LESSON 15.1 — GIS Concepts, Components, Raster vs Vector Data Structures
A. Standard Map
| Topic | Governing Source | Exam Focus |
|---|---|---|
| GIS — definition | Geographic Information System | Definition |
| GIS components | Hardware, software, data, people, methods | 5 components |
| Spatial vs non-spatial data | Geometric vs attribute | Distinction |
| Raster data | Grid of cells; satellite imagery | Structure + use |
| Vector data | Points, lines, polygons | Structure + use |
| Raster vs vector comparison | Trade-offs | Strengths + weaknesses |
| Coordinate systems | Geographic (lat-long); projected (UTM) | Distinction |
| Georeferencing | Map to real-world coordinates | Concept |
| GIS operations | Overlay, buffer, network, query | Operations + use |
| Major GIS software | QGIS, ArcGIS, GRASS, MapInfo | Examples |
B. Why It’s Used
Paper II §15 of the TGPSC syllabus specifies “GIS concepts, components and their functions. Data types-raster and vector data structures, raster data capture, processing and analysis, Spatial data creation and linking of attribute data, Geo-spatial data base creation.” GIS is the modern planner’s primary analytical tool — every Master Plan, every land use survey, every infrastructure network analysis, every property tax mapping exercise uses GIS. The exam tests GIS definition and components, raster vs vector distinction (the most-tested GIS concept), GIS operations (buffer, overlay, network), and major GIS software. Telangana-specific: HMDA’s GIS-based land use mapping, the Telangana State Remote Sensing Applications Centre (TRAC), DTCP’s use of GIS in layout approvals.
C. Mechanism in Words
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A Geographic Information System (GIS) is a computer-based system for capturing, storing, analysing, and displaying spatially-referenced data — data that has a geographic location attached. Three key features distinguish GIS from a generic information system or drawing software: (a) spatial data — every piece of information is tied to a real-world location (typically via coordinates); (b) attribute data — non-spatial information linked to spatial features (e.g., a parcel’s owner, value, use); (c) topology — the spatial relationships between features (adjacency, containment, connectivity). GIS enables queries and analyses that paper maps cannot support — “show all parcels within 500 m of a metro station, zoned residential, with area > 200 sq m” is a one-line query in GIS but impossible on paper.
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GIS has five components. Hardware — the computers, servers, GPS devices, scanners, plotters that capture, process, store, and output GIS data. Software — the GIS application (QGIS, ArcGIS, GRASS, MapInfo, etc.) that provides functions for data entry, editing, analysis, and display. Data — the most expensive and important component; includes spatial data (vector/raster) and attribute data; sources include satellite imagery, GPS field surveys, digitised maps, and tabular databases. People — the GIS analysts, planners, technicians who design, operate, and interpret the system; even the best software is useless without trained people. Methods — the business rules, workflows, data standards, and operating procedures that govern how the GIS is used; without documented methods, GIS becomes an ad-hoc tool with inconsistent outputs.
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Spatial data has two dimensions: geometric (where) and attribute (what). The geometric component describes the feature’s location and shape — a point (a single x,y coordinate), a line (a sequence of points), or a polygon (a closed sequence of points). The attribute component describes the feature’s characteristics — for a parcel: ownership, value, land use, area, year built. The two are linked by a unique identifier (often a parcel ID); GIS enables queries that filter on either dimension. Spatial query — “show all features in this area” (filter on geometry). Attribute query — “show all residential parcels over 200 sq m” (filter on attributes). Combined query — the power of GIS.
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Raster and vector are the two principal data models in GIS. Raster data represents geographic phenomena as a grid of cells (pixels) — each cell has a value, and the cells together form an image. Satellite imagery is the canonical raster — each pixel records the light intensity at that location for a given wavelength band. Digital Elevation Models (DEMs) are rasters where each cell value is the elevation. Raster data is excellent for continuous phenomena (temperature, elevation, soil moisture, vegetation cover) where the value varies smoothly across space. The cell size (resolution) determines the level of detail — 30 m Landsat pixels capture regional patterns; 0.5 m WorldView pixels capture individual buildings.
