Geology topics

G. Chander

Publications and source records attributed to G. Chander.

At least 19 recordsLinked to original sources

USGS2014

Landsat TM and ETM+ thermal band calibration

Landsat-5 has been imaging the Earth since March 1984, and Landsat-7 was added to the series of Landsat instruments in April 1999. The Landsat Project Science Office and the Landsat-7 Image Assessment System have been monitoring the on-board calibration of Landsat-7 since launch. Additionally, two separate university teams have been evaluating the on-board thermal calibration of Landsat-7 through ground-based measurements since launch. Although not monitored as closely over its lifetime, a new effort is currently being made to validate the calibration of Landsat-5. Two university teams are beginning to collect ground truth under Landsat-5, along with using other vicarious calibration methods to go back into the archive to validate the history of the calibration of Landsat-5. This paper considers the calibration efforts for the thermal band, band 6, of both the Landsat-5 and Landsat-7 instruments. Though stable since launch, Landsat-7 had an initial calibration error of about 3 K, and changes were made to correct for this beginning 1 October 2000 for data processed with the National Landsat Archive Production System (NLAPS) and beginning 20 December 2000 for data processed with the Landsat Product Generation System (LPGS). Recent results from Landsat-5 vicarious calibration efforts show an offset of 0.7 K over the lifetime of the instrument. This suggests that historical calibration efforts may have been detecting errors in processing systems rather than changes in the instrument. A correction to the Landsat-5 processing has not yet been implemented but will be in the near future.

Canadian Journal of Remote Sensing↗

USGS2014

Establishing the Antarctic Dome C community reference standard site towards consistent measurements from Earth observation satellites

Establishing satellite measurement consistency by using common desert sites has become increasingly more important not only for climate change detection but also for quantitative retrievals of geophysical variables in satellite applications. Using the Antarctic Dome C site (75°06′S, 123°21′E, elevation 3.2 km) for satellite radiometric calibration and validation (Cal/Val) is of great interest owing to its unique location and characteristics. The site surface is covered with uniformly distributed permanent snow, and the atmospheric effect is small and relatively constant. In this study, the long-term stability and spectral characteristics of this site are evaluated using well-calibrated satellite instruments such as the Moderate Resolution Imaging Spectroradiometer (MODIS) and Sea-viewing Wide Field-of-view Sensor (SeaWiFS). Preliminary results show that despite a few limitations, the site in general is stable in the long term, the bidirectional reflectance distribution function (BRDF) model works well, and the site is most suitable for the Cal/Val of reflective solar bands in the 0.4–1.0 µm range. It was found that for the past decade, the reflectivity change of the site is within 1.35% at 0.64 µm, and interannual variability is within 2%. The site is able to resolve calibration biases between instruments at a level of ~1%. The usefulness of the site is demonstrated by comparing observations from seven satellite instruments involving four space agencies, including OrbView-2–SeaWiFS, Terra–Aqua MODIS, Earth Observing 1 (EO-1) – Hyperion, Meteorological Operational satellite programme (MetOp) – Advanced Very High Resolution Radiometer (AVHRR), Envisat Medium Resolution Imaging Spectrometer (MERIS) – dvanced Along-Track Scanning Radiometer (AATSR), and Landsat 7 Enhanced Thematic Mapper Plus (ETM+). Dome C is a promising candidate site for climate quality calibration of satellite radiometers towards more consistent satellite measurements, as part of the framework for climate change detection and data quality assurance for the Global Earth Observation System of Systems (GEOSS).

Canadian Journal of Remote Sensing↗

USGS2014

Terrestrial reference standard sites for postlaunch sensor calibration

In an era when the number of Earth observation satellites is rapidly growing and measurements from satellite sensors are used to address increasingly urgent global issues, often through synergistic and operational combinations of data from multiple sources, it is imperative that scientists and decision-makers are able to rely on the accuracy of Earth observation data products. The characterization and calibration of these sensors, particularly their relative biases, are vital to the success of the developing integrated Global Earth Observation System of Systems (GEOSS) for coordinated and sustained observations of the Earth. This can only reliably be achieved in the postlaunch environment through the careful use of observations by multiple sensor systems over common, well-characterized terrestrial targets (i.e., on or near the Earth's surface). Through greater access to and understanding of these vital reference standard sites and their use, the validity and utility of information gained from Earth remote sensing will continue to improve. This paper provides a brief overview of the use of reference standard sites for postlaunch sensor radiometric calibration from historical, current, and future perspectives. Emphasis is placed on optical sensors operating in the visible, near-infrared, and shortwave infrared spectral regions.

