Modeling Aboveground Biomass in Hulunber Grassland Ecosystem by Using Unmanned Aerial Vehicle Discrete Lidar

Dongliang Wang, Xiaoping Xin, Quanqin Shao, Matthew Brolly, Zhiliang Zhu, Jin Chen

Research output: Contribution to journalArticleResearchpeer-review

Abstract

Abstract : Accurate canopy structure datasets, including canopy height and fractional cover, are required to monitor aboveground biomass as well as to provide validation data for satellite remote sensing products. In this study, the ability of an unmanned aerial vehicle (UAV) discrete light detection and ranging (lidar) was investigated for modeling both the canopy height and fractional cover in Hulunber grassland ecosystem. The extracted mean canopy height, maximum canopy height, and fractional cover were used to estimate the aboveground biomass. The influences of flight height on lidar estimates were also analyzed. The main findings are: (1) the lidar-derived mean canopy height is the most reasonable predictor of aboveground biomass (R2 = 0.340, root-mean-square error (RMSE) = 81.89 g·m−2, and relative error of 14.1%). The improvement of multiple regressions to the R2 and RMSE values is unobvious when adding fractional cover in the regression since the correlation between mean canopy height and fractional cover is high; (2) Flight height has a pronounced effect on the derived fractional cover and details of the lidar data, but the effect is insignificant on the derived canopy height when the flight height is within the range (<100 m). These findings are helpful for modeling stable regressions to estimate grassland biomass using lidar returns. Keywords: UAV lidar; grasslands; canopy height; fractional cover; aboveground biomass
Original languageEnglish
Pages (from-to)1-19
Number of pages19
JournalSensors
Volume17
Issue number1
DOIs
Publication statusPublished - 19 Jan 2017

Fingerprint

aboveground biomass
lidar
canopy
modeling
flight
vehicle
grassland ecosystem
grassland
multiple regression
detection
remote sensing

Bibliographical note

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Keywords

  • UAV lidar
  • grasslands
  • canopy height
  • fractional cover
  • aboveground biomass

Cite this

Wang, Dongliang ; Xin, Xiaoping ; Shao, Quanqin ; Brolly, Matthew ; Zhu, Zhiliang ; Chen, Jin. / Modeling Aboveground Biomass in Hulunber Grassland Ecosystem by Using Unmanned Aerial Vehicle Discrete Lidar. In: Sensors. 2017 ; Vol. 17, No. 1. pp. 1-19.
@article{7196b7f894e843479e71e2d01ba6fc66,
title = "Modeling Aboveground Biomass in Hulunber Grassland Ecosystem by Using Unmanned Aerial Vehicle Discrete Lidar",
abstract = "Abstract : Accurate canopy structure datasets, including canopy height and fractional cover, are required to monitor aboveground biomass as well as to provide validation data for satellite remote sensing products. In this study, the ability of an unmanned aerial vehicle (UAV) discrete light detection and ranging (lidar) was investigated for modeling both the canopy height and fractional cover in Hulunber grassland ecosystem. The extracted mean canopy height, maximum canopy height, and fractional cover were used to estimate the aboveground biomass. The influences of flight height on lidar estimates were also analyzed. The main findings are: (1) the lidar-derived mean canopy height is the most reasonable predictor of aboveground biomass (R2 = 0.340, root-mean-square error (RMSE) = 81.89 g·m−2, and relative error of 14.1{\%}). The improvement of multiple regressions to the R2 and RMSE values is unobvious when adding fractional cover in the regression since the correlation between mean canopy height and fractional cover is high; (2) Flight height has a pronounced effect on the derived fractional cover and details of the lidar data, but the effect is insignificant on the derived canopy height when the flight height is within the range (<100 m). These findings are helpful for modeling stable regressions to estimate grassland biomass using lidar returns. Keywords: UAV lidar; grasslands; canopy height; fractional cover; aboveground biomass",
keywords = "UAV lidar, grasslands, canopy height, fractional cover, aboveground biomass",
author = "Dongliang Wang and Xiaoping Xin and Quanqin Shao and Matthew Brolly and Zhiliang Zhu and Jin Chen",
note = "This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).",
year = "2017",
month = "1",
day = "19",
doi = "10.3390/s17010180",
language = "English",
volume = "17",
pages = "1--19",
journal = "Sensors",
issn = "1424-8220",
number = "1",

