Bonilla Bedoya, Santiago
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Bonilla Bedoya, Santiago
Main Affiliation
Quito
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santiagobonilla@uti.edu.ec
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55360745200

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Publication

Central parks as air quality oases in the tropical Andean city of Quito

2024 , Zalakeviciute R. , Bonilla Bedoya, Santiago , Mejia Coronel D. , Bastidas M. , Buenano A. , Diaz-Marquez A.

Urban ecosystem is an intricate agglomeration of human, fauna and flora populations coexisting in natural and artificial environments. As a city develops and expands over time; it may become unbalanced, affecting the quality of ecosystem and urban services and leading to environmental and health problems. Fine particulate matter (particulate matter with aerodynamic diameter ≤2.5 μm - PM2.5) is the air pollutant posing the greatest risk to human health. Quito, the capital city of Ecuador, exhibits a high occurrence of exposure to unhealthy levels of PM2.5 due to a combination of natural and social variables. This study focused on three central parks of this high elevation city, investigating the spatial distribution of PM2.5 concentrations. The particle pollution was then modeled using Normalized Difference Vegetation Index (NDVI). Hazardous instantaneous levels of PM2.5 were consistently found on the edges of the parks along busy avenues, which are also the most frequented areas. This raises concerns about both short- and long-term exposures to toxic traffic pollution in recreational areas within urban dwellings in the global south. The NDVI model successfully predicted the spatial concentrations of PM2.5 in a smaller urban park, suggesting its potential application in other cities. However, further research is required to validate its effectiveness. © 2024 The Authors

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Calculating minimum safety distance against wildfires at the wildland-urban interface in Chile and Spain

2022 , Castillo Soto, M.E. , Molina Martínez, J.R. , Bonilla Bedoya, Santiago , Moreno García, R.A.

Wildfires in the urban-forest interface constitute a civil protection emergency, causing considerable personal injury and damage to properties. The potential impacts of wildfires on buildings can be minimized by reducing the surrounding fuel and the use of structural materials with low flammability. However, the costs associated with implementing these actions and the responsibility for maintenance usually present conflicts with the property owners. This study aimed to identify minimum safety distances in wildland-urban interfaces within priority areas. The priority areas were identified based on the integration of fire risk and fuel hazard. Radiant heat is a variable in the behavior of fire that directly influences the definition of safety distances. In this research the radiant heat transfer was calculated based on the potential fire behavior for each study area. A comparative study of the horizontal heat transfer method and the radiant heat flux model was carried out. The horizontal heat transfer method indicated the highest vegetation-free distances, ranging from 23 m to 32 m. Some safety distances were validated using experimental fires and wildfires. The findings from the experimental fires and wildfires emphasize the need for a progressive fuel load reduction to mitigate radiant heat transfer. This may include both the removal of surface fuel and removal of trees to mitigate against crown fires. Our findings provide relevant information for decision-making on the effectiveness and efficiency of safety distances at the wildland-urban interface. © 2022 The Author(s)

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Sentinel satellite data monitoring of air pollutants with interpolation methods in Guayaquil, Ecuador

2023 , Mejía C. D. , Alvarez H. , Zalakeviciute R. , Macancela D. , Sanchez C. , Bonilla Bedoya, Santiago