Canadian Journal of Remote Sensing↗

USGS2013

Assessment of spectral, misregistration, and spatial uncertainties inherent in the cross-calibration study

Cross-calibration of satellite sensors permits the quantitative comparison of measurements obtained from different Earth Observing (EO) systems. Cross-calibration studies usually use simultaneous or near-simultaneous observations from several spaceborne sensors to develop band-by-band relationships through regression analysis. The investigation described in this paper focuses on evaluation of the uncertainties inherent in the cross-calibration process, including contributions due to different spectral responses, spectral resolution, spectral filter shift, geometric misregistrations, and spatial resolutions. The hyperspectral data from the Environmental Satellite SCanning Imaging Absorption SpectroMeter for Atmospheric CartograpHY and the EO-1 Hyperion, along with the relative spectral responses (RSRs) from the Landsat 7 Enhanced Thematic Mapper (TM) Plus and the Terra Moderate Resolution Imaging Spectroradiometer sensors, were used for the spectral uncertainty study. The data from Landsat 5 TM over five representative land cover types (desert, rangeland, grassland, deciduous forest, and coniferous forest) were used for the geometric misregistrations and spatial-resolution study. The spectral resolution uncertainty was found to be within 0.25%, spectral filter shift within 2.5%, geometric misregistrations within 0.35%, and spatial-resolution effects within 0.1% for the Libya 4 site. The one-sigma uncertainties presented in this paper are uncorrelated, and therefore, the uncertainties can be summed orthogonally. Furthermore, an overall total uncertainty was developed. In general, the results suggested that the spectral uncertainty is more dominant compared to other uncertainties presented in this paper. Therefore, the effect of the sensor RSR differences needs to be quantified and compensated to avoid large uncertainties in cross-calibration results.

IEEE Transactions on Geoscience and Remote Sensing↗

USGS2013

Assessment of spectral band impact on intercalibration over desert sites using simulation based on EO-1 Hyperion data

Since the beginning of the 1990s, stable desert sites have been used for the calibration monitoring of many different sensors. Many attempts at sensor intercalibration have been also conducted using these stable desert sites. As a result, site characterization techniques and the quality of intercalibration techniques have gradually improved over the years. More recently, the Committee on Earth Observation Satellites has recommended a list of reference pseudo-invariant calibration sites for frequent image acquisition by multiple agencies. In general, intercalibration should use well-known or spectrally flat reference. The reflectance profile of desert sites, however, might not be flat or well characterized (from a fine spectral point of view). The aim of this paper is to assess the expected accuracy that can be reached when using desert sites for intercalibration. In order to have a well-mastered estimation of different errors or error sources, this study is performed with simulated data from a hyperspectral sensor. Earth Observing-1 Hyperion images are chosen to provide the simulation input data. Two different cases of intercalibration are considered, namely, Landsat 7 Enhanced Thematic Mapper Plus with Terra Moderate Resolution Imaging Spectroradiometer (MODIS) and Environmental Satellite MEdium Resolution Imaging Spectrometer (MERIS) with Aqua MODIS. The simulation results have confirmed that intercalibration accuracy of 1% to 2% can be achieved between sensors, provided there are a sufficient number of available measurements. The simulated intercalibrations allow explaining results obtained during real intercalibration exercises and to establish some recommendations for the use of desert sites for intercalibration.