}

Modeling Aboveground Biomass in Hulunber Grassland Ecosystem by Using Unmanned Aerial Vehicle Discrete Lidar. / Wang, Dongliang; Xin, Xiaoping; Shao, Quanqin; Brolly, Matthew; Zhu, Zhiliang; Chen, Jin.

In: Sensors, Vol. 17, No. 1, 19.01.2017, p. 1-19.

Research output: Contribution to journalArticleResearchpeer-review

TY - JOUR

T1 - Modeling Aboveground Biomass in Hulunber Grassland Ecosystem by Using Unmanned Aerial Vehicle Discrete Lidar

AU - Wang, Dongliang

AU - Xin, Xiaoping

AU - Shao, Quanqin

AU - Brolly, Matthew

AU - Zhu, Zhiliang

AU - Chen, Jin

N1 - This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

PY - 2017/1/19

Y1 - 2017/1/19

N2 - Abstract : Accurate canopy structure datasets, including canopy height and fractional cover, are required to monitor aboveground biomass as well as to provide validation data for satellite remote sensing products. In this study, the ability of an unmanned aerial vehicle (UAV) discrete light detection and ranging (lidar) was investigated for modeling both the canopy height and fractional cover in Hulunber grassland ecosystem. The extracted mean canopy height, maximum canopy height, and fractional cover were used to estimate the aboveground biomass. The influences of flight height on lidar estimates were also analyzed. The main findings are: (1) the lidar-derived mean canopy height is the most reasonable predictor of aboveground biomass (R2 = 0.340, root-mean-square error (RMSE) = 81.89 g·m−2, and relative error of 14.1%). The improvement of multiple regressions to the R2 and RMSE values is unobvious when adding fractional cover in the regression since the correlation between mean canopy height and fractional cover is high; (2) Flight height has a pronounced effect on the derived fractional cover and details of the lidar data, but the effect is insignificant on the derived canopy height when the flight height is within the range (<100 m). These findings are helpful for modeling stable regressions to estimate grassland biomass using lidar returns. Keywords: UAV lidar; grasslands; canopy height; fractional cover; aboveground biomass

AB - Abstract : Accurate canopy structure datasets, including canopy height and fractional cover, are required to monitor aboveground biomass as well as to provide validation data for satellite remote sensing products. In this study, the ability of an unmanned aerial vehicle (UAV) discrete light detection and ranging (lidar) was investigated for modeling both the canopy height and fractional cover in Hulunber grassland ecosystem. The extracted mean canopy height, maximum canopy height, and fractional cover were used to estimate the aboveground biomass. The influences of flight height on lidar estimates were also analyzed. The main findings are: (1) the lidar-derived mean canopy height is the most reasonable predictor of aboveground biomass (R2 = 0.340, root-mean-square error (RMSE) = 81.89 g·m−2, and relative error of 14.1%). The improvement of multiple regressions to the R2 and RMSE values is unobvious when adding fractional cover in the regression since the correlation between mean canopy height and fractional cover is high; (2) Flight height has a pronounced effect on the derived fractional cover and details of the lidar data, but the effect is insignificant on the derived canopy height when the flight height is within the range (<100 m). These findings are helpful for modeling stable regressions to estimate grassland biomass using lidar returns. Keywords: UAV lidar; grasslands; canopy height; fractional cover; aboveground biomass

KW - UAV lidar

KW - grasslands

KW - canopy height

KW - fractional cover

KW - aboveground biomass

U2 - 10.3390/s17010180

DO - 10.3390/s17010180

M3 - Article

VL - 17

SP - 1

EP - 19

JO - Sensors

JF - Sensors

SN - 1424-8220

IS - 1

ER -