# Potential of Forest Parameter Estimation Using Metrics from Photon Counting LiDAR Data in Howland Research Forest

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## Abstract

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## 1. Introduction

## 2. Study Site and Data

#### 2.1. Study Site

#### 2.2. Photon Counting LiDAR Data from SIMPL

#### 2.3. Airborne LiDAR Data from G-LiHT

#### 2.4. Field Measurement

## 3. Methods

#### 3.1. Overview

#### 3.2. Extraction of Ground and Canopy Surface

#### 3.3. Co-Registration between SIMPL and G-LiHT Data

#### 3.4. Metrics and Accuracy Assessment

## 4. Results

#### 4.1. Results of Extraction of Ground and Canopy Surface

#### 4.2. Results of Co-Registration between SIMPL and G-LiHT Data

#### 4.3. Results of Metrics from SIMPL Data

#### 4.4. Validation with Field Measurements

## 5. Discussion

## 6. Conclusions

## Author Contributions

## Funding

## Acknowledgments

## Conflicts of Interest

## References

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**Figure 1.**The location (

**right**) of the Howland forest area, and image (

**left**) of the Goddard’s LiDAR, Hyperspectral and Thermal Imager (G-LiHT) Canopy Height Model (CHM); the red line represents the SIMPL trajectory.

**Figure 2.**The profile of the photon counting LiDAR data from SIMPL within the Howland Research Forest. The horizontal x-axis stands for the UTM x coordinate; the vertical y-axis stands for the ellipsoidal height.

**Figure 3.**The 1 m resolution DTM and CHM of the study site driven from G-LiHT. (

**a**) The DTM from G-LiHT. (

**b**) The CHM from G-LiHT.

**Figure 5.**The distance matrix from the horizontal ellipse searching area, a darker and thicker line indicates closer reachability between these points.

**Figure 8.**The relationship between the max value of all photon heights from SIMPL and the max value of all return heights from G-LiHT for different scales.

**Figure 9.**The relationship between the 99th percentile of all photon heights from SIMPL and the 99th percentile of all return heights from G-LiHT for different scales.

**Figure 10.**The relationship between the mean value of all photon heights from SIMPL and the mean value of all return heights from G-LiHT for different scales.

**Figure 11.**The relationship between the 50th percentile of all photon heights from SIMPL and the 50th percentile of all return heights from G-LiHT for different scales.

**Figure 12.**The relationship between the fraction of the number of photons above 1.3 m from SIMPL and the fraction of the number of points above 1.3 m from G-LiHT for different scales.

**Figure 13.**The relationship between the standard deviation of all photon heights from SIMPL and the standard deviation of all return heights from G-LiHT for different scales.

**Figure 14.**The relationship between the coefficient of variation of all photon heights from SIMPL and the coefficient of variation of all return heights from G-LiHT for different scales.

**Figure 16.**The sensitivity analyses between the SIMPL and G-LiHT data in Howland site for different scale sizes.

**Figure 17.**The relative error distribution of different bins for metrics at various scale sizes. The vertical y-axis represents the relative error (measurements from G-LiHT are used as reference values); the numbers in horizontal x-axis represent certain bin sizes. For example, in maxH graph, 15 stands for tree height within 0–15 m; 20 stands for 15–20 m; 25 stands for 20–25 m; 30 stands for 25–30 m; 35 stands for tree height above 30 m.

**Table 1.**Statistics for the Howland stem map collected in 2010. Min is the minimum value, Max is the maximum value, Mean is the averaged value, and SD is the standard deviation.

Species | No. of Trees | Statistics | Height (m) | DBH (cm) | d-East-West (m) | d-North-South (m) |
---|---|---|---|---|---|---|

Hemlock | 7239 | Min | 3.17 | 2.90 | 0.21 | 1.10 |

Max | 37.99 | 60.90 | 6.91 | 13.21 | ||

Mean | 12.94 | 12.12 | 1.19 | 4.5 | ||

SD | 7.91 | 8.10 | 0.53 | 2.75 | ||

Aspen | 750 | Min | 4.36 | 3.0 | 0.23 | 1.05 |

Max | 46.47 | 61.8 | 2.66 | 11.22 | ||

Mean | 15.47 | 10.9 | 1.12 | 3.74 | ||

SD | 9.49 | 7.37 | 0.43 | 2.29 | ||

All | 7989 | Min | 3.17 | 2.9 | 0.21 | 1.05 |

Max | 46.47 | 61.8 | 6.91 | 13.21 | ||

Mean | 12.83 | 12.0 | 1.19 | 4.43 | ||

SD | 7.86 | 8.04 | 0.52 | 2.72 |

Source of Data | Name of the Metrics | Description |
---|---|---|

Metrics from SIMPL | SmaxH | Max value of all photon heights |

SmeanH | Mean value of all photon heights | |

Sh99 | 99th percentile of all photon heights | |

Sh50 | 50th percentile of all photon heights | |

SPercentage | Fraction of the number of photons above 1.3 m | |

SSTD | Standard deviation of all photon heights | |

SCV | Coefficient of variation of all photon heights | |

Metrics from G-LiHT | GmaxH | Max value of all return heights |

GmeanH | Mean value of all return heights | |

Gh99 | 99th percentile of all return heights | |

Gh50 | 50th percentile of all return heights | |

GPercentage | Fraction of the number of points above 1.3 m | |

GSTD | Standard deviation of all return heights | |

GCV | Coefficient of variation of all return heights |

**Table 3.**Result of validation using the Howland stem map. MAE is mean absolute error, SD is the standard deviation, and RMSE is the root mean square error.

Data Source | Scale Size | MAE (m) | SD (m) | RMSE (m) |
---|---|---|---|---|

G-LiHT | 10 m | 2.9 | 3.9 | 3.6 |

16 m | 2.4 | 1.7 | 2.1 | |

20 m | 1.7 | 1.8 | 2.1 | |

30 m | 1.2 | 2.1 | 1.9 | |

Mean value | 2.1 | 2.4 | 2.4 | |

SIMPL | 10 m | 3.5 | 4.6 | 4.5 |

16 m | 2.7 | 5.7 | 5.3 | |

20 m | 3 | 5.4 | 5 | |

30 m | 2.4 | 5.3 | 4.9 | |

Mean value | 2.9 | 5.3 | 4.9 |

© 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

## Share and Cite

**MDPI and ACS Style**

Chen, B.; Pang, Y.; Li, Z.; North, P.; Rosette, J.; Sun, G.; Suárez, J.; Bye, I.; Lu, H.
Potential of Forest Parameter Estimation Using Metrics from Photon Counting LiDAR Data in Howland Research Forest. *Remote Sens.* **2019**, *11*, 856.
https://doi.org/10.3390/rs11070856

**AMA Style**

Chen B, Pang Y, Li Z, North P, Rosette J, Sun G, Suárez J, Bye I, Lu H.
Potential of Forest Parameter Estimation Using Metrics from Photon Counting LiDAR Data in Howland Research Forest. *Remote Sensing*. 2019; 11(7):856.
https://doi.org/10.3390/rs11070856

**Chicago/Turabian Style**

Chen, Bowei, Yong Pang, Zengyuan Li, Peter North, Jacqueline Rosette, Guoqing Sun, Juan Suárez, Iain Bye, and Hao Lu.
2019. "Potential of Forest Parameter Estimation Using Metrics from Photon Counting LiDAR Data in Howland Research Forest" *Remote Sensing* 11, no. 7: 856.
https://doi.org/10.3390/rs11070856