OpenStreetMap: Challenges and opportunities in machine learning and remote sensing
OpenStreetMap (OSM) is a community-based, freely available, editable map service created
as an alternative to authoritative sources. Given that it is edited mainly by volunteers with …
as an alternative to authoritative sources. Given that it is edited mainly by volunteers with …
Progress and challenges in infectious disease cartography
Quantitatively mapping the spatial distributions of infectious diseases is key to both
investigating their epidemiology and identifying populations at risk of infection. Important …
investigating their epidemiology and identifying populations at risk of infection. Important …
The six dimensions of built environment on urban vitality: Fusion evidence from multi-source data
Long-standing attention has been given to urban vitality and its association with the built
environment (BE). However, the multiplicity and complex impacts of BE factors that shape …
environment (BE). However, the multiplicity and complex impacts of BE factors that shape …
The world's user-generated road map is more than 80% complete
C Barrington-Leigh, A Millard-Ball - PloS one, 2017 - journals.plos.org
OpenStreetMap, a crowdsourced geographic database, provides the only global-level,
openly licensed source of geospatial road data, and the only national-level source in many …
openly licensed source of geospatial road data, and the only national-level source in many …
Spatially disaggregated population estimates in the absence of national population and housing census data
Population numbers at local levels are fundamental data for many applications, including
the delivery and planning of services, election preparation, and response to disasters. In …
the delivery and planning of services, election preparation, and response to disasters. In …
Classifying urban land use by integrating remote sensing and social media data
Urban land use information plays an important role in urban management, government
policy-making, and population activity monitoring. However, the accurate classification of …
policy-making, and population activity monitoring. However, the accurate classification of …
Improved population mapping for China using remotely sensed and points-of-interest data within a random forests model
Remote sensing image products (eg brightness of nighttime lights and land cover/land use
types) have been widely used to disaggregate census data to produce gridded population …
types) have been widely used to disaggregate census data to produce gridded population …
Mapping fine-scale population distributions at the building level by integrating multisource geospatial big data
Fine-scale population distribution data at the building level play an essential role in
numerous fields, for example urban planning and disaster prevention. The rapid …
numerous fields, for example urban planning and disaster prevention. The rapid …
Assessment of the sustainable development of rural minority settlements based on multidimensional data and geographical detector method: A case study in Dehong …
In a developing country, paying attention to the sustainable development of rural areas is
conducive to the development of the entire country. Ethnic minority areas are an important …
conducive to the development of the entire country. Ethnic minority areas are an important …
An optimized random forest model and its generalization ability in landslide susceptibility mapping: application in two areas of Three Gorges Reservoir, China
D Sun, J Xu, H Wen, Y Wang - Journal of Earth Science, 2020 - Springer
Numerous researches have been published on the application of landslide susceptibility
assessment models; however, they were only applied in the same areas as the models were …
assessment models; however, they were only applied in the same areas as the models were …