Spatial Analysis in GIS: Raster, Vector, Network & Surface Modeling

Core Concepts: What is Spatial Analysis?

Spatial analysis in GIS refers to the process of examining spatial data to detect patterns, relationships, and trends. Unlike traditional statistical analysis, it focuses on location, distance, direction, and spatial relationships between features. Key operations include:

• Overlay analysis (combining layers)
• Buffering (creating zones around features)
• Proximity analysis (measuring distances)
• Terrain analysis (elevations, slopes, viewsheds)

1. Raster-Based Spatial Analysis

Raster data represents the world as a grid of cells (pixels), where each cell holds a value (e.g., elevation, land cover). Common operations:

Key Operations

How It Works: Slope Calculation from DEM

1. Input: Digital Elevation Model (DEM) raster.
2. Process: Use the slope formula for each cell: $$\text{Slope}=\arctan \left(\frac{\text{change in elevation}}{\text{distance}}\right)$$
3. Output: Slope raster (degrees or percentage).

graph LR
    A["DEM Raster"] -->|"Slope Algorithm"| B["Slope Raster"]
    B --> C["Steep Areas\n(>30°)"]
    B --> D["Gentle Slopes\n(<10°)"]

Advantages & Limitations

2. Vector-Based Spatial Analysis

Vector data represents features as points, lines, or polygons with attributes. Key operations:

Key Operations

How It Works: Buffer Analysis for Pathao Delivery Zones

1. Input: Pathao delivery partner locations (points) + customer addresses (points).
2. Process: Create a 1km buffer around each partner.
3. Output: Areas where customers can order without additional delivery fees.

Advantages & Limitations

3. Network Analysis

Network analysis models connected systems (e.g., roads, rivers, utilities) to solve pathfinding, connectivity, or flow problems.

Key Operations

How It Works: NTC Bus Route Optimization

1. Input: Bus stops (points) + road network (lines) with travel times.
2. Process: Use Dijkstra’s algorithm to find the fastest route from New Bus Parking to Kathmandu University.
3. Output: Optimal path with estimated travel time (e.g., 45 minutes).

4. Surface Modeling

Surface modeling represents continuous phenomena (e.g., elevation, temperature) using:

• Raster: Regular grid (DEM).
• Vector: Triangulated Irregular Network (TIN).

Key Techniques

How It Works: Flood Risk Mapping for Bagmati River

1. Input: DEM + river polygon + rainfall data.
2. Process:
   • Calculate slope from DEM.
   • Identify low-lying areas (slope < 5°).
   • Overlay with river buffer (500m).
3. Output: Flood-prone zones for evacuation planning.

In the Real World

1. eSewa & Kathmandu Traffic Routes

   • Idea Used: Network analysis (shortest path).
   • How: eSewa’s partner apps (e.g., Pathao, HamroBus) use GIS to calculate the fastest route for deliveries or public transport, avoiding traffic jams. For example, a Pathao rider’s app dynamically reroutes based on real-time traffic data from NTC cameras.

2. Ncell Tower Placement

   • Idea Used: Viewshed analysis + surface modeling.
   • How: Ncell uses DEM data to model terrain and viewshed analysis to determine optimal tower locations that maximize coverage while minimizing interference from hills. A tower in Chandragiri might be placed higher to cover Kathmandu Valley despite surrounding mountains.

3. Daraz Delivery Logistics

   • Idea Used: Buffer analysis + OD cost matrix.
   • How: Daraz uses 1km–3km buffers around warehouses to define delivery zones. Their OD cost matrix calculates delivery fees based on distance and terrain (e.g., hilly areas in Pokhara cost more than flat areas in Lalitpur).

4. Nepal Electricity Authority (NEA) Grid Planning

   • Idea Used: Surface modeling (DEM) + proximity analysis.
   • How: NEA uses DEM data to model terrain for power line routes, avoiding steep slopes (which increase construction costs). Proximity analysis helps identify the nearest substations to new residential areas in Bhaktapur.