IEEE Transactions on Geoscience and Remote Sensing↗

USGS2013

Overview of intercalibration of satellite instruments

Inter-calibration of satellite instruments is critical for detection and quantification of changes in the Earth’s environment, weather forecasting, understanding climate processes, and monitoring climate and land cover change. These applications use data from many satellites; for the data to be inter-operable, the instruments must be cross-calibrated. To meet the stringent needs of such applications requires that instruments provide reliable, accurate, and consistent measurements over time. Robust techniques are required to ensure that observations from different instruments can be normalized to a common scale that the community agrees on. The long-term reliability of this process needs to be sustained in accordance with established reference standards and best practices. Furthermore, establishing physical meaning to the information through robust Système International d'unités (SI) traceable Calibration and Validation (Cal/Val) is essential to fully understand the parameters under observation. The processes of calibration, correction, stability monitoring, and quality assurance need to be underpinned and evidenced by comparison with “peer instruments” and, ideally, highly calibrated in-orbit reference instruments. Inter-calibration between instruments is a central pillar of the Cal/Val strategies of many national and international satellite remote sensing organizations. Inter-calibration techniques as outlined in this paper not only provide a practical means of identifying and correcting relative biases in radiometric calibration between instruments but also enable potential data gaps between measurement records in a critical time series to be bridged. Use of a robust set of internationally agreed upon and coordinated inter-calibration techniques will lead to significant improvement in the consistency between satellite instruments and facilitate accurate monitoring of the Earth’s climate at uncertainty levels needed to detect and attribute the mechanisms of change. This paper summarizes the state-of-the-art of post-launch radiometric calibration of remote sensing satellite instruments, through inter-calibration.

IEEE Transactions on Geoscience and Remote Sensing↗

USGS2013

CEOS visualization environment (COVE) tool for intercalibration of satellite instruments

Increasingly, data from multiple instruments are used to gain a more complete understanding of land surface processes at a variety of scales. Intercalibration, comparison, and coordination of satellite instrument coverage areas is a critical effort of international and domestic space agencies and organizations. The Committee on Earth Observation Satellites Visualization Environment (COVE) is a suite of browser-based applications that leverage Google Earth to display past, present, and future satellite instrument coverage areas and coincident calibration opportunities. This forecasting and ground coverage analysis and visualization capability greatly benefits the remote sensing calibration community in preparation for multisatellite ground calibration campaigns or individual satellite calibration studies. COVE has been developed for use by a broad international community to improve the efficiency and efficacy of such calibration planning efforts, whether those efforts require past, present, or future predictions. This paper provides a brief overview of the COVE tool, its validation, accuracies, and limitations with emphasis on the applicability of this visualization tool for supporting ground field campaigns and intercalibration of satellite instruments.

IEEE Transactions on Geoscience and Remote Sensing↗

USGS2013

Absolute radiometric calibration of Landsat using a pseudo invariant calibration site

Pseudo invariant calibration sites (PICS) have been used for on-orbit radiometric trending of optical satellite systems for more than 15 years. This approach to vicarious calibration has demonstrated a high degree of reliability and repeatability at the level of 1-3% depending on the site, spectral channel, and imaging geometries. A variety of sensors have used this approach for trending because it is broadly applicable and easy to implement. Models to describe the surface reflectance properties, as well as the intervening atmosphere have also been developed to improve the precision of the method. However, one limiting factor of using PICS is that an absolute calibration capability has not yet been fully developed. Because of this, PICS are primarily limited to providing only long term trending information for individual sensors or cross-calibration opportunities between two sensors. This paper builds an argument that PICS can be used more extensively for absolute calibration. To illustrate this, a simple empirical model is developed for the well-known Libya 4 PICS based on observations by Terra MODIS and EO-1 Hyperion. The model is validated by comparing model predicted top-of-atmosphere reflectance values to actual measurements made by the Landsat ETM+ sensor reflective bands. Following this, an outline is presented to develop a more comprehensive and accurate PICS absolute calibration model that can be Système international d'unités (SI) traceable. These initial concepts suggest that absolute calibration using PICS is possible on a broad scale and can lead to improved on-orbit calibration capabilities for optical satellite sensors.

IEEE Transactions on Geoscience and Remote Sensing↗

USGS2012

Complementarity of ResourceSat-1 AWiFS and Landsat TM/ETM+ sensors

Considerable interest has been given to forming an international collaboration to develop a virtual moderate spatial resolution land observation constellation through aggregation of data sets from comparable national observatories such as the US Landsat, the Indian ResourceSat and related systems. This study explores the complementarity of India's ResourceSat-1 Advanced Wide Field Sensor (AWiFS) with the Landsat 5 Thematic Mapper (TM) and Landsat 7 Enhanced Thematic Mapper Plus (ETM+). The analysis focuses on the comparative radiometry, geometry, and spectral properties of the two sensors. Two applied assessments of these data are also explored to examine the strengths and limitations of these alternate sources of moderate resolution land imagery with specific application domains. There are significant technical differences in these imaging systems including spectral band response, pixel dimensions, swath width, and radiometric resolution which produce differences in observation data sets. None of these differences was found to strongly limit comparable analyses in agricultural and forestry applications. Overall, we found that the AWiFS and Landsat TM/ETM+ imagery are comparable and in some ways complementary, particularly with respect to temporal repeat frequency. We have found that there are limits to our understanding of the AWiFS performance, for example, multi-camera design and stability of radiometric calibration over time, that leave some uncertainty that has been better addressed for Landsat through the Image Assessment System and related cross-sensor calibration studies. Such work still needs to be undertaken for AWiFS and similar observatories that may play roles in the Global Earth Observation System of Systems Land Surface Imaging Constellation.

