TWIST-NZ - Tree Water and Soil Moisture Integration for Satellite Calibration and Validation in New Zealand - Early BIOMASS results

Kurzfassung

The ESA BIOMASS mission aims to retrieve above-ground biomass and forest height data to enhance our knowledge about the state of the Earth’s forests and the carbon cycle. Besides these primary mission parameters, its P-band (430 MHz) SAR sensor is also able to provide information on secondary geophysical variables, such as tree trunk water content (TWC) and upper root-zone soil moisture (RZSM). These parameters are essential for understanding the Earth’s climate and vegetation-hydrology interactions, and play an essential role in the soilplant-atmosphere feedback processes [1,2]. However, they remain insufficiently validated in current global Earth Observation frameworks. The TWIST-NZ project seeks to establish a framework to validate secondary mission products at three sites in New Zealand. New Zealand offers a unique environment with varying climatic zones, soil types, and geology with the same dominant tree species, Pinus radiata (D. Don) [3], making it an ideal location for testing satellite-derived estimates of TWC and RZSM based on P-band BIOMASS observations. Additionally, during the Forest Flows program (2019-2025) research sites were intensely measured with a series of integrated terrestrial and remote sensing measurements [4], including airborne P-Band SAR [5]. We will take advantage of the established sensor networks and previous measurements to evaluate the sensitivity of the Pband radar sensor to RZSM, assess the seasonality in TWC, and examine the variability in RZSM across three different forest with contrasting climate, geology and soil. For the estimation of TWC and SM from P-band BIOMASS data, the approaches from [1,2,6] should be adapted and further refined. These approaches include polarimetric decomposition of SAR observations as well as signal modeling based on physically-constrained methods (such as the multi-layer soil scattering and radar vegetation interaction models). For the validation of the secondary products, in situ measurements from the Forest Flows monitoring network (https://www.forestflows.nz), acquired airborne P-band SAR observations from the SlimSAR system (aligning with BIOMASS satellite overpasses to ensure comparable environmental conditions), and satellite observations (e.g., NiSAR) should be employed and integrated in a multi-scale observation framework. By validating these secondary products, TWIST-NZ aims to enhance the scientific reliability and extend the practical relevance of BIOMASS for ecosystem monitoring, hydrological modeling, and forest management. Further, all processed datasets, validation results, and analysis methods will be made publicly available, e.g., via the ESA Multi-Mission Algorithm and Analysis Platform (MAAP). [1] Fluhrer, A., T. Jagdhuber, A. Tabatabaeenejad, H. Alemohammad, C. Montzka, P. Friedl, E. Forootan, and H. Kunstmann (2022): Remote sensing of complex permittivity and penetration depth of soils using P-band SAR polarimetry. Remote Sensing 14(12), 2755. DOI:10.3390/rs14122755 [2] Fluhrer, A., T. Jagdhuber, C. Montzka, M. Schumacher, H. Alemohammad, A. Tabatabaeenejad, H. Kunstmann, and D. Entekhabi (2024): Soil Moisture Profile Estimation by Combining P-band SAR Polarimetry with Hydrological and Multi-Layer Scattering Models. Remote Sensing of Environment 305, 114067. DOI:10.1016/j.rse.2024.114067 [3] Zhu, H., Meason, D.F., Salekin, S., Hu, W., Lad, P., Jing, Y. and J. Xue (2024). Time stability of soil volumetric water content and its optimal sampling design in contrasting forest catchments. Journal of Hydrology 131344; DOI:10.1016/j.jhydrol.2024.131344 [4] Meason, D.F., Matson, A., Baillie, B., Moller, D., Dudley, B., Srinivasan, M.S., Rajanayaka, C., Zammit, C., and D. White (2021): Forest Flows – Real time monitoring of water quantity and quality spatio-temporal dynamics in planted forests. IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium, Waikoloa, HI, USA, 2020: 4626-4629; DOI:10.1109/IGARSS39084.2020.9324637 [5] Zhao, Y. -H., Moller, D., Meason, D., and M. Moghaddam (2024). Multifrequency Subsurface Soil Moisture Retrieval for Forest Flows: A Case Study in Te Hiku, New Zealand. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing; DOI:10.1109/JSTARS.2024.3493118 [6] Fluhrer, A., H. Alemohammad, and T. Jagdhuber (2025): Analyzing the dihedral scattering component of Pband SAR signals for trunk permittivity estimation–a concept study. Science of Remote Sensing 11, 100236. DOI:10.1016/j.srs.2025.100236