Remote Sensing
Multi-source and multi-scale remote sensing at HIF, Photo: Sandra Lorenz(1)
The group uses different remote analyses to develop less invasive and high-resolution methods for the exploration of mineral resources from regional over deposit to outcrop scale. Its focus lies on the integration of data from different sensors, platforms and distances, such as hyperspectral reflectance, topographical or geophysical data from satellite, airplane or drone. When combined into a composite model, these multi-scale and multi-source data become a powerful tool to detect and assess the potential of natural mineral deposits.
Current Research
- Lithological and mineral mapping workflows from regional to outcrop scale and for different deposit types
- Multi-sensor (e.g. hyperspectral and geomagnetic) and/or multi-scale (e.g. air-borne and drone-borne) data integration
- Complete acquisition and processing workflows for drone-borne sensors
- Spatial geostatistics and statistical prediction mapping
- Geomorphological and tectonic analysis of digital elevation models
- Direct and indirect detection of raw materials of interest such as rare earth elements
Applied Data
- Multi- and hyperspectral satellite, airplane or drone reflectance data in the range of visible light to thermal-infrared radiation (VNIR, SWIR, LWIR)
- High-resolution photogrammetry, laser and radar data to calculate surface models and to derive geomorphological values
- Geophysical data (magnetics and gamma spectroscopy) for the acquisition of sub-surface information
Data Correction
The required data correction and processing routines are mostly developed in-house and are adapted to the specific issues of remote mineral exploration. Two python-based toolboxes are developed, used and maintained within the group.
- TecGeM toolbox: provides a uniform framework for the tectonic and geomorphic analysis of digital elevation models, such as morphometric maps or stream profile and catchment analysis
- Mineral Exploration Hyperspectral Toolbox (MEPHySTo): delivers a wide range of workflows for the handling, correction and processing of any spectral imaging datasets
Effects on data precision caused by vibrations and spatial movements, Photo: Sandra Lorenz(2)
Equipment
Drone, type TholegTHO-R-PX-8/12, Photo: Yuleika Madriz Dias
Unmanned aircraft systems
- Sensefly ebee and ebeePlus: deposit-scale high-resolution photogrammetry and multi-spectral data acquisition in the visible and near-infrared portion of the electromagnetic spectrum
- Aibotix Aibot X6v2: payload of up to 2 kg; is used for outcrop-scale surveying with a hyperspectral camera as well as for the photogrammetric mapping in quarries
- DJI Phantom 2 serves for video recording and surveying in sites, which are difficult to access
- TholegTHO-R-PX-8/12: payload of up to 5 kg, used for outcrop-scale surveying with LiDAR, hyperspectral imaging and UAS magnetics
→ Our UAS are used in compliance with the relevant laws and guidelines (e.g. LuftVG, LuftVO) and with a valid permit.
Sensors
- RIKOLA hyperspectral camera 500-900 nm, 50 free selectable channels
- Nikon CoolpixA/Canon IXUS for photogrammetry
- Sensys MagDrone R1 and MagBase as well as GEMsystems GSMP-35U magnetometers
- Yellowscan Mapper II LiDAR
Selected Publications
- Jackisch R., Lorenz S., Zimmermann R., Möckel R., Gloaguen R. (2018)
Drone-Borne Hyperspectral Monitoring of Acid Mine Drainage: An Example from the Sokolov Lignite District. Remote Sens., 10, 385
DOI-Link: 10.3390/rs10030385(3)
- Jakob, S., Zimmermann, R., Gloaguen, R. (2017)
The Need for Accurate Geometric and Radiometric Corrections of Drone-Borne Hyperspectral Data for Mineral Exploration: MEPHySTo—A Toolbox for Pre-Processing Drone-Borne Hyperspectral Data. Remote Sens., 9, 88
DOI-Link: 10.3390/rs9010088(4)
- Zimmermann, R., Brandmeier, M., Andreani, L., Mhopjeni, K., Gloaguen, R. (2016)
"Remote Sensing Exploration of Nb-Ta-LREE-Enriched Carbonatite (Epembe/Namibia)", Remote Sensing
DOI-Link: 10.3390/rs8080620(5)
Inhalt aus Sidebar
URL dieses Artikels
https://www.hzdr.de/db/Cms?pOid=45916