Monitoring changing environmental conditions for short-term periods is a key aspect of adaptive urban planning. Unfortunately, the official environmental datasets are often produced at too large time intervals, and sometimes the speed of urban transformation requires real-time monitoring data. In this work we employed ESRI ArcGIS (ver. 10.8.1) to process two normalized difference vegetation indices for the campus area of the Izmir Institute of Technology (Turkey). The area of this campus constitutes an optimal site for testing whether alterations to the soil due to excavation and new construction can be monitored in small areas of land. We downloaded two different Sentinel acquisitions from the Copernicus ONDA DİAS platform: one taken on 28 March 2021 and the second taken on 13 March 2022. We processed the images while elaborating the normalized difference vegetation index for both years and compared them. Results demonstrate that all major and minor soil degradations on the campus during the intervening year were detected and empirically quantified in terms of NDVİ reduction (abrupt changes). These findings confirm that detailed seasonal environmental monitoring of every part of the world is now possible using semi-automatic procedures to process original Sentinel data and recommend site-specific ecological compensation measures.

In the coming decades, climate change will be one of the most significant challenges for urban areas. The quantity, duration and intensity of events, such as flash rains and heat waves, will increase the vulnerability of urban regions while exposing citizens to potentially dangerous conditions. According to the current literature, mainstreaming resilience in urban planning means designing rules that strengthen urban systems’ adaptive and self-regulating functions by reducing their vulnerability. In this work, we aimed to build knowledge for the application of the sponge district concept to Izmir (Türkiye), one of Europe’s most vulnerable areas to pluvial flooding. To do this, we first analyzed the runoff in each urban sub-watershed, then employed a composite index to determine potential areas of intervention for nature-based solutions. Results show that 10% of Izmir’s urban areas are extremely vulnerable to cloudbursts, which means that 40% of the urban population is exposed to this phenomenon. Moreover, the runoff calculation in the sub-watershed demonstrated that the potential flood volume is underestimated, especially in the upslope areas. The results can be used as a template to suggest a stepwise approach to mainstream the resilience of densely-inhabited coastal urban catchments.

Modeling ecosystem services is a growing trend in scientific research, and Nature-based Solutions (NbSs) are increasingly used by land-use planners and environmental designers to achieve improved adaptation to climate change and mitigation of the negative effects of climate change. Predictions of ecological benefits of NbSs are needed early in design to support decision making. In this study, we used ecological analysis to predict the benefits of two NbSs applied to a university masterplan and adjusted our preliminary design strategy according to the first modeling results. Our Area of Interest was the IZTECH campus, which is located in a rural area of the eastern Mediterranean region (Izmir/Turkey). A primary design goal was to improve habitat quality by revitalizing soil. Customized analysis of the Baseline Condition and two NbSs scenarios was achieved by using local values obtained from a high-resolution photogrammetric scan of the catchment to produce flow accumulation and habitat quality indexes. Results indicate that anthropogenic features are the primary cause of habitat decay and that decreasing imperviousness reduces habitat decay significantly more than adding vegetation. This study creates a method of supporting sustainability goals by quickly testing alternative NbSs. The main innovation is demonstrating that early approximation of the ecological benefits of NbSs can inform preliminary design strategy. The proposed model may be calibrated to address specific environmental challenges of a given location and test other forms of NbSs.