10.4.3 - Inverse Distance Weighting Method (IDW)
Enroll to start learning
You’ve not yet enrolled in this course. Please enroll for free to listen to audio lessons, classroom podcasts and take practice test.
Practice Questions
Test your understanding with targeted questions
What is the main purpose of the Inverse Distance Weighting Method?
💡 Hint: Think about why geographic distance matters.
Explain why IDW uses distance squared in its formula?
💡 Hint: What happens to weight when distance increases?
4 more questions available
Interactive Quizzes
Quick quizzes to reinforce your learning
What is the primary benefit of using IDW?
💡 Hint: Remember how distance affects the influence of station data.
IDW may not function well in regions with significant what?
💡 Hint: Think of areas with hills, valleys, or varied elevations.
2 more questions available
Challenge Problems
Push your limits with advanced challenges
You have rainfall data from three stations; A (30mm, 1km), B (60mm, 5km), and C (80mm, 3km). Estimate rainfall at a new station using IDW. Explain your calculations.
💡 Hint: What does the IDW formula tell you about weighting?
Consider a scenario where you have a missing rainfall reading at a station surrounded by six others. After applying IDW, you notice the estimate is significantly lower than expected. Discuss the possible reasons.
💡 Hint: What external factors could distort data readings?
Get performance evaluation
Reference links
Supplementary resources to enhance your learning experience.