Remote Sensing Roadmap for Mineral Mapping using Satellite Imagery
| Autor: | Roheet Bhatnagar, Devesh Kumar Srivastava, Priyanka Nair |
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| Rok vydání: | 2020 |
| Předmět: |
Earth observation
Spectral signature 010504 meteorology & atmospheric sciences Computer science 0211 other engineering and technologies 02 engineering and technology 01 natural sciences Field (computer science) Mineral exploration Remote sensing (archaeology) Pattern recognition (psychology) Satellite imagery 021101 geological & geomatics engineering 0105 earth and related environmental sciences Remote sensing |
| Zdroj: | 2nd International Conference on Data, Engineering and Applications (IDEA). |
| Popis: | The application of data mining in remote sensing has been expanding encompassing various extents and fields of earth observations. The Earth is facing unparalleled changes, which require global-scale observation and monitoring. The information about an object, an area of a phenomenon can be obtained in remote sensing by analyzing the data acquired by a device that is not in contact with the investigation entity. Terabytes of earth observation data are generated in terms of volume, variety, and velocity and are seemingly increasing beyond numbers. They are collected in the form of satellite imagery using spectral signatures and electromagnetic radiations. Data Mining, machine learning, and artificial intelligence are the emerging fields of study that have emanated to pursue solutions to automation of extracting data from Earth observations and deduce meaningful patterns for efficient tracking and control mechanisms. The paper attempts to review the work carried out in the field of earth observation data science and explore the intricacies of one of the challenging application areas of remote sensing akin to the field of lithology with mineral mapping considering little to barren vegetation areas subjected to mineral exploration accustomed to pattern recognition and fracture detection employing Machine learning and thereby earth space data science essentials. |
| Databáze: | OpenAIRE |
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