Some neural network applications in environmental sciences. Part I: forward and inverse problems in geophysical remote measurements

Inverse Identification of Circular Cavity in a 2D Object via Boundary Temperature Measurements Using Artificial Neural Network

In geometric inverse problems, it is assumed that some parts of domain boundaries are not accessible and geometric shape and dimensions of these parts cannot be measured directly. The aim of inverse geometry problems is to approximate the unknown boundary shape by conducting some experimental measurements on accessible surfaces. In the present paper, the artificial neural network is used to sol...

Part I : Forward and Inverse Problems in Geophysical Remote Measurements by Vladimir

2D inversion of gravity data in bedrock identification (case study: a part of Qotrum plain in Yazd province)

Introduction The gravity method measures the vertical component of the acceleration at the Earth’s surface. The earth’s gravity field is affected by the density of different rocks and structures. Therefore, this method can be used in mineral exploration or studying the subsurface cavities and structures such as bedrocks, channels, and dikes. Inverse modeling is useful in understanding the p...

Solving inverse problems by Bayesian iterative inversion of a forward model with applications to parameter mapping using SMMR remote sensing data

Inverse problems have been often considered ill-posed, i.e., the statement of the problem does not thoroughly constrain the solution space. In this paper we take advantage of this lack of information by adding additional informative constraints to the problem solution using Bayesian methodology. Bayesian modeling gains much of its power from its ability to isolate and incorporate causal models ...

Prediction of Soil Salinity Using Neural Network and Multivariate Regression Based on Remote Sensing Indices and Comparison: A Case Study of Qazvin plain's Salt Marsh

Introduction: The spatial and temporal distribution of salts in the soil, the great extent of the Iranian deserts, and the adverse climatic conditions prevailing over them make it difficult to accurately determine the parameters and field measurements in some cases. In the last two decades, the use of field techniques and their combination with remote sensing data has contributed significantly ...