- "Remote sensing is the acquisition of information about an object or phenomenon without making physical contact with the object, in contrast to in situ or on-site observation."
How to interpret remote sensing images, including the principles of visual interpretation, image enhancement techniques, and digital image processing.
Fundamentals of Remote Sensing: Introduction to the principles of remote sensing, electromagnetic spectrum, sensors, and satellite systems.
Image Acquisition Systems: Classification of remote sensing sensors such as passive, active, imaging, and non-imaging systems. Understanding sensor characteristics like resolution, spatial, temporal, spectral, and radiometric.
Pre-processing and Enhancement Techniques: Image pre-processing techniques such as georeferencing, image calibration, and orthorectification. Enhancement techniques which includes geometric, radiometric, and spatial filtering.
Image Interpretation Techniques: Identification and interpretation of key features like land cover, vegetation, water bodies, natural resources, and man-made structures.
Classification Techniques: Classification of land cover using supervised and unsupervised classification methods. Clustering techniques which include k-means algorithms, Fuzzy c-means algorithm, and hierarchical clustering algorithm.
Multi-temporal Analysis: Assess changes over time using multi-temporal imagery, and evaluate alterations in land use and land cover changes.
Hyperspectral Imaging: Introduction to hyperspectral data processing-pipeline and steps followed for preprocessing, processing, and analysis of hyperspectral data.
Radar Imaging: Processing and interpretation of Synthetic Aperture Radar (SAR) data and application in Earth Science.
GIS (Geographical Information Systems): Integration of remote sensing data into GIS software, spatial data analysis, and representation.
Visualization Techniques: Representation of remote sensing data such as NDVI map, temperature distribution map, digital elevation map, and natural color composite image.
Image processing using Deep Learning: Application of artificial intelligence and deep learning techniques to process remote sensing data easily and efficiently.
Applications of Remote Sensing: Understanding the applications of remote sensing in the earth sciences, agriculture, forestry, land-use planning, climate change, natural resource management, and disaster management.
State of the Art Remote Sensing Techniques: Understanding the state of the art techniques in remote sensing such as Unmanned Aerial Vehicles (UAV), Light Detection and Ranging (LiDAR) and Very High-Resolution imagery.
Data Fusion: Integration of data obtained from multiple sources to increase information content.
Data sharing and Open data: Understanding Remote Sensing Data sharing policies and the importance of Open Data for scientific advancement.
Visual interpretation: A technique that involves visual analysis and interpretation of remotely sensed images to extract information about features, patterns, and processes on the Earth's surface.
Photointerpretation: The process of interpreting aerial photographs to extract useful information about features on the Earth's surface.
Multispectral interpretation: The process of analyzing multispectral images to extract information about the spectral characteristics of different features on the Earth's surface.
Hyperspectral interpretation: A technique that involves analyzing hyperspectral images to extract detailed information about the spectral characteristics of different features on the Earth's surface.
Radar interpretation: The process of interpreting radar images to extract information about features on the Earth's surface based on their backscatter characteristics.
LiDAR interpretation: A technique that uses LiDAR data to extract detailed information about the topography and elevation of features on the Earth's surface.
Thermal interpretation: The process of analyzing thermal images to extract information about the temperature and thermal properties of different features on the Earth's surface.
Synthetic Aperture Radar (SAR) interpretation: A technique that uses SAR data to extract information about features on the Earth's surface based on their backscatter characteristics and polarization.
Machine learning-based interpretation: A technique that involves using machine learning algorithms to automatically extract information from remotely sensed images.
Object-based image analysis: A technique that involves dividing images into objects and analyzing them based on their characteristics and relationships with each other.
Change detection analysis: A technique that involves comparing two or more images of the same area taken at different times to identify changes in features on the Earth's surface.
- "Remote sensing is used in numerous fields, including geophysics, geography, land surveying, and most Earth science disciplines."
- "Exploration geophysics, hydrology, ecology, meteorology, oceanography, glaciology, geology"
- "It also has military, intelligence, commercial, economic, planning, and humanitarian applications, among others."
- "The term remote sensing generally refers to the use of satellite- or aircraft-based sensor technologies to detect and classify objects on Earth."
- "It includes the surface and the atmosphere and oceans, based on propagated signals."
- "Active remote sensing is when a signal is emitted by a satellite or aircraft to the object and its reflection detected by the sensor." - "Passive remote sensing is when the reflection of sunlight is detected by the sensor."
- "The term is applied especially to acquiring information about Earth and other planets."
- "It includes the surface and the atmosphere and oceans, based on propagated signals (e.g. electromagnetic radiation)."
- "It may be split into 'active' remote sensing and 'passive' remote sensing."
- "Active remote sensing is when a signal is emitted by a satellite or aircraft to the object and its reflection detected by the sensor." - "Passive remote sensing is when the reflection of sunlight is detected by the sensor."
- "The term remote sensing generally refers to the use of satellite- or aircraft-based sensor technologies to detect and classify objects on Earth."
- "It includes the surface and the atmosphere and oceans, based on propagated signals (e.g. electromagnetic radiation)."
- "Exploration geophysics, hydrology, ecology, meteorology, oceanography, glaciology, geology"
- "It also has military, intelligence, commercial, economic, planning, and humanitarian applications, among others."
- "Remote sensing is the acquisition of information about an object or phenomenon without making physical contact with the object, in contrast to in situ or on-site observation."
- "The term is applied especially to acquiring information about Earth and other planets."
- "Remote sensing is the acquisition of information about an object or phenomenon without making physical contact with the object."
- "Remote sensing is used in numerous fields, including geophysics, geography, land surveying and most Earth science disciplines."
- "Remote sensing is the acquisition of information about an object or phenomenon without making physical contact with the object, in contrast to in situ or on-site observation."