CA PLS Exam Preparation
Comprehensive preparation for the California Professional Land Surveyor (PLS) exam. Based on the January 2025 Test Plan with 6 modules and 57 topics. Content adapted from CalTrans LS/LSIT Video Exam Preparation Course materials.
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Module 1: Business Practices and Project Management
1Explaining Land Surveying to the Public2Proposals and Contracts3Procuring Surveying Services4Directing Personnel5Coordinating with Third Parties6Project Standards7Project Execution Planning8Monument Preservation9Managing a Surveying Business10Subdivision Map Act11Professional Land Surveyors Act12Conflicts of Interest
Module 2: Research, Project Planning and Preparation
Module 3: Field Operations and Investigations
Module 4: Analysis and Evaluation
33Analyzing Field Evidence and Documentation34Evaluating Historic vs. Measured Accuracy35Spatial Relationships of Maps and Data36Boundary Location Conflicts37Title Conflicts38Survey Adjustments (Least Squares, Error Analysis)39Quality Assurance and Control40Reconciling Deeds with Field Evidence41Technology Limitations in Practice
Module 5: Mapping and Document Preparation
Lesson 3
3D Models (BIM, DTM, Point Clouds)
3D Models (BIM, DTM, Point Clouds)
Overview
Three-dimensional models are increasingly important survey deliverables. Understanding their creation, characteristics, and limitations is essential for modern practice.
Learning Objectives
- Understand 3D model types
- Create and validate surface models
- Work with point cloud data
- Deliver models meeting specifications
Key Concepts
Model Types
Common 3D survey products:
- DTM: Digital Terrain Model (bare earth)
- DSM: Digital Surface Model (first returns)
- TIN: Triangulated Irregular Network
- BIM: Building Information Model
Point Cloud Processing
Working with point cloud data:
- Classification (ground, vegetation, buildings)
- Noise removal
- Feature extraction
- Surface generation
- Quality assessment
Surface Modeling
Creating terrain surfaces:
- Data collection requirements
- Breakline incorporation
- Surface validation
- Accuracy assessment
- Deliverable formats
Quality Considerations
Ensuring model quality:
- Source data accuracy
- Processing methodology
- Validation procedures
- Accuracy reporting
- Metadata documentation
Key Terms
- Point Cloud: Dense collection of 3D points
- Breakline: Linear feature controlling surface shape
- Classification: Categorization of point cloud returns
Practice Questions
- What is the difference between a DTM and DSM?
- How is point cloud data processed to create a terrain surface?
Based on CalTrans LS/LSIT Video Exam Preparation Course materials.