The measurement of forest structural characteristics is important for a variety of Monitoring, Reporting, and Verification (MRV) protocols in resource management.\r\nOne characteristic of particular importance is Forest Stand Height (FSH), or the average height of trees in a forest stand. In this context, FSH can be used an indicator\r\nof the age of a forest stand, plant and animal habitats, and the amount of Above Ground Biomass (AGB) held in the forest stand. FSH can be measured through the\r\nuse of terrestrial and/or airborne lidar, with airborne lidar being especially useful due to its wide area coverage and direct measurement of forest height. A difficulty\r\nwith airborne measurements, however, is that while these measurements work well at the tens- to hundreds-of-hectares-level, they are difficult to scale beyond that.\r\nOne method for the spatial scaling of FSH is through the use of spaceborne Synthetic Aperture Radar (SAR), especially at L-band repeat-pass Interferometric SAR\r\n(InSAR), which can be obtained through repeat observations from ALOS-2 and the future NISAR mission. In this scenario, the measure of InSAR decorrelation can\r\nbe related to FSH through the use of localized training data obtained from lidar. This chapter focuses on the use of repeat-pass InSAR for FSH estimation, and\r\npresents the theory, software, and examples of these methods. Although there is currently a limited availability of L-band SAR from ALOS-2, when NISAR launches\r\nin 2021, the presented method of FSH determination can be applied over large regions, especially when initialized using instruments such as the Global Ecosystems\r\nDynamics Investigation Lidar (GEDI) aboard the International Space Station, or other lidar observations.