# Uncertainties and Perspectives on Forest Height Estimates by Sentinel-1 Interferometry
## 1 Introduction  
Forest height is a key parameter in forestry since it is adopted to retrieve above ground biomass [1, 2] and characterized canopy vertical structure [3, 4, 5]. It is often used to detect forests [6], and to assess forest ecosystem services (e.g., timber production [7], forest protection capabilities against natural hazards [8], biodiversity [9, 10]). Forest height is ordinarily measured through ground campaigns by means of hyposmeters, with precision ranging between 1 and 3 m [11, 12]. Unfortunately, ground surveys are time and 33 cost consuming, making them poorly dense over forested areas. Conversely, remote sensing can fill this gap, providing continuous forest height measures over wide areas, and showing accuracy comparable to ground surveys [13].  
Space-borne Earth Observation missions fit forest requirements well, making it possible to map and monitor wide areas, allowing near-early change detection and a frequent updating of forest properties [14]. Synthetic aperture radars (SARs) are known to be to be useful for estimating forest geometric features when recording data in all-weather condition, including equatorial/tropical climates, where clouds almost constantly cover the forest. Among SAR application and methods, the SAR interferometry (InSAR) technique has been extensively adopted to generate digital elevation models (DEM) intended to provide a continuous representation of Earth topography, including forest areas. Theoretically speaking, radar interferometry can generate highly precise height estimates related to the differences of path length between scattered signals received by two properly positionedantennas. The ordinary InSAR processing workflow relies on a phase unwrapping step aimed at unambiguously recovering the local topography, which is generally achieved by unitarily processing the entire scene. Ordinarily, these algorithms tend to avoid these areas during unwrapping [15; 16], so the approach has proven to consistently fail where signal coherence values are low. This makes InSAR-derived DEM over vegetation highly unreliable [17].  
An alternative existing approach, not widely explored in the literature [18; 19; 20], is considered in this work for obtaining more reliable and accurate estimates of forest height from InSAR data by avoiding phase unwrapping. This method changes the working paradigm from a mapping problem involving the entire scene to a local paradigm based on the comparison between a forest pixel interferogram and a reference one closely located outside the forest. Specifically, the potentialities and limitations of such an approach are explored and discussed.  
In this work, with reference to the above-mentioned approach, a sensitivity analysis was also performed with the aim of properly initializing the relevant operational parameters (i.e., baseline and multilooking factor) to maximize the theoretical accuracy of height measures. To support the technological transfer, all the analyses were made with reference to SAR open data (guaranteeing a cost-effective data access) with a specific focus on the Copernicus Sentinel-1 (S1) mission.