Forest Biomass Estimation at High Spatial Resolution: Radar Versus Lidar Sensors

Mihai Tanase, Rocco Panciera, Kim Lowell, Cristina Aponte, Jorg Hacker, jeffrey walker

    Research output: Contribution to journalArticlepeer-review

    11 Citations (Scopus)


    This letter evaluates the biomass-retrieval error in pine-dominated stands when using high-spatial-resolution airborne measurements from fully polarimetric L-band radar and airborne laser scanning sensors. Information on total above-ground biomass was estimated through allometric relationships from plot-level field measurements. Multiple-linear-regression models were developed to model relationships between biomass and radar/lidar data. Overall, lidar data provided lower estimation errors (17.2 t · ha-1, 28% relative) when compared with radar data (30.3 t · ha-1, 61% relative). However, for the 30-100 t · ha-1 biomass range, the relative error from radar-based models was only 9% higher than that from lidar-based models. This suggests that high-spatial-resolution radar data could provide fundamentally similar results to lidar for some biomass intervals. This is an important finding for large-scale biomass estimation that needs to rely upon satellite data, as there are no lidar satellites planned for the foreseeable future.

    Original languageEnglish
    Article number6583278
    Pages (from-to)711-715
    Number of pages5
    JournalGeoscience and Remote Sensing Letters, IEEE
    Issue number3
    Publication statusPublished - 2014


    • Biomass
    • L-band radar
    • Small-footprint lidar


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