Mapping Lorey’s height over Hyrcanian forests of Iran using synergy of ICESat/GLAS and optical images

Pourrahmati, Manizheh Rajab; Baghdadi, Nicolas; Darvishsefat, A A; Namiranian, M; Gond, Valéry; Bailly, Jean-Stéphane; Zargham, N

doi:10.1080/22797254.2017.1405717

Cited by 17 publications

(7 citation statements)

References 50 publications

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“…ICESat/GLAS pulsed one of its three 1064 nm lasers at a time, at 40 Hz, producing ellipsoidal shaped footprints with a diameter of~60 m at~170 m along-track intervals, and several kilometers across tracks. ICESat/GLAS was used during its operational and post-operational period in many studies for the precise estimation of forest characteristics such as canopy height and biomass [11,[13][14][15][16][17][18][19]. However, most of the previously mentioned studies focused on forests with relatively flat terrain since ICESat/GLAS with its large footprint size was susceptible to overestimating forest characteristics (e.g., canopy heights, and AGB) over terrains with high relief [20,21].…”

Section: Introductionmentioning

confidence: 99%

Terrain Slope Effect on Forest Height and Wood Volume Estimation from GEDI Data

et al. 2021

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The Global Ecosystem Dynamics Investigation LiDAR (GEDI) is a new full waveform (FW) based LiDAR system that presents a new opportunity for the observation of forest structures globally. The backscattered GEDI signals, as all FW systems, are distorted by topographic conditions within their footprint, leading to uncertainties on the measured forest variables. In this study, we explore how well several approaches based on waveform metrics and ancillary digital elevation model (DEM) data perform on the estimation of stand dominant heights (Hdom) and wood volume (V) across different sites of Eucalyptus plantations with varying terrain slopes. In total, five models were assessed on their ability to estimate Hdom and four models for V. Results showed that the models using the GEDI metrics, such as the height at different energy quantiles with terrain data from the shuttle radar topography mission’s (SRTM) digital elevation model (DEM) were still dependent on the topographic slope. For Hdom, an RMSE increase of 14% was observed for data acquired over slopes higher than 20% in comparison to slopes between 10 and 20%. For V, a 74% increase in RMSE was reported between GEDI data acquired over slopes between 0–10% and those acquired over slopes higher than 10%. Next, a model relying on the height at different energy quantiles of the entire waveform (HTn) and the height at different energy quartiles of the bare ground waveform (HGn) was assessed. Two sets of the HGn metrics were generated, the first one was obtained using a simulated waveform representing the echo from a bare ground, while the second one relied on the actual ground return from the waveform by means of Gaussian fitting. Results showed that both the simulated and fitted models provide the most accurate estimates of Hdom and V for all slope ranges. The simulation-based model showed an RMSE that ranged between 1.39 and 1.66 m (between 26.76 and 39.26 m3·ha−1 for V) while the fitting-based method showed an RMSE that ranged between 1.26 and 1.34 m (between 26.78 and 36.29 m3·ha−1 for V). Moreover, the dependency of the GEDI metrics on slopes was greatly reduced using the two sets of metrics. As a conclusion, the effect of slopes on the 25-m GEDI footprints is rather low as the estimation on canopy heights from uncorrected waveforms degraded by a maximum of 1 m for slopes between 20 and 45%. Concerning the wood volume estimation, the effect of slopes was more pronounced, and a degradation on the accuracy (increased RMSE) of a maximum of 20 m3·ha−1 was observed for slopes between 20 and 45%.

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Section: Introductionmentioning

confidence: 99%

Terrain Slope Effect on Forest Height and Wood Volume Estimation from GEDI Data

et al. 2021

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“…Although GLAS's ~60 m diameter footprint was larger than the ideal resolution for forest observations [13], its capability to estimate forest parameters (e.g. canopy heights and biomass) has been exploited in numerous studies during its operational and post-operational periods [5], [14]- [20].…”

Section: Introductionmentioning

confidence: 99%

Assessment of GEDI's LiDAR Data for the Estimation of Canopy Heights and Wood Volume of Eucalyptus Plantations in Brazil

Fayad

Baghdadi

Álvares

et al. 2021

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

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“…Remote sensing techniques can be helpful in such cases and have been commonly used for this purpose [1][2][3][4]. Such studies mostly focus on estimation of canopy height since this is the most critical factor to predict risk [1,[5][6][7][8][9] but they also estimate other inventory parameters like tree basal area, volume (e.g., [3]) or ecosystem services [10]. The detection of individual trees in dense forests is also possible, driving the forest inventory from stand-and plot-level to single tree levels [11][12][13].…”

Section: Introductionmentioning

confidence: 99%

UAV RTK/PPK Method—An Optimal Solution for Mapping Inaccessible Forested Areas?

et al. 2019

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Mapping hard-to-access and hazardous parts of forests by terrestrial surveying methods is a challenging task. Remote sensing techniques can provide an alternative solution to such cases. Unmanned aerial vehicles (UAVs) can provide on-demand data and higher flexibility in comparison to other remote sensing techniques. However, traditional georeferencing of imagery acquired by UAVs involves the use of ground control points (GCPs), thus negating the benefits of rapid and efficient mapping in remote areas. The aim of this study was to evaluate the accuracy of RTK/PPK (real-time kinematic, post-processed kinematic) solution used with a UAV to acquire camera positions through post-processed and corrected measurements by global navigation satellite systems (GNSS). To compare this solution with approaches involving GCPs, the accuracies of two GCP setup designs (4 GCPs and 9 GCPs) were evaluated. Additional factors, which can significantly influence accuracies were also introduced and evaluated: type of photogrammetric product (point cloud, orthoimages and DEM) vegetation leaf-off and leaf-on seasonal variation and flight patterns (evaluated individually and as a combination). The most accurate results for both horizontal (X and Y dimensions) and vertical (Z dimension) accuracies were acquired by the UAV RTK/PPK technology with RMSEs of 0.026 m, 0.035 m and 0.082 m, respectively. The PPK horizontal accuracy was significantly higher when compared to the 4GCP and 9GCP georeferencing approach (p < 0.05). The PPK vertical accuracy was significantly higher than 4 GCP approach accuracy, while PPK and 9 GCP approach vertical accuracies did not differ significantly (p = 0.96). Furthermore, the UAV RTK/PPK accuracy was not influenced by vegetation seasonal variation, whereas the GCP georeferencing approaches during the vegetation leaf-off season had lower accuracy. The use of the combined flight pattern resulted in higher horizontal accuracy; the influence on vertical accuracy was insignificant. Overall, the RTK/PPK technology in combination with UAVs is a feasible and appropriately accurate solution for various mapping tasks in forests.

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Mapping Lorey’s height over Hyrcanian forests of Iran using synergy of ICESat/GLAS and optical images

Abstract: International audienc

Cited by 17 publications

References 50 publications

Terrain Slope Effect on Forest Height and Wood Volume Estimation from GEDI Data

Terrain Slope Effect on Forest Height and Wood Volume Estimation from GEDI Data

Assessment of GEDI's LiDAR Data for the Estimation of Canopy Heights and Wood Volume of Eucalyptus Plantations in Brazil

UAV RTK/PPK Method—An Optimal Solution for Mapping Inaccessible Forested Areas?

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