Improving extraction of forest canopy height through reprocessing ICESat-2 ATLAS and GEDI data in sparsely forested plain regions

GIScience & Remote Sensing, Journal Year: 2024, Volume and Issue: 61(1)

Published: Aug. 27, 2024

Forest canopy height (FCH) is one of the most important variables for carbon stock estimation. While many studies have focused on extracting FCH from spaceborne LiDAR in regions with spatially continuous and large patch sizes forested lands, limited research has addressed challenges extraction plain sparse fragmented forest distributions. In this study, we proposed innovative processing approaches to extract ICESat-2 photons GEDI footprints Anhui Province, China. Specifically, a sectional photon denoising method data geolocation error correction data. Airborne were used validate extracted products across typical regions. The results demonstrated effectiveness methods improving accuracy. Evaluation indicated that directly ATL08 L2A had Pearson's correlation coefficients (r) 0.6 0.93, respectively. After methods, 2019 exhibited r 0.82 relative root mean square (rRMSE) 31.11% based 3,217 segments, showed 0.96 rRMSE 18.35% 4,862 footprints. Further application these years 2020, 2021, 2022 their promise addressing vegetation coverage

Language: Английский

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Evaluation and Comparison of ICESat-2 and GEDI Data for Terrain and Canopy Height Retrievals in Short-Stature Vegetation

Remote Sensing, Journal Year: 2023, Volume and Issue: 15(20), P. 4969 - 4969

Published: Oct. 15, 2023

Two space-borne light detection and ranging (LiDAR) missions, Global Ecosystem Dynamics Investigation (GEDI) Ice, Cloud, land Elevation Satellite-2 (ICESat-2), have demonstrated high capabilities in extracting terrain canopy heights forest environments. However, there been limited studies evaluating their performance for height retrievals short-stature vegetation. This study utilizes airborne LiDAR data to validate compare the accuracies of vegetation using latest versions ICESat-2 (Version 5) GEDI 2). Furthermore, this also analyzes influence various factors, such as type, slope, height, cover, on retrievals. The results indicate that (bias = −0.05 m, RMSE 0.67 m) outperforms 0.39 1.40 extraction, with similar observed from both missions. Additionally, findings reveal significant differences retrieval between under different acquisition scenarios. Error analysis demonstrate slope plays a pivotal role influencing accuracy extraction particularly data, where decreases significantly increasing slope. has most substantial impact estimation heights. Overall, these confirm strong potential areas, provide valuable insights future applications vegetation-dominated ecosystems.

Language: Английский

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Assessing canopy height measurements from ICESat-2 and GEDI orbiting LiDAR across six different biomes with G-LiHT LiDAR

Environmental Research Ecology, Journal Year: 2024, Volume and Issue: 3(2), P. 025001 - 025001

Published: April 3, 2024

Abstract The height of woody plants is a defining characteristic forest and shrubland ecosystems because responds to climate, soil disturbance history. Orbiting LiDAR instruments, Ice, Cloud land Elevation Satellite-2 (ICESat-2) Global Ecosystem Dynamics Investigation (GEDI), can provide near-global datasets plant at plot-level resolution. We evaluate canopy measurements from ICESat-2 GEDI with high resolution airborne in six study sites different biomes dryland shrub tall forests, mean across 0.5–40 m. reliable estimates for the relative RMSE absolute error (MAE) 7.49 4.64 m (all ICESat-2) 6.52 4.08 GEDI) 98th percentile heights. Both slightly overestimate short shrubs (1–2 5 reference height), underestimate that trees (by 6–7 40 height) are highly biased (>3 m) <5 m, perhaps difficulty distinguishing ground signals. were only weakly sensitive cover terrain slope ( R 2 < 0.06) had lower night compared day samples (ICESat-2 night: 5.57 day: 6.82 m; 5.94 7.03 m). For GEDI, versus differences varied sample heights little effect on bias. Accuracy varies among biomes, highest MAE was observed tallest, densest (GEDI: 7.85 ICESat-2: 7.84 (night) 12.83 (day)). Improvements estimation would come better discrimination photons background noise improvements algorithm decomposing returns GEDI. benefit methods distinguish outlier samples.

Language: Английский

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Earth-Observation-Based Monitoring of Forests in Germany—Recent Progress and Research Frontiers: A Review

Remote Sensing, Journal Year: 2023, Volume and Issue: 15(17), P. 4234 - 4234

Published: Aug. 29, 2023

One-third of Germany’s land surface area is covered by forest (around 11.4 million hectares), and thus, it characterizes the landscape. The a habitat for large number animal plant species, source raw materials, important climate protection, well-being refuge people, to name just few its many functions. During annual condition surveys, crown German forests assessed on basis field samples at fixed locations, as trees considered an indicator their vitality. Since start surveys in 1984, mean defoliation all tree species has increased, now averaging about 25% species. Additionally, shows strong rise rate dieback. In 2019, most significant changes were observed. Due drastic recent years, efforts are being made assess situation using different remote sensing methods. There freely available products provided public, more will follow result numerous projects context earth-observation (EO)-based monitoring mapping Germany. 2020, regarding use was already investigated detail. However, these results no longer reflect current situation. last 3 years content this publication. For study, 84 citable research publications thoroughly analyzed compared with 2020. As major result, we found shift focus towards disturbance tendency cover larger areas, including national-scale studies. addition review scientific literature, also reviewed related products. congruence developments terms journals, need comprehensive, timely, large-area, complementary EO-based information around expressed multiple political programs. With review, provide update previous work link activities. We conclude that there still gaps between needs managers who usually rely from perspectives

