Geology topics

James C. Storey

Publications and source records attributed to James C. Storey.

At least 19 recordsLinked to original sources

USGS2022

Landsat 9 geometric characteristics using underfly data

The Landsat program has a long history of providing remotely sensed data to the user community. This history is being extended with the addition of the Landsat 9 satellite, which closely mimics the Landsat 8 satellite and its instruments. These satellites contain two instruments, the Operational Land Imager (OLI) and the Thermal Infrared Sensor (TIRS). OLI is a push-broom sensor that collects visible and near-infrared (VNIR) and short-wave infrared (SWIR) wavelengths at 30 m ground sample distance, along with a panchromatic 15 m band. The TIRS sensor contains two long-wave thermal spectral channels centered at 10.9 and 12 µm. The data from these two instruments, on both satellites, are combined into a single Landsat product. The Landsat 5–9 satellites follow a 16 day repeat cycle designated as the Worldwide Reference System (WRS-2), which provides a global notional gridded mapping for identifying individual Landsat scenes. The Landsat 8 and 9 satellites are flown such that their orbital tracks are separated by 8 days in this 16 day cycle. During the commissioning period of Landsat 9, and during its ascent to its operational WRS-2 orbit, the Landsat 9 satellite’s orbital track went under and crossed over the orbital track of the Landsat 8 satellite. This produced a unique situation where nearly time-coincident imagery could be obtained from the instruments of the two spacecrafts. From a radiometric standpoint, this allowed for near-time cross-calibration between the instruments to be performed. From a geometry perspective, calibration is achieved through high-resolution reference imagery over specific ground locations, thus ensuring calibration of the instruments and for the instruments to be well cross-calibrated geometrically. Although these underfly data do not provide calibration of the instruments between the platforms from a geometric perspective, they allow for the verification of the calibration steps involving the instruments and spacecraft. This paper discusses the co-registration of this unique set of data while also discussing other geometric aspects of these data by looking at and comparing the differences in sensor viewing and sun angles associated with the collections from the two platforms for imagery obtained over common geographic locations. The image-to-image comparisons between Landsat 8 and 9 coincident pairs, where both datasets are precision terrain products, are registered to within 2.2 m with respect to their root-mean-squared radial error (RMSEr). The 2.2 m represents less than 0.1 of a 30 m multispectral pixel in misregistration between the L9 and L8 underfly products that will be available to the user community. This unique dataset will provide well-registered, near-coincident image acquisitions between the two platforms that can be a key to any calibration or application comparisons. The paper also presents that, for images for which one of the image pairs failed precision corrections and became a terrain-corrected only product type, a range of 8–14 m RMSEr could be expected in co-registration, while, in cases where both image pairs failed the precision correction step and both images became a terrain-corrected only product type, a 14 m RMSEr could be expected for co-registration.

Remote Sensing↗

USGS2021

Geometric calibration updates to Landsat 7 ETM+ instrument for Landsat Collection 2 products

The Landsat 7 (L7) spacecraft and its instrument, the enhanced thematic mapper plus (ETM+), have been consistently characterized and calibrated since its launch in April of 1999. 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 launch. Starting in 2016, the USGS adopted a tiered collection management structure for its Landsat data products that ensures a consistent method of processing for the Landsat archive within a given collection while allowing a set of calibration updates to be performed between any two given collections. The time frame between 2016 and the end of 2020 was part of the Landsat data Collection 1, in the middle of 2020 was the start of the Landsat Collection 2 data products. The start of a given collection initiates the reprocessing of the Landsat archive, which may involve one or more of a set of updated calibration parameters, improvements in the support data needed for product generation, and improved algorithms used in both the processing flow of products along with the characterization and calibration of the Landsat instruments and spacecraft. This paper discusses only the ETM+ geometric spacecraft and instrument calibration improvements for Collection 2. Three ETM+ calibration updates were made for the ETM+; updates to the thermal band odd-to-even detector alignment, sensor to attitude control system (ACS) alignment, and a cold-to-warm focal plane alignment adjustment. The sensor alignment updates impact only the accuracy of the systematic terrain products (L1GT), which are the products generated before applying any corrections based on the ground control used in registration. The band alignment changes impacted only bands 5, 6, and 7 within the focal plane. Other geometric calibration updates, such as scan mirror alignment, are done on a routine basis and are not part of the Collection 2 updates due to their more dynamic characteristics.

Remote Sensing↗

USGS2021

Landsat 8 thermal infrared sensor scene select mechanism open loop operations

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 United States Geological Survey (USGS) Landsat image assessment system (IAS), which has been performing this function since its launch. The TIRS on-orbit geometric calibration procedures in-clude TIRS-to-OLI alignment, TIRS sensor chip assembly (SCA) alignment, and TIRS band align-ment. 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 en-coder 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 dis-cusses 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 impacts on products. The results shown in this paper demonstrate that the ability to have on-going 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.

