Rob Tapella

Space-based laser altimetry has revolutionized our capacity to characterize terrestrial ecosystems through the direct observation of vegetation structure and the terrain beneath it. Data from NASA’s ICESat-2 mission provide the first comprehensive look at canopy structure for boreal forests from space-based lidar. The objective of this research was to create ICESat-2 aboveground biomass density (AGBD) models for the global entirety of boreal forests at a 30 m spatial resolution and apply those models to ICESat-2 data from the 2019–2021 period. Although limited in dense canopy, ICESat-2 is the only space-based laser altimeter capable of mapping vegetation in northern latitudes. Along each ICESat-2 orbit track, ground and vegetation height is captured with additional modeling required to characterize biomass. By implementing a similar methodology of estimating AGBD as GEDI, ICESat-2 AGBD estimates can complement GEDI’s estimates for a full global accounting of aboveground carbon. Using a suite of field measurements with contemporaneous airborne lidar data over boreal forests, ICESat-2 photons were simulated over many field sites and the impact of two methods of computing relative height (RH) metrics on AGBD at a 30 m along-track spatial resolution were tested; with and without ground photons. AGBD models were developed specifically for ICESat-2 segments having land cover as either Evergreen Needleleaf or Deciduous Broadleaf Trees, whereas a generalized boreal-wide AGBD model was developed for ICESat-2 segments whose land cover was neither. Applying our AGBD models to a set of over 19 million ICESat-2 observations yielded a 30 m along-track AGBD product for the pan-boreal. The ability demonstrated herein to calculate ICESat-2 biomass estimates at a 30 m spatial resolution provides the scientific underpinning for a full, spatially explicit, global accounting of aboveground biomass.

Reference: https://www.sciencedirect.com/science/article/pii/S2666017224000348

Dry forests and savannas have highly heterogeneous horizontal and vertical structure of woody vegetation and high temporal variability in moisture and phenology. This presents distinct challenges to SAR-based approaches to mapping canopy-height compared to tropical and temperate forests. Dense time-series of C-band (Sentinel-1A/1B) and, in future, L-band (NASA/ISRO NISAR) provide a pathway to reduce the impact of signal-noise and environmental conditions and to extract additional information more directly related to height, using repeat-pass Interferometric SAR (InSAR) techniques.  This work explores the potential information in Sentinel-1(S1) C-band InSAR temporal decorrelation and Global Ecosystem Dynamics Investigation (GEDI)-derived relative height metrics for canopy height estimation. The 12-day InSAR correlation (𝛾) and seasonal median were analyzed over a wide range of canopy heights and woody ecosystems, with a focus on dry forests and savannas in Australia, India, and South Africa as part of a NASA Carbon Monitoring System (CMS) investigation. To scale up the geographical extent, the algorithm was deployed on NASA’s Multi-Mission Algorithm and Analysis Platform (MAAP). To further enhance the computational efficiency, a tile-based approach is employed using the Military Grid Reference System. The canopy height maps were produced for  ~12.3 million km²  by processing nearly 1500 1⁰x1⁰ Sentinel-1 C-band Coherence tiles and approximately 130 million GEDI samples. In summary, this study provides new insights into the applicability and limitations of using InSAR data for canopy-height estimation in dry forest and savanna studies. Implementation of the proposed canopy-height estimation algorithm on the NASA-MAAP enables global scalability with current and future InSAR time series. The limitations with the C-band could be overcome partly, if not completely, with longer wavelengths like the L-band, such as those proposed for the upcoming NISAR, ALOS-3/PALSAR-4, and ROSE-L missions.

Figure 1. Maps of estimated canopy height for three countries using Sentinel-1 InSAR coherence and GEDI RH98. 

Test site	No. of1ᵒ x 1ᵒtiles	No. of GEDI samples x106	100m		500m		1000m
			r	RMSE	r	RMSE	r	RMSE
Australia	910	68.3	0.75	3.74	0.85	2.56	0.89	2.05
India	408	52.1	0.66	5.18	0.83	3.49	0.88	2.71
South Africa	165	9.2	0.44	3.35	0.56	2.38	0.59	2.02

Narayanarao Bhogapurapu¹ Paul Siqueira¹, John Armston², Mikhail Urbazaev²,  Xiaoxuan Li³, Konrad Wessels³, Laura Duncanson²

¹ University of Massachusetts Amherst,² University of Maryland, ³ George Mason University

Related Publications: 

• N. Bhogapurapu, P. Siqueira, J. Armston, Xiaoxuan Li, M. Urbazaev, K. Wessels, and L. Duncanson 2023 “Largescale forest stand height estimation using C-band InSAR correlation,” Geoscience and Remote Sensing Symposium(IGARSS), IEEE International.
• N. Bhogapurapu, P. Siqueira, J. Armston, Xiaoxuan Li, M. Urbazaev, K. Wessels, and L. Duncanson 2023 “Large-scale Canopy Height Estimation using C-band InSAR Correlation,” PolInSAR 2023: 11th International Workshop on Science and Applications of SAR Polarimetry and Polarimetric Interferometry and BIOMASS Workshop
• N. Bhogapurapu, P. Siqueira, J. Armston, Xiaoxuan Li, K. Wessels, L. Duncanson 2022 “Temporal analysis of C-band InSAR decorrelation for canopy height mapping over dry forests and tropical savannas “, AGU Fall Meeting 2022.