In Ecuador, there is a limitation on air quality monitoring due to the cost of monitoring networks. Although air quality monitoring stations are instruments for air measurement, they do not cover an entire city due to their scope. Satellite remote sensing is now an effective tool to study atmospheric pollutants and has been applied to continuously assess a region and overcome the limitations of fixed stations. Despite the application of satellite data for air quality monitoring, there are some limitations, such as measurement frequency, cloud cover and wide spatial resolution, which do not allow the assessment of air pollution in cities. Therefore, downscaling, applying interpolation methods, is essential for continuous air quality monitoring at smaller scales. For this research, Nitrogen Dioxide (NO2) data from the Sentinel-5 satellite percussor was used in the city of Guayaquil for January–December 2020, which is considered before, during and after the COVID-19 quarantine. This mid-size port city does not have a permanent monitoring network, which prevents us from knowing the air quality. Due to the limitation of pixel size, this study used satellite data to apply interpolation techniques and reduce pixels to assess air quality. Two categories of interpolation were selected: deterministic and stochastic. The empirical Bayesian kriging (EBK) interpolation obtained a R2 of 0.9546, which was superior to the other methods applied. Therefore, the EBK method had the best accuracy for tropospheric NO2 concentration. Finally, the method used in this research can help monitor air quality in cities lacking continuous monitoring networks, as the reduction of the pixel size gives us a better pattern of pollutants. © 2023 The Authors

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Exploring Wardriving Potential in the Ecuadorian Amazon for Indirect Data Collection

2021 , Santos F. , Pesantes P. , 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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Socioecological system and potential deforestation in Western Amazon forest landscapes

2018 , Bonilla Bedoya, Santiago , Estrella-Bastidas A. , Molina J.R. , Herrera M.Á.

The ecosystem services provided by tropical forests are affected by deforestation. Territorial management strategies aim to prevent and mitigate forest loss. Therefore, modeling potential land use changes is important for forest management, monitoring, and evaluation. This study determined whether there are relationships between forest vulnerability to deforestation (potential deforestation distribution) and the forest management policies applied in the Ecuadorian Amazon. Proxy and underlying variables were used to construct a statistical model, based on the principle of maximum entropy that could predict potential land use changes. Entropy can be seen as a measure of uncertainty for a density function. Receiver operating characteristics (ROC) analysis and the Jackknife Test were used to validate the model. The importance of input variables in the model was determined through: Percent Contribution (PC) and Permutation Importance (PI). The results were compared with prevailing regional forest management strategies. The socioeconomic variables that provided the largest amount of information in the overall model (AUC = 0.81) and that showed most of the information not present in other variables were: “Protected areas-Intangible zone” (PC = 24%, PI = 12.4%), “timber harvesting programs” (PC = 21.7%, PI = 4.7%), “road network” (PC = 18.9%, PI = 7.7%), and “poverty rate” (PC = 3.7%, PI = 6.1%). Also, the biophysical variable “temperature” (PC = 7,9%, PI = 22.3%) provided information in the overall model. The results suggested the need for changes in forest management strategies. Forest policies and management plans should consider integrating and strengthening protected areas and intangible zones, as well as restricting timber harvesting in native forest and establishing forest areas under permanent management. Furthermore, the results also suggested that financial incentive programs to reduce deforestation have to be evaluated because their present distribution is inefficient. In this context, conservation incentive plans need to be revised so that they focus on areas at deforestation risk. © 2018 Elsevier B.V.

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Urban soils as a spatial indicator of quality for urban socio-ecological systems

2021 , Bonilla Bedoya, Santiago , López-Ulloa M. , Mora-Garcés A. , Macedo-Pezzopane J.E. , Salazar L. , Herrera M.Á.

The development of criteria and indicators to quantify the transition to sustainability of the urban socio-ecological systems quality is determinant for planning policies and the 21st century urban agenda. This study models the spatial variation in the concentration and distribution of some macronutrients, micronutrients, and trace nutrients in the soil of a high-altitude city in the Andes. Meanwhile, machine learning methods were employed to study some interactions between the different dimensions that constitute an urban socio-ecosystem that caused these variations. We proposed a methodology that considered two phases: a) field work to collect data on 300 soil samples; laboratory analysis to measure the concentrations of 24 macronutrients, micronutrients, and trace nutrients; and the design of geophysical, spectral, and urban co-variables; b) statistical and geo-informatics analysis, where multivariate analysis grouped the elements into factors; and, machine learning integrated with co-variables was applied to derive the intensity of each factor across the city. Multivariate statistics described the variation in soil co-concentrations with a moderate percentage (42%). Four factors were determined that grouped some of the analyzed elements, as follows: F1 (Zn, S, Cu, Pb, Ni, and Cr), F2 (Ba, Ag, K, In, and Mg), F3 (B, V, Li, and Sr), and F4 (Si and Mn). The percentage R2 out-of-bag of the spatial model were: F1 = 20%, F2 = 8%, F3 = 14%, and F4 = 10%. Our outputs show that the enrichment and contamination by anthropogenic factors, such as the increase in population density, land use, road network, and traffic generated by fossil fuel vehicles, should be prioritized in urban planning decisions. © 2021

