The International Daylight Measurement Programme will generate a large amount of data from distinct locations worldwide. To ensure comparability of results, data must be identified uniquely and standardisation of data analysis including the determination of derived quantities is necessary. A number of formulae are proposed for the normalisation and analysis of direct beam, global and diffuse irradiances and illuminances and sky luminance distributions. Graphical representation of results is discussed and a graphical approach, the P-G-D diagram, is put forward as a solution for irradiance and illuminance data presentation.

One of the tasks in sky modelling is the determination of the location and amount of cloud coverage in the sky. Analysis using digital camera systems is possible but requires an automated method of separating sky images into clear sky and cloud regions. Two segmentation approaches have been used in this research, one based purely upon the colour characteristics of sky regions, the other a neural network approach using a wider range of variables. A convolution technique was developed to reduce classification errors prior to defining cloud outlines using polylines. Sensitivity analysis shows that this can be carried out efficiently with little loss of accuracy.

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The International Daylight Measurement Programme has stimulated wide research in daylighting measurement analysis and modelling, however there are deficiencies in all these areas. Data collection, especially, is still limited geographically and some variables, such as cloud cover and distribution, have proved difficult to measure and have, consequently, largely been ignored. Furthermore, data that has been collected has limitations on its accuracy that does not appear to have been factored into much analysis and model building. This paper discusses errors associated with techniques of data gathering and measurement accuracy with examples. The extension of daylight measurement in tropical regions will not be immune from these potential sources of error even with superficially static daylight climates.

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