Image Gravimetry: A New Remote Sensing Approach for Gravity Analysis in Geophysics

TL;DR

This paper introduces a novel remote sensing method called image gravimetry that estimates gravity in geophysics using satellite imagery and spheroidal spline interpolation, demonstrated through a case study in Iran.

Contribution

It presents a new satellite image-based gravimetry approach utilizing spheroidal spline interpolation, expanding remote sensing techniques in gravity analysis.

Findings

Gravity values derived from satellite images have a standard deviation of 6.71 milli Gal compared to reference data.

The maximum difference between estimated and reference gravity values is 35 milli Gal.

The method successfully estimates regional gravity with acceptable accuracy.

Abstract

In this paper a new Geophysical gravimetry approach is presented, which is based on satellite imagery in remote sensing. The method uses a satellite image, together with a set of points in the image the gravity values of which are known. Template-based spheroidal spline method of interpolation is used to constitute a system of equations to find the values of gravity at other points in the image. A real case study is presented for the Qom region in Iran. Values of gravity are determined from the Landsat satellite image for this region, using 9 points in the image whose gravity values are known. Reference ellipsoid gravity values, which are based on coefficients derived from satellite gravimetry, are computed for this region, as well. Comparison between gravity values derived from Landsat image and those from reference ellipsoid shows that the standard deviation of the results is around 6.71 milli Gal, with the maximum of differences being 35 milli Gal.