skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.


Title: Evaluation of SPL100 Single Photon Lidar Data
Geiger-mode and single photon lidar sensors have recently emerged on the commercial market, advertising greater collection efficiency than the traditional linear mode lidar (LML) systems. Non-linear photon detection is a new technology for the geospatial community, and its performance characteristics for surveying and mapping are not yet well understood. Therefore, the geospatial quality of the data produced by one of these new sensors, the Leica SPL100, is examined by comparing the achieved lidar point cloud accuracy, precision, digital elevation model (DEM) generation, canopy penetration, and multiple return generation to a LML point cloud. We find the SPL100 has a lower ranging precision than linear mode lidar and that the precision is more negatively affected by surface properties such as low intensity and high incidence angle. The accuracy of the SPL100 point cloud, however, was found to be comparable to LML for smooth horizontal surfaces. A 1 m resolution SPL100 DEM was also comparable to a corresponding LML DEM, but the SPL100 was observed to have a reduced ability to resolve multiple returns through vegetation when compared to a LML sensor. In its current state, the SPL100 is likely best suited for applications in which the need for collection efficiency outweighs the need for maximum precision and canopy penetration and modeling.  more » « less
Award ID(s):
1830734
PAR ID:
10161825
Author(s) / Creator(s):
; ;
Date Published:
Journal Name:
Remote Sensing
Volume:
12
Issue:
4
ISSN:
2072-4292
Page Range / eLocation ID:
722
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. Accurate measurements of terrain elevation are crucial for many ecological applications. In this study, we sought to assess new global three-dimensional Earth observation data acquired by the spaceborne Light Detection and Ranging (LiDAR) missions Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) and Global Ecosystem Dynamics Investigation (GEDI). For this, we examined the “ATLAS/ICESat-2 L3A Land and Vegetation Height”, version 5 (20 × 14 m and 100 × 14 m segments) and the “GEDI Level 2A Footprint Elevation and Height Metrics”, version 2 (25 m circle). We conducted our analysis across four land cover classes (bare soil, herbaceous, forest, savanna), and six forest types (temperate broad-leaved, temperate needle-leaved, temperate mixed, tropical upland, tropical floodplain, and tropical secondary forest). For assessment of terrain elevation estimates from spaceborne LiDAR data we used high resolution airborne data. Our results indicate that both LiDAR missions provide accurate terrain elevation estimates across different land cover classes and forest types with mean error less than 1 m, except in tropical forests. However, using a GEDI algorithm with a lower signal end threshold (e.g., algorithm 5) can improve the accuracy of terrain elevation estimates for tropical upland forests. Specific environmental parameters (terrain slope, canopy height and canopy cover) and sensor parameters (GEDI degrade flags, terrain estimation algorithm; ICESat-2 number of terrain photons, terrain uncertainty) can be applied to improve the accuracy of ICESat-2 and GEDI-based terrain estimates. Although the goodness-of-fit statistics from the two spaceborne LiDARs are not directly comparable since they possess different footprint sizes (100 × 14 m segment or 20 × 14 m segment vs. 25 m circle), we observed similar trends on the impact of terrain slope, canopy cover and canopy height for both sensors. Terrain slope strongly impacts the accuracy of both ICESat-2 and GEDI terrain elevation estimates for both forested and non-forested areas. In the case of GEDI the impact of slope is, however, partly caused by horizontal geolocation error. Moreover, dense canopies (i.e., canopy cover higher than 90%) affect the accuracy of spaceborne LiDAR terrain estimates, while canopy height does not, when considering samples over flat terrains. Our analysis of the accuracy and precision of current versions of spaceborne LiDAR products for different vegetation types and environmental conditions provides insights on parameter selection and estimated uncertainty to inform users of these key global datasets. 
