scholarly journals 4-D Automatic detection of copper mineralization using TanDEM-X satellite data

2019 ◽  
Vol 244 ◽  
pp. 012001
Author(s):  
M Marghany
Keyword(s):  
Satellite Data ◽  
Automatic Detection ◽  
Copper Mineralization

scholarly journals Mineral Exploration in Mawat Region, Kurdistan-Iraq, Based on Satellite Data and Terrain Prospection

2021 ◽  
Vol 8 (4) ◽  
pp. 249-272
Author(s):  
Marinko Oluić ◽  
Sreten Romandić ◽  
Ratko Vasiljević
Keyword(s):  
Satellite Data ◽  
Mineral Exploration ◽  
Digital Processing ◽  
Field Work ◽  
Measured Concentration ◽  
Copper Mineralization ◽  
Rock Formations ◽  
Lithological Composition ◽  
Color Composite ◽  
Host Rocks

The main goal of the presented exploration was to estimate potential for mineralization in the Mawat ophiolitic massif in Kurdistan, Iraq. The aim of the study was to explore existing copper mineralization and assessor elements gold, platinoids and chromium. Geological exploration detected two types of Cu occurrence a) secondary Cu carbonates (malachite) and b) Cu sulfides (chalcopyrite-pyrite). The Mawat region is mostly built of ultrabasic and basic rocks: peridotites, gabbros, serpentinites and basalts which are heavily deformed, with faults mostly oriented NNW-SSE, and NE-SW. The first phase of exploration comprised digital processing of ASTER and QuickBird satellite images, with appropriate geometrical and radiometric corrections and transformation into coordinate system. Color composite images were produced in different scales. They served to define lithological composition, tectonic settings, location of the points of interest etc. The field work was designed to check satellite data in situ, with focus on perspective rock formations, which might host copper mineralization, and other elements. The host rocks of the ore occurrences are primarily gabbros and metagabbros intersected by diabase dykes, epidote and quartz veins. Secondary mineralization is the product of surficial weathering and it is represented by malachite and limonite. The geophysical survey was very useful in the detection of area with elevated induced polarization and low resistivity. Three perspective areas have been selected for detailed explorations: Waraz, Mirava-Chenara and Konjirin-Kuradawi. The concentration of copper varies highly in very wide ranges; the maximum measured concentration of Cu was determined in Waraz area 6.7%. Some rock samples also show concentration of gold from 0.36 to 2.59 ppm Au. Keywords: Mawat ophiolitic massif, geologic-geophysical explorations, copper mineralization, Kurdistan-Iraq

Aeroplane Detection Techniques in Optical Satellite Sensors

2020 ◽  
pp. 148-165
Keyword(s):  
Remote Sensing ◽  
Satellite Data ◽  
Principle Component Analysis ◽  
Automatic Detection ◽  
Remote Sensing Images ◽  
Detection Techniques ◽  
Principle Component ◽  
Detection Approach ◽  
Satellite Sensors ◽  
Optical Satellite Data

This chapter demonstrates an automatic detection approach for aeroplanes in optical satellite data. This chapter hypothesizes that aeroplane fuselage can be retrieved in satellite images. Aeroplane detection is a challenging task in remote sensing images due to its variable sizes, colours, complex backgrounds, and orientations. To this end, principle component analysis (PCA) and a deep belief network (DBN) are used to detect the MH370 flight. Needless to say that all detected targets are not segments of MH370.

scholarly journals Automatic Near-Real-Time Image Processing Chain for Very High Resolution Optical Satellite Data

2015 ◽  
Vol XL-7/W3 ◽  
pp. 669-676 ◽  
Author(s):  
K. Oštir ◽  
K. Čotar ◽  
A. Marsetič ◽  
P. Pehani ◽  
M. Perše ◽  
...  
Keyword(s):  
Image Processing ◽  
High Resolution ◽  
Satellite Data ◽  
Satellite Image ◽  
Atmospheric Correction ◽  
Automatic Detection ◽  
Initial Development ◽  
Processing Chain ◽  
Optical Satellite Data ◽  
Very High

In response to the increasing need for automatic and fast satellite image processing SPACE-SI has developed and implemented a fully automatic image processing chain STORM that performs all processing steps from sensor-corrected optical images (level 1) to web-delivered map-ready images and products without operator's intervention. <br><br> Initial development was tailored to high resolution RapidEye images, and all crucial and most challenging parts of the planned full processing chain were developed: module for automatic image orthorectification based on a physical sensor model and supported by the algorithm for automatic detection of ground control points (GCPs); atmospheric correction module, topographic corrections module that combines physical approach with Minnaert method and utilizing anisotropic illumination model; and modules for high level products generation. Various parts of the chain were implemented also for WorldView-2, THEOS, Pleiades, SPOT 6, Landsat 5-8, and PROBA-V. Support of full-frame sensor currently in development by SPACE-SI is in plan. <br><br> The proposed paper focuses on the adaptation of the STORM processing chain to very high resolution multispectral images. The development concentrated on the sub-module for automatic detection of GCPs. The initially implemented two-step algorithm that worked only with rasterized vector roads and delivered GCPs with sub-pixel accuracy for the RapidEye images, was improved with the introduction of a third step: super-fine positioning of each GCP based on a reference raster chip. The added step exploits the high spatial resolution of the reference raster to improve the final matching results and to achieve pixel accuracy also on very high resolution optical satellite data.

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