I have been working on the Flood susceptibility modelling and also have identified, collected and generated data of around 26 controlling factors(indicators). Furthermore, i'm going to put them into RF ML model in Arc GIS pro for the zonation. So, should i re-scale all the data to one scale (30m) or it will work fine otherwise?
Not an ArcMap user here but hope this helps...
Yes it is usually best practice to re-scale your data to a suitable resolution for this kind of analysis, however you need to be aware that re-scaling essentially changes your data. There are a number of different re-scaling algorithms (the Resample tool in ArcMap has nearest neighbor, bilinear, cubic interpolation, or majority).
Upon further reading, ArcMap doesn't require the user to resample the rasters because it will do it automatically when needed using tools from the Spatial Analyst extension. Although it does recommend the user does it because you have more control:
Different raster datasets do not need to be stored using the same cell resolution. But when you are processing between multiple datasets, the cell resolution, like the registration, ideally should be the same. When multiple raster datasets are input into any ArcGIS Spatial Analyst extension tool and their resolutions are different, one or more of the input datasets will be automatically resampled to the coarsest resolution of the input datasets.
In the default case, the nearest neighbor assignment resampling technique is used. This is because it is applicable to both discrete and continuous value types, while the other resampling types—bilinear interpolation and cubic convolution—are only applicable to continuous data. A resampling technique is necessary because rarely do the centers of the input cells align with the transformed cell centers of the desired resolution. The bilinear and cubic techniques can be applied using the Resample tool as a pre-processing step before combining rasters of different resolutions.