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Vector data represents geographic phenomena as points, lines, and polygons defined by coordinates. A point is a single (x, y) coordinate — e.g., a tree, a building centroid, a GPS waypoint. A line (also called arc or polyline) is a sequence of points connected by straight segments — e.g., a road, river, pipeline. A polygon is a closed sequence of points defining an area — e.g., a parcel, a building footprint, a lake. Vector data is excellent for discrete features with sharp boundaries (parcels, buildings, road centre-lines) where geometry and topology matter.
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The raster vs vector trade-off is the most-tested GIS concept. Raster strengths: simple data structure (grid of values); excellent for continuous phenomena; computationally efficient for overlay operations; easy capture from satellite imagery. Raster weaknesses: large file sizes (especially at fine resolution); loss of precision at cell boundaries; difficult to represent topological relationships (no “adjacency” between cells); “pixelated” appearance at fine scales. Vector strengths: precise representation of features; compact file sizes (especially for sparse data); supports topology (adjacency, containment, connectivity); visually clean at any scale. Vector weaknesses: complex data structure; computationally expensive for overlay operations; difficult capture (digitising from imagery is slow); not suited to continuous phenomena. Modern GIS combines both — raster for background imagery and continuous fields, vector for parcels and infrastructure.
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Coordinate systems map the three-dimensional Earth to a two-dimensional map. Geographic coordinate systems use latitude and longitude (in degrees) — accurate for global positioning but not for distance/area computation (1° longitude at the equator ≠ 1° at the poles). Projected coordinate systems use flat x-y coordinates (in metres) — accurate for distance/area but distort some property (shape, area, distance, or direction) to flatten the Earth. The Universal Transverse Mercator (UTM) is the most common projected system globally — it divides the Earth into 60 zones, each 6° of longitude wide, and uses a transverse Mercator projection that minimises distortion within each zone. India lies in UTM zones 42–47. Telangana falls in UTM Zone 44 North (Hyderabad longitude ~78°E). Georeferencing is the process of assigning real-world coordinates to spatial data — a scanned map, an engineering drawing, a satellite image.
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GIS operations fall into several families. Data capture and editing — digitising from imagery, importing GPS data, editing geometry. Database queries — selecting features by attribute (e.g., “all parcels with value > ₹10 lakh”) or by spatial location (e.g., “all parcels within 500 m of metro station”). Overlay operations — combining layers (union, intersect) to identify areas satisfying multiple criteria (e.g., land zoned residential AND slope < 5% AND within 1 km of water source). Buffer operations — creating zones around features at specified distances (e.g., 100 m buffer around a lake; 500 m buffer around a metro station). Network operations — analysing connected linear features (roads, pipes) for routing, service areas, shortest paths. Terrain analysis — slope, aspect, watersheds from DEMs. Spatial statistics — pattern analysis (clustered, dispersed, random), nearest-neighbour, kernel density. Together these operations enable the planner to answer complex questions — “Where are the best sites for new affordable housing?” becomes a multi-criteria overlay analysis.
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Major GIS software packages used in Indian planning. QGIS (formerly Quantum GIS) — open-source, free, full-featured; widely used in academic and government settings. ArcGIS (Esri) — commercial, the global industry standard; widely used in industry, ULBs, and research. GRASS GIS — open-source, powerful for raster analysis. MapInfo — commercial, used in some Indian government departments. SAGA GIS — open-source, strong terrain analysis. Google Earth / Google Earth Engine — free for visualisation and increasingly for analysis; widely used for quick lookups. Indian government bodies (NRSC — National Remote Sensing Centre; ISRO’s Bhuvan; state Remote Sensing Applications Centres) also develop and use custom GIS tools. Telangana’s Telangana State Remote Sensing Applications Centre (TRAC) and Andhra Pradesh State Remote Sensing Applications Centre (APSRAC) are state-level bodies supporting ULBs and state departments.
