Bonilla Bedoya, Santiago

Preferred name

Main Affiliation

Centro de Investigación para el Territorio y el Hábitat Sostenible

Quito

santiagobonilla@uti.edu.ec

ORCID

0000-0002-2464-4500

Scopus Author ID

55360745200

Now showing 1 - 10 of 32

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A transition in the theoretical and methodological paradigms for the rehabilitation of hardened pyroclastic formations in tropical Andean landscapes
(Wiley, 2026-06-09)
Bonilla Bedoya, Santiago
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Zalakeviciute, Rasa
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Mejía‐Coronel, Danilo
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Silva, Gilson F.
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Molina, Juan R.
Introduction Global ecological restoration commitments face political, economic, and technical challenges that limit their implementation and long‐term success. Among the technical constraints, the lack of effective management and monitoring plans highlights the need for tools that support efficient and accurate spatial management of restoration landscapes. Objectives This study provides theoretical and methodological contributions to digital soil mapping (DSM) for the classification and local prediction of suitable microsites for vegetation establishment, with the aim of improving restoration efficiency in hardened pyroclastic formations ( cangahua ) of the Tropical Andes. Methods Unmanned aerial vehicles equipped with multispectral cameras were used to collect environmental data in a mountainous peri‐urban landscape dominated by cangahua . In a ravine sub‐landscape, 350 soil samples were collected at a depth of 0.15 m. Soil organic carbon (SOC) was analyzed and predictively modeled using two machine‐learning algorithms: Random Forest (RF) and Convolutional Neural Networks (CNNs). Results SOC exhibited substantial spatial variability, with minimum, mean, and maximum values of 0.69%, 2.48 ± 0.71%, and 4.33%, respectively. In DSM predictions of SOC, the CNN model showed better performance ( r 2 = 34.81%) than the RF model (out‐of‐bag error‐based coefficient of determination, r 2 OOB = 24%). The most influential variables in the CNN model were the red, near‐infrared, and blue spectral bands. Conclusions DSM proved effective for identifying spatial patterns of SOC and suitable restoration microsites in cangahua landscapes. At local scales, this approach provides valuable information on landscape structure, micro‐topography, and ecological and historical memory, improving understanding of how these factors interact to influence soil properties.
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Spatial and temporal trends of surface urban heat islands in the Andean city of Cuenca, Ecuador
(Elsevier BV, 2026-09)
Alvarez, Hermel
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Zalakeviciute, Rasa
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Bonilla Bedoya, Santiago
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Mejía C, Danilo
This study aims to assess the long-term spatio-temporal dynamics and magnitude of the Surface Urban Heat Island (SUHI) in the intermediate, high-altitude Andean city of Cuenca, Ecuador (∼2560 m a.s.l.). This research addresses a significant gap in urban climatology by analyzing the SUHI evolution over 34 years, utilizing Landsat data from 1989 to 2022. The analysis focused on the correlation between Landsat-derived Land Surface Temperature (LST) and key biophysical indices: the Normalized Difference Vegetation Index (NDVI) and the Normalized Difference Built-up Index (NDBI), which serve as proxies for characterizing surface cooling and warming mechanisms, respectively. The results confirm a strong and intensifying SUHI effect in Cuenca, characterized by a net increase of 1.28 °C in SUHI Intensity (SUHII) over the study period, rising from 4.47 °C (1989) to 5.75 °C (2022). Urban areas consistently exhibited mean temperatures 4.47–5.75 °C higher than surrounding unurbanized regions. The mechanisms driving this thermal anomaly are confirmed by strong correlations: LST exhibits a negative correlation with NDVI (R2 = 0.22 to 0.59), suggesting that vegetative cover provides evaporative cooling, while the strong positive correlation with NDBI (R2 = 0.47 to 0.59) indicates that the increase in impervious, thermally massive surfaces contributes significantly to SUHI intensification. These findings provide specific evidence for the magnitude and long-term trend of surface warming within a high-altitude Andean environment, underscoring the necessity of adopting climate-responsive urban planning measures centered on green infrastructure and surface material selection to mitigate the escalating SUHI effect in this context. Copyright © 2026. Published by Elsevier Ltd.
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From smartphones to satellites: Integrating citizen science and high-resolution environmental data for mapping plant invasions in urban mountain landscapes
(Elsevier BV, 2026-11)
Bonilla Bedoya, Santiago
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Salazar-Valenzuela, David
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Oleas Gallo, Nora Helena
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Buenaño, María Belén
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Quijano-Abril, Mario
