Assessment of Atmospheric Algorithms to Retrieve Vegetation in Natural Protected Areas Using Multispectral High Resolution Imagery

Abstract

The precise mapping of vegetation covers in semi-arid areas is a complex task as this type of environment consists of sparse vegetation mainly composed of small shrubs. The launch of high resolution satellites, with additional spectral bands and the ability to alter the viewing angle, offers a useful technology to focus on this objective. In this context, atmospheric correction is a fundamental step in the pre-processing of such remote sensing imagery and, consequently, different algorithms have been developed for this purpose over the years. They are commonly categorized as imaged-based methods as well as in more advanced physical models based on the radiative transfer theory. Despite the relevance of this topic, a few comparative studies covering several methods have been carried out using high resolution data or which are specifically applied to vegetation covers. In this work, the performance of five representative atmospheric correction algorithms (DOS, QUAC, FLAASH, ATCOR and 6S) has been assessed, using high resolution Worldview-2 imagery and field spectroradiometer data collected simultaneously, with the goal of identifying the most appropriate techniques. The study also included a detailed analysis of the parameterization influence on the final results of the correction, the aerosol model and its optical thickness being important parameters to be properly adjusted. The effects of corrections were studied in vegetation and soil sites belonging to different protected semi-arid ecosystems (high mountain and coastal areas). In summary, the superior performance of model-based algorithms, 6S in particular, has been demonstrated, achieving reflectance estimations very close to the in-situ measurements (RMSE of between 2% and 3%). Finally, an example of the importance of the atmospheric correction in the vegetation estimation in these natural areas is presented, allowing the robust mapping of species and the analysis of multitemporal variations related to the human activity and climate change.

Atmospheric and Radiometric Correction Algorithms for the Multitemporal Assessment of Grasslands Productivity

“…The values of A, B, S, and L o can be determined empirically from the MODTRAN4 standards. The vision and the solar angles of the measurement and the nominal values for the surface elevation, aerosol shape, and visible range of the scene must be specified [60]. For this study, the standard model used was tropical, which is recommended for locations with Latitudes around 30 • when the scenes are taken in September-October.…”

“…This method is based on the MODerate resolution atmospheric TRANsmission (MODTRAN) radioactive transfer model [59]. The main characteristics of ATCOR2 are: a pre-classification of the scene (soil, water, fog, and clouds), recovery of atmospheric parameters (aerosol optical thickness, water vapor) and surface reflectance recovery [60]. The surface reflectance (ρ SUP ) is obtained by Equation (1).…”

Radiometric Correction of Simultaneously Acquired Landsat-7/Landsat-8 and Sentinel-2A Imagery Using Pseudoinvariant Areas (PIA): Contributing to the Landsat Time Series Legacy

“…Although it is possible to obtain a synthetic value by computing a simple mean from the nominal FWHM bandwidth, it is worth using the available RSRF and accounting for the sensitivity of every band of the satellite sensor [88,89]. After resampling field spectroradiometry data to the satellite sensor sensitivity, spectral field measurements were taken as the reference for the comparison of the accuracies of the radiometric correction methods.…”

Estimation of PM10 Distribution using Landsat 7 ETM+ Remote Sensing Data

“…The atmospheric correction, which is generally taken as preprocessing in remote sensing applicaions, has been effectively used for pollution distibution mapping (Marcello et al, 2016). The derived equation can be used for PM10 distribution mapping using Landsat E TM+ data for the study area.…”