The Inventory
Previous criteria and considerations. All kinds of possible means, which will begin with a compilation of existing information (which will be analyzed to determine its quality, intrinsic, own data, both external, if they are oriented more or less to our needs) will be used and which are to be complemented by field visits, interviews with experts and/or sampling of variables that we try to introduce into the inventory. The scale of the work has been of be more or less standardized (insofar as possible) and cartografiable. For all variables ideally have a same scale to be able to superimpose a few items with others. The scale of work is somehow determined by budget and deadlines we have to deliver the work and carry out the project, although it is sometimes possible to determine these after the selection of the scale. It is important that this first analysis we detect the elements and factors more delicate and significant for the EIA through the means already mentioned.
Environmental inventory variables. The selection of the variables of the inventory (that we should not forget, they have to be the most significant factors and that they may be subject to alteration due to the project), has to meet the following conditions: significance. The variables have to be significant for our study. Operability. The variables have to be easily usable and integrated into the survey process (in this sense we can classify the variables into two types: those which) they are the result of integrating other simpler and those that are self-explanatory). Ease of obtaining the data. Precision.
It should take into account what degree of accuracy we can achieve insofar as the variables that they fall within the inventory. Modelizable. Although it is not a very common feature within the variables that are usually handled, the knowledge of the functioning of the system (which, ultimately, is what interests us in this phase) can transform into the possibility of predicting the future behavior of the same with greater or lesser reliability (hence the importance of precision in our measurements).