Mapping global forest canopy height through integration of GEDI and Landsat data

Potapov, Peter; Li, Xinyuan; Hernández-Serna, Andrés; Tyukavina, Alexandra; Hansen, Matthew C.; Kommareddy, Anil; Pickens, Amy; Turubanova, Svetlana; Tang, Hao; Silva, Carlos Edibaldo; Armston, John; Dubayah, Ralph; Blair, J. B.; Hofton, M. A.

doi:10.1016/j.rse.2020.112165

Cited by 631 publications

(599 citation statements)

References 38 publications

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“…Addressing these issues may further improve our assessment of SMAP's ability to detect changes in soil moisture in forested regions. Our findings are consistent with reference [65], which also showed that SMAP does have sensitivity to soil moisture under forest canopy.…”

Section: Discussionsupporting

confidence: 93%

Validation of SMAP Soil Moisture at Terrestrial National Ecological Observatory Network (NEON) Sites Show Potential for Soil Moisture Retrieval in Forested Areas

Ayres¹,

Colliander²,

Cosh³

et al. 2021

Preprint

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Soil moisture influences forest health, fire occurrence and extent, and insect and pathogen impacts, creating a need for regular, globally extensive soil moisture measurements that can only be achieved by satellite-based sensors, such as NASA’s Soil Moisture Active Passive (SMAP). However, SMAP data for forested regions, which account for ~20% of land cover globally, are flagged as unreliable due to interference from vegetation water content, and forests were underrepresented in previous validation efforts, preventing an assessment of measurement accuracy in these biomes. Here we compare over twelve thousand SMAP soil moisture measurements, representing 88 site-years, to in-situ soil moisture measurements from forty National Ecological Observatory Network (NEON) sites throughout the US, half of which are forested. At unforested NEON sites, agreement with SMAP soil moisture (unbiased RMSD: 0.046 m3 m-3) was similar to previous sparse network validations (which include inflation of the metric due to spatial representativeness errors). For the forested sites, SMAP achieved a reasonable level of accuracy (unbiased RMSD: 0.06 m3 m-3 or 0.053 m3 m-3 after accounting for random representativeness errors) indicating SMAP is sensitive to changes in soil moisture in forest ecosystems. Moreover, we identified that both an index of vegetation water content and canopy height were related to mean difference, which incorporates measurement bias and representativeness bias, and suggests a potential approach to improve SMAP algorithm parameterization for forested regions. In addition, expanding the number and extent of soil moisture measurements at forested validation sites would likely further reduce mean difference by minimizing representativeness errors.

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Section: Discussionsupporting

confidence: 93%

Validation of SMAP Soil Moisture at Terrestrial National Ecological Observatory Network (NEON) Sites Show Potential for Soil Moisture Retrieval in Forested Areas

Ayres¹,

Colliander²,

Cosh³

et al. 2021

Preprint

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show abstract

“…For further validation studies of GEDI with airborne LiDAR data, it would be recommended to establish a mathematical transformation model between both data sources for a correct extrapolation of the valuable information from GEDI data. It would also be advisable to explore the theory of authors such as Potapov, et al [59] or Lang, et al [60] who indicate that > REPLACE THIS LINE WITH YOUR PAPER IDENTIFICATION NUMBER (DOUBLE-CLICK HERE TO EDIT) < 15 such extrapolation could be carried out using multispectral images such as those of Landsat, Sentinel or many others.…”

Section: Discussionmentioning

confidence: 99%

GEDI Elevation Accuracy Assessment: A Case Study of Southwest Spain

Quiros

Polo

Fragoso-Campon

2021

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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Information about forest structures is becoming crucial to Earth's global carbon cycle, forest habitats and biodiversity. The Global Ecosystem Dynamics Investigation (GEDI) provides 25-m diameter footprints of the surface for 3D structure measurements. The main goal of this study is to compare 12 031 footprints of GEDI data with other airborne and spaceborne Digital Elevation Models (DEMs) for Southwest Spain. Ground elevation differences (ELM) are analyzed by comparing GEDI measurements with ALS LiDAR-and TanDEM-X-derived DEMs. The vertical structure (RH100) is compared to the ALS LiDAR measurement. Ten zones are analyzed, considering different degrees of coverage and slopes. We achieved an RMSE of 6.13 m for the ELM when comparing GEDI and LiDAR data and an RMSE of 7.14 m when comparing GEDI and TanDEM-X data. For some of the studied areas, these values were considerably smaller, with RMSE values even lower than 1 m. For the RH100 metric, an RMSE of 3.56 m was achieved when comparing GEDI and LiDAR data, but again with a minimum value of 2.09 m for one zone. The results show a clear relation to coverage and slope, especially for the latter. This work also evaluates the positional uncertainty of GEDI footprints, shifting them ±10 and ±5 m along and across the track of the satellite orbit and their intermediate angular positions. The outcomes reveal a strong tendency to obtain better results in the ELM when setting the footprint to 270° and displacing it within 10 m of its positional uncertainty in comparison with the LiDAR and TanDEM-X data.

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“…Canopy height data were also used to determine whether a reach was forested (height ≥ 3 m) following Potapov et al. (2021). We also explored these results across the aggregated level III Omernik ecoregions that were used by the Wadeable Streams Assessment (WSA) (US Environmental Protection Agency, 2006) to capture patterns in WHR across regions with variable physiographic, hydroclimatic, and ecological settings.…”

Section: Methodsmentioning

confidence: 99%

Predicting Light Regime Controls on Primary Productivity Across CONUS River Networks

Savoy

Harvey

2021

Geophysical Research Letters

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Riparian zones limit light availability, and thus primary productivity, until channel width is 1.7 times the height of riparian trees • Light attenuation from water depth and clarity limit productivity for 50% of river length and 80% of river surface area • The percentage of river length and surface area limited by riparian zones and water column processes varies across ecoregions Supporting Information:

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Mapping global forest canopy height through integration of GEDI and Landsat data

Cited by 631 publications

References 38 publications

Validation of SMAP Soil Moisture at Terrestrial National Ecological Observatory Network (NEON) Sites Show Potential for Soil Moisture Retrieval in Forested Areas

Validation of SMAP Soil Moisture at Terrestrial National Ecological Observatory Network (NEON) Sites Show Potential for Soil Moisture Retrieval in Forested Areas

GEDI Elevation Accuracy Assessment: A Case Study of Southwest Spain

Predicting Light Regime Controls on Primary Productivity Across CONUS River Networks

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