The essence of this chapter for last-minute revision: the definitions of GIS and Spatial Information Technology, the five components of GIS, the raster/vector comparison, the sequence of GIS activities, the three matching types, and the overlay/buffer worked case studies. The full notes, with the complete explanation, are available separately.
1 Definitions to learn by heart
The word spatial is derived from space: features and phenomena distributed over a geographically definable, measurable space.
Spatial Information Technology relates to the use of technological inputs in collecting, storing, retrieving, displaying, manipulating, managing and analysing spatial information. It is an amalgamation of Remote Sensing, GPS, GIS, Digital Cartography and Database Management Systems.
GIS (Geographical Information System): a system for capturing, storing, checking, integrating, manipulating, analysing and displaying data which are spatially referenced to the Earth. It is an amalgamation of Computer Assisted Cartography and a Database Management System, available since mid 1970’s.
2 Spatial vs non-spatial data, and the twelve allied fields
| Data type | Meaning | Box 4.1 example |
|---|---|---|
| Spatial data | Positional, linear or areal form of appearance; has a definite map location | Literate population of Kerala, Maharashtra, Gujarat and Punjab (1981) |
| Non-spatial (attribute) data | Can be located anywhere; not tied to a map position | Stock register of a cycle shop |
GIS draws its conceptual and methodological strength from 12 fields: Computer Science, Statistics, Cartography, Remote Sensing, Database Technology, Geography, Geology, Hydrology, Agriculture, Resource Management, Environmental Science and Public Administration.
3 Five components of GIS
| Component | Comprises |
|---|---|
| Hardware | Processing, storage, display, and input/output sub-systems |
| Software | Data entry/editing/maintenance; analysis/transformation/manipulation; display/output modules |
| Data | Spatial and tabular data, the backbone of GIS |
| People | Hardware/software engineers to policy-makers and monitoring agencies |
| Procedures | Retrieval, input, storage, management, transformation, analysis, output |
4 Raster vs Vector data formats (Box 4.2)
| Raster | Vector | |
|---|---|---|
| Structure | Grid of cells (pixels); each cell has a position and value | Coordinates of points (X,Y or X,Y,Z); lines have direction, polygons from points/lines |
| Best used for | Aerial photos/satellite images/scanned maps; low cost; “backdrop” maps | Highly precise applications; small file size; individual-feature analysis |
| Advantages | Simple structure, easy overlaying, compatible with satellite imagery, efficient for high spatial variability | Compact structure, efficient network analysis, efficient projection transformation, accurate map output |
| Disadvantages | Inefficient storage, errors in perimeter/shape, difficult network analysis | Complex structure, difficult overlay operations, incompatible with satellite imagery |
| Input method (book) | The book names no best method | Manual digitising, the best way of vector data input |
Resolution (raster) = relationship between cell size and number of cells, e.g. a 50 m pixel grid of 20×16 = 320 pixels versus a 25 m pixel grid of 40×36 = 1,440 pixels for the same area.
Raster, real-world and vector entities shown side by side: Point → a hotel; Line → electric supply lines; Area → a forest; Network → roads; Surface → elevation.
5 Sequence of five GIS activities
1. Spatial data input → 2. Entering the attribute data → 3. Data verification and editing → 4. Spatial and attribute data linkages → 5. Spatial analysis.
| Input category | Sub-stages / notes |
|---|---|
| (a) From a data supplier | Check scale, geo-referencing, collection technique, quality, classification method, mapping-unit size, record length; transferred via DAT tapes, CD ROMS, floppy disks |
| (b) Manual input | Entering spatial data → entering attribute data → verification/editing → linking spatial to attribute; via Digitisation or Scanning |
Scanners convert analogue data into digital grid-based images using CCD (Charged Coupled Devices) sensors. A scanned image is never perfect: it always carries the original’s smudges/defects, so excess data must be removed to make it usable.
6 Three error types and data linkage/matching
| Error type | Cause |
|---|---|
| Incomplete or double data | Gaps left by raster-vector conversion |
| Wrong scale | Errors during geo-referencing |
| Distorted data | Lens/relief/tilt distortion on aerial photos; rain, sunshine, folding damage on paper maps |
| Matching type | Worked example |
|---|---|
| Exact Matching | Two files about towns, joined using the town’s name as a common key |
| Hierarchical Matching | Land transformation data (small areas, more detail, less frequent) added together until the grouped areas match the large-area land use data (collected frequently), then matched exactly |
| Fuzzy Matching | Crop-field boundaries overlaid with soil-type boundaries to compute crop productivity per soil type |
Linkages worked example: to find child mortality due to malnutrition, combine a file of the number of children under 10 with a file of malnutrition mortality rate, then divide one figure by the other.
7 Spatial analysis: Overlay and Buffer
Integrates multiple map layers of the same area into a new map layer (like sieve mapping). Fig. 4.7 formula: x + y = z (Road map + Rail map = Transportation Map). Worked case study: Aligarh City’s 1974 and 2001 urban land-use maps overlaid to detect change and map urban sprawl.
A zone of specified distance around a point/line/area feature; generates polygon features; used to find who is served/denied a facility (hospitals, medical stores, parks) or affected by a pollution source (e.g. households within a 1 km buffer of a chemical industrial unit). Fig. 4.11 distances: 500 m (point), 500 m (line/road), 1,000 m (area/industrial unit). Worked case study: buffers of 2, 4, 6, 8, 10 km around six western UP cities with major hospitals, namely Saharanpur, Muzaffarnagar, Meerut, Ghaziabad, Gautam Budh Nagar, Aligarh, showing closer areas better served, farther areas least benefitted.
Four named spatial analysis operations: Overlay, Buffer, Network analysis, Digital Terrain Model. The chapter discusses only the first two in detail.
8 Named software and websites
| Type | Names |
|---|---|
| GIS software | Arc View/ArcGIS, Geomedia, Quantum GIS (free open software) |
| Websites to learn more | schoolgis.nic.in · bhuvan.nrsc.gov.in · www.iirs.gov.in |
- Spatial Info Technology = Remote Sensing + GPS + GIS + Digital Cartography + DBMS
- GIS since mid-1970’s; 5 components = Hardware, Software, Data, People, Procedures
- Raster = grid of cells (pixels); Vector = coordinates of points (X,Y/X,Y,Z)
- Resolution example: 50m pixel 20×16=320px vs 25m pixel 40×36=1,440px
- 3 matching types: Exact, Hierarchical, Fuzzy; CCD = Charged Coupled Devices
- 4 spatial analysis operations: Overlay, Buffer, Network analysis, Digital Terrain Model (only first 2 detailed)
- Overlay formula x+y=z (Road+Rail=Transportation); Aligarh City 1974 & 2001 case study
- Buffer distances: Fig 4.11 = 500m/500m/1,000m; UP case study = 2,4,6,8,10 km around Saharanpur, Muzaffarnagar, Meerut, Ghaziabad, Gautam Budh Nagar, Aligarh
- Software: Arc View/ArcGIS, Geomedia, Quantum GIS · Websites: schoolgis.nic.in, bhuvan.nrsc.gov.in, www.iirs.gov.in