# The Role of Earth Observation, with a Focus on SAR Interferometry, for Sinkhole Hazard Assessment
## 1 Introduction to Sinkhole Hazards  
Many regions around the globe are characterised by the presence of highly soluble calcium carbonate (dolomite or limestone) or evaporite (typically halite or gypsum) rocks [1; 2; 3; 4; 5; 6; 7]. These areas are frequently associated with sudden, catastrophic collapse of the surface in a process known as sinkhole development. Sinkholes can be small (less than 1 m in diameter) but can reach up to hundreds of metres in diameter in extreme cases [8; 9]. In many sinkhole prone regions, population growth as well as social and political drivers force communities to settle in areas characterised by the presence of sinkhole hazards [10; 11]. In such instances, risk avoidance measures, like prohibiting development of any kind, is not feasible [1]. In these areas, sinkholes can cause substantial damage to infrastructure [2; 7; 9; 12; 13; 14; 15; 16] and places restrictions on the construction of buildings, roads and other critical infrastructure [13]. Sinkholes have also caused environmental problems, especially in cases where they change the local hydrology, potentially draining streams, rivers and dams [8; 9; 17]. Due to the risks involved with sinkhole development, significant efforts have been devoted to sinkhole hazard assessment. Sinkhole hazard assessment can be grouped into three distinct stages namely; (1) predicting the spatial and temporal distribution of future sinkholes (or probability of occurrence) [12; 15; 18], (2) assessing their severity (or capability to do damage) [18], or (3) finding precursory deformation indicative of impending failures that acts as warning signs of impendingsinkhole formation [2; 16; 19; 20; 21]. The calculation of the probability of sinkhole occurrence relies on the availability of a sinkhole inventory of the area of interest which describes past sinkhole events in addition to the local conditions at the time of their formation [15; 22]. In fact, the construction of the sinkhole inventory is considered to be the most important step in sinkhole hazard assessment [11; 17; 22]. The predictions derived from these models assume that sinkhole phenomena in the future will form in similar conditions as sinkholes in the past [12; 23]. Quantitative risk assessment then involves the statistical analysis of sinkhole events in relation to their controlling conditions. In this way, cause-and effect relationships between sinkholes that happened in the past and controlling conditions can be used to perform quantitative risk assessments or probabilistic sinkhole hazard assessment with the aim of identifying high risk areas [12; 24] and the production of sinkhole susceptibility maps [15]. To complement these assessments, several approaches have been adopted to identify or confirm the presence of underground cavities in high risk areas which generally relies on geophysical surveys or percussion drilling [25; 26; 27]. The information derived from the analysis of sinkhole inventories and the mapping of underground cavities can be used to identify high risk areas. The safest strategy is to avoid or prohibit development on high risk areas [12]. However, centuries of urbanisation and urban expansion may imply that communities have already settled in areas that may be deemed unsuitable for development due to the presence of sinkhole hazards. Therefore, to complement sinkhole risk mitigation in high risk areas, recent approaches have focused on the detection and monitoring of small-scale precursory deformation that may, or may not, be present prior to the collapse of a sinkhole [28]. If precursory deformation can be detected, reliably, an early warning can be provided to mitigate the impact of sinkholes on affected communities [16; 20]. Although all three stages of sinkhole hazard assessment generally rely extensively on field surveying campaigns and in situ measurements, these approaches are resources intensive and time consuming and frequently impractical for sinkhole hazard assessment over extensive and remote areas.