Predicting the distribution of invasive species in urban mountain ecosystems is important for biodiversity conservation and effective management. We developed a sequential two-stage species distribution modelling framework to characterize habitat suitability for the invasive vine Thunbergia alata in the Metropolitan District of Quito and to evaluate the contribution of citizen science records, systematic field surveys, and multi-source environmental data. In the first stage, 637 iNaturalist occurrence records retained after quality control were combined with 12 bioclimatic variables from WorldClim to develop a preliminary MaxEnt model. The resulting habitat suitability map was classified into five categories and used to design a stratified field survey across the predicted suitability gradient. We sampled 1009 locations, obtaining 450 confirmed presences and 559 independent absence records. In the second stage, the field-derived occurrence data were used to develop a refined MaxEnt model incorporating the bioclimatic variables together with elevation, slope, land cover, VIIRS nighttime lights, NDVI, and the red spectral band. Environmental predictors were standardized to a common 5 m. spatial resolution and screened for multicollinearity. Both models were evaluated using receiver-operating characteristic analyses and AUC, with 10 replicate runs and 25% of occurrence records withheld for testing. Mean AUC values were 0.851 ± 0.012 and 0.902 ± 0.008 for the preliminary and refined models, respectively. In the preliminary model, habitat suitability was primarily associated with broad-scale climatic variables, particularly precipitation seasonality and temperature-related variables. In the refined model, nighttime light intensity and elevation showed the highest contributions and permutation importance, while NDVI and climatic variables also contributed to model predictions. Independent field validation showed that 47.2% of absence observations occurred in the two lowest suitability classes, whereas 33.5% occurred in areas classified as highly or very highly suitable. The refined model therefore captured substantial spatial variation in habitat suitability while also revealing areas of mismatch between predicted suitability and field observations. These results demonstrate the value of sequentially integrating citizen science, systematic field observations, and fine-resolution environmental predictors to improve invasive species mapping. This framework provides a practical approach for supporting targeted monitoring and management of invasive plants in complex urban mountain ecosystems. © 2026 The Authors.
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Tourism transport capacity under wildfire risk: A framework for highly visited protected areas
(Elsevier BV, 2026-09)
Ortega, M.
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Bonilla Bedoya, Santiago
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Molina, J.R.
Ecotourism is a major driver of rural development, particularly in natural protected areas. Existing approaches to estimating sustainable tourism capacity in these areas have focused primarily on physical, ecological, perceptual, and economic dimensions. However, these frameworks do not explicitly incorporate risks to people, vehicles, and infrastructure under wildfire scenarios. Given the global rise in large wildfires, this study develops a framework to quantify tourism transport capacity in a highly visited protected area. Tourism transport fire capacity is defined as the maximum number of vehicles permitted within a given sector to minimize wildfire exposure and potential impacts on infrastructure and assets. This capacity is determined by the interaction among structural infrastructure risk, tourism transport fire exposure, and the fire spread index. Under extreme fire spread conditions, results indicate that the number of vehicles during summer weekends should be reduced by 28–34% relative to current levels. Furthermore, when flame lengths exceed 4.3 m, 83.3% of the vegetation-free buffer strips tested in experimental burns fail to prevent impacts on infrastructure or vehicles. This study advances a risk-informed framework for integrating wildfire dynamics into tourism transport capacity assessments. The proposed approach should be incorporated into protected area management planning guidelines, in alignment with evolving fire regimes and regulatory requirements.
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Modelling the relationship between urban expansion processes and urban forest characteristics: An application to the Metropolitan District of Quito
(2020)
Bonilla Bedoya, Santiago
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Mora A., Vaca A.
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Estrella A.
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Herrera M.Á.