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War Impact on Air Quality in Ukraine

2022 , Zalakeviciute, R. , Mejia, D. , Alvarez, H. , Bermeo, X. , Bonilla Bedoya, Santiago , Rybarczyk, Y. , Lamb, B.

In the light of the 21st century, after two devastating world wars, humanity still has not learned to solve their conflicts through peaceful negotiations and dialogue. Armed conflicts, both international and within a single state, still cause devastation, displacement, and death all over the world. Not to mention the consequences that war has on the environment. Due to a lack of published research about war impact on modern air quality, this work studies air pollution evolution during the first months of the Russian-Ukrainian conflict. Satellite images of NO2, CO, O3, SO2, and PM2.5 over Ukrainian territory and PM2.5 land monitoring data for Kyiv were analyzed. The results showed that NO2 and PM2.5 correlated the most with war activities. CO and O3 levels increased, while SO2 concentrations reduced four-fold as war intensified. Drastic increases in pollution (especially PM2.5) from bombing and structural fires, raise additional health concerns, which might have serious implications for the exposed local and regional populations. This study is an invaluable proof of the impact any armed conflict has on air quality, the population, and environment. © 2022 by the authors.

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Mapping 50 years of contribution to the development of soil quality biological indicators

2023 , Bonilla Bedoya, Santiago , Valencia K. , Herrera M.Á. , López-Ulloa M. , Donoso D.A. , Macedo Pezzopane J.E.

Biological indicators of soil quality express the capacity of a soil to maintain its ecosystem functions and services between socio-ecosystem inflection thresholds; therefore, they are determinants in management and land use decisions. However, their development until a few decades ago was limited for several reasons: reductionism and early development of other dimensions, such as physical and chemical indicators or their methodological complexity, thus affecting the importance given to biological factors and the integral evaluation of soil quality or health. Thus, this review presents a mapping of the scientific contributions of the last 50 years oriented to the theoretical and methodological development of biological indicators of soil quality, identifying their development and application in these decades. We conducted a bibliometric analysis that allowed us to present an overview of the field with respect to scientific production: temporality, geographical origin, institutional origin, journals that promote the development of the field, articles with greater influence by citation in the field of study, and the co-occurrences of these indicators in research. This analysis was complemented at the second stage by a systematic review of the literature with the greatest impact by citation. We found 2320 scientific papers distributed mainly in the United States (17.8%), China (12.2%), Brazil (8.3%), India (6.3%), and European Mediterranean countries, such as Spain, France, and Italy (14.2%). Our review showed 25 biological indicators with the highest occurrence; for example, microbial biomass (1 1 8), enzymatic activity (90), and organic matter (78); other indicators, such as earthworms, nematodes, or springtails, are also reported. All indicators showed relationships, to a greater or lesser extent, with soil biodiversity and its functions in the landscape. Important advances in soil indicators have developed gradually in the last few decades, with scientific efforts mainly concentrated in developed and emerging countries. In the last decade, the production curve continues with a growth trend., and research questions in the field revolve around the linkage of diversity and function from a molecular point of view. The scope goes beyond productivity, manifesting the real need to conserve and manage the ecosystem services of a limited and non-renewable natural resource. Pioneering research should begin to report on the scope of soil biological monitoring and its influence on policy, management, and land use. Finally, the promotion of research networks with developing countries can foster the development of regional and local soil monitoring policies in these regions. © 2023 The Author(s)

