Title | Evaluation of vegetation biophysical variables time series derived from synthetic Sentinel-2 images |
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Author | Djamai, N ; Zhong,
D ; Fernandes, R ; Zhou, F |
Source | Remote Sensing vol. 11, 13, 1547, 2019., https://doi.org/10.3390/rs11131547 Open Access |
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Year | 2019 |
Alt Series | Natural Resources Canada, Contribution Series 20190630 |
Document | serial |
Lang. | English |
Media | paper; on-line; digital |
File format | pdf |
Subjects | geophysics; remote sensing; vegetation |
Program | Canada Centre for Remote Sensing Divsion |
Released | 2019 06 29 |
Abstract | Traditional polarization architectures transmit and receive linear polarizations (LL). Canadas RADARSAT Constellation Mission (RCM) will be equipped with a hybrid architecture that will transmit a
circular polarization and receive linear polarizations (CL). The objective of this study is to assess the benefits of CL polarization images, in comparison to LL, for automated structural mapping in Canadian Shield terrain. RADARSAT-2 data acquired
over the Manicouagan impact crater are used to simulate RCM data through the Natural Resources Canada RCM-CP (compact polarimetric) v3 program. Circular transmit/receive (CC) polarization images were also generated and included in this study. The
structural mapping benefits of each polarization architecture have been assessed via comparisons with a manually inferred fault map, escarpment map, and optical data illustrating faults indicated through extended linear waterbodies. The results
demonstrate that the CL and LL architectures provide a complementary overview of the structural geology. CL, in relation to LL, provides a greater spatial extent of lineaments, better optimizes faults expressed through linear waterbodies, and
highlights the largest number of manually inferred faults, while LL better recognizes faults related to moderate relief. We conclude that RCMs CL architecture will provide an additional benefit for structural mapping in the Canadian Shield and
equivalent terrains. © 2018, © 2018 Canadian Aeronautics and Space Institute. |
GEOSCAN ID | 321959 |
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