The rapid process of global urbanisation engenders changes in urban socio-ecological systems and in the landscape structure. However, the future processes of urban expansion in Latin American cities has been little studied even though the wellbeing of its citizens will depend on territorial management and on planning the provision of ecosystemic benefits and services. This research, considering different socio-ecological dimensions, proposed to determine the causes of potential urban expansion, analysing the dimensions and possible predictors that would explain the expansion of a high Andean city and its influence on peri-urban forest landscapes. To develop a model that integrates the complexity of the system, we used the following five dimensions: biophysics, land cover and management, infrastructure and services, socio-economics, and landscape metrics, and we opted for a binomial analysis through a spatial logistic regression model developed from 33 predictors. Considering the odd radio of the model, we observe that the independent increase in predictors, including building blocks, drinking water, sewerage, waste collection, average land size, the Interspersion and Juxtaposition Index (IJI) and Largest Patch Index (LPI), and the constant behaviour of the others predictors, would increase the probability of a potential urbanisation of the territory. Similarly, the independent increase in predictors, including the presence of protected areas, the presence of protected forests, land cover, unemployment, and the Shannon Diversity Index(SHDI), reduce the probability of the urbanisation process. Our results suggest that the territorial vulnerability from a potential urbanisation process is strongly related to an increase in infrastructure, services, and the average size of properties variables. Moreover, the landscape with the greatest potential for urbanisation presents an adequate intercalation of the different patches that compose it. However, the presence of variables such as protected areas and protective forests, in addition to monitoring indicators such as landscape diversity and mitigation strategies, could be considered to focus the analysis on the current dynamics of urbanisation processes in Latin America. © 2019 Elsevier Ltd
Scopus© Citations 31 69
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The effect of national protest in Ecuador on PM pollution
(2021)
Zalakeviciute R.
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Alexandrino K.
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Mejia D.
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Bastidas M.G.
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Oleas N.H.
Particulate matter (PM) accounts for millions of premature deaths in the human population every year. Due to social and economic inequality, growing human dissatisfaction manifests in waves of strikes and protests all over the world, causing paralysis of institutions, services and circulation of transport. In this study, we aim to investigate air quality in Ecuador during the national protest of 2019, by studying the evolution of PM2.5 (PM ≤ 2.5 µm) concentrations in Ecuador and its capital city Quito using ground based and satellite data. Apart from analyzing the PM2.5 evolution over time to trace the pollution changes, we employ machine learning techniques to estimate these changes relative to the business-as-usual pollution scenario. In addition, we present a chemical analysis of plant samples from an urban park housing the strike. Positive impact on regional air quality was detected for Ecuador, and an overall − 10.75 ± 17.74% reduction of particulate pollution in the capital during the protest. However, barricade burning PM peaks may contribute to a release of harmful heavy metals (tire manufacture components such as Co, Cr, Zn, Al, Fe, Pb, Mg, Ba and Cu), which might be of short- and long-term health concerns. © 2021, The Author(s).
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Exploring Wardriving Potential in the Ecuadorian Amazon for Indirect Data Collection
(2021)
Santos F.
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Pesantes P.
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Bonilla Bedoya, Santiago
Digital inclusion in the Ecuadorian amazon is known as a problem, which intensified with the pandemic. Since social distance is now the norm, we constructed a WiFi access point (WAP) scanner to map and analyze its data. We correlated it with ancillary geoinformation to observe its potential and limitations as a method for indirect data collection. Our result indicate that WAP correlate weakly but positively with nightlight, young population, accessibility to economical centres, and negatively with slope. Moreover, we differentiated vulnerability naming patters from Service Set Identifiers (SSDI) and differentiated the number of WAPs according to land cover for differentiate urban from rural areas. This output is now offering increasing applications to get updated rought estimates of internet activity and indirectly correlations to socio-economic conditions, technology practices, and opportunities for natural language processing. Therefore, we conclude that wardriving offer interesting opportunities for mapping social data but also concerns as an indirect data collection method. © Published under licence by IOP Publishing Ltd.
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Gradient boosting machine to assess the public protest impact on urban air quality
(2021)
Zalakeviciute R.
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Rybarczyk Y.
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Alexandrino K.
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Bonilla Bedoya, Santiago
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Mejia D.
