In recent years, social media emerged as a potential resource to improve the management of crisis situations such disasters triggered by natural hazards. Although there is growing research body concerned with analysis usage during disasters, most previous work has concentrated on using stand-alone information source, whereas its combination other sources holds still underexplored potential. This article presents an approach enhance identification relevant messages from that relies upon...

Abstract In the past 10 years, collaborative maps of OpenStreetMap (OSM) have been used to support humanitarian efforts around world as well fill important data gaps for implementing major development frameworks such Sustainable Development Goals. This paper provides a comprehensive assessment evolution mapping within OSM community, seeking understand spatial and temporal footprint these large-scale efforts. The spatio-temporal statistical analysis OSM’s full history since 2008 showed that...

Abstract OpenStreetMap (OSM) has evolved as a popular dataset for global urban analyses, such assessing progress towards the Sustainable Development Goals. However, many analyses do not account uneven spatial coverage of existing data. We employ machine-learning model to infer completeness OSM building stock data 13,189 agglomerations worldwide. For 1,848 centres (16% population), footprint exceeds 80% completeness, but remains lower than 20% 9,163 cities (48% population). Although...

In the past few years, volunteers have produced geographic information of different kinds, using a variety crowdsourcing platforms, within broad range contexts. However, there is still lack clarity about specific types tasks that can perform for deriving from remotely sensed imagery, and how quality be assessed particular task types. To fill this gap, we analyse existing literature propose typology in crowdsourcing, which distinguishes between classification, digitisation conflation tasks....

Tourism is one of the most economically important industries. It is, however, vulnerable to disaster events. Geotagged social media data, as forms volunteered geographic information (VGI), has been widely explored support prevention, preparation, and response phases management, while little effort put on recovery phase. This study develops a scientific workflow methods monitor assess post-disaster tourism using geotagged Flickr photos, which involve viewshed based data quality enhancement,...

Reliable techniques to generate accurate data sets of human built-up areas at national, regional, and global scales are a key factor monitor the implementation progress Sustainable Development Goals as defined by United Nations. However, scarce availability up-to-date settlement remains major challenge, e.g., for humanitarian organizations. In this paper, we investigated complementary value crowdsourcing deep learning fill gaps existing earth observation-based (EO) products. To end, propose...

Abstract OpenStreetMap (OSM) has been intensively used to support humanitarian aid activities, especially in the Global South. Its data availability South greatly improved via recent mapping campaigns. However, large rural areas are still incompletely mapped. The timely provision of map is often essential for work actors case disaster preparation or response. Therefore, it become a vital challenge boost speed and efficiency existing workflows. We address this by proposing novel few‐shot...

Natural hazards threaten millions of people all over the world. To address this risk, exposure and vulnerability models with high resolution data are essential. However, in many areas world, rather coarse aggregated large areas. Although OpenStreetMap (OSM) offers great potential to assess risk at a detailed building-by-building level, completeness OSM building footprints is still heterogeneous. We present an approach close gap by means crowd-sourcing based on mobile app MapSwipe, where...

Abstract This paper investigates different methods for quantifying thaw subsidence using terrestrial laser scanning (TLS) point clouds. Thaw is a slow (millimetre to centimetre per year) vertical displacement of the ground surface common in ice‐rich permafrost‐underlain landscapes. It difficult quantify tundra areas as they often lack stable reference frames. Also, there no solid serve basis elevation measurements, due continuous moss–lichen cover. We investigate how an expert‐driven method...

AI-assisted mapping is an innovative approach to data production in OpenStreetMap (OSM), designed add new buildings maps using advanced editing tools based on deep learning techniques and recently released global-scale building datasets derived from satellite imagery. However, the identification of OSM AI-generated remains challenging without a comprehensive global overview scale, magnitude, impact OSM. The present study examines evolution spatiotemporal OSM, applying ohsome framework,...

Abstract OpenStreetMap (OSM) has evolved as a popular geospatial dataset for global studies, such monitoring progress towards the Sustainable Development Goals (SDGs). However, many applications turn blind eye on its uneven spatial coverage. We utilized regression model to infer OSM building completeness within 13,189 urban agglomerations home 50% of population. Our results reveal that 1,510 cities footprint data exceeds 80% completeness. Humanitarian mapping efforts have significantly...

Natural hazards threaten millions of people all over the world. To address risk, exposure and vulnerability models with high resolution data are essential. However, in many areas world, rather coarse aggregated large areas. Although OpenStreetMap (OSM) offers great potential to assess risk at a detailed building-by-building level, completeness OSM building footprints is still heterogeneous. We present an approach close this gap by means crowdsourcing based on mobile App MapSwipe, where...

Social networks have been used to overcome the problem of incomplete offi cial data, and provide a more detailed description disaster. However, fi ltering relevant messages on-the-fl y remains challenging due large amount misleading, outdated or inaccurate information. This paper presents an approach for automated geographic prioritization social network fl ood risk management based on sensor data streams. It was evaluated using from Twitter monitoring agency Brazil. The results revealed...

Abstract. Climate change is causing rapid warming in the Arctic region, resulting thawing of permafrost. This has substantial environmental implications, such as release and mobilisation contaminants from past present industrial activities. However, freely accessible public geographical information scarce on sites activities much Arctic, which makes scientific research impact assessment difficult. OpenStreetMap (OSM) can be a valuable resource for identifying assessing contamination. OSM...