The results obtained allow us to calculate the extension of urban light intensity in terms of both space and time. With respect to space, the first result presented below is a general overview of the surface area that presented light levels, in all the 86 districts that comprise the studied territory. This is complemented by an analysis of the mean light levels displayed by each district. There follows an examination of light intensity in terms of time, with a special focus, as mentioned above, on the Balearic Islands, one of the regions with the most notable seasonal variations in this respect.
3.2. Light Intensity in Terms of Time
One of the main features of the contemporary urbanization process is the fact that its dynamics tend not only to embrace an entire region, to a greater or lesser extent, but also reflect notable variations in time of the uses that characterize it. Thus, the intensity of the urbanization process varies not only in space but also in time. Despite their limitations, nighttime satellite images of the Earth offer an innovative means of observing this phenomenon, as demonstrated below by an examination of the seasonal evolution of light on the Balearic Islands and the Pitiüses.
Any analysis of seasonal variations in brightness obviously requires an indicator that measures the amounts of light emitted by each territory at various times of the year, thereby providing a basis for intra- and inter-territorial seasonal comparisons. In our case, this indicator is provided by the images of the mean monthly composites for each of the nine months available, and the variable used will be what is known as the total emitted light, also used by authors like [27
]. This is the sum of the light values (radiant intensity) for each area/territory multiplied by its surface area and thus covers both the lit surface area and the light level, making it possible to compare a single territory on a seasonal basis, as the result obtained indicates the total light total emitted per district. In order to facilitate comparisons between different seasons and between different territories, the mean value of the light emitted by each of the latter will be correlated via an index of 100 (Figure 7
and Figure 8
). In this case we have considered brightness values above 2 nW/cm2
/sr in order to obviate any noise from the instrument itself, as explained in, for example, [27
]. Although the threshold of urban intensity enables us to differentiate intensities as regards land use, it does not take into account any settlements with lower intensity. In this exercise our concern is to use light to measure the activity of the human presence in the territory as a whole.
The usefulness of this exercise is particularly well demonstrated by its application to a territory such as the Balearic Islands. It is well known that, in territorial terms, these islands are characterized by both the vigor of by their urbanization process [34
] and their striking seasonal variations in activity and population as a result of tourism [38
]. An analysis of the total emitted light clearly reveals the intensity and variability of both these phenomena, although it must be stressed once again that the lack of data for the months of May, June and July, as explained above, represents a significant obstacle to a seasonal analysis of light using our source.
The results show that the average total light emitted in the various months of the year falls below the mean in the period from October to March but is well above it from April to September. This pattern obviously reflects the seasonal nature of the economic activities connected to the islands’ tourism. Nevertheless, the contrasts in light emission are not as marked as in other variables, as we shall see in more detail below. This suggests, in the first instance, a possibility that the seasonal increases recorded in some territories are compensated by greater stability in others.
It is useful to verify these results by analyzing the differentiated behavior of the various areas of the Balearic territory (islands and districts) with respect to the whole. Thus, the ten areas under consideration can be divided into three groups, according to their seasonal behavior. First, the most numerous group would comprise the islands of Formentera, Eivissa and Menorca, as well as the areas of Nord, Llevant, and Sud in Mallorca. These areas, with behavior that would most closely reflect seasonal tourism, are characterized by very high values on the 100 index from April to September and lower ones from October to December. Overall, we could classify them as districts marked by tourism. This seasonal behavior contrasts with the relative stability of the Badia de Palma, the biggest urban hub in Mallorca. Finally, a third group, comprising mountains and the interior of Mallorca—Raiguer, Tramuntana, and Pla—present a more erratic behavior. The following figure shows three examples of this contrasting seasonal behavior.
The tendency of certain territories to give off more light in the summer months of tourist activity is thus verified, as it has been in other Mediterranean islands, but it would also be interesting to establish the sensitivity of the fluctuations in brightness to the seasonal nature of the activity, for a similar case on some Greek islands, see [33
]. This involves contrasting the evolution of the data obtained from the nighttime satellite images with specific socioeconomic indicators.
To do this, we have collated the variations in the number of workers affiliated to the Social Security, as these are registered on a monthly basis on a municipal scale. On the basis of data supplied by the Ministry of Labor and Social Security on workers signed up with the Social Security on the final days of each month in 2017. It should be noted, however, that although the data on Social Security affiliation cover all workers on a monthly basis, the municipalities in which they are recorded correspond to their employers’ contribution center, which in many cases does not physically coincide with the location of their workplace. This would be the case, for example, when a hotel chain has a single provincial contribution center in which all its workers are registered, even though they are spread over hotels in various municipalities within a province. Despite this limitation, a comparison between this variable and nighttime brightness proves to be of value, as we shall see.
To make this comparison, we first grouped together all the affiliated workers from all the municipalities in each of the areas (islands and districts) used in the brightness analysis for all the months of 2017 for which data on nighttime brightness were available. We then calculated the differences in the 100 index in each district with respect to the mean number of workers in these 9 months. An examination of the districts and their relationship with the affiliated workers shows that for the islands as a whole this is 0.689. A more detailed analysis, in line with the typology of the areas studied above, shows that areas with the most intense tourist activity present an even more significant relationship (0.8507) (Table 3
Despite this clear relationship, however, the variations in brightness are considerably less marked than changes in occupation (Figure 9
). Whilst there are only 16 points (in indexed numbers) separating the months with the most and least brightness, the monthly difference in terms of affiliated workers is 60 points. Brightness is therefore sensitive to seasonal variations but it is also subject to great inertia over the course of the year. This lack of precise correlation between the intensities of light and activity is, we believe, a very significant finding, with respect to both analytical procedures and energy and environmental policies.