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An Integrated Optical Remote Sensing System for Environmental Perturbation Research

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7 Author(s)
Cho-ying Huang ; Dept. of Geogr., Nat. Taiwan Univ., Taipei, Taiwan ; Ching-Wen Chai ; Chao-ming Chang ; Jr-Chuan Huang
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Remote sensing is the only technology that can systematically monitor physical properties of the biosphere over a vast region. However, it is still a challenge to make these measures meaningful for assessing the impacts of environmental perturbation. Here, we integrate an optical remote sensing system termed EcoiRS (Ecosystem observation by an integrated Remote Sensing system) specifically for this purpose. EcoiRS consists of three subsystems: an off-the-shelf atmospheric correction model (ACORN), a cloud/shadow removal model, and an advanced spectral mixture analysis model (AutoMCU). The core of ACORN is a set of radiative transfer codes that can be used to remove the effects of molecular/aerosol scatterings and water vapor absorption from remotely sensed data, and to convert these digital signals to surface reflectance. Shadow and cloud cover that would obscure the reflective properties of land surfaces in an image can be minimized by referring to their optical and thermal spectral profiles. AutoMCU executes iterative unmixing for each pixel using selected spectral endmembers based upon the rule of Monte Carlo simulation. The main outcomes of EcoiRS include cover fractions of green vegetation, non-photosynthetically active vegetation and bare soils, along with uncertainty measures for each pixel. The dynamics of these derived products are significant indicators for monitoring the change of states of terrestrial environments, and they can be used for investigating different environmental perturbations. Here, we demonstrate studies of implementing EcoiRS to map three major but relatively less studied cases in a western Pacific island (Taiwan): typhoons, tree diseases and alien plant invasion.

Published in:

Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of  (Volume:6 ,  Issue: 6 )

Date of Publication:

Dec. 2013

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