Methodology for determining the physical parameters of ground plane by the results of the optical and radar data fusion

• Дата: 2021
• Автор: Svideniuk, Mykhailo
• Формат: Стаття
• Мова: Ukrainian
• Опубліковано: Scientific Centre for Aerospace Research of the Earth Institute of Geological Science National Academy of Sciences of Ukraine, Kyiv, Ukraine 2021
• Теми: optical and radar data; soil moisture; permittivity; surface roughness; physical temperature; thermal emissivity; supreme measurements; ground truth; оптические и радиолокационные данные; влажность грунта; диэлектрическая проницаемость; шероховатость поверхности; физическая температура; коэффициент теплового излучения; подспутниковые измерения; оптичні та радіолокаційні супутникові дані; вологість ґрунту; діелектрична проникність; шорсткість поверхні; фізична температура; коефіцієнт теплового випромінювання; підсупутникові вимірювання
• Онлайн доступ: https://ujrs.org.ua/ujrs/article/view/197
• Назва журналу: Ukrainian Journal of Remote Sensing of the Earth

The methodology of multispectral optical and dual-polarized radar satellite data fusion for soils physical parameters estimation is developed. In particular, the methodology comprises relative permittivity estimation based on the Integral Equation Model (IEM) by using high resolution Sentinel-1 GRDH radar data. The calibration of ε was provided based on the compensation of soil acidity and temperature destabilizing effects. High-resolution multispectral images PlanetScope were used for vegetation indices and thermal emissivity estimation. Both, low-resolution MODIS and medium resolution Landsat-7/8 ETM+/TIRS thermal infrared images were processed in order to estimate ground plane thermodynamic temperature. An investigated approach for the radar signal depolarization compensation is based on local signal deviations and surface roughness estimation. The relief heterogeneity is restored based on the medium-resolution digital terrain elevation model ALOS AWD3D. Aiming to evaluate the accuracy of a soil moisture estimation model designed based on the presented methodology, ground truth measurements were carried out. Specifically, they included soil samples retrieving for the gravimetric soil moisture. In addition, the soil acidity and temperature were measured by applying the GM1312 differential thermometer and WALCOM multifunction device. The estimated parameters and ground truth data were used in order to retrieve the soil moisture based on the multivatiative regression dependence. Root mean square error of soil moisture retrieving was estimated as 4,73 %. Such accuracy is completely acceptable for the soil moisture monitoring of natural-reserved fund territories