Alegria Caicedo, A. C., Zimanyi, E., Cornelis, J., & Sahli, H. (2017). Hazard Mapping of Landmines and ERW Using Geo-Spatial Techniques. Journal of Remote Sensing & GIS, 6(2), 1-11. Article 5. https://doi.org/10.4172/2469-4134.1000197

@article{ad8e1f3c9f714d07a2737a3cbdcc1e8f,
title = "Hazard Mapping of Landmines and ERW Using Geo-Spatial Techniques",
abstract = "Landmines and Explosive Remnants of War (ERW) continue to represent a significant nuisance for society inaffected countries. Coping with humanitarian and development activities, mine action aims at both, reducing theimpacts of the presence of landmines/ERW on the population, and ultimately returning cleared land to the communities.These are the main tasks of mine action decision makers. This study combines landmine/ERW contamination datawith explanatory variables that contain information about underlying targets. They are integrated into a risk mappingframework using Geographic Information Systems with other information sources, such as remote sensing. The aim ofthis paper is to provide insights into the populations and/or locations at risk caused by landmine and ERW impacts on abroad and local scale. Thus, the concept of { extquoteleft}hotspots{ extquoteright} is particularly useful because it provides a visual representationof exposure, aided by a geo-spatial representation of { extquoteleft}priority areas for mine action planners to focus on. We apply theKernel Density Estimator (KDE) to derive such { extquoteleft}hotspots{ extquoteright}. KDE is proposed as the basis to define landmine and ERWhazard, vulnerability, and element-at-risk maps, which enable producing a final output, the landmine/ERW risk map. Thisis accomplished by using an adaptive kernel bandwidth for datasets with highly heterogeneous spatial distributions, anda problem-specific method for generating point samples from polygon data, before using them as inputs for KDE. Thegeo-statistical model presented here is a time-and-cost-efficient method to construct a landmine risk map, that is asrepresentative as those produced by mine action actors. It can be used as a complement to the risk area maps madeby these actors because they are slightly different but show a large degree of overlap. Moreover, the method helpsrevealing the variables which are the most linked to landmine/ERW-related events in the study area",
keywords = "Humanitarian mine action, Landmine risk, Risk indicators, Risk mapping, Geo-Spatial models, KDE",
author = "{Alegria Caicedo}, {Aura Cecilia} and Esteban Zimanyi and Jan Cornelis and Hichem Sahli",
year = "2017",
month = jun,
day = "30",
doi = "10.4172/2469-4134.1000197",
language = "English",
volume = "6",
pages = "1--11",
journal = "Journal of Remote Sensing & GIS",
issn = "2469-4134",
number = "2",
}