GIS AND REMOTE SENSING in civil engineering.pptx

Very important topic

1. Use Of Remote Sensing and Geographical Information System in Disaster Management BY – Harshdeep Verma And Prince Kumar

2. Remote Sensing: A Bird's-Eye View Remote sensing  is the process of detecting and monitoring the physical characteristics of an area by measuring its reflected and emitted radiation at a distance. This is typically done using satellites or aircraft. Special cameras collect remotely sensed images, which help researchers “sense” things about the Earth. Applications : - Early Warning Systems : Remote sensing can track weather patterns and detect early signs of natural disasters like hurricanes, floods, and wildfires - Flood Monitoring : Satellite images can monitor water levels in rivers and reservoirs, helping to predict and manage floods.

3. Types of Data Collected 1. Imagery: - Visual Imagery: Like colorful postcards from space—capturing landscapes, cities, and oceans. Thermal Infrared: Measures temperature (great for spotting hotspots). 2. Elevation Data (DEM): - Lidar and radar create 3D models of Earth's topography. - Ever wondered how high that mountain is? Remote sensing knows! 3. Other Cool Stuff: - Hyperspectral Imaging: Identifies specific materials (like minerals) based on spectral bands . This Photo by Unknown Author is licensed under CC BY

4. GIS: Mapping the World, One Layer at a Time GIS  stands for  Geographic Information System . It’s a technology that creates, manages, analyzes, and maps all types of data. Applications : Risk Assessment and Hazard Mapping : GIS helps in identifying and mapping areas prone to natural disasters like floods, earthquakes, and hurricanes .  - Damage Assessment : After a disaster, GIS is used to assess the extent of damage by comparing pre- and post-disaster images. 

5. The phases: Mitigation, Preparedness, Response and Recovery. 1.Mitigation - What Is It? -Fortifying the castle before the dragon arrives. - Preventing or minimizing disaster impact. - Role of Remote Sensing: - Remote sensing helps assess likelihood (e.g., earthquakes). - Role of GIS: Guide safe construction practices. 2.Preparedness- What Is It? - Packing an emergency kit before the storm. - Having a plan and being ready to act. - Role of Remote Sensing: Map evacuation routes, shelters - Role of GIS: - Real-time alerts for evacuation.

6. 3.Response - What Is It? -Superhero phase—saving lives, minimizing damage. - Kicks in when disaster strikes. - Role of Remote Sensing: - Prioritizes rescue efforts. - Provides live data during events. - Role of GIS: - Integrates data from agencies. 4.Recovery- What Is It? - Recovery: Rebuilding after the storm. - Healing wounds, restoring normalcy. - Role of Remote Sensing: - Assessing infrastructure damage. - Checks bridges, roads, utilities. The phases: Mitigation, Preparedness, Response and Recovery

7. Challenges and Limitations Cloud Cover: The Elusive Enemy - Cloud Cover: Those fluffy white things in the sky? They're not always our friends. - Satellites rely on clear skies to capture high-quality imagery. - Persistent cloud cover can hide critical information during disasters. Data Accuracy and Resolution -Ground Truthing: Sometimes, we need boots on the ground to validate remote sensing data. - Spatial Resolution: How detailed is each pixel? Smaller pixels mean sharper images.

8. Future Trends 1.Hyperspectral Sensors: They capture data across a wide range of wavelengths, allowing us to see beyond what our eyes percei . These sensors provide detailed spectral information for each pixel, enabling precise identification of materials on the Earth's surface. For disaster management, hyperspectral data can help detect subtle changes, such as early signs of vegetation stress or pollution . 2. Machine Learning (ML): ML algorithms are revolutionizing how we analyze remote sensing data. They learn from patterns and make predictions, enhancing our ability to extract meaningful information. In disaster management, ML can: Automatically classify land cover (e.g., identifying flooded areas after heavy rains).Predict damage severity (e.g., assessing building damage post-earthquake). Improve image quality (e.g., denoising satellite imagery). - ML also enables real-time processing, which is crucial during emergencies. For instance, ML algorithms can rapidly analyze incoming data streams from satellites or drones, providing timely insights to decision-makers

9. Encouraging Further Research and Innovation - Data Fusion Techniques : - Combining data from various sources (satellites, drones, ground sensors) enhances accuracy. Researchers can explore innovative ways to fuse these datasets effectively. - For example, integrating optical and radar data can improve disaster monitoring, especially in cloudy or rainy conditions. - Real-Time Processing Capabilities: - Disaster response requires swift action. Developing algorithms that process data in real time—whether it's flood extent mapping or damage assessment—will be crucial. - Imagine an earthquake scenario: Real-time processing could automatically identify collapsed buildings and prioritize rescue efforts.

10. The Power of Remote Sensing and GIS 1. Why It Matters: - Remote sensing and Geographic Information Systems (GIS) are our allies in disaster management. - They provide a bird's-eye view, helping us understand our planet's dynamics, vulnerabilities, and resilience. 2. What We've Learned: - Remote sensing captures Earth's surface data from satellites and aerial imagery. - GIS organizes, analyzes, and manages geographic information. - Together, they create a comprehensive picture of disaster-affected areas. 3. Their Roles: - Remote Sensing: - Monitors natural disasters (earthquakes, floods, wildfires) using sensors like thermal, infrared, and microwave. - Enables flood forecasting, damage assessment, and risk mapping. - GIS: - Integrates spatial data for informed decision-making.

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