Grid based sampling

Cluster sampling methods, which first identify a set of compound clusters, followed by the selection of several compounds from each cluster [73]. Grid-based sampling, which places all the compounds into a low-dimensional descriptor space divided into many cells and then chooses a few compounds from each cell [74]. 

In Monte Carlo Localization, the space is digitized into some random samples (k). As discussed above, multi modal representation is used because of the global localization. Because of this reason, it requires less memory and is computationally more capable. Grid-based approaches were also used, but more memory was required because of 3-D figures (Oxford, 2012). 

The aims of sampling are to establish whether eontaminants are present, their distribution and eoneentrations. Commonly-used sampling regimes inelude square grid, stratified random or simple random teehniques. Evenly-spaeed sampling points may be appropriate if the eontamination is visible otherwise judgement is required based on whether the land slopes or is flat. Samples are also taken near to the point of release. 

Figure 1.8. Histogram for sub-grid-scale distribution of

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