Managing hybrid methods for integration and combination of data

This chapter looks at how monitoring can combine data from multiple sources, including basic observations coupled with auxiliary information and the use of reference data for classification and modelling. A vital component of monitoring research is to be able to combine and synthesize data in a systematic, transparent way that can integrate social and environmental factors and show how these reflect, overlap with, correlate to, and influence each other. Data types and relevant analytical methods are briefly discussed, as well as aspects of classification and semantics, showing best practice in analysis and some suitable methods for describing data properties such as data quality. Typical problems of incompleteness, lack of fit to semantic classes, thematic and geometric inaccuracy, and data redundancy are discussed, with a range of examples showing how these challenges can be met by identifying and filling gaps in datasets