Remote Sensing for Geological applications Training
Remote Sensing for land and agricultural applications Course
February 16, 2019
GMB Depo
Expected Learning outcomes
By the end of this course the participants are expected to:
- Appreciate the value of remote sensing in mining organizations
- Be able to apply Remote Sensing to Delimit the total area endowed with minerals of interest
- Understand the image resolutions appropriate for Geological remote sensing
- Understand the fundamentals of spectroscopy and their applications in mineral identification and exploration
- Be able to extract geometric properties of an image and use them to support decision on whether to commence mining or determination of expansion areas for existing mines (based on the estimated return on investments (ROI))
- Be able to determine the quality of the ore grade likely to be found through indicator minerals identified
- Determine hydrothermally altered zones and the minerals controlling the identified alteration patterns
- Extract the structural (lineaments) setting of an area and determine their orientations and influence to regional mineralization and present the results using rose diagrams
Assumed knowledge
Basic digital literacy is needed to complete the practicals
Requirements of the course
Dual core laptops or desktop computers
Internet connection to download satellite images
GIS software’s
Nb: Some open software’s will be provided together with this tutorial
| Contents | |
| Part I: Fundamentals of Remote Sensing
1. Remote Sensing Overview 1.1 Definition 1.2 Remote Sensing Concept 1.3 Components in Remote Sensing 1.4 Types of Remote Sensing 1.5 Multistage Remote Sensing Data Collection 1.7 Types and Uses of Satellites
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4. Spectroscopy ( Hyper-spectral remote sensing)
4.1 Fundamentals of spectroscopy 4.2 Sources of spectroscopic data 4.3 Hyper-spectral image analysis
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| 2. Remote Sensing Data Acquisition
2.1 Electromagnetic Waves Used in Remote Sensing 2.2 Properties of Electromagnetic Waves 2.3 Spectral Reflectance and Earth Surface Interaction 2.4 Multi-spectral Remote Sensing Data (Image) 2.5 Spectral Properties and Principal Applications 2.6 Spectral Reflectance to DN (Digital Number) 2.7 Structure of Remote Sensing Data 2.8 Resolutions in Remote Sensing
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5. Remote Sensing Data for Geological applications
5.1 Land Cover Classification 5.2 Hydrothermal alteration mapping 5.3 Lineament detection 5.4 Gravity anomaly mapping 5.5 Magnetic anomaly mapping 5.6 Mineral Spectral signature identification 5.7 Geological surveying 5.8 Mineral abundance mapping 5.9 Hydrogeological mapping
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| 3. Remote Sensing Data Processing and Analysis
3.1 Remote Sensing Data Pre-processing 3.2 Visual Interpretation (Band combination) 3.3 Apply Algorithms 3.4 Multi-spectral Classification 3.5 Digital Elevation Model (DEM) processing Catchment extraction Drainage network extraction |
6. Practical applications of RS in Agricultural applications
6.1 Digital image processing (Sentinel 2 and landsat8) 6.2 Image classification 6.3 Spectral resampling for sentinel 2 MSI 6.4 NDVI calculations 6.5 Above ground biomass calculation 6.6 Extracting spectral properties of an image 6.7 Hydrothermal alteration mapping using mineral indices and band ratios 6.8 Lineament extraction from images 6.9 Practical Examples Lithium and Gold
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| 7. Image filtering techniques
7.1 Edge detection and enhancement 7.2 Directional filters
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Software’s
Integrated Land and Water Information System (ILWIS)
Quantum Geographic Information System (QGIS)
Snap
Sen2core
Nb: All these are open source software ie they are distributed for free
Datasets
Landsat 8 Operational Land imager
Sentinel 2 satellite image
Suggested Reading materials
ISRS Proceeding Papers of Sort Interactive Session ISPRS TC VIII International Symposium on “Operational Remote Sensing Applications: Opportunities, Progress and Challenges”, Hyderabad, India, December 9 – 12, 2014