Remote Sensing of Environment↗

USGS2010

Monitoring on-orbit calibration stability of the Terra MODIS and Landsat 7 ETM+ sensors using pseudo-invariant test sites

The ability to detect and quantify changes in the Earth's environment depends on sensors that can provide calibrated, consistent measurements of the Earth's surface features through time. A critical step in this process is to put image data from different sensors onto a common radiometric scale. This work focuses on monitoring the long-term on-orbit calibration stability of the Terra Moderate Resolution Imaging Spectroradiometer (MODIS) and the Landsat 7 (L7) Enhanced Thematic Mapper Plus (ETM+) sensors using the Committee on Earth Observation Satellites (CEOS) reference standard pseudo-invariant test sites (Libya 4, Mauritania 1/2, Algeria 3, Libya 1, and Algeria 5). These sites have been frequently used as radiometric targets because of their relatively stable surface conditions temporally. This study was performed using all cloud-free calibrated images from the Terra MODIS and the L7 ETM+ sensors, acquired from launch to December 2008. Homogeneous regions of interest (ROI) were selected in the calibrated images and the mean target statistics were derived from sensor measurements in terms of top-of-atmosphere (TOA) reflectance. For each band pair, a set of fitted coefficients (slope and offset) is provided to monitor the long-term stability over very stable pseudo-invariant test sites. The average percent differences in intercept from the long-term trends obtained from the ETM + TOA reflectance estimates relative to the MODIS for all the CEOS reference standard test sites range from 2.5% to 15%. This gives an estimate of the collective differences due to the Relative Spectral Response (RSR) characteristics of each sensor, bi-directional reflectance distribution function (BRDF), spectral signature of the ground target, and atmospheric composition. The lifetime TOA reflectance trends from both sensors over 10 years are extremely stable, changing by no more than 0.4% per year in its TOA reflectance over the CEOS reference standard test sites.

Remote Sensing of Environment↗

USGS2010

A procedure for radiometric recalibration of Landsat 5 TM reflective-band data

From the Landsat program's inception in 1972 to the present, the Earth science user community has been benefiting from a historical record of remotely sensed data. The multispectral data from the Landsat 5 (L5) Thematic Mapper (TM) sensor provide the backbone for this extensive archive. Historically, the radiometric calibration procedure for the L5 TM imagery used the detectors' response to the internal calibrator (IC) on a scene-by-scene basis to determine the gain and offset for each detector. The IC system degraded with time, causing radiometric calibration errors up to 20%. In May 2003, the L5 TM data processed and distributed by the U.S. Geological Survey (USGS) Earth Resources Observation and Science Center through the National Landsat Archive Production System (NLAPS) were updated to use a lifetime lookup-table (LUT) gain model to radiometrically calibrate TM data instead of using scene-specific IC gains. Further modification of the gain model was performed in 2007. The L5 TM data processed using IC prior to the calibration update do not benefit from the recent calibration revisions. A procedure has been developed to give users the ability to recalibrate their existing level-1 products. The best recalibration results are obtained if the work-order report that was included in the original standard data product delivery is available. However, if users do not have the original work-order report, the IC trends can be used for recalibration. The IC trends were generated using the radiometric gain trends recorded in the NLAPS database. This paper provides the details of the recalibration procedure for the following: 1) data processed using IC where users have the work-order file; 2) data processed using IC where users do not have the work-order file; 3) data processed using prelaunch calibration parameters; and 4) data processed using the previous version of the LUT (e.g., LUT03) that was released before April 2, 2007.

