Statistical properties of hybrid estimators proposed for GEDI—NASA’s global ecosystem dynamics investigation

Abstract

NASA's Global Ecosystem Dynamics Investigation (GEDI) mission will collect waveform lidar data at a dense sample of ∼25 m footprints along ground tracks paralleling the orbit of the International Space Station (ISS). GEDI's primary science deliverable will be a 1 km grid of estimated mean aboveground biomass density (Mg ha −1 ), covering the latitudes overflown by ISS (51.6°S to 51.6°N). One option for using the sample of waveforms contained within an individual grid cell to produce an estimate for that cell is hybrid inference, which explicitly incorporates both sampling design and model parameter covariance into estimates of variance around the population mean. We explored statistical properties of hybrid estimators applied in the context of GEDI, using simulations calibrated with lidar and field data from six diverse sites across the United States. We found hybrid estimators of mean biomass to be unbiased and the corresponding estimators of variance appeared to be asymptotically unbiased, with under-estimation of variance by approximately 20% when data from only two clusters (footprint tracks) were available. In our study areas, sampling error contributed more to overall estimates of variance than variability due to the model, and it was the design-based component of the variance that was the source of the variance estimator bias at small sample sizes. These results highlight the importance of maximizing GEDI's sample size in making precise biomass estimates. Given a set of assumptions discussed here, hybrid inference provides a viable framework for estimating biomass at the scale of a 1 km grid cell while formally accounting for both variability due to the model and sampling error.

Use of Remote Sensing Data to Improve the Efficiency of National Forest Inventories: A Case Study from the United States National Forest Inventory

“…Other approaches were also developed in anticipation of the GLAS-like data provided by NASA Global Ecosystem Dynamics Investigation (GEDI) mission, which includes a full-waveform lidar instrument that was mounted on the International Space Station (ISS) and was launched in 2018 [245]. For example, Ståhl et al [59], McRoberts et al [58], Saarela et al [246], and Patterson et al [247] discuss estimators that combine FIA and GEDI data. They use various combinations of wall-to-wall optical data (typically Landsat), a sample of more highly-correlated data (such as GLAS or GEDI), and sparse ground plots (FIA) to produce estimates and confidence intervals that are interpretable through the lens of sampling theory.…”

Detecting Change in Forest Structure with Simulated GEDI Lidar Waveforms: A Case Study of the Hemlock Woolly Adelgid (HWA; Adelges tsugae) Infestation

“…Each of GEDI's tracks samples the Earth's surface with a waveform every 60 m along its path. By gridding these discrete samples at the 1 km scale, the mission will produce global data products of vegetation structure for regions between~51.6 degrees N and S latitude [31].…”

Mapping deep peat carbon stock from a LiDAR based DTM and field measurements, with application to eastern Sumatra

“…12. By late 2021, ICESat-2 data alone is targeted to provide nearglobal coverage (between 88° north and south latitudes; [97]) of N-S oriented flight lines at intervals of less than 2 km at the equator [97,101], with GEDI expected to provide additional coverage with a spacing between tracks of about ~ 600 m [99] between 51.6° north and south latitudes [102]. This will allow creation of landscape DTMs as demonstrated by [69], that are suitable for rapid global mapping of peat domes applying the method presented in this paper, and thereby improving estimates of regional and global peat carbon stocks and their vulnerability.…”