STUDY MODULE - Wildlife Ecology and Management (B.Sc. Zoology-6th Semester, NEP / FYUGP )
Written by
Dr Chandralekha Deka
Assistant professor
Dept of Zoology, PDUAM
1. INTRODUCTION
Wildlife habitat management is a scientific approach focused on protecting, restoring, and maintaining environments where animals live and reproduce. With increasing anthropogenic pressure such as deforestation, urbanization, mining, and climate change, wildlife habitats are shrinking rapidly. Conservationists therefore require accurate, large-scale, and real-time environmental data.
Geographic Information Systems (GIS) and Remote Sensing (RS) have emerged as powerful technological tools that help scientists monitor landscapes, analyze ecological patterns, and make evidence-based conservation decisions.
Traditional ecological surveys depend heavily on fieldwork, which is often expensive, time-consuming, and geographically restricted. In contrast, satellite-based technologies can observe vast and inaccessible terrains within minutes.
This module explores the concepts, principles, tools, applications, and future scope of GIS and Remote Sensing in wildlife habitat management.
2. LEARNING OBJECTIVES
After completing this module, students will be able to:
1. Define GIS and Remote Sensing.
2. Understand the components and working principles of spatial technologies.
3. Differentiate between GIS and Remote Sensing.
4. Explain the role of spatial data in wildlife conservation.
5. Analyze habitat changes using geospatial tools.
6. Evaluate the advantages and limitations of modern conservation technologies.
3. CONCEPT OF REMOTE SENSING
Remote sensing is the science of acquiring information about the Earth's surface without making physical contact. It uses sensors mounted on satellites, drones, or aircraft to detect reflected or emitted electromagnetic radiation.
3.1 Principles of Remote Sensing
The working mechanism involves several steps:
1. Energy Source – Usually the Sun provides electromagnetic radiation.
2. Radiation Interaction – Energy interacts with atmospheric particles.
3. Reflection – Different surfaces reflect energy differently.
4. Detection – Sensors capture reflected radiation.
5. Processing – Data is converted into digital images.
6. Interpretation – Scientists analyze images to extract information.
3.2 Types of Remote Sensing
A. Passive Remote Sensing:
Uses natural solar radiation. Example: Landsat satellites.
B. Active Remote Sensing:
Emits its own signal (e.g., RADAR, LiDAR) and measures the reflection. Works during night and cloudy conditions.
3.3 Resolution in Remote Sensing
1) Spatial Resolution – Size of the smallest object detectable.
2) Spectral Resolution – Ability to distinguish wavelengths.
3) Temporal Resolution – Frequency of satellite revisit.
4) Radiometric Resolution – Sensitivity to intensity differences.
Higher resolution improves ecological accuracy.
4. ADVANTAGES OF REMOTE SENSING
1. Provides synoptic (large-area) coverage.
2. Enables monitoring of inaccessible habitats.
3. Facilitates long-term environmental assessment.
4. Minimizes disturbance to wildlife.
5. Supports disaster monitoring such as forest fires and floods.
5. CONCEPT OF GIS
A Geographic Information System (GIS) is a computer-based system designed to capture, store, analyze, manage, and visualize spatial or geographic data.
It integrates maps with databases, allowing researchers to detect patterns, relationships, and environmental trends.
5.1 Components of GIS
Hardware – Computers, GPS devices, servers.
Software – QGIS, ArcGIS, GRASS GIS.
Data – Satellite images, topographic maps, field surveys.
People – Ecologists, GIS analysts, planners.
Methods – Analytical procedures and models.
5.2 Functions of GIS
1) Spatial data visualization
2) Habitat suitability analysis
3) Corridor identification
4) Population distribution mapping
5) Climate vulnerability assessment
6. GIS DATA TYPES
Vector Data:
Represents features using points, lines, and polygons.
Example: animal locations, rivers, park boundaries.
Raster Data:
Represents continuous data using grid cells.
Example: satellite imagery, temperature maps.
7. DIFFERENCE BETWEEN GIS AND REMOTE SENSING
Feature | Remote Sensing | GIS |
Purpose | Data collection | Data analysis |
Tools | Satellites, drones | Computer software |
Output | Images | Maps & models |
Role | Input | Decision-making |
8. APPLICATIONS IN WILDLIFE HABITAT MANAGEMENT
8.1 Habitat Mapping
Satellite imagery helps classify forests, wetlands, deserts, and grasslands.
8.2 Monitoring Deforestation
Detects vegetation loss and fragmentation.
8.3 Wildlife Corridor Planning
Ensures genetic flow and reduces human-wildlife conflict.
8.4 Species Distribution Modeling
Predicts species presence based on environmental variables.
8.5 Climate Change Analysis
Tracks shifts in vegetation and habitat ranges.
8.6 Anti-Poaching Surveillance
Drones and spatial analytics support law enforcement.
8.7 Protected Area Design
Helps governments establish national parks and buffer zones.
9. MODERN TECHNOLOGIES INTEGRATED WITH GIS
1. Drones (UAVs) – High-resolution habitat imaging.
2. GPS Collars – Real-time animal tracking.
3. LiDAR – 3D forest structure mapping.
4. Artificial Intelligence – Automated species detection.
5. Cloud GIS – Real-time data sharing.
10. LIMITATIONS
• High initial infrastructure cost.
• Requires skilled professionals.
• Data misinterpretation risks.
• Weather interference.
• Need for ground-truth validation.
11. FUTURE SCOPE
Integration of AI, big data, and real-time satellite monitoring will transform conservation from reactive to predictive.
Emerging trends include:
1) Smart conservation systems
2) Automated habitat alerts
3) Predictive migration models
12. CONCLUSION
GIS and Remote Sensing have revolutionized wildlife habitat management by enabling data-driven conservation strategies. These technologies enhance ecological understanding, improve planning efficiency, and support sustainable biodiversity protection.
