Abstract
Current space-based SAR offers unique opportunities to classify vegetation types and to monitor vegetation growth due to its frequent acquisitions and its sensitivity to vegetation geometry. However, SAR signals also experience frequent temporal fluctuations caused by precipitation events, complicating the mapping and monitoring of vegetation. In this paper, we show that the influence of a priori known precipitation events on the signals can be used advantageously for the classification of vegetation conditions. For this, we exploit the change in Sentinel-1 backscatter response between consecutive acquisitions under varying wetness conditions, which we show is dependent on the state of vegetation. The performance further improves when a priori information on the soil type is taken into account.
Original language | English |
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Pages (from-to) | 1-17 |
Number of pages | 17 |
Journal | Remote Sensing |
Volume | 10 |
Issue number | 10 |
DOIs | |
Publication status | Published - 2018 |
Bibliographical note
After publication of the research paper [1], the authors wish to make the following correction.The link to the affiliation of Ramon F. Hanssen should have been (1). Hence, the affiliation of Ramon
F. Hanssen is Geoscience and Remote Sensing at Delft University of Technology. The authors would like to apologize for any inconvenience caused. The change does not affect the scientific results.
The manuscript will be updated and the original will remain online on the article webpage, with a reference to this correction.
Reference
1. Molijn, R.A.; Iannini, L.; López Dekker, P.; Magalhães, P.S.; Hanssen, R.F. Vegetation Characterization
through the Use of Precipitation-Affected SAR Signals. Remote Sens. 2018, 10, 1647. [CrossRef]
Keywords
- Incidence angle
- Precipitation
- SAR signals
- Soil type
- Vegetation classification