What should I consider when overlaying data?
Every dataset on Resource Watch has its own dedicated metadata page with information on methodology, cautions, spatial scales and dates of coverage which you should check for every layer used in an overlay. It is always good practice to ensure that the time frame and spatial scales for your overlayed datasets are compatible before analyzing the data or drawing conclusions.
Example, regarding dates of coverage: When researching a country’s progress to increase tree cover in order to meet an international agreement, you should overlay tree cover change data that reflects changes in tree cover only after the agreement was signed.
Example, regarding spatial scales: When assessing the relationship between air quality and access to electricity, a misleading overlay would include data points of neighborhood-level air quality and national statistics about access to electricity. The air quality data, which is often collected in cities, may not align spatially with the lack of access to electricity, which includes statistics from rural areas.