Geospatial Roof Type Identification via Multi-Directional Gradient Calculations

Solution Overview

Problem

Automated topographical models struggle to accurately distinguish between different types of building structures, particularly in urban areas with numerous buildings, due to the complexity of roof types such as flat, sloped, and domed roofs, requiring manual intervention which is time-consuming and costly.

Innovation Solution

A geospatial modeling system that uses multi-directional gradient calculations, including Robert's cross calculations, to identify building roof types by analyzing building roof data points, and substitutes appropriate geometric shapes for rendering, allowing for automated identification and rendering of flat, sloped, complex sloped, and domed roofs.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If manual intervention is used to identify building roof types, then accuracy of building structure identification is improved, but time consumption and cost increase

Engineering Contradiction:

Improvebuilding roof type identification accuracyVSAvoidtime consumption

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The system enables automated self-identification of building roof types through multi-directional gradient calculations applied to building data points. The computer automatically analyzes the geometric characteristics of building structures and classifies roof types without requiring manual operator intervention, thereby maintaining high accuracy while dramatically reducing time consumption and costs.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent replaces the manual mechanical process of visual inspection and classification with an automated computational system. Multi-directional gradient calculations are performed on building data points to automatically detect and classify roof types (flat, sloped, domed, etc.), substituting human operators with algorithmic processing that achieves comparable or superior accuracy at much lower time and cost.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Measurement precision

If manual intervention is used to identify building roof types, then accuracy of building structure identification is improved, but cost increases

Engineering Contradiction:

Improvebuilding roof type identification accuracyVSAvoidcost

Core Design Contradiction:

Measurement precisionVSEase of manufacture

Solution Approach 1:

The system enables automated self-identification of building roof types through multi-directional gradient calculations applied to building data points. The computer automatically analyzes the geometric characteristics of building structures and classifies roof types without requiring manual operator intervention, thereby maintaining high accuracy while dramatically reducing time consumption and costs.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent replaces the manual mechanical process of visual inspection and classification with an automated computational system. Multi-directional gradient calculations are performed on building data points to automatically detect and classify roof types (flat, sloped, domed, etc.), substituting human operators with algorithmic processing that achieves comparable or superior accuracy at much lower time and cost.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

3Productivity

If automated processes are used for building identification, then productivity is improved, but measurement precision deteriorates

Engineering Contradiction:

Improveprocessing speedVSAvoidbuilding roof type identification accuracy

Core Design Contradiction:

ProductivityVSMeasurement precision

Solution Approach 1:

The patent replaces the manual mechanical process of visual inspection and classification with an automated computational system. Multi-directional gradient calculations are performed on building data points to automatically detect and classify roof types (flat, sloped, domed, etc.), substituting human operators with algorithmic processing that achieves comparable or superior accuracy at much lower time and cost.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system uses multi-directional gradient calculations that analyze building data points from multiple angular perspectives. By computing gradients in different directions and synthesizing this information, the automated system achieves accurate roof type classification while maintaining high processing speed, overcoming the traditional trade-off between automation and precision.

Inventive Principle:

Principle #35Parameter changes

Data Source

PatentUS7752018B2Geospatial modeling system providing building roof type identification features and related methods

Publication Date: 2010.07.06 HARRIS CORP

AI summary

A geospatial modeling system may include a geospatial model database and a processor. The processor may cooperate with the geospatial database for identifying a building roof type defined by building roof data points as being from among a plurality of possible building roof types. This may be done based upon applying multi-directional gradient calculations to the building roof data points.