## 4 Discussion  
LULC changes measure the transitions of different land uses in complex interactions between humans and the physical environment [81; 82]. Analysing LULC changes helps facilitate sustainable land use planning to protect and conserve the natural habitat and resources. The present study applied available remote sensing technology to classified course land uses, similarly to what has been presented in several studies [83; 84; 23; 81; 85; 86]. The macro-classes identified were water, built-up, vegetation and bare soil. This first division allowed us to discriminate NDVI spectral indexes to improve a latter classification. Fractions of the area of study divided into macro-classes help us to observe the evolution of the city and its metropolitan area development and to explore the possible drivers forcing the changes in this initial classification. Broadly, some socio-economic factors, climate and topography were proposed as possible drivers. These drivers have also been identified as important factors for land use evolution [87; 88; 23; 89]. This paper identified that security, precipitation, climate and topography were the main drivers causing LULC changes. Measurements such as producer accuracy (PA) and user accuracy (UA) showed high confidence, since they were higher than 90% for most of the macro-classes. These values are comparable and even superior to previous studies found in literature [49; 84; 89; 90]. One can observe that the maximum likelihood classifier (MLC) is a suitable classification method to obtain acceptable results, as cited by several scientific contributions [34; 35; 58]. After the analysis of the macro-classes, 14 classes were exhaustively found to analyze and identify the land use in detail. Among those classes, some discussions are driven. Industry has experienced no change since the last petrochemical complex opened in 2015. Commercial areas have declined and residential zones present a slow increment due to the above-mentioned socio-economic drivers, which served to confirm the proposed hypothesis. Mixed forest and bare surfaces with low vegetation density tended to increase in surface area because reforestation programs and vegetation implemented in the coastline by the government have been a priority, as wind erosion has provoked much damage to the city's infrastructure [91]. Swamps (i.e., wetlands) also showed an important decrease in spatial contribution, losing about 2 km\({}^{2}\). This, in turn, might become an important environmental issue, since swamps are seen as important regulators of water pollution, carbon storage and habitat of species [92; 93; 94; 95]. For that reason, actions need to be considered to avoid the continuous degradation of local wetlands and swamps. Additionally, it was observed that about 80% of the bare surface areas came from sparse vegetation and grassland areas. Associated changes in precipitation and high temperatures throughout the assessment period were responsible for these changes, as shown in results section. As a result of increments of bare surfaces, infiltration decreases and overland flow is exacerbated because soil properties such density, porosity and hydraulic conductivity depend on the level of established vegetation [96; 97]. Lastly, a LULC transition matrix reflected the changes in surface area for each of the classes identified in this study. This is the baseline for future research that involves local problems in the city of Coatzacoalcos. A subsequent prediction of the land use using more extended spatial information of the drivers forcing the changes observed here will be proposed as an extension of this work. Additionally, the city is facing an issue with the relocation of solid residues, which naturally correlated with the actual land use. As a result, this study and methodology using higher-resolution imagery (i.e., sentinel satellite) help to study possible and suitable landfill sites.