Language: Английский

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Accuracy assessment of topography and forest canopy height in complex terrain conditions of Southern China using ICESat-2 and GEDI data

Frontiers in Plant Science, Journal Year: 2025, Volume and Issue: 16

Published: March 20, 2025

ICESat-2 and GEDI offer unique capabilities for terrain canopy height retrievals; however, their performance measurement precision are significantly affected by conditions. Furthermore, differences in data scales complicate direct comparisons of capabilities. This study evaluates the accuracy retrievals from LiDAR complex environments. Jinghong City Pu’er Southwest China were selected as areas, with high-precision airborne serving a reference. Ground elevation retrieval accuracies compared before after scale unification to 30 m × under varying slope Results indicate that shows significant advantage retrieval, RMSE values 4.75 4.21 unification, respectively. In comparison, achieved 4.94 4.96 m. Both systems maintain high flat regions, but declines increasing slope. For outperforms ICESat-2. Before an R² 0.73 5.15 m, 0.67 5.32 contrast, showed lower performance, 0.65 7.42 0.53 8.29 unification. maintains higher across all levels. Post-scale both show ground being superior. achieves better accuracy. These findings highlight synergistic strengths ICESat-2’s photon-counting GEDI’s full-waveform techniques, demonstrating advancements satellite laser altimetry retrieval.

Language: Английский

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Unveiling the performance and influential factors of GEDI L2A for building height retrieval

GIScience & Remote Sensing, Journal Year: 2025, Volume and Issue: 62(1)

Published: May 1, 2025

Language: Английский

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Use of GEDI Signal and Environmental Parameters to Improve Canopy Height Estimation over Tropical Forest Ecosystems in Mayotte Island

Canadian Journal of Remote Sensing, Journal Year: 2024, Volume and Issue: 50(1)

Published: May 14, 2024

Canopy height is a fundamental parameter for describing forest ecosystems. GEDI spaceborne LiDAR system that was designed to measure vegetation's vertical structure at global scale. This study evaluates the accuracy of GEDI-derived canopy estimates over complex tropical forests in Mayotte Island (Overseas France) characterized by moderate and biomass levels as well relatively steep terrain. The influence signal environmental parameters (canopy height, beam sensitivity slope) on assessed. Linear non-linear approaches were implemented using L2A product estimate height. Empirical models trained reference data derived from airborne scanning. results showed regression built multiple metrics yielded improved accuracies compared direct estimation single metric. terrain slope found have significant impact waveforms. Conversely, both linear produced unbiased stable estimates.

Language: Английский

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Carbon Storage Estimation of Quercus aquifolioides Based on GEDI Spaceborne LiDAR Data and Landsat 9 Images in Shangri-La

Sustainability, Journal Year: 2023, Volume and Issue: 15(15), P. 11525 - 11525

Published: July 25, 2023

The assessment of forest carbon storage plays a crucial role in management and ecosystem exploration, enabling the evaluation quality, resources, cycle management. Global Ecosystem Dynamics Investigation (GEDI) satellite provides means to accurately measure these various vertical structure parameters by penetrating canopy. However, distribution footprint along orbit track is heterogeneous discontinuous, preventing acquisition spatially distributed formation at county level. Consequently, this study integrated GEDI Landsat 9 data estimate Quercus aquifolioides Shangri-La. By applying Kriging interpolation previously pretreated footprints, surface information from L2B footprints was obtained. At same time, vegetation indices band reflectance were extracted analyze correlation with samples. Then, three methods (support vector machine, bagging, random forest) used create estimation model for research results showed that (1) among models selection based on semi-variance, optimal digital_elevation_model spherical model, while best percentage tree cover MODIS (modis_treecover) foliage height diversity index (fhd_normal) exponential model. (2) Analyzing thirty-three independent variable factors correlated top five variables highest digital_elevation_model, modis_treecover, fhd_normal, DEM, 1 (B1). (3) After selection, R2 = 0.82 RMSE 11.92 t/hm2 values established via obtained, its precision superior support machine method bagging regression. primarily range 8.22~94.63 t/hm2, mean value 42.44 total about 5,374,137.62 t. findings paper illustrated feasibility obtaining scale combining LiDAR optical data. also suggested new perspective other remote sensing images parameters.

Language: Английский

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Canopy Height Extraction Over Mountainous Areas From GEDI Lidar Deconvoluted Waveforms

IEEE Geoscience and Remote Sensing Letters, Journal Year: 2024, Volume and Issue: 21, P. 1 - 5

Published: Jan. 1, 2024

The extraction of canopy heights from spaceborne lidar received waveforms over mountainous areas is a challenging task, as the waveform signal broadening and overlapping effects make vegetation ground returns difficult to identify. This study aims obtain deconvoluted using Richardson–Lucy deconvolution algorithm for better separation overlapped components. Specifically, top elevation extracted start bin calculated centroid return, which determined by shuttle radar topography mission (SRTM) data waveform. height difference between elevations. Eight track GEDI rugged Larkspur Mountain Colorado are employed validate proposed method. results demonstrate that mean error, absolute root square error derived terrain with surface slopes more than 20° greatly reduced 86.7%, 23.2%, 19.5% relative products. prove method applicable derive areas.

Language: Английский

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Integration of very high-resolution stereo satellite images and airborne or satellite Lidar for Eucalyptus canopy height estimation

Science of Remote Sensing, Journal Year: 2024, Volume and Issue: 10, P. 100170 - 100170

Published: Oct. 11, 2024

Language: Английский

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