Abstract
The demonstrated efficacy of interferometric synthetic aperture radar (InSAR) techniques has spurred the development of innovative SAR satellite missions like BIOMASS and NiSAR, poised for extensive application in forest monitoring. Nevertheless, prevailing methodologies for retrieving forest variables, including forest height and above-ground biomass, encounter substantial limitations. Traditionally, successful forest mapping necessitates a non-zero spatial perpendicular baseline, full polarimetry, and a relatively small (close-to-zero) temporal baseline. This study presents a novel approach for extracting forest biophysical variables by modeling the temporal decorrelation of repeat-pass InSAR coherence. We explore a hypothesis regarding the potential relationship between the temporal decorrelation of InSAR coherence and forest variables, such as tree height and aboveground biomass. This hypothesis is tested across diverse test sites in Finland, Canada, and Germany. Our findings suggest a viable means of extracting forestry information by quantifying the temporal decorrelation of C-Band InSAR coherence.
Original language | English |
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Title of host publication | IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium |
Subtitle of host publication | Proceedings |
Publisher | IEEE Institute of Electrical and Electronic Engineers |
Pages | 4230-4234 |
Number of pages | 5 |
ISBN (Electronic) | 9798350360325 |
DOIs | |
Publication status | Published - 2024 |
MoE publication type | A4 Article in a conference publication |
Event | 2024 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2024 - Athens, Greece Duration: 7 Jul 2024 → 12 Jul 2024 |
Conference
Conference | 2024 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2024 |
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Country/Territory | Greece |
City | Athens |
Period | 7/07/24 → 12/07/24 |
Keywords
- aboveground biomass
- coherence
- forest height
- SAR interferometry
- temporal decorrelation
- time series