*3.1. Segmentation Accuracy*

The average values of the Scale and the ED2 were 25 and 0.45, respectively (Table 2). The most precise segmentations were from 1977 and 2016, with a Scale of 20 and an ED2 of 0.35 in both. The least accurate segmentations were the ones of 1956 and 2004, with ED2 values of 0.59 and 0.51, respectively. The lowest RMSE was obtained in the image of 2016, with a value of 46.38 m<sup>2</sup> and an MBE of −6.36 m2, overestimating the cover area of the shrubs. The highest RMSE was up to 120.64 m2, and in 5 of the 8 years (1956, 1977, 1997, 2004, and 2008) the area of the shrubs was underestimated as indicated by the MBE. With a computation time of 20 s per segmentation, we spent 36 h for a total of 6480 segmentations.



#### *3.2. Classification and Characteristics of Ziziphus lotus Shrubs*

The analysis of class separability and threshold with the SEaTH algorithm showed that the best features for discriminating between classes (i.e., those with the highest separability) were mainly related to texture (i.e., the family of features related to the Gray-Level Co-Occurrence Matrix (GLCM)) and brightness of objects (Table 3).


**Table 3.** Features used in the classifications and separability between them using the separability and threshold (SEaTH) algorithm. In bold, the two features for each year with the highest separability used to classify the images.

All the classifications were highly accurate, with values of OA and KIA close to 1 (Table 4). The most accurately segmented image (OA = 0.98; KIA = 0.97) was the image of 2004, whereas the worst one was the image of 1956 (OA = 0.89; KIA = 0.79).

**Table 4.** Error matrix of all the classified images in the study. Z, *Ziziphus lotus*; S, Bare soil with sparse vegetation patches; Uncl., Unclassified; Prod., Producer's accuracy; User, User's accuracy; Held, Helden; KIA-c, KIA per class; AO, Overall accuracy; KIA, Kappa index of agreement. Highest (best) KIA values for Z (*Z. lotus*) and S (Bare soil) classes are highlighted in bold type.



**Table 4.** *Cont.*

#### *3.3. Shrub Number, Area, and Shape Dynamics*

During the 60-year period evaluated, the number of shrubs decreased by 742. The moment of highest shrub population was 1977, with 2625 shrubs. Conversely, the lowest number of shrubs was detected in 2016, with 1883 shrubs (Table 5). However, the total shrub area between 1956 and 2016 increased by 3692 m2. In addition, we observed an increase in the maximum cover area value of shrubs after 1997. Finally, the most circular shrubs appeared in 1956 (i.e., the lowest values of the round shape index) and the high values of the round shape index increased over the years (Table 5).

**Table 5.** The number of shrubs detected each year and their cover-related average statistics. The highest number of bushes, the maximum area, the total cover area, and the lowest (best) round shape index are highlighted in bold type.


In general, the cover area of shrubs between pairs of years showed an increase, with a trend of smaller individuals to lose more cover area than larger shrubs. In the period 1984–1997, 1423 shrubs reduced their cover area. In the period 1977–1984 (Table 6), 1650 shrubs increased their cover area.

**Table 6.** Change of cover and frequency of the difference in *Ziziphus lotus* area in the studied years (1956–2016). The negative and positive areas are the result of the subtraction between the year and its predecessor. The highest lost area, the largest positive area, the balance between greater areas, the positive frequency and the negative frequency of shrubs are highlighted in bold type.


*3.4. Sand Extraction Mapping and Curvature Analysis*

The results of the analyses indicated that more than 187 m<sup>3</sup> of sand were extracted in the study area (4.2 km2). According to [30], a visual analysis of resulting maps also suggested that sand extractions were distributed spatially following a connected network and following existing roads in the area (Figure 2).

**Figure 2.** Sand extraction areas and differences of cover areas of *Ziziphus lotus* shrubs in the 1956–1977 period, when massive sand extractions took place in the study area. In red are shown negative areas, in green, positive areas, and in black, shrub loss. Spatial coordinate system, WGS84/UTM Zone 30 N.

#### *3.5. Spatial Relationships of Shrubs with Sand Extractions, Coastline (Seawater Intrusion), and Protected Area*

Between 1956–1977, 752 shrubs reduced their cover area in the sand mining event. The AMD between the shrubs and the zones of sand extractions presented an average minimum distance of 25.57 ± 37.49 m. The ARD analysis showed an average minimum distance of 127.48 m ± 23.68 m between the random simulated shrubs and the zones of the sand extractions (Figure 2).

Seawater intrusion (1977–1984) reduced the cover area by 903 shrubs. The AMD analysis showed an average minimum distance of 681.32 m ± 50.15 m to the coastline. The ARD analysis showed an average minimum distance of 882.67 m ± 57.66 m between the random simulated shrubs and the coastline (Figure 3).

**Figure 3.** Differences of cover areas of *Ziziphus lotus* shrubs in the 1977–1984 period, when massive groundwater withdrawals took place in the study area. In red are shown negative areas and in green, positive areas. Spatial coordinate system, WGS84/UTM Zone 30 N.

In the period 1984–2016, 551 individuals were lost (Figure 4), but in the area there was a total gain of more than 23 m<sup>2</sup> (Table 5), coinciding with the protection of the study zone under the Cabo de Gata-Níjar Natural Park.

**Figure 4.** Differences of cover areas of *Ziziphus lotus* shrubs in the 1984–2016 period, when the area was protected under the Cabo de Gata-Níjar Natural Park. In red are shown negative areas, in green, positive areas, and in black, shrub loss. Spatial coordinate system, WGS84/UTM Zone 30 N.