D. Core Concept Explanations
C1. GIS — five components
| Component | Function |
|---|---|
| Hardware | Computers, servers, GPS, scanners, plotters |
| Software | GIS application (QGIS, ArcGIS, etc.) |
| Data | Spatial + attribute; the most expensive component |
| People | GIS analysts, planners, technicians |
| Methods | Workflows, data standards, business rules |
C2. Spatial vs attribute data
| Dimension | Description | Example |
|---|---|---|
| Geometric (spatial) | Where — location and shape | A parcel at coordinates (X, Y) |
| Attribute (non-spatial) | What — characteristics | Parcel ID, owner, value, land use |
C3. Raster vs vector
| Dimension | Raster | Vector |
|---|---|---|
| Basic unit | Grid cell (pixel) | Point, line, polygon |
| Best for | Continuous phenomena (temperature, elevation, vegetation) | Discrete features (parcels, buildings, roads) |
| File size | Large (especially fine resolution) | Compact |
| Topology | Difficult | Supported (adjacency, connectivity) |
| Capture | From satellite imagery; DEMs | Digitising from imagery; GPS |
| Overlay | Computationally simple | Computationally expensive |
| Examples | Landsat imagery; DEM; land cover | Parcels; road network; building footprints |
C4. Vector primitives
| Primitive | Geometry | Examples |
|---|---|---|
| Point | Single (x, y) coordinate | Tree, building centroid, GPS waypoint |
| Line (arc, polyline) | Sequence of points connected | Road, river, pipeline |
| Polygon | Closed sequence of points | Parcel, building footprint, lake |
C5. GIS operations
| Operation | What it does | Example |
|---|---|---|
| Spatial query | Select features by location | All parcels within 500 m of metro |
| Attribute query | Select by attributes | All residential parcels > 200 sq m |
| Overlay | Combine layers (union, intersect) | Residential AND slope < 5% |
| Buffer | Zone around features at given distance | 100 m buffer around a lake |
| Network analysis | Routing on linear features | Shortest path; service area |
| Terrain analysis | Slope, aspect, watersheds from DEM | Slope < 10% for buildable area |
| Spatial statistics | Pattern analysis | Clustered/dispersed/random |
E. Worked Numericals and Parameter Tables
E1. Raster resolution and file size
A 1 km × 1 km area raster at 10 m resolution (Sentinel-2): grid is 100 × 100 = 10,000 cells. At 4 bytes per cell (4-band multispectral), file size = 10,000 × 4 × 4 = 160,000 bytes ≈ 160 KB. At 0.5 m resolution (WorldView): grid is 2000 × 2000 = 4 million cells; file = 4M × 4 × 4 = 64 MB. Finer resolution = much larger file.
E2. Vector point count
A road network with 10,000 km of roads, digitised at 50 m vertex spacing: total vertices = 10,000,000 / 50 = 200,000 vertices. Each vertex stored as (x, y) at 16 bytes = 3.2 MB — compact.
E3. Buffer computation
A lake of 1 sq km area; 100 m buffer zone. Buffer area = original area + perimeter × 100 m + π × 100². For a circular lake of 1 sq km (radius ~564 m, perimeter ~3,545 m): buffer area = 1,000,000 + 3,545 × 100 + 31,416 = 1,000,000 + 354,500 + 31,416 = 1,385,916 sq m ≈ 1.39 sq km. The 100 m buffer adds 0.39 sq km of regulated area.
E4. Overlay intersection
Two layers: Layer A = residential zoning (5 sq km); Layer B = slope < 5% (8 sq km). Intersect: only areas that are both residential AND slope < 5%. If the overlap is 3 sq km, this is the buildable area for residential development.
F. Design Criteria
| Parameter | Standard / Typical value | Source |
|---|---|---|
| Landsat resolution | 30 m multispectral; 15 m panchromatic | NASA / USGS |
| Sentinel-2 resolution | 10 m multispectral | ESA |
| WorldView resolution | 0.5 m panchromatic; 2 m multispectral | Maxar |
| UTM zones | 60 zones, each 6° longitude wide | UTM convention |
| India UTM zones | 42–47 | UTM convention |
| Telangana UTM zone | 44 North | UTM convention |
| Common GIS software | QGIS (open source); ArcGIS (commercial) | Industry |
G. Application Zones
- Land use mapping — Master Plan preparation; URDPFI standards.
