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Title: Towards an improved LAI collection protocol via simulated field-based PAR sensing

Abstract

In support of NASA’s next-generation spectrometer—the Hyperspectral Infrared Imager (HyspIRI)—we are working towards assessing sub-pixel vegetation structure from imaging spectroscopy data. Of particular interest is Leaf Area Index (LAI), which is an informative, yet notoriously challenging parameter to efficiently measure in situ. While photosynthetically-active radiation (PAR) sensors have been validated for measuring crop LAI, there is limited literature on the efficacy of PAR-based LAI measurement in the forest environment. This study (i) validates PAR-based LAI measurement in forest environments, and (ii) proposes a suitable collection protocol, which balances efficiency with measurement variation, e.g., due to sun flecks and various-sized canopy gaps. A synthetic PAR sensor model was developed in the Digital Imaging and Remote Sensing Image Generation (DIRSIG) model and used to validate LAI measurement based on first-principles and explicitly-known leaf geometry. Simulated collection parameters were adjusted to empirically identify optimal collection protocols. Furthermore, these collection protocols were then validated in the field by correlating PAR-based LAI measurement to the normalized difference vegetation index (NDVI) extracted from the “classic” Airborne Visible Infrared Imaging Spectrometer (AVIRIS-C) data (R2 was 0.61). The results indicate that our proposed collecting protocol is suitable for measuring the LAI of sparse forest (LAI < 3–5 (more » m2/m2)).« less

Authors:
 [1];  [2];  [1];  [1];  [1]
  1. Rochester Institute of Technology, Rochester, NY (United States)
  2. Rochester Institute of Technology, Rochester, NY (United States); Univ. College London, London (United Kingdom)
Publication Date:
Research Org.:
Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
Sponsoring Org.:
USDOE Laboratory Directed Research and Development (LDRD) Program
OSTI Identifier:
1263884
Grant/Contract Number:  
AC05-00OR22725
Resource Type:
Accepted Manuscript
Journal Name:
Sensors
Additional Journal Information:
Journal Volume: 16; Journal Issue: 7; Journal ID: ISSN 1424-8220
Publisher:
MDPI AG
Country of Publication:
United States
Language:
English
Subject:
47 OTHER INSTRUMENTATION; HyspIRI; AVIRIS; DIRSIG; leaf area index; photosynthetically active radiation

Citation Formats

Yao, Wei, Van Leeuwen, Martin, Romanczyk, Paul, van Aardt, Jan, and Kelbe, David. Towards an improved LAI collection protocol via simulated field-based PAR sensing. United States: N. p., 2016. Web. doi:10.3390/s16071092.
Yao, Wei, Van Leeuwen, Martin, Romanczyk, Paul, van Aardt, Jan, & Kelbe, David. Towards an improved LAI collection protocol via simulated field-based PAR sensing. United States. https://doi.org/10.3390/s16071092
Yao, Wei, Van Leeuwen, Martin, Romanczyk, Paul, van Aardt, Jan, and Kelbe, David. Thu . "Towards an improved LAI collection protocol via simulated field-based PAR sensing". United States. https://doi.org/10.3390/s16071092. https://www.osti.gov/servlets/purl/1263884.
@article{osti_1263884,
title = {Towards an improved LAI collection protocol via simulated field-based PAR sensing},
author = {Yao, Wei and Van Leeuwen, Martin and Romanczyk, Paul and van Aardt, Jan and Kelbe, David},
abstractNote = {In support of NASA’s next-generation spectrometer—the Hyperspectral Infrared Imager (HyspIRI)—we are working towards assessing sub-pixel vegetation structure from imaging spectroscopy data. Of particular interest is Leaf Area Index (LAI), which is an informative, yet notoriously challenging parameter to efficiently measure in situ. While photosynthetically-active radiation (PAR) sensors have been validated for measuring crop LAI, there is limited literature on the efficacy of PAR-based LAI measurement in the forest environment. This study (i) validates PAR-based LAI measurement in forest environments, and (ii) proposes a suitable collection protocol, which balances efficiency with measurement variation, e.g., due to sun flecks and various-sized canopy gaps. A synthetic PAR sensor model was developed in the Digital Imaging and Remote Sensing Image Generation (DIRSIG) model and used to validate LAI measurement based on first-principles and explicitly-known leaf geometry. Simulated collection parameters were adjusted to empirically identify optimal collection protocols. Furthermore, these collection protocols were then validated in the field by correlating PAR-based LAI measurement to the normalized difference vegetation index (NDVI) extracted from the “classic” Airborne Visible Infrared Imaging Spectrometer (AVIRIS-C) data (R2 was 0.61). The results indicate that our proposed collecting protocol is suitable for measuring the LAI of sparse forest (LAI < 3–5 ( m2/m2)).},
doi = {10.3390/s16071092},
journal = {Sensors},
number = 7,
volume = 16,
place = {United States},
year = {2016},
month = {7}
}

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Estimating Cotton leaf area Index Nondestructively with a Light Sensor
journal, July 2005


Comparison of Three Leaf Area Index Meters in a Corn Canopy
journal, July 2000


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Works referencing / citing this record:

A Simulation Study Using Terrestrial LiDAR Point Cloud Data to Quantify Spectral Variability of a Broad-Leaved Forest Canopy
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