MDPI Remote Sensing↗

USGS2020

The new Landsat Collection-2 Digital Elevation Model

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.

Remote Sensing↗

USGS2020

Harmonizing the Landsat ground reference with the Sentinel-2 Global Reference Image using space-based bundle adjustment

There is an ever-increasing need to use accurate and consistent geometric ground reference in the processing of remotely sensed data products as it reduces the burden on the end-users to account for the differences between the data products from different missions. In this regard, United States 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 have discussed 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 5 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 m 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 mis-registration error of less than 8 m Circular Error Probable at 90 % (CE90), an improvement from 25 meters prior to harmonization. The improvements to the Landsat products using the harmonized GCPs will be available to the public as part of Landsat Collection-2 processing by the end of 2020.

MDPI Remote Sensing↗

USGS2020

Landsat 9: Empowering open science and applications through continuity

The history of Earth observation from space is well reflected through the Landsat program. With data collection beginning with Landsat-1 in 1972, the program has evolved technical capabilities while maintaining continuity of land observations. In so doing, Landsat has provided a critical reference for assessing long-term changes to Earth's land environment due to both natural and human forcing. Poised for launch in mid-2021, the joint NASA-USGS Landsat 9 mission will continue this important data record. In many respects Landsat 9 is a clone of Landsat-8. The Operational Land Imager-2 (OLI-2) is largely identical to Landsat 8 OLI, providing calibrated imagery covering the solar reflected wavelengths. The Thermal Infrared Sensor-2 (TIRS-2) improves upon Landsat 8 TIRS, addressing known issues including stray light incursion and a malfunction of the instrument scene select mirror. In addition, Landsat 9 adds redundancy to TIRS-2, thus upgrading the instrument to a 5-year design life commensurate with other elements of the mission. Initial performance testing of OLI-2 and TIRS-2 indicate that the instruments are of excellent quality and expected to match or improve on Landsat 8 data quality. Landsat-9 will maintain the current data acquisition rate of up to 740 scenes per day, with these scenes available from the Landsat archive at no cost to users. In this communication, we provide background and rationale for the Landsat 9 mission, describe the instrument payloads and ground system, and discuss data products available from the Landsat 9 mission through USGS.

Remote Sensing of Environment↗

USGS2020

Landsat Collection 2 geometric calibration updates

The U.S. Geological Survey (USGS) changed the management and delivery of Landsat products to the public in its archive through the implementation of Collections. The Collections process ensures consistent data quality through time and across all the Landsat sensors with a few modifications to the metadata. The consistent data products from Collections are more conducive for applications such as time-series analysis, because the data can be used without a need for sensor-specific geometric or radiometric adjustments. The Collections process also allows for calibration improvements from updated reference sources, model trending, and enhanced algorithms that are grouped together and applied at one time, thus limiting the operational impacts to users. The first collection, Collection-1 was released in 2016, and Collection-2 is expected to be released in 2020. This paper addresses the geometric improvements to the Collection -2 dataset. Geometric improvements in Collection-2 include improvements to the geometric accuracy and interoperability of all Landsat products by implementing the Sentinel 2 Global Reference Image (GRI), improved elevation dataset using NASADEM and other sources of Digital Elevation Model (DEM) for terrain correction, improvements to the precision correction process for Enhanced Thematic Mapper Plus (ETM+) and Thematic Mapper (TM) sensors, changes to the Thermal Infrared Sensor (TIRS) to Operational Land Imager (OLI) alignment estimates, thermal band detector alignments and focal plane adjustments for ETM+, and improvements to the ETM+ sensor to attitude control system (ACS).

Conference Paper↗

USGS2019

Bundle adjustment using space based triangulation method for improving the Landsat global ground reference

There is an ever-increasing interest and need for accurate geo-registration of remotely sensed data products to a common global geometric reference. Although the geo-registration has improved significantly 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 provide 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.

Remote Sensing↗

USGS2016

A note on the temporary misregistration of Landsat-8 Operational Land Imager (OLI) and Sentinel-2 Multi Spectral Instrument (MSI) imagery

The Landsat-8 and Sentinel-2 sensors provide multi-spectral image data with similar spectral and spatial characteristics that together provide improved temporal coverage globally. Both systems are designed to register Level 1 products to a reference image framework, however, the Landsat-8 framework, based upon the Global Land Survey images, contains residual geolocation errors leading to an expected sensor-to-sensor misregistration of 38 m (2σ). These misalignments vary geographically but should be stable for a given area. The Landsat framework will be readjusted for consistency with the Sentinel-2 Global Reference Image, with completion expected in 2018. In the interim, users can measure Landsat-to-Sentinel tie points to quantify the misalignment in their area of interest and if appropriate to reproject the data to better alignment.

