Forest Applications

Abstract

The application of polarimetric Synthetic Aperture Radar (SAR) to forest observation for mapping, classification and parameter estimation (especially biomass) has a relatively long history. The radar penetration through forest volume, and hence the multi-layer nature of scattering models, make fully polarimetric data the observation space enabling a robust and full inversion of such models. A critical advance came with the introduction of polarimetric SAR interferometry, where polarimetry provides the parameter diversity, while the interferometric baseline proves a user-defined entropy control as well as spatial separation of scattering components, together with their location in the third dimension (height). Finally, the availability of multiple baselines leads to the full 3-D imaging of forest volumes through TomoSAR, the quality of which is again greatly enhanced by the inclusion of polarimetry. The objective of this Chapter is to review applications of SAR polarimetry, polarimetric interferometry and tomography to forest mapping and classification, height estimation, 3-D structure characterization and biomass estimation. This review includes not only models and algorithms, but it also contains a large number of experimental results in different test sites and forest types, and from airborne and space borne SAR data at different frequencies.

Polarimetric information content of Sentinel-1 for land cover mapping: An experimental case study using quad-pol data synthesized from complementary repeat-pass acquisitions

“…In turn, urban areas in this study only partially fulfill this assumption. A better agreement between the theoretical and observed distribution is observed for forest areas, which are characterized by diffuse scattering and medium Entropy therefore should largely be assigned to zones five and 8 (random anisotropic scatterers; Papathanassiou et al, 2021), which is the case for our data. However, as all classes show a similar trend regarding the distribution of values inside the Entropy Alpha plane, they must be subject to a systematic error of yet unknown degree which must have been introduced during the processing.…”

Very High Spatial Resolution Soil Moisture Observation of Heterogeneous Subarctic Catchment Using Nonlocal Averaging and Multitemporal SAR Data

“…The total amount of water per unit area in the canopy, i.e., the canopy water content m v (kg/m 2 ), is then n W v A h. Typically, the canopy water content is taken to be related to the stem volume, especially when using longer wavelengths. In the C-band, however, also leaves contribute to scattering markedly, as their dimensions are comparable to the wavelength [58]- [60]. The branches of the dominating species of the area, the northern Norway spruce ("candle spruce"), are so small and hidden behind the shoots that their contribution to the C-band is not significant [61].…”

Interacting Sentinel-2A, Sentinel 1A, and GF-2 Imagery to Improve the Accuracy of Forest Aboveground Biomass Estimation in a Dry-Hot Valley

“…Santoro et al [12] combined multiple synthetic-aperture radar (SAR) satellite observations from around 2010 to generate a global aboveground living biomass dataset that could have a significant impact on climate, carbon, and socioeconomic modeling, and provide a basis for future estimates of carbon stock changes. Among these, multispectral remote-sensing data possess the benefits of being both multi-temporal and multi-resolution, providing rich spectral information, with advanced technology utilizing infrared bands sensitive to plant data, this method has been extensively employed in estimating forest biomass [13,14]. The Sentinel-2A (S2) satellites are open-source, with rich band information, moderate spatial and temporal resolution, and a wide detection range.…”