Lecture_8 Spatial and 3D analysis

Introduction to GIS - Spatial and 3D Analysis

• GIS (Geographic Information Systems) are used to analyze spatial and 3D data.
• Presentation outlines spatial analysis, overlay techniques, proximity analysis, interpolation, Euclidean distance, 3D models, and 3D analysis.

Spatial Analysis

• GIS can be used as a computerized map control system for police vehicles and ambulances.
• Real-time tracking and route-finding capabilities allow controllers to identify the fastest route for emergency vehicles.
• Historical incident data can be used to analyze and identify patterns related to black spots.

Overlay Techniques

• Combining map layers (e.g., rainfall and soil type) reveals additional insights beyond single layers.
• Overlay techniques allow selecting objects from one layer that reside within an object from a different layer.
• The output is a combined layer, with new information derived from the combination of layers.
• Thematic overlays combine various factors (e.g., social, economic, environmental data) to analyze an area. Examples used in the presentation are social, economic, transport, land use, administrative and environmental factors.

Cont. Overlay for optimum rice growing areas

• Optimum rainfall for high rice yield is 10mm/day, and soil type required is sandy loam.
• Combining rainfall maps and soil type maps simplifies locating the optimum growing areas.
• Assigning numeric values to rainfall and soil types (e.g., 5mm/day, clay) makes the resultant combined map easier to interpret.

Cont. Overlay - Results

• The accuracy of overlay results depends on the input data accuracy.
• Spatial querying helps analyze and understand the world around us.
• GIS helps perform complex analyses, which would otherwise be difficult or impossible without the software.

Proximity Analysis

• Proximity analysis, through multiple ring buffers, identifies areas of common interest by finding overlaps.
• Allows for defining areas, given specific distances from input features (e.g., roads, landmarks).
• Proximity analysis helps determine areas of common interest.
• The intersection of the buffers highlights an area of shared interest.
• Proximity analysis is useful in various contexts, depending on the problem being studied.

Interpolation

• Interpolation creates a surface representation from point data, such as showing concentration or magnitude patterns.
• Sample points are used as reference points for mathematically estimating values in between points.
• Interpolation techniques generate raster or vector output surfaces.
• Often used when field data is expensive to gather, as data collection may not be comprehensive to fill all areas. Useful for predicting values where direct measurement isn't taken.

Eg. Interpolation

• Interpolation, such as Inverse Distance Weighted (IDW), can create raster surfaces from point values.
• Contours can be generated from interpolation surfaces.

Eg. 3D Interpolated Surface

• Visual representation of interpolated data forming a surface.

Euclidean Distance

• Euclidean distance is a method to find the nearest point/area of interest.
• For example, determining the nearest hospital location for emergency helicopter deployment, or finding areas of close proximity to roads and other structures on a map.
• Euclidean distance can show how far an object is from other features in a map.
• Used in creating suitability maps where distances from various features are critical.

3D Models and Surface Analysis

• 2-D representations necessitate interpretation and imagination.
• The real world is inherently 3-D.
• GIS's capability to create dynamic and attractive 3-D models offers substantial advantages.

Height Information

• Map makers use various symbols (e.g., contours, spot heights, hill shading) to convey height information and illustrate the terrain's undulations.
• Specific symbols, such as spot heights, contours, hill shading and viewpoint symbols are vital for representing elevation in various formats.

Capture of Height Information

• Height information is captured in a similar manner to capturing the shape and locations of objects in a GIS.
• 3-D models of a terrain are generated from elevation data recorded at discrete points.
• The data is typically stored with latitude, longitude, and elevation values as a standard convention.
• Z-values are used to represent variations in height across an area.

Data Models Used for DTM in GIS

• Spot Height/LIDAR data, Contours, Grids, and DEM (Digital Elevation Models) are various data models.

Basic Data Structures for Elevation

• Spot heights/LIDAR data and contour lines are vector models. This is in contrast to 'raster' models.

Raster Elevation Data Structure

• Raster models divide the world into grid cells, storing elevation data for each cell, making analysis easy.

Two Ways of Representing Elevation

• Representing elevation data as contour lines or raster grids present different analysis capabilities. Raster grids are preferable for more complex analysis

Methods of Interpolation Elevation Surface

• TIN (Triangulated Irregular Networks), Voronoi Diagrams, Inverse Distance Weighted (IDW method), Kriging, Topogrid, and Surf (RST) Regularized Spline with Tension are methods.

TIN Surface

• A TIN forms a continuous surface by connecting irregularly spaced points to form a continuous surface.
• The surface's flatness is maintained within each generated triangle.

3D Surface Analysis

• Contour creation derives from the elevation raster data.

Two Ways GIS Works with Digital Elevation Data

• GIS performs spatial 2-D and 3-D terrain analysis, for instance of erosion, rainfall and elevation.

Realistic 3D Models

• Creating realistic 3-D models involves applying color to surfaces, draping map imagery or aerial photos, and integrating additional data (e.g., buildings).

Slope Derivation

• Slope derivation calculates inclination degrees from a dataset.
• Slope is commonly expressed as a percentage or degree value.
• The slope itself is a percentage, and is based on run over rise.

Aspect Derivation

• Aspect analysis identifies the directional slope of terrain surfaces.
• The analysis classifies aspects into different directional segments, such as north, northeast, south or west, for each cell and assigns directions such as north, northwest, south and east

Hillshade Derivation

• Creates a 3D visualization of the surface.
• Used for understanding the lighting effects by terrain.
• Azimuth and lighting contribute to the 3D visualization effect.

Viewshed Surface Analysis

• Areas that can be observed by a specific view point. The area of a surface that is visible from a given point is important data.

3D Model

• A 3-D model of terrain and structures, incorporating building elevation and structures onto the 3D model.

Buildings and Roads - Perspective Viewing

• Visualization of buildings and roads within the 3D model.

Developing a DTM (Digital Terrain Model)

• Elevation points are connected to generate contours.
• 3-D GIS data is stored in a grid format with X, Y, and Z coordinates.
• A computer constructs a 3-D model from this grid.