- Parcel / property tax mapping — ULB e-governance reform.
- Infrastructure network planning — water supply, sewerage, drainage, roads.
- Site suitability analysis — multi-criteria overlay for housing, industry, facilities.
- Disaster management — hazard mapping; risk analysis; evacuation planning.
- Environment — EIA, forest cover, wetland monitoring.
H. Common Confusions
| Confusion | Reality |
|---|---|
| “GIS is just map-making software.” | No — GIS is a spatial database with analysis capabilities. Cartography is one output; analysis is the core. |
| “Raster and vector are interchangeable.” | Different data models with different strengths — raster for continuous; vector for discrete. |
| “Vector is always better than raster.” | No — depends on application. Continuous phenomena are best in raster. |
| “Geographic coordinate (lat-long) is the same as projected (UTM).” | No — geographic is degrees on the Earth’s surface; projected is metres on a flat plane. |
| “Buffer and overlay are the same operation.” | No — buffer creates zones around features; overlay combines layers. |
| “QGIS is the only open-source GIS.” | No — GRASS, SAGA, gvSIG are also open-source. |
| “UTM zones are 15° wide.” | No — UTM zones are 6° wide (60 zones × 6° = 360°). |
I. Compare & Contrast
I1. Raster vs vector
| Dimension | Raster | Vector |
|---|---|---|
| Basic unit | Cell (pixel) | Point/line/polygon |
| Best for | Continuous | Discrete |
| File size | Large | Compact |
| Topology | Hard | Supported |
| Examples | Satellite imagery; DEM | Parcels; roads; buildings |
I2. Geographic vs projected coordinate systems
| Type | Coordinates | Use |
|---|---|---|
| Geographic | Latitude, longitude (degrees) | Global positioning; GPS |
| Projected (e.g., UTM) | X, Y (metres) | Distance/area computation; engineering |
J. Memory Hooks
- “Hardware-Software-Data-People-Methods” — GIS 5 components.
- “Raster = cells; Vector = points/lines/polygons” — the core distinction.
- “Raster for continuous; Vector for discrete” — application rule.
- “Landsat 30 m; Sentinel 10 m; WorldView 0.5 m” — three resolutions.
- “UTM 60 zones × 6° each” — global grid.
- “Telangana = UTM Zone 44 N”.
- “QGIS open; ArcGIS commercial” — two principal software.
- “Query-Overlay-Buffer-Network-Terrain-Statistics” — 6 GIS operations.
K. Revision Ladder
| Order | Item | Time |
|---|---|---|
| 1 | Memorise GIS definition + 5 components | 30 min |
| 2 | Memorise spatial vs attribute distinction | 20 min |
| 3 | Memorise raster vs vector with strengths/weaknesses | 45 min |
| 4 | Memorise vector primitives (point, line, polygon) | 15 min |
| 5 | Memorise geographic vs projected coordinate systems | 30 min |
| 6 | Memorise UTM structure (60 zones, 6° each; Telangana 44N) | 20 min |
| 7 | Memorise GIS operations (6 types) | 30 min |
| 8 | Memorise major satellite resolutions (Landsat, Sentinel, WorldView) | 20 min |
| 9 | Practise raster size, vector vertex, buffer computations | 30 min |
L. Exam Traps
| Trap | Correct response |
|---|---|
| Question pairs raster with discrete features. | False — raster is for continuous; vector for discrete. |
| Question lists UTM zone width as 15°. | False — 6° (60 zones × 6° = 360°). |
| Question lists GIS as just mapping software. | False — GIS is a spatial database with analysis. |
| Question pairs buffer with overlay. | Different — buffer creates zones; overlay combines layers. |
| Question pairs lat-long with projected coordinates. | Different — geographic (degrees) vs projected (metres). |
| Question lists QGIS as commercial. | False — QGIS is open-source / free. ArcGIS is commercial. |
| Question pairs vector with continuous phenomena. | False — vector for discrete; raster for continuous. |
M. Answer-Writing Cues
- For definition questions, give the three distinguishing features: “A GIS is a computer-based system for capturing, storing, analysing, and displaying spatially-referenced data — distinguished by spatial data, attribute data, and topology.”
