UPSC MainsZOOLOGY-PAPER-I202015 Marks
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Q21.

Describe the uses of remote sensing in sustainable development.

How to Approach

This question requires a comprehensive understanding of remote sensing technologies and their applications in various facets of sustainable development. The answer should begin by defining remote sensing and its core principles. Then, it should systematically explore its uses across different pillars of sustainability – environmental, economic, and social – providing specific examples. Structuring the answer around these pillars will ensure a logical flow. Mentioning relevant technologies (e.g., LiDAR, hyperspectral imaging) and recent advancements will add value.

Model Answer

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Introduction

Remote sensing, the acquisition of information about an object or area without physical contact, has emerged as a crucial tool for monitoring and managing Earth’s resources. Utilizing electromagnetic radiation reflected or emitted from the Earth’s surface, it provides a synoptic view and repetitive coverage, making it invaluable for sustainable development initiatives. The increasing availability of high-resolution satellite imagery, coupled with advancements in data processing techniques, has significantly expanded its applications. Sustainable development, defined by the Brundtland Report (1987) as “development that meets the needs of the present without compromising the ability of future generations to meet their own needs,” relies heavily on informed decision-making, which remote sensing facilitates.

Remote Sensing for Environmental Sustainability

Remote sensing plays a vital role in monitoring and protecting the environment. Key applications include:

  • Forest Cover Monitoring: Satellite imagery (e.g., Landsat, Sentinel) is used to track deforestation rates, assess forest health, and monitor reforestation efforts. The Global Forest Watch platform utilizes remote sensing data to provide near-real-time deforestation alerts.
  • Water Resource Management: Remote sensing helps in mapping water bodies, monitoring water quality (using spectral analysis), assessing snow cover and glacial melt (critical for understanding water availability), and detecting illegal water extraction.
  • Land Degradation Assessment: Techniques like Normalized Difference Vegetation Index (NDVI) and soil moisture mapping help identify areas affected by desertification, erosion, and salinization.
  • Disaster Management: Remote sensing is crucial for early warning systems for natural disasters like floods, droughts, wildfires, and landslides. Data from satellites like MODIS provides real-time fire detection.
  • Biodiversity Conservation: Mapping habitats, identifying critical ecosystems, and monitoring species distribution are facilitated by remote sensing.

Remote Sensing for Economic Sustainability

Remote sensing contributes to economic development by providing data for efficient resource management and infrastructure planning:

  • Agriculture: Crop health monitoring, yield prediction, precision farming (optimizing fertilizer and water use), and assessment of agricultural land suitability are all enabled by remote sensing. Hyperspectral imaging can detect plant stress before it’s visible to the naked eye.
  • Urban Planning: Mapping urban sprawl, identifying suitable locations for infrastructure development, monitoring traffic patterns, and assessing environmental impacts of urbanization are key applications.
  • Mineral Exploration: Remote sensing techniques, including hyperspectral and thermal infrared imaging, can identify geological features indicative of mineral deposits.
  • Fisheries Management: Monitoring ocean currents, sea surface temperature, and phytoplankton blooms (indicators of fish populations) supports sustainable fisheries management.
  • Infrastructure Monitoring: Detecting ground deformation, monitoring pipeline integrity, and assessing the condition of roads and bridges.

Remote Sensing for Social Sustainability

Remote sensing supports social well-being by providing data for addressing social and humanitarian challenges:

  • Population Mapping: High-resolution satellite imagery can be used to estimate population density and distribution, aiding in urban planning and resource allocation.
  • Health Monitoring: Remote sensing can identify breeding grounds for disease vectors (e.g., mosquitoes) and monitor environmental factors contributing to health risks.
  • Poverty Mapping: Combining remote sensing data with socio-economic data can help identify areas with high poverty rates and target development interventions.
  • Conflict Monitoring: Satellite imagery can be used to monitor displacement of populations, assess damage to infrastructure, and document human rights violations.
  • Climate Change Vulnerability Assessment: Identifying communities most vulnerable to climate change impacts (e.g., sea-level rise, extreme weather events).

Advancements in Remote Sensing Technologies

Recent advancements are further enhancing the capabilities of remote sensing:

  • LiDAR (Light Detection and Ranging): Provides highly accurate 3D data for terrain mapping, forest structure analysis, and urban modeling.
  • Unmanned Aerial Vehicles (UAVs) or Drones: Offer high-resolution imagery and flexibility for localized monitoring.
  • Synthetic Aperture Radar (SAR): Provides data regardless of cloud cover or sunlight, making it valuable for monitoring in all weather conditions.
  • Big Data Analytics and Machine Learning: Enable efficient processing and analysis of large volumes of remote sensing data.

Conclusion

Remote sensing is an indispensable tool for achieving sustainable development goals. Its ability to provide timely, accurate, and spatially explicit information across diverse sectors makes it crucial for informed decision-making. Continued investment in remote sensing technologies, data infrastructure, and capacity building is essential to maximize its potential. Integrating remote sensing data with other data sources (e.g., GIS, socio-economic data) will further enhance its effectiveness in addressing complex sustainability challenges and ensuring a more resilient and equitable future.

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 and red portions of the electromagnetic spectrum. Higher NDVI values generally indicate denser and healthier vegetation.
Geospatial Technology
Geospatial technology encompasses the tools and techniques used to acquire, analyze, and manage geographically referenced data. This includes remote sensing, Geographic Information Systems (GIS), and Global Positioning Systems (GPS).

Key Statistics

The global remote sensing market was valued at USD 8.6 billion in 2023 and is projected to reach USD 14.8 billion by 2030, growing at a CAGR of 8.2% from 2024 to 2030.

Source: Grand View Research, 2024 (Knowledge Cutoff: Jan 2024)

India has over 50 operational remote sensing satellites, making it one of the leading countries in space-based Earth observation.

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 imagery to monitor deforestation in the Amazon rainforest. The DETER system provides near-real-time alerts of deforestation events, enabling enforcement agencies to take action.

Frequently Asked Questions

What are the limitations of remote sensing?

Limitations include atmospheric interference (clouds, haze), data processing complexities, the need for ground truthing (validation with field data), and the cost of acquiring and processing high-resolution imagery. Interpretation requires skilled personnel.

Topics Covered

GeographyEnvironmentRemote SensingSustainable DevelopmentGIS