An integrated approach for extraction of lithology information using the SPOT 6 imagery in a heavily Quaternary‐covered region—North Baoji District of China

Abstract

We studied the applicability of SPOT (Systeme Probatoire d'Observation de la Terre) 6 satellite imagery for red sandstone interpretation in the heavily loess‐covered northern Baoji District, China, which is always a crucial but challenging issue in remote sensing geological mapping. First, the non‐ or sparsely vegetated subareas were outlined in order to narrow the interpretation target area; second, band‐math and the fractal “DN‐N” (digital number‐frequency) algorithm was conducted to extract the sandstone‐associated anomalies; third, a series of spatial analysis, for example, overlaying and clumping, was employed for elimination of the false anomalies; finally, we took advantage of matched filtering to discern the non‐ (red) sandstone outcrops in local areas. Generally, the interpretation accuracy based on this novel technical proposal is acceptable—74% or slightly less (taking the geological sketch as reference criteria)—and can be well proven by field investigation. This study may have contributed a useful case study for remote‐sensing lithological mapping in the Quaternary‐covered areas.

A Novel Approach for Cloud Detection in Scenes with Snow/Ice Using High Resolution Sentinel-2 Images

“…Additionally, the "area" is the product of the pixel size and frequency (denoted N) of a certain DN threshold; thus, the "DN-A" schema is equivalent to and can be substituted for by the "DN-N" (namely, pixel value frequency) schema. Han et al demonstrated its feasibility in remote sensing analysis [45]. We performed DN-N fractal processing on the MF values, and the details of the procedure and algorithm implemented in MATLAB are found in Zhao [46].…”

A Review of Geological Applications of High-Spatial-Resolution Remote Sensing Data

“…(i) Lithology: geologists have used SPOT images to extract lithologic information and predict bedrock geology mapping [43,44].…”

Central China Orogen along the Silk Road (Part 2): Mineral deposits, hydrocarbons, geohazards, and environments

“…In the paper by Cui et al (), landscape ecological risk assessment was undertaken in Qinling Mountain using Landsat remote sensing data. Han, Zhao, Wu, Zhang, et al () used SPOT 6 imagery to extract lithological information in a heavily Quaternary‐covered region of North China. In the paper by Shi et al (), longitudinal profiles of the Upper Weihe River and variation in channel steepness index were used as evidence for recognizing late Cenozoic uplift in the north‐eastern part of the Tibetan Plateau.…”