Question

Which of the following is the best technique for monitoring urban sprawl?

• A. Theodolite surveys
• B. Multi-temporal image analysis
• C. Hyperspectral imaging
• D. Topographic surveys

Hint:

Sprawl Monitoring Principle: Sprawl is a dynamic process defined by two factors—large geographic spaces and time transitions. To measure it effectively, you need Multi-temporal (cross-time) satellite Images to visualize changes across vast regional landscapes instantly.

Answer 1

The Correct Option is B

Concept: Urban sprawl is the uncoordinated, outward expansion of a city across rural land peripheries over time. Monitoring sprawl requires analyzing macro-scale land changes across vast geographic expanses over specific historical timelines.

Step 1: Understanding Multi-temporal Image Analysis.
Multi-temporal image analysis involves gathering satellite or aerial remote sensing imagery of the exact same geographic region captured at different points in time (e.g., comparing spatial data from 2000, 2010, and 2020). \[ \Delta \text{Built-up Area} = \text{Image}_{t_2} - \text{Image}_{t_1} \] By applying automated pixel classification algorithms (such as NDVI or built-up index mappings), urban geographers can isolate where green fields converted into built asphalt or concrete structures. This allows planners to measure the velocity, direction, and structural shape of outward urban expansion.

Step 2: Evaluating the alternative options.
Let us review why the alternative choices are inefficient for monitoring regional sprawl:
• Theodolite Surveys Topographic Surveys: Traditional ground-based land surveying techniques. While highly accurate for mapping specific boundary layout lines or elevations for a single construction project, their high cost and slow progress make them impractical for tracking macro-scale growth across hundreds of square kilometers.
• Hyperspectral Imaging: Records hundreds of narrow, contiguous spectral bands to identify specific chemical compositions, plant diseases, or mineral types. While technologically advanced, it provides unnecessary spectral detail for tracking standard built-up land changes, which are easily monitored using more common, accessible multi-spectral imagery. Consequently, multi-temporal image analysis serves as the most effective method for tracking regional urban sprawl over time.