UGC NET Environmental Science Unit-I: Fundamentals of Environmental Sciences Flashcards

24 sample cards from the Unit-I: Fundamentals of Environmental Sciences deck

Sampled from the end of the deck, so these are different cards from the ones shown on the syllabus page.

1. Distinguish between active and passive remote sensing.

   Passive sensors record natural radiation reflected or emitted by the target (e.g. optical/thermal sensors using sunlight). Active sensors generate their own energy and measure the returned signal (e.g. RADAR, LiDAR), enabling day/night and all-weather operation.

2. What is spectral reflectance (signature) and why is it useful?

   Spectral reflectance is the proportion of incident energy a surface reflects across different wavelengths. Each feature has a characteristic reflectance curve (spectral signature)—e.g. healthy vegetation strongly reflects near-IR—allowing features to be identified and distinguished.

3. List the four types of resolution in remote sensing.

   Spatial resolution (smallest distinguishable ground area/pixel size), Spectral resolution (number and width of wavelength bands), Radiometric resolution (sensitivity to energy differences/bit depth), and Temporal resolution (revisit frequency of a location).

4. What is the 'atmospheric window' in remote sensing?

   Atmospheric windows are wavelength ranges where the atmosphere is largely transparent (low absorption/scattering), allowing radiation to pass through to sensors. The visible, parts of the infrared, and microwave regions are key windows used in remote sensing.

5. Define a Geographic Information System (GIS).

   A GIS is a computer-based system for capturing, storing, managing, analysing, and displaying spatially referenced (geographic) data. It links attribute data to geographic location, enabling spatial query, overlay, and modelling for decision-making.

6. What are the main components of a GIS?

   The five components are: Hardware, Software, Data (spatial + attribute), People (users/experts), and Methods/Procedures. Data is often considered the most important and expensive component.

7. Compare raster and vector data models in GIS.

   Raster represents space as a grid of cells/pixels, each holding a value—good for continuous data (imagery, elevation). Vector represents features as points, lines, and polygons with coordinates—good for discrete features (roads, boundaries) and precise mapping.

8. What is a data layer (overlay) in GIS and why is it powerful?

   A layer is a themed dataset (e.g. roads, land use, soils) referenced to common coordinates. Overlay analysis stacks and combines layers spatially to reveal relationships and produce new information—a core GIS analytical capability for suitability and planning.

9. Differentiate spatial data from attribute data in GIS.

   Spatial data describes the location, shape, and geometry of features (where things are—coordinates). Attribute data describes the characteristics or properties of those features (what they are—e.g. name, population, land-use type), stored in linked tables.

10. What is digital image processing in remote sensing?

    Digital image processing is the computer-based manipulation and analysis of digital remote-sensing images (arrays of pixels with DN values) to correct distortions, enhance features, and extract thematic information. Main steps: pre-processing, enhancement, transformation, and classification.

11. What is image rectification/geometric correction?

    Geometric correction (rectification) removes geometric distortions (from sensor, platform, Earth curvature/rotation) and aligns the image to a map coordinate system (georeferencing), so pixels correspond to true ground positions. It often uses ground control points and resampling.

12. Name three common image enhancement techniques.

    (1) Contrast stretching (expanding the range of DN values to improve visibility), (2) Spatial filtering (low-pass smoothing or high-pass edge enhancement), and (3) Band ratioing / band combinations (e.g. creating indices or false-colour composites).

13. Differentiate supervised and unsupervised image classification.

    Supervised classification uses analyst-defined training samples of known classes to teach the algorithm (e.g. maximum likelihood). Unsupervised classification automatically groups pixels into spectral clusters (e.g. ISODATA, K-means) which the analyst then labels.

14. What is ground truthing (ground verification) in remote sensing?

    Ground truthing is the collection of in-situ reference data (field observations, GPS points, measurements) to verify, calibrate, and validate the interpretation/classification of remotely sensed imagery, ensuring accuracy of the derived maps.

15. What is an accuracy assessment and the error (confusion) matrix?

    Accuracy assessment compares classified-map results against ground-truth reference data to measure correctness. An error/confusion matrix cross-tabulates classified vs reference classes, yielding producer's accuracy, user's accuracy, overall accuracy, and the Kappa coefficient.

16. What is NDVI and what does it indicate?

    The Normalized Difference Vegetation Index = (NIR − Red)/(NIR + Red). It ranges from −1 to +1; high positive values indicate dense, healthy green vegetation, while low/negative values indicate bare soil, water, or built-up surfaces. It is widely used in vegetation studies.

17. Distinguish land cover from land use.

    Land cover refers to the physical/biophysical material on the Earth's surface (forest, water, grass, built-up, bare soil). Land use refers to how humans utilise the land (agriculture, residential, industrial, recreation). RS/GIS produces LULC (Land Use/Land Cover) maps.

18. How are remote sensing and GIS used to study urban sprawl?

    Multi-temporal satellite images are classified to map built-up areas over different years; change-detection in GIS quantifies the rate, direction, and pattern of urban expansion into surrounding rural/green land, supporting urban planning and growth management.

19. Give two applications of RS and GIS in forestry.

    (1) Mapping forest cover, type, and density and monitoring deforestation/afforestation through change detection; (2) Estimating biomass/carbon stock, assessing forest health, and detecting/monitoring forest fires and encroachment.

20. How do RS and GIS support natural resource management?

    They enable inventory and mapping of resources (water, soil, minerals, vegetation), monitoring of their condition and change over time, suitability analysis for sustainable use, watershed management, and identification of groundwater potential and degraded lands.

21. How are RS and GIS applied in solid waste management?

    They are used for suitable landfill/dumpsite site selection via multi-criteria overlay (considering land use, water bodies, settlements, roads, geology), monitoring existing dumpsites, optimising collection/transport routes, and assessing environmental impact of waste sites.

22. How do remote sensing and GIS contribute to climate change studies?

    They monitor large-scale indicators—glacier/ice-sheet retreat, sea-level and sea-surface temperature, deforestation, land-use change, greenhouse-gas and aerosol concentrations, vegetation/phenology shifts—and model impacts and vulnerability for mitigation and adaptation planning.

23. What is a false colour composite (FCC) and why is it used for vegetation?

    An FCC assigns near-infrared, red, and green bands to the red, green, and blue display channels respectively. Healthy vegetation, which reflects NIR strongly, appears bright red, making it easy to discriminate vegetation type, vigour, and stress.

24. What is change detection in remote sensing and GIS?

    Change detection is the process of identifying differences in the state of a feature or area by analysing co-registered images acquired at different times. It quantifies what has changed, where, and how much—used for LULC change, deforestation, urban growth, and disaster assessment.

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Unit-I: Fundamentals of Environmental Sciences flashcards FAQ