- PII
- S3034540525050097-1
- DOI
- 10.7868/S3034540525050097
- Publication type
- Status
- Published
- Authors
- Volume/ Edition
- Volume / Issue number 5
- Pages
- 99-104
- Abstract
- This study demonstrates the feasibility of using L-band two-pass Differential Interferometric Synthetic Aperture Radar (DInSAR) for monitoring boreal forest height dynamics with ALOS-2 PALSAR-2 data featuring an extremely long temporal baseline (2114 days). Scattering phase center despite the challenge of temporal decorrelation, high-quality interferometric measurements were achieved through careful selection of an interferometric pair with exceptionally similar atmospheric and forest–ground surface conditions. Validation against reference data confirmed that the resulting scattering phase center displacement map reflects real physical processes (height decrease due to logging and height increase due to growth) rather than decorrelation noise. The results prove the practical applicability of multi-temporal DInSAR pairs for monitoring changes in forest ecosystems.
- Keywords
- радиолокационная интерферометрия спутниковые данные космический мониторинг лесные экосистемы высота леса PALSAR-2
- Date of publication
- 21.03.2026
- Year of publication
- 2026
- Number of purchasers
- 0
- Views
- 5
References
- 1. Бондур В.Г., Гордо К.А. Космический мониторинг площадей, пройденных огнем, и объемов эмиссий вредных примесей при лесных и других природных пожарах на территории Российской Федерации // Исследование Земли из космоса. 2018. № 3. С. 41–55. https://doi.org/10.7868/S020596141803003X
- 2. Бондур В.Г., Гордо К.А., Кладов В.Л. Пространственновременные распределения площадей природных пожаров и эмиссий углеродсодержащих газов и аэрозолей на территории северной Евразии по данным космического мониторинга // Исследование Земли из космоса. 2016. № 6. С. 3–20. https://doi.org/10.7868/S0205961416060105
- 3. Bondur V., Chimitdorzhiev T., Kirbizhekova I., Dmitriev A. A Novel Method of Boreal Zone Reforestation/Afforestation Estimation Using PALSAR-1, 2 and Landsat-5, 8 Data. Forests 2024, 15, 132. https://doi.org/10.3390/f15010132
- 4. Bondur V., Chimitdorzhiev T., Kirbizhekova I., Dmitriev A. Estimation of Postfire Reforestation with SAR Polarimetry and NDVI Time Series. Forests 2022, 13, 814. https://doi.org/10.3390/f13050814
- 5. Cloude S.R., Papathanassiou K.P. Three-stage inversion process for polarimetric SAR interferometry. // IEE Proceedings - Radar, Sonar and Navigation 2003. V. 150. No. 3. P. 125–134. https://doi.org/10.1049/ip-rsn:20030449
- 6. ERA5-Land Hourly - ECMWF Climate Reanalysis, 2025, [Электронный ресурс], URL: https://developers.google.com/earth-engine/datasets/catalog/ECMWF_ERA5LAND_HOURLY (Дата обращения 23 сентября 2025).
- 7. Kugler F., Schulze D., Hajnsek I., Pretzsch H., Papathanassiou K.P. TanDEM-X Pol-InSAR Performance for Forest Height Estimation // IEEE Transactions on Geoscience and Remote Sensing. 2014. V. 52. No. 10. P. 6404–6422. https://doi.org/10.1109/TGRS.2013.2296533
- 8. Lavalle M., Hensley S. Extraction of Structural and Dynamic Properties of Forests From Polarimetric-Interferometric SAR Data Affected by Temporal Decorrelation // IEEE Transactions on Geoscience and Remote Sensing. 2015. V. 53. No. 9. P. 4752–4767. https://doi.org/10.1109/TGRS.2015.2409066
- 9. Muñoz-Sabater J., Dutra E., Agustí-Panareda A., Albergel C., Arduini G., Balsamo G., Boussetta S., Choulga M., Harrigan S., Hersbach H., Martens B., Miralles D.G., Piles M., Rodríguez-Fernández N.J., Zsoter E., Buontempo C., Thépaut J.-N. ERA5-Land: a state-of-the-art global reanalysis dataset for land applications // Earth System Science Data. 2021. V. 13. No. 9. P. 4349–4383. https://doi.org/10.5194/essd-13-4349-2021
- 10. Papathanassiou K.P., Cloude S.R. Single-baseline polarimetric SAR interferometry // IEEE Transactions on Geoscience and Remote Sensing. 2001. V. 39. No. 11. P. 2352–2363. https://doi.org/10.1109/36.964971
- 11. Simard M., Hensley S., Lavalle M., Dubayah R., into N., Hofton M. An Empirical Assessment of Temporal Decorrelation Using the Uninhabited Aerial Vehicle Synthetic Aperture Radar over Forested Landscapes // Remote Sensing. 2012. V. 4. No. 4. P. 975–986. https://doi.org/10.3390/rs4040975
- 12. Tebaldini S., Ho Tong Minh D., Mariotti d’Alessandro M., Villard L., Le Toan T., Chave J. The Status of Technologies to Measure Forest Biomass and Structural Properties: State of the Art in SAR Tomography of Tropical Forests // Surv Geophys. 2019. V. 40. No. 4. P. 779–801. https://doi.org/10.1007/s10712-019-09539-7
- 13. Yu C., Li Z., Penna N.T., Crippa P. Generic Atmospheric Correction Model for Interferometric Synthetic Aperture Radar Observations // Journal of Geophysical Research: Solid Earth. 2018. V. 123. No. 10. P. 9202–9222. https://doi.org/10.1029/2017JB015305
- 14. Zebker H.A., Villasenor J. Decorrelation in interferometric radar echoes // IEEE Transactions on Geoscience and Remote Sensing. 1992. V. 30. No. 5. P. 950–959. https://doi.org/10.1109/36.175330
