The DOI matches its Crossref record.
Decorrelation in interferometric radar echoes
Abstract
A radar interferometric technique for topographic mapping of surfaces, implemented utilizing a single synthetic aperture radar (SAR) system in a nearly repeating orbit, is discussed. The authors characterize the various sources contributing to the echo correlation statistics, and isolate the term which most closely describes surficial change. They then examine the application of this approach to topographic mapping of vegetated surfaces which may be expected to possess varying backscatter over time. It is found that there is decorrelation increasing with time but that digital terrain model generation remains feasible. The authors present such a map of a forested area in Oregon which also includes some nearly unvegetated lava flows. Such a technique could provide a global digital terrain map.>
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Cited by
A multi‐temporal InSAR method incorporating both persistent scatterer and small baseline approaches
Hooper, A. (2008) · Geophysical Research Letters · doi:10.1029/2008gl034654 · Cited by 1,257
Quantifying Forest Biomass Carbon Stocks From Space
Rodríguez-Veiga, P., Wheeler, J., Louis, V., Tansey, K., & Balzter, H. (2017) · Current Forestry Reports · doi:10.1007/s40725-017-0052-5 · Cited by 177
Metadata
- Authors
- Zebker, H. A., & Villasenor, J.
- Venue
- IEEE Transactions on Geoscience and Remote Sensing
- Published
- 1992
- Volume
- 30
- Issue
- 5
- Pages
- 950-959
- ISSN
- 0196-2892 (ISSN-L)
- OpenAlex
- W2141414687
- Cited by
- 2,453
- References
- 0
- FWCI
- 27.50
- Type
- journal article
- Language
- en
- Open access
- closed
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- Zebker, H. A., & Villasenor, J. (1992). Decorrelation in interferometric radar echoes. IEEE Transactions on Geoscience and Remote Sensing. https://doi.org/10.1109/36.175330
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.