Modeling canopy height in a savanna ecosystem using spaceborne lidar waveforms

Gwenzi, David; Lefsky, M. A.

doi:10.1016/j.rse.2013.11.024

Cited by 42 publications

(24 citation statements)

References 29 publications

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“…Photons that fall on very short and open stands are difficult to discriminate between noise, canopy and ground. This confirms with results from waveform data where we demonstrated that short height stands on steep terrain pose the main height modeling challenge (Gwenzi & Lefsky, 2014a For vegetation studies, we do not expect actual data from ICESat-2's ATLAS sensor to give better results due to the higher background noise levels and lower sampling rates associated with the larger footprint and use of only the green wavelength. Having few photons in areas that already have low vegetation cover makes it difficult to characterize the vertical distribution of the vegetation at small aggregation blocks.…”

Section: Discussionsupporting

confidence: 87%

“…Small footprint discrete return lidar (DRL) systems are ideally useful for small extents while large footprint waveform lidar systems are the most ideal for studies at larger extents (Hall et al, 2011). The Geoscience Laser Altimeter System (GLAS) aboard the Ice, Cloud and land Elevation Satellite (ICESat) has been the only available spaceborne lidar sensor and it has provided waveform data with a proven capability to estimate canopy height in various ecosystems (Lefsky, et al, 2007;Duncanson et al, 2010;Xing et al, 2010;Lefsky, 2010;Simard et al, 2011;Gwenzi & Lefsky, 2014a). However, ICESat was decommissioned in 2010 and the earliest planned future mission is its successor, ICESat-2, which will use the Advanced Topography Laser Altimeter System (ATLAS).…”

Section: Introductionmentioning

confidence: 99%

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Prospects of photon counting lidar for savanna ecosystem structural studies

Gwenzi

Lefsky

2014

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:Discrete return and waveform lidar have demonstrated a capability to measure vegetation height and the associated structural attributes such as aboveground biomass and carbon storage. Since discrete return lidar (DRL) is mainly suitable for small scale studies and the only existing spaceborne lidar sensor (ICESat-GLAS) has been decommissioned, the current question is what the future holds in terms of large scale lidar remote sensing studies. The earliest planned future spaceborne lidar mission is ICESat-2, which will use a photon counting technique. To pre-validate the capability of this mission for studying three dimensional vegetation structure in savannas, we assessed the potential of the measurement approach to estimate canopy height in a typical savanna landscape. We used data from the Multiple Altimeter Beam Experimental Lidar (MABEL), an airborne photon counting lidar sensor developed by NASA Goddard. MABEL fires laser pulses in the green ( 532 nm) and near infrared (1064 nm) bands at a nominal repetition rate of 10 kHz and records the travel time of individual photons that are reflected back to the sensor. The photons' time of arrival and the instrument's GPS positions and Inertial Measurement Unit (IMU) orientation are used to calculate the distance the light travelled and hence the elevation of the surface below. A few transects flown over the Tejon ranch conservancy in Kern County, California, USA were used for this work. For each transect we extracted the data from one near infrared channel that had the highest number of photons. We segmented each transect into 50 m, 25 m and 10 m long blocks and aggregated the photons in each block into a histogram based on their elevation values. We then used an expansion window algorithm to identify cut off points where the cumulative density of photons from the highest elevation resembles the canopy top and likewise where such cumulative density from the lowest elevation resembles mean ground elevation. These cut off points were compared to DRL derived canopy and mean ground elevations. The correlation between MABEL and DRL derived metrics ranged from R 2 = 0.70, RMSE = 7.9 m to R 2 = 0.83, RMSE = 2.9 m. Overall, the results were better when analysis was done at smaller block sizes, mainly due to the large variability of terrain relief associated with increased block size. However, the increase in accuracy was more dramatic when block size was reduced from 50 m to 25 m than it was from 25 m to 10 m. Our work has demonstrated the capability of photon counting lidar to estimate canopy height in savannas at MABEL's signal and noise levels. However, analysis of the Advanced Topography Laser Altimeter System (ATLAS) sensor on ICESat-2 indicate that signal photons will be substantially lower than those of MABEL while sensor noise will vary as a function of solar illumination, altitude and declination, as well as the topographic and reflectance properties of surfaces. Therefore, there are reasons to believe that the actual data from ICESat-2 will give poorer re...

