Green Infrastructure are increasingly adopted by municipalities to mitigate urbanization's environmental impacts and providing ecosystem services. However, efficiency of green infrastructure depends on proper maintenance, which often falls short due to lack of inspection and monitoring. External factors such as littering, leaves falling, or sediment accumulation from nearby activities increases maintenance needs of green infrastructure, yet maintenance requirements and planning for green infrastructure remains unexplored. Current study investigates the requirements for mapping risks from external factors affecting green infrastructure performance in urban areas. Two types of green infrastructure, namely bioswales and rain gardens will be investigated. A two-step decision tree method is applied to study failure events and search for modeling methods or proxies. First, external factors influencing performance and maintenance are identified. The second step evaluates data for available models regarding sensitivity, availability, and suitability as proxies. Where models are unavailable, alternative data sources will be explored. Results will include a list of parameters to create hotspot maps for maintenance needs, supporting proactive planning for bioswales and rain gardens to enhance green infrastructure performance and longevity.