IEEE Transactions on Geoscience and Remote Sensing↗

USGS2010

Radiometric, geometric, and image quality assessment of ALOS AVNIR-2 and PRISM sensors

The Advanced Land Observing Satellite (ALOS) was launched on January 24, 2006, by a Japan Aerospace Exploration Agency (JAXA) H-IIA launcher. It carries three remote-sensing sensors: 1) the Advanced Visible and Near-Infrared Radiometer type 2 (AVNIR-2); 2) the Panchromatic Remote-Sensing Instrument for Stereo Mapping (PRISM); and 3) the Phased-Array type L-band Synthetic Aperture Radar (PALSAR). Within the framework of ALOS Data European Node, as part of the European Space Agency (ESA), the European Space Research Institute worked alongside JAXA to provide contributions to the ALOS commissioning phase plan. This paper summarizes the strategy that was adopted by ESA to define and implement a data verification plan for missions operated by external agencies; these missions are classified by the ESA as third-party missions. The ESA was supported in the design and execution of this plan by GAEL Consultant. The verification of ALOS optical data from PRISM and AVNIR-2 sensors was initiated 4 months after satellite launch, and a team of principal investigators assembled to provide technical expertise. This paper includes a description of the verification plan and summarizes the methodologies that were used for radiometric, geometric, and image quality assessment. The successful completion of the commissioning phase has led to the sensors being declared fit for operations. The consolidated measurements indicate that the radiometric calibration of the AVNIR-2 sensor is stable and agrees with the Landsat-7 Enhanced Thematic Mapper Plus and the Envisat MEdium-Resolution Imaging Spectrometer calibration. The geometrical accuracy of PRISM and AVNIR-2 products improved significantly and remains under control. The PRISM modulation transfer function is monitored for improved characterization.

IEEE Transactions on Geoscience and Remote Sensing↗

USGS2009

Summary of current radiometric calibration coefficients for Landsat MSS, TM, ETM+, and EO-1 ALI sensors

This paper provides a summary of the current equations and rescaling factors for converting calibrated Digital Numbers (DNs) to absolute units of at-sensor spectral radiance, Top-Of-Atmosphere (TOA) reflectance, and at-sensor brightness temperature. It tabulates the necessary constants for the Multispectral Scanner (MSS), Thematic Mapper (TM), Enhanced Thematic Mapper Plus (ETM+), and Advanced Land Imager (ALI) sensors. These conversions provide a basis for standardized comparison of data in a single scene or between images acquired on different dates or by different sensors. This paper forms a needed guide for Landsat data users who now have access to the entire Landsat archive at no cost.

Remote Sensing of Environment↗

USGS2009

Developing consistent Landsat data sets for large area applications: the MRLC 2001 protocol

One of the major efforts in large area land cover mapping over the last two decades was the completion of two U.S. National Land Cover Data sets (NLCD), developed with nominal 1992 and 2001 Landsat imagery under the auspices of the MultiResolution Land Characteristics (MRLC) Consortium. Following the successful generation of NLCD 1992, a second generation MRLC initiative was launched with two primary goals: (1) to develop a consistent Landsat imagery data set for the U.S. and (2) to develop a second generation National Land Cover Database (NLCD 2001). One of the key enhancements was the formulation of an image preprocessing protocol and implementation of a consistent image processing method. The core data set of the NLCD 2001 database consists of Landsat 7 Enhanced Thematic Mapper Plus (ETM+) images. This letter details the procedures for processing the original ETM+ images and more recent scenes added to the database. NLCD 2001 products include Anderson Level II land cover classes, percent tree canopy, and percent urban imperviousness at 30-m resolution derived from Landsat imagery. The products are freely available for download to the general public from the MRLC Consortium Web site at http://www.mrlc.gov.

