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Mapping Surface Structure and Topography by Airborne and Spaceborne Altimetry

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Remote Sensing in Geology, Geomorphology and Hydrology".

Deadline for manuscript submissions: closed (10 August 2021) | Viewed by 5960

Special Issue Editors

ESPACE-DEV, UMR 228 IRD/UM/UR/UG/UA, Institut de Recherche pour le Développement (IRD), 34093 Montpellier, France
Interests: space hydrology (radar altimetry); spatial distribution of soils using knowledge-based models and remote sensing (visible; IR; and SAR); characterization of land use (texture analysis; object-oriented approaches; expert classifications; modeling)
Special Issues, Collections and Topics in MDPI journals
Consiglio Nazionale delle Ricerche (CNR), Area della Ricerca CNR S. Cataldo, Via Moruzzi 1, 56100 Pisa, Italy
Interests: ocean and land remote sensing; satellite radar altimetry; water level; coastal zone; inland waters
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The topography of the earth’s surface is the result of long-term structural and tectonic evolution of the earth together with the distribution of the gravity field that conditions the circulation of water. The circulation of water at the surface of the ground, in the subsurface, and at depth shapes reliefs through mechanical and chemical erosion. Topography is, in turn, one of the factors affecting the differentiation of soils and their microbial communities; it is essential for the characterization of watersheds and, therefore, for hydrological modeling; and it is one of the parameters of sun illumination and, thus, the amount of energy received by the earth’s surface and, consequently, one of the discriminating parameters of plant phenology. Spatialized knowledge of topography is essential in managing flood or landslide risks as well as in urban planning. The absolute and relative accuracy of global numerical terrain models is insufficient for applications that require, for example, discrimination of the shape of slopes, characterization of soil typology, or determination of flood risk in urban areas.

Satellite radar altimetry missions have been used for characterization of the ocean surface and, thus, the topography of the ocean floor as well for geodesic studies concerning the distribution of the gravity field on the earth’s surface. Since TOPEX/Poseidon and ERS, altimeter spatial data have begun to be used to characterize the surface of continental water bodies (e.g., lakes, rivers, reservoirs, wetlands, etc.). Some drift orbit missions have been used to map the surface of polar ice caps or continental surfaces. Great advances are expected given the possibility offered by new missions (e.g., CryoSat-2, Sentinel-3) in rethinking processing over the various complex surfaces using along-track unfocused/focused synthetic aperture radar (SAR) approaches. Some uses of GPS or Galileo (GNSS) signals may also allow for better mapping of topography. The use of images in the visible domain in stereoscopic mode or the use of oblique images is a means of producing terrain mapping. Studying the phase of images in the microwave spectrum is also one of the ways to map the terrain or its evolution in a short time.

The aim of this Special Issue is to take stock of the latest knowledge in these different fields and to address the crucial issue of accuracy in global topographical models.

Dr. Frédérique Seyler
Dr. Stefano Vignudelli
Guest Editors

Manuscript Submission Information

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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

  • radar altimetry
  • radar/optical imagery
  • GNSS
  • topography

Published Papers (2 papers)

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Research

25 pages, 13276 KiB  
Article
An Analytical Method for Dynamic Wave-Related Errors of Interferometric SAR Ocean Altimetry under Multiple Sea States
by Yao Chen, Mo Huang, Yuanyuan Zhang, Changyuan Wang and Tao Duan
Remote Sens. 2021, 13(5), 986; https://doi.org/10.3390/rs13050986 - 05 Mar 2021
Cited by 4 | Viewed by 2012
Abstract
The spaceborne interferometric synthetic aperture radar (InSAR) is expected to measure the sea surface height (SSH) with high accuracy over a wide swath. Since centimeter-level accuracy is required to monitor the ocean sub-mesoscale dynamics, the high accuracy implies that the altimetric errors should [...] Read more.
The spaceborne interferometric synthetic aperture radar (InSAR) is expected to measure the sea surface height (SSH) with high accuracy over a wide swath. Since centimeter-level accuracy is required to monitor the ocean sub-mesoscale dynamics, the high accuracy implies that the altimetric errors should be totally understood and strictly controlled. However, for the dynamic waves, they move randomly all the time, and this will lead to significant altimetric errors. This study proposes an analytical method for the dynamic wave-related errors of InSAR SSH measurement based on the wave spectrum and electromagnetic scattering model. Additionally, the mechanisms of the dynamic wave-related errors of InSAR altimetry are analyzed, and the detailed numerical model is derived. The proposed analytical method is validated with NASA’s Surface Water and Ocean Topography (SWOT) project error budget, and the Root-Mean-Square Errors (RMSEs) are in good agreement (0.2486 and 0.2470 cm on a 0.5 km2 grid, respectively). Instead of analysis for a typical project, the proposed method can be applied to different radar parameters under multiple sea states. The RMSEs of Ka-band under low sea state, moderate sea state, and high sea state are 0.2670, 1.3154, and 6.6361 cm, respectively. Moreover, the RMSEs of X-band and Ku-band are also simulated and presented. The experimental results demonstrate that the dynamic wave-related errors of InSAR altimetry are not sensitive to the frequencies but are sensitive to the sea states. The error compensation method is necessary for moderate and higher sea states for centimetric accuracy requirements. This can provide feasible suggestions on system design and error budget for the future interferometric wide-swath altimeter. Full article
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20 pages, 4720 KiB  
Article
Mean Sea Surface Model over the Sea of Japan Determined from Multi-Satellite Altimeter Data and Tide Gauge Records
by Jiajia Yuan, Jinyun Guo, Yupeng Niu, Chengcheng Zhu and Zhen Li
Remote Sens. 2020, 12(24), 4168; https://doi.org/10.3390/rs12244168 - 19 Dec 2020
Cited by 15 | Viewed by 2832
Abstract
Mean sea surface (MSS) is an important datum for the study of sea-level changes and charting data, and its accuracy in coastal waters has always been the focus of marine geophysics and oceanography. A new MSS model with a grid of 1′ × [...] Read more.
Mean sea surface (MSS) is an important datum for the study of sea-level changes and charting data, and its accuracy in coastal waters has always been the focus of marine geophysics and oceanography. A new MSS model with a grid of 1′ × 1′ over the Sea of Japan and its adjacent ocean (named SJAO2020) (25° N~50° N, 125° E~150° E) was established. It ingested 12 different satellites altimeter data (including TOPEX/Poseidon, Jason-1/2/3, ERS-1/2, Envisat, GFO, HaiYang-2A, SRL/Altika, Sentinel-3A, Cryosat-2) and 24 tide gauge stations’ records and joint GNSS data. The latter were used to correct the sea surface height within 10 km from the coastline by using the Gaussian inverse distance weighting method in SJAO2020. The differences among SJAO2020, CLS15, and DTU18, as well as the differences between them and the altimeter data of HY-2A, Jason-3, and Sentinel-3A were introduced. By comparing with tide gauge records, satellite altimeter data, and other models (DTU18, DTU15, CLS15, CLS11 and WHU13), it was demonstrated that SJAO2020 produces the smallest errors, and its coastal accuracy is relatively reliable. Full article
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