On the Sensitivity of TanDEM-X-Observations to Boreal Forest Structure

The structure of forests is important to observe for understanding coupling to global dynamics of ecosystems, biodiversity, and management aspects. In this paper, the sensitivity of X-band to boreal forest stem volume and to vertical and horizontal structure in the form of forest height and horizontal vegetation density is studied using TanDEM-X satellite observations from two study sites in Sweden: Remningstorp and Krycklan. The forest was analyzed with the Interferometric Water Cloud Model (IWCM), without the use of local data for model training, and compared with measurements by Airborne Lidar Scanning (ALS). On one hand, a large number of stands were studied, and in addition, plots with different types of changes between 2010 and 2014 were also studied. It is shown that the TanDEM-X phase height is, under certain conditions, equal to the product of the ALS quantities for height and density. Therefore, the sensitivity of phase height to relative changes in height and density is the same. For stands with a phase height >5 m we obtained an root-mean-square error, RMSE, of 8% and 10% for tree height in Remningstorp and Krycklan, respectively, and for vegetation density an RMSE of 13% for both. Furthermore, we obtained an RMSE of 17% for estimation of above ground biomass at stand level in Remningstorp and in Krycklan. The forest changes estimated with TanDEM-X/IWCM and ALS are small for all plots except clear cuts but show similar trends. Plots without forest management changes show a mean estimated height growth of 2.7% with TanDEM-X/IWCM versus 2.1% with ALS and a biomass growth of 4.3% versus 4.2% per year. The agreement between the estimates from TanDEM-X/IWCM and ALS is in general good, except for stands with low phase height

Tropospheric Products from High-Level GNSS Processing in Latin America

ARTÍCULO PUBLICADO EN REVISTA EXTERNA. The present geodetic reference frame in Latin America and the Caribbean is given by a network of about 400 continuously operating GNSS stations. These stations are routinely processed by ten Analysis Centres following the guidelines and standards set up by the International Earth Rotation and Reference Systems Service (IERS) and International GNSS Service (IGS). The Analysis Centres estimate daily and weekly station positions and station zenith tropospheric path delays (ZTD) with an hourly sampling rate. This contribution presents some attempts aiming at combining the individual ZTD estimations to generate consistent troposphere solutions over the entire region and to provide reliable time series of troposphere parameters, to be used as a reference. The study covers ZTD and IWV series for a time-span of 5 years (2014–2018). In addition to the combination of the individual solutions, some advances based on the precise point positioning technique using BNC software (BKG NTRIP Client) and Bernese GNSS Software V.5.2 are presented. Results are validated using the IGS ZTD products and radiosonde IWV data. The agreement was evaluated in terms of mean bias and rms of the ZTD differences w.r.t IGS products (mean bias 1.5 mm and mean rms 6.8 mm) and w.r.t ZTD from radiosonde data (mean bias 2 mm and mean rms 7.5 mm). IWV differences w.r.t radiosonde IWV data (mean bias 0.41 kg/m2 and mean rms 3.5 kg/m2).Sitio de la revista: https://link.springer.com/chapter/10.1007/1345_2020_12

A Macroecological Analysis of SERA Derived Forest Heights and Implications for Forest Volume Remote Sensing

Individual trees have been shown to exhibit strong relationships between DBH, height and volume. Often such studies are cited as justification for forest volume or standing biomass estimation through remote sensing. With resolution of common satellite remote sensing systems generally too low to resolve individuals, and a need for larger coverage, these systems rely on descriptive heights, which account for tree collections in forests. For remote sensing and allometric applications, this height is not entirely understood in terms of its location. Here, a forest growth model (SERA) analyzes forest canopy height relationships with forest wood volume. Maximum height, mean, H100, and Lorey's height are examined for variability under plant number density, resource and species. Our findings, shown to be allometrically consistent with empirical measurements for forested communities world-wide, are analyzed for implications to forest remote sensing techniques such as LiDAR and RADAR. Traditional forestry measures of maximum height, and to a lesser extent H100 and Lorey's, exhibit little consistent correlation with forest volume across modeled conditions. The implication is that using forest height to infer volume or biomass from remote sensing requires species and community behavioral information to infer accurate estimates using height alone. SERA predicts mean height to provide the most consistent relationship with volume of the height classifications studied and overall across forest variations. This prediction agrees with empirical data collected from conifer and angiosperm forests with plant densities ranging between 102–106 plants/hectare and heights 6–49 m. Height classifications investigated are potentially linked to radar scattering centers with implications for allometry. These findings may be used to advance forest biomass estimation accuracy through remote sensing. Furthermore, Lorey's height with its specific relationship to remote sensing physics is recommended as a more universal indicator of volume when using remote sensing than achieved using either maximum height or H100