# ERS-1/2 and Sentinel-1 SAR Data Mining for Flood Hazard and Risk Assessment in Lima, Peru
## 1 Introduction  
Floods are among the impacts of recent extreme weather phenomena that highlight a significant vulnerability and exposure of some ecosystems and many human systems to current climate variability [1]. El Nino-Southern Oscillation (ENSO) is believed to be the most likely driver of such interannual variability on a global scale [2; 3; 4; 5] and the increased frequency of floods, landslides and avalanches in the Latin America [3; 4; 6]. Peru is one of the most affected countries, given its coastal location and exposure [3; 7; 8; 9; 10; 11]. Between 1980 and 2008 there were 495,000 people affected by floods (equal to 15% of the total impacted bynatural disasters) and at least 23% of the Peruvian population lives in flood-prone areas. In 1981 there were economic losses of 6 million US dollars for flood events [12]. The Peruvian government is, therefore, committed to enhancing preparedness and resilience to floods [13]. There are scientific studies that can provide the necessary evidence base to achieve a better understanding of this natural hazard and identify the appropriate mitigation measures. From a social and psychological perspective, [PERSON] et al. [14] investigated the risk perception of people living in vulnerable zones of Lima during floods. [PERSON] et al. [15] focused on diagnosing the Peru floods of 2017 and examining possible large-scale forces, using precipitation record station and climate indices. [PERSON] et al. [16] assessed the capabilities of the Global Flood Awareness System (GloFAS) using a holistic evaluation framework in Peru for the years 2009-2015. [PERSON] et al. [17], instead, used pre-existing geomorphology cartography, soil use, soil economic assessment and human exposure to define a proposal for management and territorial order for the city of Iquitos. The geographic focus of the present paper is the capital city of Lima and its urban footprint within the hydrological basin of the Rimac River. Various studies associate \"El Nino events\" with \"anomalous\" rains that occurred in Lima and its hydrological basin over the past four and a half centuries [18; 19; 20; 21; 22; 23]. The effect due to ENSO sums up with other different predisposing factors (natural, geological and anthropogenic) and, consequentially, flooding risk is of great concern [9; 24; 25; 26; 27; 11; 28]. [PERSON] et al. [28] conducted a spatial analysis of the geological hazards in the metropolitan area of Lima and the Callao region, aiming to interpret the evolution of the geomorphological landscape, identify processes that can cause disasters, and propose prevention and mitigation measures. The study was based on the use of aerial photographs from the 1960s to 1970s, and satellite Landsat images for the years 1995-2000 and 2003-2005. These time intervals are of particular interest, because according to the historical records, the most recent and catastrophic floods in Lima happened in 1997-1998 and 2017-2018 [8; 9; 11; 21; 22; 23; 26]. These events caused more than 600 fatalities, more than 2 million people affected, and over 7.5 million US dollars of total damage [29]. Given their significance and impact, this study focuses on these flood events. The aim of the present research is to demonstrate that multi-temporal change detection analysis of satellite synthetic aperture radar (SAR) images can provide spatial and temporal information of: (i) environmental and anthropogenic transformations in urban settlements and the territory that may contribute to increase (or decrease) the hazard and/or exposure to flooding risk, and (ii) damage and impacts experienced in the urban areas that have been already flooded during recent events. Alongside datasets of hazard factors and exposed elements, such information mined from SAR images can then be used as a geospatial input to develop, within the geographic information system (GIS) environment, a flooding risk classification map at basin scale.