Exam Tip: How to Score Full Marks

1. Define Clearly
   • Always start with precise definitions (e.g., "Raster analysis operates on a grid of cells where each cell holds a single value...").
   • Example: For "surface modeling", define it as "the process of representing continuous phenomena (e.g., elevation) using either raster (DEM) or vector (TIN) structures."

2. Compare Raster vs. Vector

   • Use a table (as shown above) to contrast operations, advantages, and use cases. Examiners love structured comparisons.

3. Link to Real-World Examples

   • For network analysis, mention Pathao/Daraz delivery routes or NTC bus optimization.
   • For surface modeling, cite flood risk mapping (Bagmati River) or Ncell tower siting.

4. Show Worked Steps

   • For buffer analysis, write:

     "Step 1: Input layer = school locations (points). Step 2: Buffer distance = 500m. Step 3: Output = polygon layer showing catchment areas."

   • For slope calculation, include the formula and a DEM → slope raster flowchart.

5. Avoid Vague Statements

   • ❌ "GIS is used everywhere."
   • ✅ "In Nepal, eSewa uses network analysis to optimize delivery routes, while NEA applies surface modeling to plan power lines along cost-effective terrain."

6. Visuals = Extra Marks

   • Sketch a simple flowchart (e.g., DEM → slope → flood risk) or label a real map (e.g., Pathao delivery zones). Even a rough diagram with annotations can boost your score.

Practice Questions with Model Answers

Q1: Define raster-based analysis. How does it differ from vector-based analysis? [5+5]

Model Answer: Raster-based analysis in GIS involves processing spatial data stored as a grid of cells (pixels), where each cell contains a single value (e.g., elevation, land cover). Operations include local (e.g., slope), neighborhood (e.g., focal mean), and zonal (e.g., average rainfall in a watershed) calculations.

Key Differences:

Visual:

Q2: Explain how network analysis is used in transportation logistics. Provide an example. [5]

Model Answer: Network analysis in GIS models connected systems (e.g., roads, railways) to solve problems like route optimization, service area definition, and facility location. Key techniques include:

1. Shortest Path: Finds the optimal route between two points (e.g., Google Maps).
2. Service Area: Defines reachable zones within a time/cost threshold (e.g., Ncell tower coverage).
3. Closest Facility: Locates the nearest service (e.g., nearest hospital to a village).

Example: Pathao Delivery Optimization

1. Input: Pathao partner locations (points) + road network (lines with travel times).
2. Process:
   • Use shortest path to assign orders to the nearest available rider.
   • Apply service area to define delivery zones (e.g., 1km radius per partner).
3. Output: Reduced delivery time and fuel costs. Visual:

Q3: Describe surface modeling in GIS. How is it used in environmental analysis? [5+5]

Model Answer: Surface modeling in GIS represents continuous phenomena (e.g., elevation, temperature) using:

• Raster: Digital Elevation Model (DEM) as a grid.
• Vector: Triangulated Irregular Network (TIN) for precise surfaces.

Key Techniques:

1. DEM: Elevation data for terrain analysis.
2. Slope/Aspect: Derived from DEM to study land stability.
3. Viewshed: Identifies visible areas from a viewpoint (e.g., tower placement).
4. Contour Lines: Represent elevation changes on maps.

Environmental Applications:

1. Flood Risk Mapping:
   • Input: DEM + river data.
   • Process: Identify low-lying areas (slope < 5°) near rivers.
   • Output: Evacuation zones for Bagmati River.
2. Landslide Prediction:
   • Input: DEM + rainfall data.
   • Process: Combine steep slopes (>30°) with high rainfall zones.
   • Output: High-risk areas for early warnings.
3. Wildfire Management:
   • Input: DEM + vegetation data.
   • Process: Model fire spread using slope and wind direction.
   • Output: Evacuation routes and firebreaks.

Visual: