat 5 TM only, Landsat 7 ETM + only, and both sensors combined, to examine the relative benefits of using one or both Landsat sensors. The results demonstrate the utility of combing both Landsat 5 TM and Landsat 7 ETM + data streams to take advantage of their different acquisition patterns and to mitigate the deleterious impact of the Landsat 7 ETM + 2003 scan line failure. Sensor combination provided a greater global acquisition coverage with a 1.7% to 14.4% higher percentage of land locations acquired monthly compared to considering Landsat 7 ETM + data alone. The mean global monthly probability of a cloud-free land surface observation for the combined sensors was up to nearly 1.4 and 6.7 times greater than for ETM + and TM alone respectively. The probability of acquiring a cloud-free Landsat land surface observation in different seasons was greater when more years of data were considered and when both Landsat sensor data were combined. Considering combined sensors and 36 months of data, 86.4% and 84.2% of the global land locations had probabilities ≥ 0.95 for the 2000 and 2010 epochs respectively, with a global mean probability of 0.92 (σ 0.24) for the 2000 epoch and 0.90 (σ 0.28) for the 2010 epoch. These results indicate that 36 months of combined Landsat sensor data will provide sufficient land surface observations for 30 m global land cover mapping using a multi-temporal supervised classification scheme.
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The availability of cloud-free Landsat ETM+ data over the conterminous United States and globally
Remote Sensing of Environment, 2008Co-Authors: Junchang Ju, David P. RoyAbstract:The U.S. Landsat satellite series provide the longest dedicated land remote sensing data record with a balance between requirements for localized high spatial resolution studies and global monitoring. As with any other optical wavelength satellite sensor, cloud contamination greatly compromises image usability for land surface studies. Additionally, selective scene acquisition due to payload, ground station and mission cost constraints further reduces Landsat image availability. Since the 1999 launch of the Landsat Enhanced Thematic Mapper Plus (ETM+) a Long-term Acquisition Plan (LTAP) has been used to anticipate user requests with the goal of annually refreshing a global daytime archive of cloud-free ETM+ data. This research evaluates the availability of cloud-free Landsat ETM+ data over the conterminous U.S. and globally using 3 years of ETM+ cloud fraction metadata archived by the U.S. Landsat project. Landsat application requirements including obtaining at least one cloud-free observation in a year, a season, and two different seasons, or at least a pair of cloud-free observations occurring no more than 16, 32, 48, 64, and 80 days apart within a year and season are considered. Probabilistic analyses indicate that over the conterminous U.S., land applications requiring at least one cloud-free observation in a year, a season, two different seasons, or at least two cloud-free observations occurring within any period of the year, are on average largely unaffected by cloud cover, except for certain Winter applications and cloudy scenes near the U.S.-Canada border and the Great Lakes. Cloud becomes a constraint when at least two cloud-free observations are required from the same season over the conterminous U.S., especially when the separation between observations is restricted to short time intervals. Global applications requiring at least one cloud-free observation in a season, in two different seasons, and applications requiring at least two cloud-free observations in a year, are all severely affected by cloud and data availability constraints; and globally it is generally not practical to consider land applications that require at least two cloud-free observations in any season. Globally, only land applications requiring at least one cloud-free observation per year are largely unaffected by cloud cover and the reduced global ETM+ data availability. These results are specific only to the U.S. Landsat ETM+ archive; they suggest the need for an increased global Landsat acquisition rate for the current and future Landsat missions and/or the development of new approaches to mitigating cloud contamination in the U.S. global Landsat ETM+ archive. © 2007 Elsevier Inc. All rights reserved.
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Continuous calibration improvement in solar reflective bands: Landsat 5 through Landsat 8
Remote Sensing of Environment, 2016Co-Authors: Nischal Mishra, Dennis L. Helder, Julia A. Barsi, Brian L MarkhamAbstract:Launched in February 2013, the Operational Land Imager (OLI) on-board Landsat 8 continues to perform exceedingly well and provides high science quality data globally. Several design enhancements have been made in the OLI instrument relative to prior Landsat instruments: pushbroom imaging which provides substantially improved Signal-to-Noise Ratio (SNR), spectral bandpasses refinement to avoid atmospheric absorption features, 12 bit data resolution to provide a larger dynamic range that limits the saturation level, a set of well-designed onboard calibrators to monitor the stability of the sensor. Some of these changes such as refinements in spectral bandpasses compared to earlier Landsats and well-designed on-board calibrator have a direct impact on the improved radiometric calibration performance of the instrument from both the stability of the response and the ability to track the changes. The on-board calibrator lamps and diffusers indicate that the instrument drift is generally less than 0.1% per year across the bands. The refined bandpasses of the OLI indicate that temporal uncertainty of better than 0.5% is possible when the instrument is trended over vicarious targets such as Pseudo Invariant Calibration Sites (PICS), a level of precision that was never achieved with the earlier Landsat instruments. The stability measurements indicated by on-board calibrators and PICS agree much better compared to the earlier Landsats, which is very encouraging and bodes well for the future Landsat missions too.