IEEE Geoscience and Remote Sensing Letters↗

USGS2009

SSTL UK-DMC SLIM-6 data quality assessment

Satellite data from the Surrey Satellite Technology Limited (SSTL) United Kingdom (UK) Disaster Monitoring Constellation (DMC) were assessed for geometric and radiometric quality. The UK-DMC Surrey Linear Imager 6 (SLIM-6) sensor has a 32-m spatial resolution and a ground swath width of 640 km. The UK-DMC SLIM-6 design consists of a three-band imager with green, red, and near-infrared bands that are set to similar bandpass as Landsat bands 2, 3, and 4. The UK-DMC data consisted of imagery registered to Landsat orthorectified imagery produced from the GeoCover program. Relief displacements within the UK-DMC SLIM-6 imagery were accounted for by using global 1-km digital elevation models available through the Global Land One-km Base Elevation (GLOBE) Project. Positional accuracy and relative band-to-band accuracy were measured. Positional accuracy of the UK-DMC SLIM-6 imagery was assessed by measuring the imagery against digital orthophoto quadrangles (DOQs), which are designed to meet national map accuracy standards at 1 : 24 000 scales; this corresponds to a horizontal root-mean-square accuracy of about 6 m. The UK-DMC SLIM-6 images were typically registered to within 1.0-1.5 pixels to the DOQ mosaic images. Several radiometric artifacts like striping, coherent noise, and flat detector were discovered and studied. Indications are that the SSTL UK-DMC SLIM-6 data have few artifacts and calibration challenges, and these can be adjusted or corrected via calibration and processing algorithms. The cross-calibration of the UK-DMC SLIM-6 and Landsat 7 Enhanced Thematic Mapper Plus was performed using image statistics derived from large common areas observed by the two sensors.

IEEE Transactions on Geoscience and Remote Sensing↗

USGS2009

Using the Sonoran Desert test site to monitor the long-term radiometric stability of the Landsat TM/ETM+ and Terra MODIS sensors

Pseudo-invariant ground targets have been extensively used to monitor the long-term radiometric calibration stability of remote sensing instruments. The NASA MODIS Characterization Support Team (MCST), in collaboration with members from the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center, has previously demonstrated the use of pseudo-invariant ground sites for the long-term stability monitoring of Terra MODIS and Landsat 7 ETM+ sensors. This paper focuses on the results derived from observations made over the Sonoran Desert. Additionally, Landsat 5 TM data over the Sonoran Desert site were used to evaluate the temporal stability of this site. Top-ofatmosphere (TOA) reflectances were computed for the closely matched TM, ETM+, and MODIS spectral bands over selected regions of interest. The impacts due to different viewing geometries, or the effect of test site Bi-directional Reflectance Distribution Function (BRDF), are also presented. ?? 2009 SPIE.

Conference Paper↗

USGS2009

Cross-comparison of the IRS-P6 AWiFS sensor with the L5 TM, L7 ETM+, & Terra MODIS sensors

As scientists and decision makers increasingly rely on multiple Earth-observing satellites to address urgent global issues, it is imperative that they can rely on the accuracy of Earth-observing data products. This paper focuses on the crosscomparison of the Indian Remote Sensing (IRS-P6) Advanced Wide Field Sensor (AWiFS) with the Landsat 5 (L5) Thematic Mapper (TM), Landsat 7 (L7) Enhanced Thematic Mapper Plus (ETM+), and Terra Moderate Resolution Imaging Spectroradiometer (MODIS) sensors. The cross-comparison was performed using image statistics based on large common areas observed by the sensors within 30 minutes. Because of the limited availability of simultaneous observations between the AWiFS and the Landsat and MODIS sensors, only a few images were analyzed. These initial results are presented. Regression curves and coefficients of determination for the top-of-atmosphere (TOA) trends from these sensors were generated to quantify the uncertainty in these relationships and to provide an assessment of the calibration differences between these sensors. ?? 2009 SPIE.

Conference Paper↗

USGS2008

Evaluation and comparison of the IRS-P6 and the landsat sensors

The Indian Remote Sensing Satellite (IRS-P6), also called ResourceSat-1, was launched in a polar sun-synchronous orbit on October 17, 2003. It carries three sensors: the highresolution Linear Imaging Self-Scanner (LISS-IV), the mediumresolution Linear Imaging Self-Scanner (LISS-III), and the Advanced Wide-Field Sensor (AWiFS). These three sensors provide images of different resolutions and coverage. To understand the absolute radiometric calibration accuracy of IRS-P6 AWiFS and LISS-III sensors, image pairs from these sensors were compared to images from the Landsat-5 Thematic Mapper (TM) and Landsat-7 Enhanced TM Plus (ETM+) sensors. The approach involves calibration of surface observations based on image statistics from areas observed nearly simultaneously by the two sensors. This paper also evaluated the viability of data from these nextgeneration imagers for use in creating three National Land Cover Dataset (NLCD) products: land cover, percent tree canopy, and percent impervious surface. Individual products were consistent with previous studies but had slightly lower overall accuracies as compared to data from the Landsat sensors.

IEEE Transactions on Geoscience and Remote Sensing↗