Survey Errors – Understanding Systematic Errors in Field Measurements Which statement best characterizes systematic errors in surveying observations and instruments, in contrast to random (accidental) errors?

Introduction:
Error analysis is central to reliable surveying. Systematic errors differ fundamentally from random errors: they follow known laws and hence can often be modeled and corrected. Identifying this distinction guides calibration, observation procedures, and error budgeting in traverse, levelling, and angle work.

Given Data / Assumptions:

• Survey observations include random and systematic components.
• Examples: tape length error, collimation error, refraction, temperature expansion.
• Goal: select the most accurate characterization of systematic errors.

Concept / Approach:

Systematic errors have a known or knowable cause-and-effect relation (predictable sign and approximate magnitude). Because their behavior is understood, they are amenable to prevention (instrument adjustment) or correction (mathematical compensation). Random errors, by contrast, are unpredictable in sign and magnitude for individual observations but follow statistical laws collectively.

Step-by-Step Solution:

Verification / Alternative check:

Calibration reports (e.g., tape standardization) quantify systematics via constants and coefficients, confirming their predictable nature and enabling corrections.

Why Other Options Are Wrong:

(a) contradicts the essence of systematic errors; (c) is often true but describes a consequence rather than the defining trait—definitionally, “predictable/understood character” is primary; (e) describes random errors, not systematic ones; (d) is invalid.

Common Pitfalls:

Defining by effect (cumulative) rather than by cause (predictable law); assuming systematics always vanish without explicit correction.

Final Answer:

Errors whose character is understood (predictable behavior)