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Section: Discussionsupporting

confidence: 87%

Section: Introductionmentioning

confidence: 99%

Prospects of photon counting lidar for savanna ecosystem structural studies

Gwenzi

Lefsky

2014

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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“…Many studies used airborne or spaceborne LiDAR for the estimation of forest canopy heights (e.g., [6][7][8][9][10][11]). While canopy height estimation using airborne LiDAR data can be very precise (RMSE better than 2 m, [12]), spaceborne LiDAR has a lower precision on the canopy height estimation ranging between 2 m and 10 m depending on the characteristics of the forest (e.g., [7,10,11,[13][14][15][16][17][18][19]). In addition, Airborne LiDAR is limited in the horizontal domain (limited spatial coverage for airborne data and limited acquisition density for satellite data), whereas spaceborne LiDAR provides global coverage of waveform data, but with a relatively low point density (about 0.51 points/km 2 over French Guiana for example) and inhomogeneous spatial sampling (sampling lines along satellite tracks).…”

Section: Introductionmentioning

confidence: 99%

Regional Scale Rain-Forest Height Mapping Using Regression-Kriging of Spaceborne and Airborne LiDAR Data: Application on French Guiana

Fayad¹,

Baghdadi²,

Bailly

et al. 2016

Remote Sensing

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LiDAR data has been successfully used to estimate forest parameters such as canopy heights and biomass. Major limitation of LiDAR systems (airborne and spaceborne) arises from their limited spatial coverage. In this study, we present a technique for canopy height mapping using airborne and spaceborne LiDAR data (from the Geoscience Laser Altimeter System (GLAS)). First, canopy heights extracted from both airborne and spaceborne LiDAR were extrapolated from available environmental data. The estimated canopy height maps using Random Forest (RF) regression from airborne or GLAS calibration datasets showed similar precisions (~6 m). To improve the precision of canopy height estimates, regression-kriging was used. Results indicated an improvement in terms of root mean square error (RMSE, from 6.5 to 4.2 m) using the GLAS dataset, and from 5.8 to 1.8 m using the airborne LiDAR dataset. Finally, in order to investigate the impact of the spatial sampling of future LiDAR missions on canopy height estimates precision, six subsets were derived from the initial airborne LiDAR dataset. Results indicated that using the regression-kriging approach a precision of 1.8 m on the canopy height map was achievable with a flight line spacing of 5 km. This precision decreased to 4.8 m for flight line spacing of 50 km.

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“…Airborne laser scanning (ALS), in particular, has been established as a standard technology for high-precision three-dimensional topographic data acquisition [13]. It has a powerful penetrating ability and can obtain vertical structure information for forests, thereby improving accuracy in estimating forest height and structure [14,15]. ALS is mostly operated in form of small-footprint discrete-return or waveform systems and allows for estimating AGB using area-based or individual tree detection approaches [16][17][18][19][20].…”

Section: Introductionmentioning

confidence: 99%

Influence of Site-Specific Conditions on Estimation of Forest above Ground Biomass from Airborne Laser Scanning

Novotný

Navrátilová

Janoutová

et al. 2020

Forests

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Forest aboveground biomass (AGB) is an important variable in assessing carbon stock or ecosystem functioning, as well as for forest management. Among methods of forest AGB estimation laser scanning attracts attention because it allows for detailed measurements of forest structure. Here we evaluated variables that influence forest AGB estimation from airborne laser scanning (ALS), specifically characteristics of ALS inputs and of a derived canopy height model (CHM), and role of allometric equations (local vs. global models) relating tree height, stem diameter (DBH), and crown radius. We used individual tree detection approach and analyzed forest inventory together with ALS data acquired for 11 stream catchments with dominant Norway spruce forest cover in the Czech Republic. Results showed that the ALS input point densities (4–18 pt/m2) did not influence individual tree detection rates. Spatial resolution of the input CHM rasters had a greater impact, resulting in higher detection rates for CHMs with pixel size 0.5 m than 1.0 m for all tree height categories. In total 12 scenarios with different allometric equations for estimating stem DBH from ALS-derived tree height were used in empirical models for AGB estimation. Global DBH models tend to underestimate AGB in young stands and overestimate AGB in mature stands. Using different allometric equations can yield uncertainty in AGB estimates of between 16 and 84 tons per hectare, which in relative values corresponds to between 6% and 37% of the mean AGB per catchment. Therefore, allometric equations (mainly for DBH estimation) should be applied with care and we recommend, if possible, to establish one’s own site-specific models. If that is not feasible, the global allometric models developed here, from a broad variety of spruce forest sites, can be potentially applicable for the Central European region.

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Modeling canopy height in a savanna ecosystem using spaceborne lidar waveforms

Cited by 42 publications

References 29 publications

Prospects of photon counting lidar for savanna ecosystem structural studies

Prospects of photon counting lidar for savanna ecosystem structural studies

Regional Scale Rain-Forest Height Mapping Using Regression-Kriging of Spaceborne and Airborne LiDAR Data: Application on French Guiana

Influence of Site-Specific Conditions on Estimation of Forest above Ground Biomass from Airborne Laser Scanning

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