Improving Landsat Multispectral Scanner (MSS) geolocation by least-squares-adjustment based time-series co-registration
Published 2020 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Improving Landsat Multispectral Scanner (MSS) geolocation by least-squares-adjustment based time-series co-registration
Authors
Keywords
Landsat, MSS, Geolocation, Registration, Analysis ready data, Time series
Journal
REMOTE SENSING OF ENVIRONMENT
Volume 252, Issue -, Pages 112181
Publisher
Elsevier BV
Online
2020-11-19
DOI
10.1016/j.rse.2020.112181
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- A conterminous United States analysis of the impact of Landsat 5 orbit drift on the temporal consistency of Landsat 5 Thematic Mapper data
- (2020) David P. Roy et al. REMOTE SENSING OF ENVIRONMENT
- Operational Coregistration of the Sentinel-2A/B Image Archive Using Multitemporal Landsat Spectral Averages
- (2020) Philippe Rufin et al. IEEE Geoscience and Remote Sensing Letters
- Landsat 4, 5 and 7 (1982 to 2017) Analysis Ready Data (ARD) Observation Coverage over the Conterminous United States and Implications for Terrestrial Monitoring
- (2019) Alexey Egorov et al. Remote Sensing
- Current status of Landsat program, science, and applications
- (2019) Michael A. Wulder et al. REMOTE SENSING OF ENVIRONMENT
- FORCE—Landsat + Sentinel-2 Analysis Ready Data and Beyond
- (2019) David Frantz Remote Sensing
- Bundle Adjustment Using Space-Based Triangulation Method for Improving the Landsat Global Ground Reference
- (2019) James C. Storey et al. Remote Sensing
- Landsat-8 and Sentinel-2 burned area mapping - A combined sensor multi-temporal change detection approach
- (2019) David P. Roy et al. REMOTE SENSING OF ENVIRONMENT
- Lessons learned implementing an operational continuous United States national land change monitoring capability: The Land Change Monitoring, Assessment, and Projection (LCMAP) approach
- (2019) Jesslyn F. Brown et al. REMOTE SENSING OF ENVIRONMENT
- Landsats 1–5 Multispectral Scanner System Sensors Radiometric Calibration Update
- (2019) Cibele Teixeira Pinto et al. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
- Characterization of Sentinel-2A and Landsat-8 top of atmosphere, surface, and nadir BRDF adjusted reflectance and NDVI differences
- (2018) Hankui K. Zhang et al. REMOTE SENSING OF ENVIRONMENT
- Sentinel-2A multi-temporal misregistration characterization and an orbit-based sub-pixel registration methodology
- (2018) L. Yan et al. REMOTE SENSING OF ENVIRONMENT
- Automatic sub-pixel co-registration of Landsat-8 Operational Land Imager and Sentinel-2A Multi-Spectral Instrument images using phase correlation and machine learning based mapping
- (2017) Sergii Skakun et al. International Journal of Digital Earth
- Copernicus Sentinel-2A Calibration and Products Validation Status
- (2017) Ferran Gascon et al. Remote Sensing
- The global Landsat archive: Status, consolidation, and direction
- (2016) Michael A. Wulder et al. REMOTE SENSING OF ENVIRONMENT
- A note on the temporary misregistration of Landsat-8 Operational Land Imager (OLI) and Sentinel-2 Multi Spectral Instrument (MSI) imagery
- (2016) James Storey et al. REMOTE SENSING OF ENVIRONMENT
- Preliminary analysis of the performance of the Landsat 8/OLI land surface reflectance product
- (2016) Eric Vermote et al. REMOTE SENSING OF ENVIRONMENT
- An Automated Approach for Sub-Pixel Registration of Landsat-8 Operational Land Imager (OLI) and Sentinel-2 Multi Spectral Instrument (MSI) Imagery
- (2016) Lin Yan et al. Remote Sensing
- Automated cloud and cloud shadow identification in Landsat MSS imagery for temperate ecosystems
- (2015) Justin D. Braaten et al. REMOTE SENSING OF ENVIRONMENT
- Improved time series land cover classification by missing-observation-adaptive nonlinear dimensionality reduction
- (2015) L. Yan et al. REMOTE SENSING OF ENVIRONMENT
- A One Year Landsat 8 Conterminous United States Study of Cirrus and Non-Cirrus Clouds
- (2015) Valeriy Kovalskyy et al. Remote Sensing
- Spectral-Angle-based Laplacian Eigenmaps for Nonlinear Dimensionality Reduction of Hyperspectral Imagery
- (2014) Lin Yan et al. PHOTOGRAMMETRIC ENGINEERING AND REMOTE SENSING
- Landsat-8: Science and product vision for terrestrial global change research
- (2014) D.P. Roy et al. REMOTE SENSING OF ENVIRONMENT
- Automated Geometric Correction of Landsat MSS L1G Imagery
- (2013) Chabitha Devaraj et al. IEEE Geoscience and Remote Sensing Letters
- Assessment of the NASA–USGS Global Land Survey (GLS) datasets
- (2013) Garik Gutman et al. REMOTE SENSING OF ENVIRONMENT
- Conterminous United States demonstration and characterization of MODIS-based Landsat ETM+ atmospheric correction
- (2013) D.P. Roy et al. REMOTE SENSING OF ENVIRONMENT
- Landsat: Building a strong future
- (2012) Thomas R. Loveland et al. REMOTE SENSING OF ENVIRONMENT
- Radiometric Calibration of the Landsat MSS Sensor Series
- (2011) Dennis L. Helder et al. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
- Automated registration and orthorectification package for Landsat and Landsat-like data processing
- (2010) Jeffrey Masek Journal of Applied Remote Sensing
- Development of time series stacks of Landsat images for reconstructing forest disturbance history
- (2009) Chengquan Huang et al. International Journal of Digital Earth
- Web-enabled Landsat Data (WELD): Landsat ETM+ composited mosaics of the conterminous United States
- (2009) David P. Roy et al. REMOTE SENSING OF ENVIRONMENT
- Turning images into 3-D models
- (2008) Fabio Remondino et al. IEEE SIGNAL PROCESSING MAGAZINE
- An experimental evaluation of non‐rigid registration techniques on Quickbird satellite imagery
- (2007) V. Arévalo et al. INTERNATIONAL JOURNAL OF REMOTE SENSING
- The availability of cloud-free Landsat ETM+ data over the conterminous United States and globally
- (2007) Junchang Ju et al. REMOTE SENSING OF ENVIRONMENT
Publish scientific posters with Peeref
Peeref publishes scientific posters from all research disciplines. Our Diamond Open Access policy means free access to content and no publication fees for authors.
Learn MoreCreate your own webinar
Interested in hosting your own webinar? Check the schedule and propose your idea to the Peeref Content Team.
Create Now