Extended Literature Review

General

In this section a more in depth literature review on the specific subject of reforestation after forest fires is done to assess whether or not a robot is a desirable artifact to be created for such a purpose. Several aspects are investigated including but not limited to biodiversity, need for controlled seeding, effectiveness of current methods, costs of current methods. General information about the project can be found at PRE2017 4 Groep6.

Current methods of reforestation

Aerial seeding

Aerial seeding is perhaps the most novel method for reforestation among the other options, which have generally existed for many centuries. Its main premise is a reduction in labour, as seeds can be sown at a much higher rate than manual seeding could ever produce and time-effectiveness, as an airplane can easily cover an area of several hectares at a much quicker rate than manual seeding using volunteers. However the question remains if this method is truly beneficial in case of actual saplings it produces and the costs it inherently carries, considering an aircraft of several metric tons needs to be lifted in the air burning kerosine and enormous amounts of seeds are spread. Contrary to intuitive belief aerial seeding is in most cases not a standalone method, in order to be effective more often than not some preliminary ground work is required to prepare the area to be seeded (in terms of boosting the receptiveness of the ground to the dropped seeds) (Régnière, 1982) . A very crude probabilistic model, taking into account two classes of possible areas (highly receptive due to site preparation or natural levels) and a constant occupation of highly receptive area per unit of area exists <ref name="probability model">, which reveals that higher seeding rates do in general lead to more saplings, however the relation is only linear in the case of pure natural occupation. If the site is prepared and occupation rates become higher, the relation between the number of saplings per unit approaches more or less rooted relationships. This model further reveals that the variance of the pattern in saplings per unit area severely depend on the width between airplane runs, with lowest variance only occurring at 1 meter distances. However, for each and every combination of width between airplane runs and seeding density a minimum in variance exists to create an optimal balance between the two. Using a purely random (obtained by uniform seeding density created by narrow spacing) seed distribution as a measure for maximum obtainable sapling rate, it was found that the efficiency of a real process with a limited spacing decreases rapidly as the spacing becomes larger, although there is a compensating effect for higher seeding rates, albeit the amplitude of this compensation is much smaller than the amplitude of the decrease in efficiency at wider spacing. Very counterintuitive, for equal spacing between the airplane runs, the efficiency of the process first drops to a minimum of 88% after which it slowly increases for larger seeding drop densities, meaning that more does not necessarily mean better, unless ridiculous amounts of seeds are used.