What is Remote Sensing?
Historical Background
Key Points
8 points- 1.
Fundamental Principle: Different materials on Earth reflect or emit electromagnetic energy differently, creating unique spectral signatures.
- 2.
Sensors: Utilize various types of sensors including optical, thermal, microwave (SAR), and hyperspectral sensors.
- 3.
Data Acquisition: Data is collected from platforms like satellites, aircraft, and drones.
- 4.
Applications: Diverse applications including forest health monitoring, water resource management, mineral exploration, disaster management, urban planning, and climate change studies.
- 5.
Indices: Uses various indices like Normalised Difference Vegetation Index (NDVI) for vegetation health and Normalised Difference Water Index (NDWI) for water bodies.
- 6.
Advantages: Provides synoptic view large area coverage, repetitive coverage for change detection, and access to inaccessible areas.
- 7.
Challenges: Requires specialized expertise for data interpretation, ground validation is crucial for accuracy, and issues of data access and commercial exploitation.
- 8.
Components: Involves data acquisition, data processing, data analysis, and data dissemination.
Recent Developments
5 developmentsIntegration of Artificial Intelligence (AI) and Machine Learning (ML) for enhanced data processing and analysis.
Proliferation of CubeSats and small satellites for more frequent and high-resolution data.
Increased commercialization of remote sensing data and services.
Development of advanced sensors like hyperspectral and LiDAR for more detailed information.
Focus on real-time monitoring for disaster response and precision agriculture.