Development of green infrastructure during the COVID-19 pandemic using spatial analysis methods

In Latin America, there is a lack of green infrastructure (GI) to enhance urban resilience and reduce the contagion levels, particularly in times of pandemic. Therefore, a simplified method is needed to define GI in critical public health risk scenarios, especially when access to geospatial information is limited. The objective of this study is to propose a simplified method called GreenNet-Covid19 in Peru during critical public health scenarios using spatial analysis methods to define the global GI index (GGII) and select the potential integration areas for GI (PIAGI). This method is based on the approach proposed by Aguileraet al. (2018), which utilized spatial analysis in Metropolitan Arequipa and its surroundings during the COVID-19 pandemic. In this study, in addition to the four dimensions proposed Aguilera et al. (2018), a fifth dimension called ‘risk due to COVID-19’ was introduced, allowing to obtain the GGII and define the PIAGI. The GGII showed high ecological and biodiversity potentials at the vegetation cover level. However, the loss of GGII connectivity in urban areas posed a threat to the intricate connectivity of the highlands, thus increasing the risk of COVID-19 spread. Meanwhile, the PIAGI exhibited relatively low values compared with those of the GGII. Yet, the loss of PIAGI connectivity in urban areas strengthened the factors contributing to COVID-19 propagation. The intersection between the COVID-19 and PIAGI risk layers at the ‘very high,’ ‘high,’ and ‘medium’ levels demonstrated a high capability for reducing the contagion risk in future pandemics. The introduction and implementation of this method in territorial planning is facilitated by its applicability to any Latin American territory.