Synthetic Aperture Radar (SAR) plays a crucial role in use-cases such as wildfire response, where it provides essential information to first responders. This is especially vital due to the impact of smoke and clouds that limit visibility during wildfire events. By leveraging the capabilities of ICEYE's X-band SAR constellation, experiments on post-fire events in boreal forests in Canada were conducted. The impact of weather information, such as soil moisture, on the radar signals of the burnt areas was studied to target the SAR acquisitions for identifying the burn scars.

SAR Interferometry (InSAR) has developed as a key method to derive Digital Elevation Models (DEMs). The large ICEYE fleet provides a unique source of data for the interferometric generation of DEMs. The constellation allows for tasking of pursuit monostatic image pairs with short temporal baselines and imaging geometries suitable for interferometric processing. DSMs (Digital Surface Models) have been produced in several locations with various terrain characteristics and different imaging configurations. Results are promising provided that temporal baselines are short enough (< 15 minutes) and perpendicular baselines suitable for InSAR (~150 m - 1500 m). The DSMs show a high amount of detail with a resolution finer than 5 m (Sliding Spotlight) and 10 m (Stripmap), and best vertical accuracies of less than 70 cm RMSE in open and unobstructed terrain (slopes < 10 degrees). The main challenges arise from decorrelation of the phase signal due to vegetation or steep terrain.

This paper addresses the estimation of forest heights and its underlying ground topography by applying dual-baseline SAR tomographic techniques to single-pass L-Band PolInSAR data. In this paper the feasibiliy of this special single-pass tomographic configuration is demontrated over boreal forests at the test site of Edson inAlberta, Canada. The estimated ground topography and tree top heights are validated against LiDAR data.

This paper addresses the estimation of forest heights and its underlying ground topography by applying dual-baseline SAR tomographic techniques to single-pass L-Band PolInSAR data. In this paper the feasibility of this special single-pass tomographic configuration is demontrated over boreal forests at the test site of Edson in Alberta, Canada. The estimated ground topography and tree top heights are validated against LiDAR data.

Two SAR tomographic estimators, namely the Capon method and the MUSIC method, are combined for the purposes of tree top height estimation and ground elevation retrieval from the dual-baseline datasets acquired by an experimental single-pass fully polarimetric L-Band InSAR system. Over two test sites, the preliminary results demonstrate a better estimation performance than our previously published results [4,5] using established single-baseline PolInSAR retrieval approaches.

Long wavelength airborne single-pass InSAR systems call for very accurate SAR focusing and motion compensation algorithms. We have analyzed 3 different techniques and evaluated their performance using real data acquired with an L-band single-pass interferometer in Canada. Time domain backprojection with terrain-dependent motion compensation shows the best performance with results close to the theoretically expected values.

Polarimetric InSAR (PolInSAR) using repeat-pass L-Band has generated interest in recent years because of its potential for extraction of forest height and of bare-earth topography beneath the canopy. However temporal de-correlation remains a problem. In previous papers a single-pass system has been demonstrated which removes the temporal issue. In this paper we extend the single-pass PolInSAR work previously described and show results for forests in which tree height maps and corresponding DTMs have been generated and compared to lidar truth.

The extraction of bio-and geophysical parameters by means of Pol-InSAR has gained a lot of interest in recent years. In particular, the exploitation of full quad-pol mode long wave-length (L-and P-band) data in combination with advanced theoretical models like the Random-Volume-over-Ground (RVoG) model has successfully been used to derive quantities like ground topography or tree height with impressive accuracy. However, to date all experiments (airborne and spaceborne) have been conducted in repeat-pass interferometry mode and thus, results have been suffering from two major limitations: temporal decorrelation and, in the airborne case, uncompensated motion errors. Both error sources can significantly reduce the usability of the acquired data, which is of importance especially if operationalmapping of large areas is being considered. This paper reports about first experiments with a single-pass airborne L-band quad-pol interferometer that has been implemented on Intermap's TopoSAR platform.

Tropical savannas cover 20% of the Earth's land surface and are important ecosystems in the global Carbon cycle due to their high productivity. This paper evaluates the capability of different shortwave synthetic aperture radar interferometry (InSAR) data for estimating above-ground biomass of the woody vegetation in heterogeneous tropical savanna woodland in Belize, Central America. Single-pass InSAR data used are X-band (Intermap) and C-band (AIRSAR and SRTM). Results show that retrieved canopy heights from both X- and C-band InSAR are indicative of general patterns of tree height, but the details remain inaccurate due to the heterogeneity of the canopy. Scattering phase centers for C-band are generally higher than for X-band over sparse woodlands, whereas dense tropical forest areas yield higher X-band scattering phase centers.

Centerline detection and line width estimation are important for many computer vision applications, e.g., road network extraction from high resolution remotely sensed imagery. Radon transform-based linear feature detection has many advantages over other approaches: for example, its robustness in noisy images. However, it usually fails to detect the centerline of a thick line due to the peak selection problem. In this paper, several key issues that affect the centerline detection using the radon transform are investigated. A mean filter is proposed to locate the true peak in the radon image and a profile analysis technique is used to further refine the line parameters. The theta-boundary problem of the radon transform is also discussed and the erroneous line parameters are corrected. Intensive experiments have shown that the proposed methodology is effective in finding the centerline and estimating the line width of thick lines.