Remote Sensing of Environment↗

USGS2015

Validation of geometric accuracy of Global Land Survey (GLS) 2000 data

The Global Land Survey (GLS) 2000 data were generated from Geocover™ 2000 data with the aim of producing a global data set of accuracy better than 25 m Root Mean Square Error (RMSE). An assessment and validation of accuracy of GLS 2000 data set, and its co-registration with Geocover™ 2000 data set is presented here. Since the availability of global data sets that have higher nominal accuracy than the GLS 2000 is a concern, the data sets were assessed in three tiers. In the first tier, the data were compared with the Geocover™ 2000 data. This comparison provided a means of localizing regions of higher differences. In the second tier, the GLS 2000 data were compared with systematically corrected Landsat-7 scenes that were obtained in a time period when the spacecraft pointing information was extremely accurate. These comparisons localize regions where the data are consistently off, which may indicate regions of higher errors. The third tier consisted of comparing the GLS 2000 data against higher accuracy reference data. The reference data were the Digital Ortho Quads over the United States, orthorectified SPOT data over Australia, and high accuracy check points obtained using triangulation bundle adjustment of Landsat-7 images over selected sites around the world. The study reveals that the geometric errors in Geocover™ 2000 data have been rectified in GLS 2000 data, and that the accuracy of GLS 2000 data can be expected to be better than 25 m RMSE for most of its constituent scenes.

Photogrammetric Engineering and Remote Sensing↗

USGS2014

Landsat 8 operational land imager on-orbit geometric calibration and performance

The Landsat 8 spacecraft was launched on 11 February 2013 carrying the Operational Land Imager (OLI) payload for moderate resolution imaging in the visible, near infrared (NIR), and short-wave infrared (SWIR) spectral bands. During the 90-day commissioning period following launch, several on-orbit geometric calibration activities were performed to refine the prelaunch calibration parameters. The results of these calibration activities were subsequently used to measure geometric performance characteristics in order to verify the OLI geometric requirements. Three types of geometric calibrations were performed including: (1) updating the OLI-to-spacecraft alignment knowledge; (2) refining the alignment of the sub-images from the multiple OLI sensor chips; and (3) refining the alignment of the OLI spectral bands. The aspects of geometric performance that were measured and verified included: (1) geolocation accuracy with terrain correction, but without ground control (L1Gt); (2) Level 1 product accuracy with terrain correction and ground control (L1T); (3) band-to-band registration accuracy; and (4) multi-temporal image-to-image registration accuracy. Using the results of the on-orbit calibration update, all aspects of geometric performance were shown to meet or exceed system requirements.

Remote Sensing↗

USGS2014

Landsat 8 thermal infrared sensor geometric characterization and calibration

The Landsat 8 spacecraft was launched on 11 February 2013 carrying two imaging payloads: the Operational Land Imager (OLI) and the Thermal Infrared Sensor (TIRS). The TIRS instrument employs a refractive telescope design that is opaque to visible wavelengths making prelaunch geometric characterization challenging. TIRS geometric calibration thus relied heavily on on-orbit measurements. Since the two Landsat 8 payloads are complementary and generate combined Level 1 data products, the TIRS geometric performance requirements emphasize the co-alignment of the OLI and TIRS instrument fields of view and the registration of the OLI reflective bands to the TIRS long-wave infrared emissive bands. The TIRS on-orbit calibration procedures include measuring the TIRS-to-OLI alignment, refining the alignment of the three TIRS sensor chips, and ensuring the alignment of the two TIRS spectral bands. The two key TIRS performance metrics are the OLI reflective to TIRS emissive band registration accuracy, and the registration accuracy between the TIRS thermal bands. The on-orbit calibration campaign conducted during the commissioning period provided an accurate TIRS geometric model that enabled TIRS Level 1 data to meet all geometric accuracy requirements. Seasonal variations in TIRS-to-OLI alignment have led to several small calibration parameter adjustments since commissioning.

Remote Sensing↗

USGS2013

Landsat Data Continuity Mission, now Landsat-8: six months on-orbit

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. © (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.

Conference Paper↗

USGS2008

Geometric performance comparison between the OLI and the ETM+

The Landsat Data Continuity Mission (LDCM) Operational Land Imager (OLI) is the successor to the Landsat 7 Enhanced Thematic Mapper Plus (ETM+) instrument and features a pushbroom architecture that is more geometrically stable than the whiskbroom scanner of the ETM+. As a tradeoff of this architecture selection, imagery must be terrain corrected to ensure accurate band registration. This paper compares the geometric performance requirements for the two instruments and discusses the implications for the Landsat user community.