For future zoologists, mastering geospatial technologies is essential.
MULTIPLE CHOICE QUESTIONS (MCQs)
1. Remote sensing refers to:
A. Collecting data without physical contact
B. Laboratory experimentation
C. Animal tagging
D. Soil sampling
Answer: A
2. The primary energy source in passive remote sensing is:
A. Moon
B. Sun
C. Radar
D. Sensors
Answer: B
3. GIS stands for:
A. Global Information Science
B. Geographic Information System
C. Geological Imaging System
D. Geographic Internet Service
Answer: B
4. Which data type uses grid cells?
A. Vector
B. Raster
C. Linear
D. Polygonal
Answer: B
5. Which technology is best for tracking animal movement?
A. Thermometer
B. GPS collar
C. Microscope
D. Hygrometer
Answer: B
6. Spatial resolution refers to:
A. Color sensitivity
B. Detectable object size
C. Satellite speed
D. Data storage
Answer: B
7. Active remote sensing includes:
A. Landsat
B. Radar
C. Aerial photography
D. Sunlight sensors
Answer: B
8. GIS is mainly used for:
A. Cooking data
B. Spatial analysis
C. Genetic mutation
D. Blood analysis
Answer: B
9. Habitat fragmentation leads to:
A. Increased biodiversity
B. Ecosystem stability
C. Population isolation
D. Faster migration
Answer: C
10. LiDAR is useful for:
A. Measuring rainfall
B. Mapping forest structure
C. Soil chemistry
D. Ocean tides
Answer: B
11. Which resolution indicates revisit frequency?
Answer: Temporal Resolution
12. Vector data represents features as:
Answer: Points, lines, and polygons
13. The integration of GIS and RS supports:
Answer: Scientific wildlife management
14. UAV stands for:
Answer: Unmanned Aerial Vehicle
15. Ground truthing means:
Answer: Field verification of satellite data
16. Which tool helps design wildlife corridors?
Answer: GIS
17. Remote sensing reduces:
Answer: Human disturbance
18. Example of raster data:
Answer: Satellite imagery
19. GIS helps identify:
Answer: Conservation hotspots
20. Radar works effectively during:
Answer: Night and cloudy weather
21. Habitat suitability analysis predicts:
Answer: Areas favorable for species survival
22. Climate change monitoring requires:
Answer: Long-term spatial data
23. Anti-poaching efforts benefit from:
Answer: Drone surveillance
24. Buffer zones are created to:
Answer: Reduce human pressure
25. AI in conservation helps:
Answer: Automate species detection
26. Which is NOT a GIS component?
Answer: Telescope
27. Remote sensing is:
Answer: Synoptic in coverage
28. Protected areas are planned using:
Answer: Spatial analysis
29. High spectral resolution improves:
Answer: Material differentiation
30. GIS combines maps with:
Answer: Databases
31. Wildlife corridors maintain:
Answer: Genetic diversity
32. Cloud GIS enables:
Answer: Real-time collaboration
33. Radiometric resolution measures:
Answer: Sensitivity to energy differences
34. One limitation of RS:
Answer: Weather dependency
35. Predictive conservation is based on:
Answer: Data modeling
Activity 1: Concept Match
Match the following:
Column A | Column B |
Remote sensing | Data collection |
GIS | Spatial analysis |
GPS | Location tracking |
Activity 2: Critical Thinking
Question:
How can GIS help reduce human-wildlife conflict?
Activity 3: Research Task
“How is satellite data used in protecting Kaziranga National Park?”
References
1. Burrough, P. A., & McDonnell, R. A. (1998). Principles of Geographical Information Systems. Oxford University Press.
2. Lillesand, T. M., Kiefer, R. W., & Chipman, J. W. (2015). Remote Sensing and Image Interpretation (7th ed.). Wiley.
3. Jensen, J. R. (2016). Introductory Digital Image Processing: A Remote Sensing Perspective (4th ed.). Pearson.
4. Campbell, J. B., & Wynne, R. H. (2011). Introduction to Remote Sensing (5th ed.). Guilford Press.
5. Longley, P. A., Goodchild, M. F., Maguire, D. J., & Rhind, D. W. (2015). Geographic Information Science and Systems (4th ed.). Wiley.
6. Chang, K. T. (2019). Introduction to Geographic Information Systems (9th ed.). McGraw-Hill Education.
7. Heywood, I., Cornelius, S., & Carver, S. (2011). An Introduction to Geographical Information Systems (4th ed.). Pearson.
8. Joseph, G. (2005). Fundamentals of Remote Sensing (2nd ed.). Universities Press, India.
9. Turner, M. G., Gardner, R. H., & O’Neill, R. V. (2001). Landscape Ecology in Theory and Practice: Pattern and Process. Springer.
10. Guisan, A., Thuiller, W., & Zimmermann, N. E. (2017). Habitat Suitability and Distribution Models: With Applications in R. Cambridge University Press.
11. Pettorelli, N. (2013). The Normalized Difference Vegetation Index. Oxford University Press.
12. Kerr, J. T., & Ostrovsky, M. (2003). From Space to Species: Ecological Applications for Remote Sensing. Trends in Ecology & Evolution, 18(6), 299–305.
13. Food and Agriculture Organization (FAO). (2018). Handbook on Geospatial Infrastructure in Support of Forestry and Natural Resource Management. FAO.
14. National Remote Sensing Centre (NRSC), ISRO. (2020). Remote Sensing Applications for Natural Resource Management. Indian Space Research Organisation.
15. United Nations Environment Programme (UNEP). (2022). Geospatial Technologies for Conservation Planning.
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