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Evaluating night-time light sources and correlation with socio-economic development using high-resolution multi-spectral Jilin-1 satellite imagery of Quito, Ecuador

2023 , Watson C.S. , Elliott J.R. , Córdova M. , Menoscal J. , Bonilla Bedoya, Santiago

Artificial light at night (ALAN) has positive and negative effects on social, economic, environmental, and ecological systems, and will increase with urban expansion. In this study, we used a multi-spectral 1.5 m resolution night-time acquisition from a Jilin-1 satellite over the city of Quito, Ecuador, to evaluate spatial lighting patterns in an expanding and topography complex-built environment. We demonstrated a requirement for robust georeferencing and orthorectification due to the complex topography, with errors on the order of 4–6 pixels (5.8–8.4 m CE95). We also quantified differences in observed brightness due to the image acquisition and local geometry. Street light type was distinguishable between high-pressure sodium (HPS) and light emitting diode (LED) sources (F1-score = 0.72–0.83) using a shark random forest decision tree approach. Additionally, street lights could be located within 10 m (F1-score = 0.71) with balanced omissions and commissions. Spatial trends revealed that the road network was the dominant source of illumination, accounting for 45% of illuminated pixels, whereas built-up areas accounted for 23%. Overall, 68% of all illuminated pixels were on or within 10 m of the road. Higher socio-economic development was associated with higher proportions of LED lighting, greater road network lighting and density of street lights, higher overall radiance for built-up areas and the road network, and greater coverage and illumination of designated green spaces. The broad impacts of ALAN mean that addressing the causes and consequences of lighting inequalities is a complex issue. Nonetheless, Jilin-1 night-time imagery offers a low-cost way to map and monitor light sources at high-resolution that will be beneficial to city-planners and progressing Sustainable Development Goals. © 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

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Mapping of the Successional Stage of a Secondary Forest Using Point Clouds Derived from UAV Photogrammetry

2023 , Cabral R.P. , da Silva G.F. , de Almeida A.Q. , Bonilla Bedoya, Santiago , Dias H.M. , De Mendonça A.R. , Rodrigues N.M.M. , Valente C.C.A. , Oliveira K. , Gonçalves F.G. , Sarcinelli T.S.

The definition of strategies for forest restoration projects depends on information of the successional stage of the area to be restored. Usually, classification of the successional stage is carried out in the field using forest inventory campaigns. However, these campaigns are costly, time-consuming, and limited in terms of spatial coverage. Currently, forest inventories are being improved using 3D data obtained from remote sensing. The objective of this work was to estimate several parameters of interest for the classification of the successional stages of secondary vegetation areas using 3D digital aerial photogrammetry (DAP) data obtained from unmanned aerial vehicles (UAVs). A cost analysis was also carried out considering the costs of equipment and data collection, processing, and analysis. The study was carried out in southeastern Brazil in areas covered by secondary Atlantic Forest. Regression models were fit to estimate total height (h), diameter at breast height (dbh), and basal area (ba) of trees in 40 field inventory plots (0.09 ha each). The models were fit using traditional metrics based on heights derived from DAP and a portable laser scanner (PLS). The prediction models based on DAP data yielded a performance similar to models fit with LiDAR, with values of R² ranging from 88.3% to 94.0% and RMSE between 11.1% and 28.5%. Successional stage maps produced by DAP were compatible with the successional classes estimated in the 40 field plots. The results show that UAV photogrammetry metrics can be used to estimate h, dbh, and ba of secondary vegetation with an accuracy similar to that obtained from LiDAR. In addition to presenting the lowest cost, the estimates derived from DAP allowed for the classification of successional stages in the analyzed secondary forest areas. © 2023 by the authors.

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