Due to the unique feature of the three-dimensional convolution neural network, it is used in
image classification. There are some problems such as noise, lack of labeled samples, the …

BACKGROUND Barley is one of the strategic agricultural products available in the world,
and yield prediction is important for ensuring food security. One way of estimating a product …

In arid and semi-arid regions, it is essential to monitor the spatiotemporal variability and
dynamics of vegetation. Among other provinces of Pakistan, Punjab has produced a …

Floods are one of the most devastating natural disasters in the world, displacing millions of
people each year and causing severe damage to people's lives and infrastructure. It is the …

The objective of this study is to develop a method based on multivariate relevance vector
regression (MVRVR) as a kernel-based Bayesian model for the estimation of above-ground …

Polarimetric synthetic aperture radar (POLSAR) images have many applications in forest
studies, especially for biomass estimation. An algorithm was proposed to extract optimized …

Very high resolution (VHR) satellite imagery and image processing algorithms allow for the
development of remote sensing applications including multi-temporal classification, tracking …

Wave velocity is used to determine rock material, porosity, degree of petrification, fluid type,
and mechanical and behavioral properties. In this study, after assessing the relationship …

Permeability is one of the important issues that must be considered in the investigation of
dam sites. Determination of this parameter in the boreholes is time-consuming, costly, and in …

Accurate estimation of total aboveground biomass (TAGB) is an important challenge in
evaluating and monitoring tree biomass. Thus, developing species-specific allometric …