UPSC MainsZOOLOGY-PAPER-I201615 Marks
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Q24.

Define remote sensing. Explain how it can be used as an effective tool for sustainable development.

How to Approach

This question requires defining remote sensing and elaborating on its applications for sustainable development. The answer should begin with a clear definition of remote sensing, outlining its principles and technologies. Subsequently, it should detail how remote sensing aids in various aspects of sustainable development – environmental monitoring, resource management, disaster management, urban planning, and agricultural practices. Specific examples and case studies should be included to demonstrate its effectiveness. The answer should be structured logically, covering different sectors and highlighting the benefits in each.

Model Answer

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Introduction

Remote sensing, derived from the French term ‘télédétection’, refers to the acquisition of information about an object or area without making physical contact with it. This is achieved by detecting and recording electromagnetic radiation reflected or emitted from the Earth’s surface. Initially limited to aerial photography, remote sensing has evolved dramatically with the advent of satellite technology, becoming an indispensable tool for understanding and managing our planet. In the context of sustainable development, which aims to meet the needs of the present without compromising the ability of future generations to meet their own needs, remote sensing provides crucial data for informed decision-making and effective resource allocation.

Understanding Remote Sensing

Remote sensing utilizes various platforms – satellites, aircraft, drones – equipped with sensors to capture data across different parts of the electromagnetic spectrum. These sensors can be passive (detecting naturally emitted radiation like sunlight) or active (emitting their own energy, like radar). The data collected is then processed and analyzed to create images and maps that reveal information about the Earth’s surface.

Remote Sensing for Sustainable Development: Sectoral Applications

1. Environmental Monitoring

  • Forest Cover Mapping: Remote sensing helps monitor deforestation, forest degradation, and reforestation efforts. Data from Landsat and Sentinel satellites are crucial for tracking changes in forest cover over time.
  • Water Quality Assessment: Sensors can detect pollutants, algal blooms, and sediment levels in water bodies, aiding in water resource management.
  • Air Pollution Monitoring: Satellites like Sentinel-5P provide data on atmospheric pollutants like nitrogen dioxide and ozone, helping to assess air quality and its impact on human health.

2. Resource Management

  • Agricultural Monitoring: Remote sensing provides information on crop health, yield estimation, and irrigation needs. Normalized Difference Vegetation Index (NDVI) is a commonly used metric.
  • Mineral Exploration: Hyperspectral imaging can identify mineral deposits based on their spectral signatures.
  • Fisheries Management: Satellite data can track ocean currents, sea surface temperature, and phytoplankton blooms, aiding in sustainable fisheries management.

3. Disaster Management

  • Flood Mapping: Radar satellites can penetrate cloud cover and provide accurate flood extent maps, enabling timely evacuation and relief efforts.
  • Earthquake Damage Assessment: Before-and-after satellite images can assess the extent of damage caused by earthquakes, guiding rescue operations.
  • Wildfire Monitoring: Thermal sensors detect hotspots and track the spread of wildfires, allowing for effective fire suppression.

4. Urban Planning

  • Land Use/Land Cover Mapping: Remote sensing provides detailed maps of urban areas, identifying different land uses and monitoring urban sprawl.
  • Infrastructure Monitoring: Satellite imagery can detect changes in infrastructure, such as road networks and building construction.
  • Green Space Assessment: Remote sensing helps assess the availability and distribution of green spaces in urban areas, contributing to urban sustainability.

5. Climate Change Studies

  • Glacier Monitoring: Satellite data tracks the retreat of glaciers and ice sheets, providing evidence of climate change.
  • Sea Level Rise Monitoring: Altimetry satellites measure sea level changes, helping to understand the impacts of climate change on coastal areas.
  • Carbon Stock Assessment: Remote sensing estimates carbon stocks in forests and other ecosystems, contributing to climate change mitigation efforts.

Challenges and Future Trends

Despite its numerous benefits, remote sensing faces challenges such as data processing complexity, high costs (though decreasing with open-source data), and the need for skilled personnel. Future trends include the use of Artificial Intelligence (AI) and Machine Learning (ML) for automated image analysis, the development of small satellite constellations for higher temporal resolution, and the integration of remote sensing data with Geographic Information Systems (GIS) for comprehensive spatial analysis.

Conclusion

Remote sensing has emerged as a powerful and versatile tool for sustainable development, providing critical information for informed decision-making across various sectors. Its ability to monitor environmental changes, manage resources effectively, and respond to disasters promptly makes it an indispensable component of any sustainable development strategy. Continued advancements in sensor technology, data processing techniques, and data accessibility will further enhance its role in achieving a more sustainable future for all.

Answer Length

This is a comprehensive model answer for learning purposes and may exceed the word limit. In the exam, always adhere to the prescribed word count.

Additional Resources

Key Definitions

Normalized Difference Vegetation Index (NDVI)
NDVI is a simple but effective index used to assess vegetation health. It is calculated from the near-infrared (NIR) and red portions of the electromagnetic spectrum. Higher NDVI values generally indicate denser and healthier vegetation.
Geographic Information System (GIS)
A GIS is a system designed to capture, store, manipulate, analyze, manage, and present all types of geographical data. It integrates remote sensing data with other spatial information to provide a comprehensive understanding of the Earth’s surface.

Key Statistics

The global Earth observation market was valued at USD 14.24 billion in 2023 and is projected to reach USD 28.48 billion by 2032, growing at a CAGR of 8.2% from 2024 to 2032.

Source: Fortune Business Insights, 2024 (Knowledge Cutoff: Jan 2024)

India has launched over 17 remote sensing satellites, making it one of the leading countries in remote sensing technology.

Source: Indian Space Research Organisation (ISRO) - Knowledge Cutoff: Jan 2024

Examples

Monitoring Amazon Deforestation

The Brazilian National Institute for Space Research (INPE) uses Landsat and Sentinel satellite data to monitor deforestation in the Amazon rainforest. This data is crucial for enforcing environmental regulations and combating illegal logging.

Frequently Asked Questions

What is the difference between spatial, spectral, temporal, and radiometric resolution in remote sensing?

Spatial resolution refers to the size of the smallest feature that can be distinguished. Spectral resolution refers to the number and width of spectral bands. Temporal resolution refers to the frequency of data acquisition. Radiometric resolution refers to the sensitivity of the sensor to differences in signal strength.

Topics Covered

GeographyEnvironmental ScienceRemote SensingGISSustainable DevelopmentEnvironmental Monitoring