Political and economic protests build-up due to the financial uncertainty and inequality spreading throughout the world. In 2019, Latin America took the main stage in a wave of protests. While the social side of protests is widely explored, the focus of this study is the evolution of gaseous urban air pollutants during and after one of these events. Changes in concentrations of NO2, CO, O3 and SO2 during and after the strike, were studied in Quito, Ecuador using two approaches: (i) inter-period observational analysis; and (ii) machine learning (ML) gradient boosting machine (GBM) developed business-as-usual (BAU) comparison to the observations. During the strike, both methods showed a large reduction in the concentrations of NO2 (31.5–32.36%) and CO (15.55–19.85%) and a slight reduction for O3 and SO2. The GBM approach showed an exclusive potential, especially for a lengthier period of predictions, to estimate strike impact on air quality even after the strike was over. This advocates for the use of machine learning techniques to estimate an extended effect of changes in human activities on urban gaseous pollution. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.
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Urban Air Pollution in the Global South: A Never-Ending Crisis?
(2025)
Rasa Zalakeviciute
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Jesus Lopez-Villada
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Alejandra Ochoa
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Valentina Moreno
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Ariana Byun
Among the challenges the human population needs to address are threats of global pandemics, increasing socioeconomic inequality, especially in developing countries, and anthropogenic climate change. The latter’s effect has been amplified with the arrival of 2023/24 El Niño, causing an exceptional drought in the Amazon basin, significantly affecting fire conditions and hydroelectric power production in several South American countries, including Ecuador. This study analyzes five criteria pollutants—carbon monoxide (CO), nitrogen dioxide (NO2), sulfur dioxide (SO2), ozone (O3), and particulate matter ≤ 2.5 µm (PM2.5)—during 2019–2024 in Quito, Ecuador, a high-elevation tropical metropolis. Despite long-term efforts to regulate emissions, air pollution levels continue to rise, driven by overlapping crises, including energy shortages, political unrest, and extreme weather events. The persistent failure to improve air quality underscores the vulnerability of developing nations to climate change-induced energy instability and the urgent need for adaptive, diversified, and resilient future energy planning. Without immediate shifts in climate adaptation policies, cities like Quito will continue to experience worsening air quality, with severe implications for public health and environmental sustainability.
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Forests and urban green areas as tools to address the challenges of sustainability in Latin American urban socio-ecological systems
(2020)
Bonilla Bedoya, Santiago
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Estrella A.
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Santos F.
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Herrera M.Á.
One sustainability challenge is confronting the process of global urbanization considering wellbeing and environmental justice. Integrating different disciplines to describe and analyze the relationships of urban socio-ecological systems gives us useful empirical tools to formulate policies and programs in urban planning considering their spatial dimension. The objective of this study is to present a model that integrates and explains the socio-ecological urban relations of a Latin American city considering three high-level approaches: forestry, geography, and psychology. Thus, we defined four factors: a) urban forest and green areas; b) urban spatial segregation; c) perceived restoration; and d) subjective wellbeing. For these, we grouped 16 measured variables and collected them with three specific procedures: a) SPOT remote sensors and object-based classification of urban coverage; b) analysis of geospatial data with census information; and c) field surveys. We applied descriptive multivariate statistics and also proposed a structural equation model (SEM) that integrates all the variables and data. We found that the factor “urban green areas” had a direct positive relationship with the factors “urban spatial segregation” and “perceived restoration.” We observed that urban green areas were meeting spaces between different socioeconomic categories, reducing segregation and multiplying opportunities for the psychological restoration of citizens. However, we found no evidence that green areas are related to subjective wellbeing. The model quantified the socio-ecological relationships produced by combining various factors of urban socio-ecological systems, suggesting the benefits of this method to generate knowledge towards planning and managing Latin American cities. Our results are encouraging in terms of environmental justice and wellbeing. In developing countries where forecasts indicate rising urban populations, the need to establish planning processes based on scientific information is vital to meet the challenges of sustainability in the twenty-first century. © 2020 Elsevier Ltd
Scopus© Citations 19 33

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