Selecting an optimal atmospheric correction model for above-ground forest biomass estimation

Nguyen Cong Hieu, Joon Heo

Research output: Contribution to conferencePaper

Abstract

Atmospheric correction is an important image-preprocessing step in which negative effects need to be minimized and convert to surface reflectance from optical remove sensing data. Our object is to select an optimal atmospheric correction model for above-ground forest biomass (AGB) estimation based on remote sensing approach. Three selected atmospheric correction models were investigated namely 1) Dark Object Subtraction (DOS), 2) Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes (FLAASH) and 3) the Second Simulation of Satellite Signal in the Solar Spectrum (6S); then they were compared with Top Of Atmospheric (TOA) reflectance. Gongju and Sejong region, South Korea was chosen to estimate AGB by using the k-Nearest Neighbor (kNN) algorithm and five Landsat ETM+ images. As a result, the 6S model provided the best RMSE's, followed by FLAASH, DOS and TOA. More importantly, a significant improvement of RMSE by 6S was found with images when the study site had higher total water vapor and temperature levels.

Original languageEnglish
Publication statusPublished - 2015 Jan 1
Event36th Asian Conference on Remote Sensing: Fostering Resilient Growth in Asia, ACRS 2015 - Quezon City, Metro Manila, Philippines
Duration: 2015 Oct 242015 Oct 28

Other

Other36th Asian Conference on Remote Sensing: Fostering Resilient Growth in Asia, ACRS 2015
CountryPhilippines
CityQuezon City, Metro Manila
Period15/10/2415/10/28

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Biomass
Water vapor
Remote sensing
Satellites
Temperature

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications

Cite this

Hieu, N. C., & Heo, J. (2015). Selecting an optimal atmospheric correction model for above-ground forest biomass estimation. Paper presented at 36th Asian Conference on Remote Sensing: Fostering Resilient Growth in Asia, ACRS 2015, Quezon City, Metro Manila, Philippines.
Hieu, Nguyen Cong ; Heo, Joon. / Selecting an optimal atmospheric correction model for above-ground forest biomass estimation. Paper presented at 36th Asian Conference on Remote Sensing: Fostering Resilient Growth in Asia, ACRS 2015, Quezon City, Metro Manila, Philippines.
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Hieu, NC & Heo, J 2015, 'Selecting an optimal atmospheric correction model for above-ground forest biomass estimation', Paper presented at 36th Asian Conference on Remote Sensing: Fostering Resilient Growth in Asia, ACRS 2015, Quezon City, Metro Manila, Philippines, 15/10/24 - 15/10/28.

Selecting an optimal atmospheric correction model for above-ground forest biomass estimation. / Hieu, Nguyen Cong; Heo, Joon.

2015. Paper presented at 36th Asian Conference on Remote Sensing: Fostering Resilient Growth in Asia, ACRS 2015, Quezon City, Metro Manila, Philippines.

Research output: Contribution to conferencePaper

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Hieu NC, Heo J. Selecting an optimal atmospheric correction model for above-ground forest biomass estimation. 2015. Paper presented at 36th Asian Conference on Remote Sensing: Fostering Resilient Growth in Asia, ACRS 2015, Quezon City, Metro Manila, Philippines.