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New sensor data also includes unmanned aerial vehicles(“drones”) and spatially referenced (georeferenced) video.Georeferenced video has been used quickly to identify sitesof standing sewage and water to aid in cholera riskmapping in Haiti 376 and vulnerability of homes in LosAngeles, California to wildfire 377 . Drones can provide veryhigh-resolution 2-D and 3-D imagery, which can be useful inmapping complex urban riverine topography, which hasbeen used in Haiti for flood modeling assessments 378 .New data sets can help in understanding vulnerability andmobility, and data to estimate mobility patterns can begleaned for example from geolocated tweets. One piece ofresearch found that by analyzing New York City tweetersbefore, during, and after Superstorm Sandy, pre-disastermobility patterns can indicate the potential range ofmobility during a disaster 379 . Other indicators of mobilityinclude transit data by bikes 380 , buses and subways beingmade available by hundreds of municipalities 381 . Transitdata can monitor population flux at different times of day,and is just one example of open Big Data cities are releasingthat could be valuable for risk assessment.4.4.4. ChallengesWhen highlighting several new advances in the use of newdata collection methods for DRR it is also important toremember that challenges remain. For example the Twitteralgorithm used to detect food crises in Indonesiamentioned earlier in this chapter also had one misfire,predicting a food crisis where there was none. Sometimesquestions arise from the representativeness of the data asin the case of the Superstorm Sandy, where in the wake ofthe storm the social media data were more highlyconcentrated in less-impacted areas of New York City,rather than in neighbourhoods in south Queens which borethe brunt of its impact 382 . In the example of crowd-sourcedinformation in Haiti, of the more than 3,500 messagespublished on the Ushahidi-Haiti crisis map, only 202messages were tagged as “verified” by the Ushahidi team,mostly from early web submissions that had been based onmedia reports 383 . The challenges related to the use of bigdata will be addressed in more depth in Chapter 7 andChapter 8 of the report.4.5. ConclusionsEffective disaster risk reduction measures will need to playa key role for disaster-prone countries in implementation ofthe post-2015 development agenda in order to preventhard won development gains from being eroded bydisasters.Disaster loss accounting and risk assessments will playa pivotal role in monitoring progress, and concertedefforts are required to improve the coverage and85quality of data, including establishment and support tonational loss databases using common methodologies.Developing disaster statistics and risk metrics will notonly improve reporting of progress towardsinternationally agreed goals and targets but alsosupport evidence-based planning and decision making.Countries will need to address the issue of baselinesetting for monitoring of progress and, despite some ofthe weaknesses of the method, use of the 10-yearaverage of observed historical data as decided in theSendai Framework for Action on global mortality mightbe the simplest option for the moment. Nevertheless,data availability is increasing rapidly and scientificassessment and modelling capacity follows suit, andnew options could be considered for future use.In recent years, partnerships between scientificorganisations and practitioners and policy makers haveenhanced the uptake of evidence in DRR. Use ofscientific research, including risk assessments andmodels, from both the academic and businesscommunity, and analysis of the underlying drivers ofrisk, should be further promoted in planning andmonitoring.The regional dimension can provide valuable supportto the implementation of both the SDGs and the SendaiFramework. Countries from the same region facesimilar problems and benefit from sharing experiences,and it can be easier to assess the transferability of theirexperiences at the regional than the global level. Theregion can also serve as the suitable level to providesupport to countries, through capacity buildingactivities, and appropriate harmonisation andvalidation initiatives.New methods and technological solutions for datagathering are being developed with increasing speed.In order to harness these as efficiently as possible,capacity development as well as more open access todata will be required to support developing countriesin making full use of the opportunities.Several questions related to definitions of terms andthe target scope, accounting methods, baselines anddata sources will need to be answered when setting upthe monitoring framework for SDGs. Therein lies agolden opportunity to align the work being done forthe post-2015 agenda with the post-Sendai DRRmonitoring framework in order to avoid duplication,and to ensure that progress in disaster risk reductioncan be reported as an integral part of progress onsustainable development. This will spare preciousresources and allow countries to focus onimplementation in order to make developmentsustainable and resilient.