Deforestation and ecosystem degradation levels have increased along with the extension of various conservation strategies such as protected areas (PAs). These areas are designated to protect the resources and services of the territories they cover. However, despite their importance, there are still needs acquire and generate more knowledge on the impact of protected areas on the conservation of ecosystem functions. Therefore, this research aims to estimate the effect of Pas under different management models on the conservation of vegetation health. The methodology included (I) extraction of MODIS images during the period 2000-2023, (II) Theil-Sen trend analysis, and (III) Mann-Kendall significance test. The results provide insight into PAs management’s current position on forest health, highlighting the importance of continuous monitoring.

The Amazon is abundant in water resources, but human actions such as excessive use of water, contamination of water sources, or increased demand result in decreased water availability. In this sense, the objective of the research was to evaluate the water availability of the Maracanã River watershed through the Water Security Index (WSI) and Water Balance to identify the status of water resources in the region. The methodological procedures involved the WSI analysis and the Water Balance calculation, with the support of Geographic Information Systems (GIS). The results showed that the watershed has the majority of ottobasins at maximum and high values, which means satisfactory water availability for human supply. However, the Water Balance calculation showed that the watershed presented a water deficit from September to November. The insights can support other studies and planning of the Maracanã River watershed regarding its environmental and agricultural management.

The Amazon has 25% terrestrial biodiversity, and its basin generates 16% of the planet's surface clear water. However, mining threatens this region through increasing deforestation. This study evaluated land use/land cover changes (LULC) to identify the impact of mining activities on the sides of the Punino River between 2019 and 2023. The study was divided into three stages: i) Sentinel 2 satellite image acquisition and processing in the Google Earth Engine (GEE), ii) LULC classification by extracting spectral indices and applying the Random Forest algorithm, and iii) calculation of transition arrays in ArcGIS Pro to quantify the spatial variation between classes. The results revealed alterations in the turbidity of the river channel associated with 836 hectares of newly deforested areas and 217 hectares of new mining settlements. This proposal allowed us to identify the effects of mining on the forest and river biomes of the Amazon.

Hydroelectric dams in the Upper Amazon contribute significantly to renewable energy generation. However, their construction can have negative impacts, such as altering ecosystems and displacing indigenous communities. In Ecuador, the Coca Codo Sinclair Power Plant (CHCCS) was built in 2016, but since 2020, landslides have been reported near the Coca River. This study aims to assess land use and land cover changes below the CHCCS using the Google Earth Engine platform to identify mass movements around the Coca River. This project was developed in three stages: 1) elaboration of cloud-free mosaics from Sentinel 2 satellite images, 2) classification of use and coverage of the scenario, and 3) analysis of mass movements around the Coca River. The results reveal three areas with the greatest soil alteration where the NDVI, NDSI and MNDWI indices provided to distinguish the different soil alterations.

The Ecuadorian Amazon stands out for its biodiversity and contribution to global climate regulation. However, it faces environmental challenges as a resource base for the country's development. This research aims to analyze land use and land cover (LULC) changes within an oil block using satellite imagery to identify disturbances in the forest caused by oil-related activities. Sentinel-2 satellite products were retrieved from the Google Earth Engine catalogue and categorized into five LULC classes, quantified in ArcGIS Pro. The results revealed a predominance of agricultural lands (69.62%). Nevertheless, access roads and human settlements linked to the oil industry led to the emergence of urban areas near El Coca (4.29%). Exposed soil (5.37%) corresponds to sedimentation from the Coca River linked to upstream operations at the hydroelectric plant. The present methodology is proposed as a tool for environmental assessments in ecologically sensitive areas.

Noise pollution is a variable usually ignored during urban planning; however, it is also necessary to estimate environmental values adequately in places difficult for humans to reach. This study analyzed the most accurate interpolation method for mapping urban noise levels. It used noise data collected between June and August 2021 from 40 students from the Escuela Superior Politécnica del Litoral (ESPOL). Each student in each time slot determined the equivalent continuous sound level (LAeq). The results were exported to ArcGIS Pro software to execute cross-validation and determine the best semivariogram model. Ordinary Kriging (OK) and Inverse Distance Weighting (IDW) allowed the generation of noise maps. The city's west experienced the maximum noise levels, while the minimum ones occurred at the entrance to "Via a la Costa" and the northeast. The busiest time slot was at 4:00 pm and the quietest at 8:00 pm. The results of this research allow the authorities to implement different proposals to reduce noise and its harmful effects on the health of the citizens of Guayaquil City.

The Pacific Refinery (PR) "Eloy Alfaro" is a petrochemical project for producing petroleum derivatives. The construction of this project in El Aromo, Manabí required infrastructure such as roads, water and energy supplies for operation. Therefore, it caused alterations in the tropical dry forest’s coverage and affected the region’s ecosystem services. In order to facilitate an evaluation of the PR implementation area’s impact, the study used K-means clustering of satellite images to conduct a multitemporal analysis of this area’s land cover. The research involved acquiring and processing Landsat 8 and Landsat 9 satellite images for 2016-2022 and unsupervised classification to identify land cover. Results indicated that by 2016, the tropical dry forest cover was 942.53 ha deforested and 226.01 ha degraded, associated with land movements for the refinery construction. In 2022, the deforested area corresponded to 793.45 ha and 278.97 ha degraded, impacting animal habitats, agricultural productivity, and water quality, necessitating appropriate land management.

The Yasuní National Park (YNP) is a protected area recognized by its biodiversity of flora and fauna. It corresponds to a territory that houses ancestral wealth, and in the last decades has been affected by the presence of anthropogenic activities that have altered the forest cover of the region. The present study proposes the exploration of the land cover inside the YNP during the year 2019. The study was processed in three stages. The first stage corresponds to the recollection and preparation of data using the Google Earth Engine platform, aiming to build a mosaic of Sentinel-2 satellite images. The second stage was based on the land cover classification using the Random Forest algorithm. The third stage focused on the postprocessing of the classified raster using the ArcGIS-Pro Software. The results revealed human activity taking place inside the YNP, represented by the construction of new roads, settlements, and engineering constructions.

One way that underdeveloped rural coastal regions of Ecuador can generate revenue is through international tourism. Certain conditions, however, must be met to support and sustain tourism. It can be difficult for investors to identify where to invest to have the greatest impact on tourism potential. This qualitative study design seeks to synthesize multicriteria spatial analysis with the evaluation of tourism potential in order to geographically calculate and visualize tourism potential and tourism-related development opportunities for the rural regions of Posorja and El Moro, Ecuador. The results of this study support that the locations within the study area with the highest tourism potential contain the highest level of natural tourism resources or the most developed general and tourism-specific infrastructure. This study could serve as an evaluative tool to guide the investment in the study area as a tourism zone.

The presence of the SARS-CoV-2 virus triggered a scenario never seen in Greater Guayaquil. Daily activities in the city were reduced due to measures of social isolation and mobility restrictions. In this context, a significant decrease in noise pollution was evidenced, which is a relevant social indicator of spatial economic distribution. In this study, the use of smartphones is proposed for crowdsourcing environmental noise data and generating noise maps in different time bands. During the measurement period, vehicular traffic and people's voices were identified as the main noise emitters. This article presents the experimental study with a group of students, that demonstrate the viability of crowdsourcing for the collection of environmental variables with trained citizens using smartphones.