    more » « less
  2. The ATLAS sensor onboard the ICESat-2 satellite is a photon-counting lidar (PCL) with a primary mission to map Earth's ice sheets. A secondary goal of the mission is to provide vegetation and terrain elevations, which are essential for calculating the planet's biomass carbon reserves. A drawback of ATLAS is that the sensor does not provide reliable terrain height estimates in dense, high-closure forests because only a few photons reach the ground through the canopy and return to the detector. This low penetration translates into lower accuracy for the resultant terrain model. Tropical forest measurements with ATLAS have an additional problem estimating top of canopy because of frequent atmospheric phenomena such as fog and low clouds that can be misinterpreted as top of the canopy. To alleviate these issues, we propose using a ConvPoint neural network for 3D point clouds and high-density airborne lidar as training data to classify vegetation and terrain returns from ATLAS. The semantic segmentation network provides excellent results and could be used in parallel with the current ATL08 noise filtering algorithms, especially in areas with dense vegetation. We use high-density airborne lidar data acquired along ICESat-2 transects in Central American forests as a ground reference for training the neural network to distinguish between noise photons and photons lying between the terrain and the top of the canopy. Each photon event receives a label (noise or signal) in the test phase, providing automated noise-filtering of the ATL03 data. The terrain and top of canopy elevations are subsequently aggregated in 100 m segments using a series of iterative smoothing filters. We demonstrate improved estimates for both terrain and top of canopy elevations compared to the ATL08 100 m segment estimates. The neural network (NN) noise filtering reliably eliminated outlier top of canopy estimates caused by low clouds, and aggregated root mean square error (RMSE) decreased from 7.7 m for ATL08 to 3.7 m for NN prediction (18 test profiles aggregated). For terrain elevations, RMSE decreased from 5.2 m for ATL08 to 3.3 m for the NN prediction, compared to airborne lidar reference profiles.ICESat-2LidarPoint cloudNoise filtering 
    more » « less
  3. The use of small unmanned aerial system (UAS)-based structure-from-motion (SfM; photogrammetry) and LiDAR point clouds has been widely discussed in the remote sensing community. Here, we compared multiple aspects of the SfM and the LiDAR point clouds, collected concurrently in five UAS flights experimental fields of a short crop (snap bean), in order to explore how well the SfM approach performs compared with LiDAR for crop phenotyping. The main methods include calculating the cloud-to-mesh distance (C2M) maps between the preprocessed point clouds, as well as computing a multiscale model-to-model cloud comparison (M3C2) distance maps between the derived digital elevation models (DEMs) and crop height models (CHMs). We also evaluated the crop height and the row width from the CHMs and compared them with field measurements for one of the data sets. Both SfM and LiDAR point clouds achieved an average RMSE of ~0.02 m for crop height and an average RMSE of ~0.05 m for row width. The qualitative and quantitative analyses provided proof that the SfM approach is comparable to LiDAR under the same UAS flight settings. However, its altimetric accuracy largely relied on the number and distribution of the ground control points. 
    more » « less
  4. Canopy heights and vertical profiles were analyzed for 12 airborne lidar tracks acquired over forests of the mid-Juruá region, Brazil. Canopy height models were classified at 1m resolution as floodplain, terrace, hillslope, or interfluvial flat; floodplains were further separated according to Horton-Strahler (HS) stream order. RH95 canopy heights, and vertical profiles at 1m intervals, were aggregated to 30m scale and compared with Copernicus DEM heights, using a DEM transform, the Relative Terrain Height (RTH). Median canopy height ranged from 15.4 m for the Juruá floodplain to 25.5 m for hillslopes; maximum canopy heights varied from 37.4 m to 60.0 m. A strong correlation between RTH and median canopy height (r = 0.75) was found for the Juruá floodplain tracks. Vertical profiles of Juruá floodplain tracks showed that the height above ground of maximum returns increased monotonically with RTH height. Our results clearly show the influence of floodplain topography on forest canopy structure. 
    more » « less
  5. Fluorescence collection from individual emitters plays a key role in state detection and remote entanglement generation, fundamental functionalities in many quantum platforms. Planar photonics have been demonstrated for robust and scalable addressing of trapped-ion systems, motivating consideration of similar elements for the complementary challenge of photon collection. Here, using an argument from the reciprocity principle, we show that far-field photon collection efficiency can be simply expressed in terms of the fields associated with the collection optic at the emitter position alone. We calculate collection efficiencies into ideal paraxial and fully vectorial focused Gaussian modes parameterized in terms of focal waist, and further quantify the modest enhancements possible with more general beam profiles, establishing design requirements for efficient collection. Toward practical implementation, we design, fabricate, and characterize two diffractive collection elements operating atλ = 397 nm; a forward emitting design is predicted to offer 0.25% collection efficiency into a single waveguide mode, while a more efficient reverse-emitting design offers 1.14% collection efficiency, albeit with more demanding fabrication requirements. Close agreement between simulated and measured emission for both designs indicates practicality of these collection efficiencies, and we indicate avenues to improved devices approaching the limits predicted for ideal beams. We point out a particularly simple integrated waveguide configuration for polarization-based remote entanglement generation enabled by integrated collection. 
    more » « less