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Spatial sampling in data collection and impact assessment: overview and recent MELIA applications

This Learning Note introduces spatial sampling as an approach to strengthen data collection and impact assessment in contexts where location and spatial relationships influence outcomes. It provides an overview of key spatial sampling methods and illustrates their application in recent MELIA work to...

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Main Authors: Chepsiror, Calvin, Song, Chun, Berti, Lorenzo
Format: Brief
Language:Inglés
Published: Bioversity International and International Center for Tropical Agriculture 2025
Subjects:
impact assessment
data collection
spatial data
quantitative analysis
policy analysis
random sampling
stratification
Online Access:https://hdl.handle.net/10568/176976
Summary:This Learning Note introduces spatial sampling as an approach to strengthen data collection and impact assessment in contexts where location and spatial relationships influence outcomes. It provides an overview of key spatial sampling methods and illustrates their application in recent MELIA work to ensure more rigorous, representative, and spatially consistent evaluations of agricultural and climate interventions.

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