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Initial Understanding of Landsat-9 Capabilities and Applications

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Earth Observation Data".

Deadline for manuscript submissions: closed (31 December 2023) | Viewed by 4442

Special Issue Editors


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Guest Editor
School of Artificial Intelligence, Shenzhen Polytechnic, Shenzhen 518055, China
Interests: earth observation and remote sensing; spectral modeling; quantitative estimation of soil properties; digital soil mapping; GIS; spatial analysis; environmental sustainability
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Retired, University of Ottawa, Ottawa, ON K1N 6N5, Canada
Interests: remote sensing satellite and UAV (multispectral, hyperspectral and radar); geomatic; natural resources; natural hazard; precision agriculture; land degradation; soil salinity; climate change; environmental impact assessment; optical sensor calibration
Special Issues, Collections and Topics in MDPI journals
School of Remote Sensing and Surveying Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China
Interests: mapping; image processing; computer vision; spatial analysis; satellite image analysis; geoinformation; geospatial science; feature extraction; classification
School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China
Interests: satellite image processing; satellite image analysis; remote sensing; image registration; image reconstruction; image restoration; cloud cover; missing data analysis; image mosaic; image fusion; image inpainting; multitemporal analysis
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Landsat is the longest running continuously operating Earth observation satellite program. During the last 50 years, Landsat satellites have documented Earth's changing landscape using four types of multispectral sensors (i.e., MSS, TM, ETM +, and OLI). The science quality of the Landsat archive, including careful calibration and standardization, allows it to serve as a “gold standard” for studies harmonizing multiple sources of data. In many respects, Landsat-9 is a clone of Landsat-8. It was launched on September 27th, 2021, in time to extend Landsat’s remarkable record of 50 years. Currently, Landsat-9 is the latest satellite in the Landsat series, and it is believed that this mission will continue and improve the capabilities of Landsat-8. The 8-day coverage of the combined Landsat-OLI (8/9) constellation will support many application areas in biosphere, cryosphere and atmosphere sciences. Moreover, this constellation will also help to better support emerging applications such as water quality monitoring, precision agriculture (crop water and fertilization stress, evapotranspiration, etc.), climate change assessment, forest and ecological systems, etc. More importantly, it is expected to support the monitoring and delivery of the UN’s Sustainable Development Goals (SDG).

The Operational Land Imager-2 (OLI-2) is identical to the OLI-1 carried onboard Landsat-8, providing data in the VNIR and SWIR wavelengths with a high quality of calibration/validation procedures. The combined virtual constellation of Landsat-OLI (8/9) and Sentinel-MSI (2A/2B) will provide coverage of the Earth's surface (land, water and ice) with a temporal resolution of less than 3 days, allowing the acquisition of 740 new scenes per day from each platform. Landsat-9 should thus continue the heritage of providing global and open access “science-grade” data to inform long-term assessments of land and aquatic change in response to both natural and human forces. For these reasons, this Special Issue provides an opportunity to collect original manuscripts on innovative research exploring the capabilities of the Landsat-9 instrument in several applications, as well as, its joint use with data acquired by other satellites.

We would like to invite you to submit articles about your recent research with respect to the following topics:

  • Radiometric calibration and atmospheric corrections of OLI-2 data;
  • Spectral characterization of OLI-2 data;
  • Spatial characterization of OLI-2 data;
  • Validation and quality-assurance assessment and characterization of the OLI-2 data (e.g., radiometry, geometry, and topography) and products (biophysical, physiological, and physical parameters);
  • Radiometric and spectral cross-calibration of OLI-2 data with other satellite sensors;
  • Comparison between OLI-2 and other optical satellite sensors (e.g., TM, ETM+, OLI-1, Sentinel-MSI, etc.);
  • Land surface monitoring using OLI-2 data, including (but not limited to) land cover and land use change, agriculture, forest, urbanization, disasters, climate modelling and hydrological applications;
  • Combination and fusion approaches of OLI-2 data with other sensors' data (e.g., Sentinel-MSI 2A and 2B, hyperspectral data, Radar data, Planet-scope, Worldview series, etc.).
  • Tools, toolboxes, and algorithms for processing and analyzing OLI-2 data;
  • Other OLI-2 related studies.