Conference Paper↗

USGS2007

A multi-scale segmentation approach to filling gaps in Landsat ETM+ SLC-off images

On 31 May 2003, the Landsat Enhanced Thematic Plus (ETM+) Scan Line Corrector (SLC) failed, causing the scanning pattern to exhibit wedge-shaped scan-to-scan gaps. We developed a method that uses coincident spectral data to fill the image gaps. This method uses a multi-scale segment model, derived from a previous Landsat SLC-on image (image acquired prior to the SLC failure), to guide the spectral interpolation across the gaps in SLC-off images (images acquired after the SLC failure). This paper describes the process used to generate the segment model, provides details of the gap-fill algorithm used in deriving the segment-based gap-fill product, and presents the results of the gap-fill process applied to grassland, cropland, and forest landscapes. Our results indicate this product will be useful for a wide variety of applications, including regional-scale studies, general land cover mapping (e.g. forest, urban, and grass), crop-specific mapping and monitoring, and visual assessments. Applications that need to be cautious when using pixels in the gap areas include any applications that require per-pixel accuracy, such as urban characterization or impervious surface mapping, applications that use texture to characterize landscape features, and applications that require accurate measurements of small or narrow landscape features such as roads, farmsteads, and riparian areas.

International Journal of Remote Sensing↗

USGS2007

Geometric correction and digital elevation extraction using multiple MTI datasets

Digital Elevation Models (DEMs) are traditionally acquired from a stereo pair of aerial photographs sequentially captured by an airborne metric camera. Standard DEM extraction techniques can be naturally extended to satellite imagery, but the particular characteristics of satellite imaging can cause difficulties. The spacecraft ephemeris with respect to the ground site during image collects is the most important factor in the elevation extraction process. When the angle of separation between the stereo images is small, the extraction process typically produces measurements with low accuracy, while a large angle of separation can cause an excessive number of erroneous points in the DEM from occlusion of ground areas. The use of three or more images registered to the same ground area can potentially reduce these problems and improve the accuracy of the extracted DEM. The pointing capability of some sensors, such as the Multispectral Thermal Imager (MTI), allows for multiple collects of the same area from different perspectives. This functionality of MTI makes it a good candidate for the implementation of a DEM extraction algorithm using multiple images for improved accuracy. Evaluation of this capability and development of algorithms to geometrically model the MTI sensor and extract DEMs from multi-look MTI imagery are described in this paper. An RMS elevation error of 6.3-meters is achieved using 11 ground test points, while the MTI band has a 5-meter ground sample distance.

Photogrammetric Engineering and Remote Sensing↗

USGS2005

Landsat 7 scan line corrector-off gap-filled product development

The Landsat 7 Enhanced Thematic Mapper Plus (ETM+) scan line corrector (SLC) failed on May 31, 2003, causing the scanning pattern to exhibit wedge-shaped scan-to-scan gaps. The ETM+ has continued to acquire data with the SLC powered off, leading to images that are missing approximately 22 percent of the normal scene area. To improve the utility of the SLC-off data, the U.S. Geological Survey (USGS) developed new products that use the data from multiple ETM+ scenes to provide complete ground coverage. These gap-filled products were developed and deployed in two phases. The gaps in the Phase I products are filled with data from imagery collected previously with a functional SLC (SLC-on). A single SLC-on scene provides complete coverage of the scan gaps, making the gap-filling procedure straightforward. Several radiometric adjustment techniques for matching the SLC-on fill scene to the SLC-off primary scene were evaluated for performance, processing speed, and ease of implementation. A simple local histogram matching method was adopted as a result of this evaluation. The Phase II products use data from multiple SLC-off scenes to fill the scan gaps with more recent data. Because the locations of the scan gaps are different for each SLC-off scene, the gap-filling process must account for scan gap interactions. The Phase II product development included a more comprehensive study of candidate radiometric adjustment techniques. This study showed that the histogram matching method used in Phase I, with minor refinements, provided the best overall performance and was adopted for Phase II as well.

Conference Paper↗

USGS2004

A geometric performance assessment of the EO-1 advanced land imager

The Earth Observing 1 (EO-1) Advanced Land Imager (ALI) demonstrates technology applicable to a successor system to the Landsat Thematic Mapper series. A study of the geometric performance characteristics of the ALI was conducted under the auspices of the EO-1 Science Validation Team. This study evaluated ALI performance with respect to absolute pointing knowledge, focal plane sensor chip assembly alignment, and band-to-band registration for purposes of comparing this new technology to the heritage Landsat systems. On-orbit geometric calibration procedures were developed that allowed the generation of ALI geometrically corrected products that compare favorably with their Landsat 7 counterparts with respect to absolute geodetic accuracy, internal image geometry, and band registration.

IEEE Transactions on Geoscience and Remote Sensing↗