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Landsat-8 Sensor Characterization and Calibration
Remote Sensing, 2015Co-Authors: Brian L Markham, James C. Storey, Ron MorfittAbstract:Landsat-8 was launched on 11 February 2013 with two new Earth Imaging sensors to provide a continued data record with the previous Landsats. For Landsat-8, pushbroom technology was adopted, and the reflective bands and thermal bands were split into two instruments. The Operational Land Imager (OLI) is the reflective band sensor and the Thermal Infrared Sensor (TIRS), the thermal. In addition to these fundamental changes, bands were added, spectral bandpasses were refined, dynamic range and data quantization were improved, and numerous other enhancements were implemented. As in previous Landsat missions, the National Aeronautics and Space Administration (NASA) and United States Geological Survey (USGS) cooperated in the development, launch and operation of the Landsat-8 mission. One key aspect of this cooperation was in the characterization and calibration of the instruments and their data. This Special Issue documents the efforts of the joint USGS and NASA calibration team and affiliates to characterize the new sensors and their data for the benefit of the scientific and application users of the Landsat archive. A key scientific use of Landsat data is to assess changes in the land-use and land cover of the Earth’s surface over the now 43-year record. [...]
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radiometric cross calibration of Landsat 8 operational land imager oli and Landsat 7 enhanced thematic mapper plus etm
Remote Sensing, 2014Co-Authors: Nischal Mishra, Dennis L. Helder, Md Obaidul Haque, Larry Leigh, David Aaron, Brian L MarkhamAbstract:This study evaluates the radiometric consistency between Landsat-8 Operational Land Imager (OLI) and Landsat 7 Enhanced Thematic Mapper Plus (ETM+) using cross calibration techniques. Two approaches are used, one based on cross calibration between the two sensors using simultaneous image pairs, acquired during an underfly event on 29–30 March 2013. The other approach is based on using time series of image statistics acquired by these two sensors over the Libya 4 pseudo invariant calibration site (PICS) (+28.55°N, +23.39°E). Analyses from these approaches show that the reflectance calibration of OLI is generally within ±3% of the ETM+ radiance calibration for all the reflective bands from visible to short wave infrared regions when the ChKur solar spectrum is used to convert the ETM+ radiance to reflectance. Similar results are obtained comparing the OLI radiance calibration directly with the ETM+ radiance calibration and the results in these two different physical units (radiance and reflectance) agree to within ±2% for all the analogous bands. These results will also be useful to tie all the Landsat heritage sensors from Landsat 1 MultiSpectral Scanner (MSS) through Landsat-8 OLI to a consistent radiometric scale.
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Landsat Data Continuity Mission, now Landsat-8: six months on-orbit
Proceedings of SPIE, 2013Co-Authors: Brian L Markham, James C. Storey, James R. IronsAbstract:The Landsat Data Continuity Mission (LDCM) with two pushbroom Earth-imaging sensors, the Operational Land Imager (OLI) and the Thermal InfraRed Sensor (TIRS), was launched on February 11, 2013. Its on-orbit check out period or commissioning phase lasted about 90 days. During this phase the spacecraft and its instruments were activated, operationally tested and their performance verified. In addition, during this period, the spacecraft was temporarily placed in an intermediary orbit where it drifted relative to the Landsat-7 spacecraft, providing near simultaneous imaging for about 3 days, allowing data comparison and cross calibration. After this tandem-imaging period, LDCM was raised to its final altitude and placed in the position formerly occupied by Landsat-5, i.e., 8 days out of phase with Landsat-7, with about a 10:10 AM equatorial crossing time. At the end of commissioning, the satellite was transferred to the United States Geological Survey (USGS), officially renamed Landsat-8 and declared operational. Data were made available to the public beginning May 31, 2013. The performance of the satellite and two instruments has generally been excellent as evidenced in the quality of the distributed data products.
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Landsat 4 Thematic Mapper Calibration Update
IEEE Transactions on Geoscience and Remote Sensing, 2012Co-Authors: Dennis L. Helder, Brian L Markham, Cory Mettler, Rimy Malla, Esad MicijevicAbstract:The Landsat 4 Thematic Mapper (TM) collected imagery of the Earth's surface from 1982 to 1993. Although largely overshadowed by Landsat 5 which was launched in 1984, Landsat 4 TM imagery extends the TM-based record of the Earth back to 1982 and also substantially supplements the image archive collected by Landsat 5. To provide a consistent calibration record for the TM instruments, Landsat 4 TM was cross-calibrated to Landsat 5 using nearly simultaneous overpass imagery of pseudo-invariant calibration sites (PICS) in the time period of 1988-1990. To determine if the radiometric gain of Landsat 4 had changed over its lifetime, time series from two PICS locations (a Saharan site known as Libya 4 and a site in southwest North America, commonly referred to as the Sonoran Desert site) were developed. The results indicated that Landsat 4 had been very stable over its lifetime, with no discernible degradation in sensor performance in all reflective bands except band 1. In contrast, band 1 exhibited a 12% decay in responsivity over the lifetime of the instrument. Results from this paper have been implemented at USGS EROS, which enables users of Landsat TM data sets to obtain consistently calibrated data from Landsat 4 and 5 TM as well as Landsat 7 ETM+ instruments.