Dr. Jingzhe Wang
Prof. Dr. Abderrazak Bannari
Dr. Jian Li
Dr. Xinghua Li
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • remote sensing
  • radiometric and atmospheric correction
  • quality assessment
  • land surface monitoring
  • land use/cover changes (LUCC)
  • natural resource monitoring and mapping

Published Papers (2 papers)

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Research

19 pages, 7899 KiB  
Article
Intercomparison of Landsat OLI and JPSS VIIRS Using a Combination of RadCalNet Sites as a Common Reference
by Mohammad H. Tahersima, Kurtis Thome, Brian N. Wenny, Norvik Voskanian and Mehran Yarahmadi
Remote Sens. 2023, 15(23), 5562; https://doi.org/10.3390/rs15235562 - 29 Nov 2023
Cited by 1 | Viewed by 684
Abstract
Independent radiometric data collected from multiple ground sites as part of vicarious calibration activities can be combined to harmonize the data products of Earth observation sensors with different temporal, spectral, and spatial resolutions. Recent coordinated international efforts for open fiducial reference measurements have [...] Read more.
Independent radiometric data collected from multiple ground sites as part of vicarious calibration activities can be combined to harmonize the data products of Earth observation sensors with different temporal, spectral, and spatial resolutions. Recent coordinated international efforts for open fiducial reference measurements have provided the worldwide user community with new ways to explore the calibration and harmonization of data produced by the sensors. To be correct, the results from each ground system must be traceable to the same well-understood standard system, and ideally to the international system of units (SI). Additionally, the calibration test site should be homogeneous over an area larger than the spatial resolutions of each sensor, so that ground measurements are representative of the area seen by the sensors being calibrated. Here, we use a combination of independent and SI-traceable radiometric data provided from two sites of the Radiometric Calibration Network (RadCalNet) to compare the radiometric response of sensors with different spectral and spatial resolutions that operate on different orbits. These sensors are Operational Land Imagers (OLI) of the Landsat-8 and Landsat-9 missions, and Visible Infrared Imaging Radiometer Suites (VIIRS) of the Suomi-National Polar-Orbiting Operational Environmental Satellite System Preparatory Project (SNPP) and Joint Polar Satellite System-1 (JPSS-1) missions. The sensor radiometric responses are compared via temporal averaging of the ratios of top-of-atmosphere reflectance values for each sensor to those reported by RadCalNet. Our intercomparison results show that these on-orbit sensors are calibrated within their absolute radiometric uncertainties. The absolute radiometric uncertainties of single-sensor over single-site intercomparisons at 550 nm is between 5% and 6%. Having the opportunity to look at the intercomparison results of Landsat-9 OLI compared to each calibration site individually and then in combination allowed us to investigate potential systematic site-dependent biases. We did not observe significant site-dependent biases in the behavior of the four on-orbit sensors compared to the calibration sites. The absolute radiometric uncertainty of a single sensor over multiple-site intercomparisons at 550 nm is 5.4%. We further investigated site-dependent biases by looking at the double-ratio calibration coefficients of the on-orbit sensors, calculated with reference to those sites. Full article
(This article belongs to the Special Issue Initial Understanding of Landsat-9 Capabilities and Applications)
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23 pages, 30351 KiB  
Article
Comparing the Capability of Sentinel-2 and Landsat 9 Imagery for Mapping Water and Sandbars in the River Bed of the Lower Tagus River (Portugal)
by Romeu Gerardo and Isabel P. de Lima
Remote Sens. 2023, 15(7), 1927; https://doi.org/10.3390/rs15071927 - 03 Apr 2023
Cited by 3 | Viewed by 2750
Abstract
Mapping river beds to identify water and sandbars is a crucial task for understanding the morphology and hydrodynamics of rivers and their ecological conditions. The main difficulties of this task so far have been the limitations of conventional approaches, which are generally costly [...] Read more.
Mapping river beds to identify water and sandbars is a crucial task for understanding the morphology and hydrodynamics of rivers and their ecological conditions. The main difficulties of this task so far have been the limitations of conventional approaches, which are generally costly (e.g., equipment, time- and human resource-demanding) and have poor flexibility to deal with all river conditions. Currently, alternative approaches rely on remote sensing techniques, which offer innovative tools for mapping water bodies in a quick and cost-effective manner based on relevant spectral indices. This study aimed to compare the capability of using imagery from the Sentinel-2 and newly launched Landsat 9 satellite to achieve this goal. For a segment of the Lower Tagus River (Portugal) with conditions of very low river discharge, comparison of the Normalized Difference Water Index, Modified Normalized Difference Water Index, Augmented Normalized Difference Water Index, and Automated Water Extraction Index calculated from the imagery of the two satellites shows that the two satellites’ datasets and mapping were consistent and therefore could be used complementarily. However, the results highlighted the need to classify satellite imagery based on index-specific classification decision values, which is an important factor in the quality of the information extracted. Full article
(This article belongs to the Special Issue Initial Understanding of Landsat-9 Capabilities and Applications)
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