Question

Kriging differs from Inverse Distance Weighting (IDW) interpolation because it:

• A. Works with raster data
• B. Uses spatial autocorrelation
• C. Ignores spatial relationships
• D. Ignores spectral analysis

Hint:

Easy comparison: \[ \boxed{ \begin{aligned} \text{IDW} &\rightarrow \text{Distance only} \text{Kriging} &\rightarrow \text{Distance + Spatial Autocorrelation} \end{aligned} } \]

Answer 1

The Correct Option is B

Concept:

Both Kriging and IDW are interpolation methods used to estimate unknown values from nearby observations.

The major difference is that Kriging uses the statistical concept of spatial autocorrelation through a variogram, whereas IDW assigns weights only based on distance.

Step 1: Understand IDW.

IDW estimates values using:

\[ w_i=\frac{1/d_i^p}{\sum (1/d_i^p)} \]

where nearby points receive higher weights.

Step 2: Understand Kriging.

Kriging considers both:

• Distance between observations.
• Spatial autocorrelation (variogram).

Thus, it generally provides statistically optimal estimates.

Step 3: Compare the methods.

\[ \begin{array}{c|c} \textbf{IDW} & \textbf{Kriging} \\ \hline \text{Distance-based} & \text{Distance + Spatial autocorrelation} \\ \text{Deterministic} & \text{Geostatistical} \\ \text{No variogram} & \text{Uses variogram} \end{array} \]

Hence, Kriging differs from IDW because it uses spatial autocorrelation.

Therefore, the correct option is (B).