- For raster vs vector questions, give a comparison table + use cases: “Raster represents continuous phenomena as a grid of cells (e.g., satellite imagery, DEM); vector represents discrete features as points, lines, and polygons (e.g., parcels, roads, building footprints).”
- For GIS operations, give operation + example: “Buffer operations create zones at a specified distance around features — a 100 m buffer around a lake is used to enforce the regulated area.”
N. PYQ Integration
Pattern questions only:
Pattern question 1 — Raster vs Vector
Q. Which of the following is best represented in raster format?
– (A) Parcels of land
– (B) Road centre-lines
– (C) Building footprints
– (D) Continuous temperature field ✓
Ans: (D). Continuous phenomena → raster. Parcels, roads, buildings → vector.
Pattern question 2 — UTM
Q. The Universal Transverse Mercator (UTM) system divides the Earth into how many zones, each how wide?
– (A) 12 zones × 30° each
– (B) 24 zones × 15° each
– (C) 60 zones × 6° each ✓
– (D) 120 zones × 3° each
Ans: (C).
Pattern question 3 — GIS components
Q. The five components of a Geographic Information System are:
– (A) Hardware, Software, Data, People, Methods ✓
– (B) Hardware, Software, Data, Printers, Internet
– (C) Computers, Maps, Software, Printers, Internet
– (D) Software, Hardware, Network, Database, Output
Ans: (A).
Pattern question 4 — MSQ
Q. Which of the following are vector primitives in GIS?
– (A) Point ✓
– (B) Line ✓
– (C) Polygon ✓
– (D) Pixel
Ans: (A), (B), (C). Pixel is the raster unit, not a vector primitive.
Pattern question 5 — Landsat resolution
Q. The multispectral resolution of Landsat satellite imagery is approximately:
– (A) 0.5 m
– (B) 5 m
– (C) 30 m ✓
– (D) 100 m
Ans: (C). Landsat TM/OLI multispectral = 30 m; panchromatic = 15 m.
O. Mini-Check — Lesson 15.1
- Define GIS and state its three distinguishing features.
- List the five components of GIS.
- Distinguish spatial from attribute data.
- State the raster and vector data models with examples.
- State three strengths each of raster and vector.
- List the three vector primitives.
- State the difference between geographic and projected coordinate systems.
- State the UTM zone structure and Telangana’s UTM zone.
- List six GIS operations.
- State the resolution of Landsat, Sentinel-2, and WorldView imagery.
Answers:
1. GIS = computer-based system for capturing, storing, analysing, displaying spatially-referenced data. Three distinguishing features: spatial data, attribute data, topology.
2. Hardware, Software, Data, People, Methods.
3. Spatial = where (location and shape); Attribute = what (characteristics).
4. Raster = grid of cells (e.g., satellite imagery, DEM). Vector = points, lines, polygons (e.g., parcels, roads, building footprints).
5. Raster strengths: continuous phenomena; efficient overlay; easy capture from imagery. Vector strengths: precise; compact; supports topology.
6. Point, line (arc/polyline), polygon.
7. Geographic uses latitude and longitude (degrees) on the Earth’s surface; projected uses flat x-y coordinates (metres) — accurate for distance/area.
8. UTM = 60 zones, each 6° longitude wide. Telangana is in UTM Zone 44 North.
9. Spatial query; attribute query; overlay (union/intersect); buffer; network analysis; terrain analysis; spatial statistics. Any six.
10. Landsat 30 m multispectral / 15 m panchromatic; Sentinel-2 10 m multispectral; WorldView 0.5 m panchromatic / 2 m multispectral.
Next: Lesson 15.2 — Remote Sensing, Spatial Database Creation & Planning Applications.