Sedimentary Changes of a Sand Layer in Liquefied Silts

A flume experiment was conducted to investigate the restratification of liquefied sediment strata under a wave load with the focus on the interbedded strata of coarse and fine sediments formed in estuarine and coastal areas.The aim of this research was to study the characteristics and processes of liquefied sediment strata in terms of wave-induced liquefaction.In the experiment,the bottom bed liquefied under the wave action and the liquefied soil moved in the same period with the overlying waves,and the track of the soil particles in the liquefied soil was an ellipse.The sand layer consisting of coarse particles in the upper part,settled into the lower silt layer.The sinking of coarse particles and upward migration of the fine particles of the lower layer induced by liquefied sediment fluctuations are the likely reasons for sedimentation of the sand layer in liquefied silt.

Big earth data analytics on Sentinel-1 and Landsat imagery in support to global human settlements mapping

Continuous global-scale mapping of human settlements in the service of international agreements calls for massive volume of multi-source,multi-temporal,and multi-scale earth observation data.In this paper,the latest developments in terms of processing big earth observation data for the purpose of improving the Global Human Settlement Layer(GHSL)data are presented.Two experiments with Sentinel-1 and Landsat data collections were run leveraging on the Joint Research Centre Earth Observation Data and Processing Platform.A comparative analysis of the results of built-up areas extraction from different remote sensing data and processing workflows shows how the information production supported by data-intensive computing infrastructure for optimization and multiple testing can improve the output information reliability and consistency within the GHSL scope.The paper presents the processing workflows and the results of the two main experiments,giving insights into the enhanced mapping capabilities gained by analyzing Sentinel-1 and Landsat data-sets,and the lessons learnt in terms of handling and processing big earth observation data.

Automated global delineation of human settlements from 40 years of Landsat satellite data archives

This paper presents the analysis of Earth Observation data records collected between 1975 and 2014 for assessing the extent and temporal evolution of the built-up surface in the frame of the Global Human Settlement Layer project.The scale of the information produced by the study enables the assessment of the whole continuum of human settlements from rural hamlets to megacities.The study applies enhanced processing methods as compared to the first production of the GHSL baseline data.The major improvements include the use of a more refined learning set on built-up areas derived from Sentinel-1 data which allowed testing the added-value of incremental learning in big data analytics.Herein,the new features of the GHSL built-up grids and the methods are described and compared with the previous ones using a reference set of building footprints for 277 areas of interest.The results show a gradual improvement in the accuracy measures with a gain of 3.6% in the balanced accuracy,between the first production of the GHSL baseline and the latest GHSL multitemporal built-up grids.A validation of the multitemporal component is also conducted at the global scale establishing the reliability of the built-up layer across time.

The grey-green divide:multi-temporal analysis of greenness across 10,000 urban centres derived from the Global Human Settlement Layer(GHSL)

The presence of green spaces within city centres has been recognized as a valuable component of the city landscape.Vegetation provides a variety of benefits including energy saving,improved air quality,reduced noise pollution,decreased ambient temperature and psychological restoration.Evidence also shows that the amount of vegetation,known as‘greenness’,in densely populated areas,can also be an indicator of the relative wealth of a neighbourhood.The‘grey-green divide’,the contrast between built-up areas with a dominant grey colour and green spaces,is taken as a proxy indicator of sustainable management of cities and planning of urban growth.Consistent and continuous assessment of greenness in cities is therefore essential for monitoring progress towards the United Nations Sustainable Development Goal 11.The availability of multi-temporal greenness information from Landsat data archives together with data derived from the city centres database of the Global Human Settlement Layer(GHSL)initiative,offers a unique perspective to quantify and analyse changes in greenness across 10,323 urban centres all around the globe.In this research,we assess differences between greenness within and outside the built-up area for all the urban centres described by the city centres database of the GHSL.We also analyse changes in the amount of green space over time considering changes in the built-up areas in the periods 1990,2000 and 2014.The results show an overall trend of increased greenness between 1990 and 2014 in most cities.The effect of greening is observed also for most of the 32 world megacities.We conclude that using simple yet effective approaches exploiting open and free global data it is possible to provide quantitative information on the greenness of cities and its changes over time.This information is of direct interest for urban planners and decision-makers to mitigate urban related environmental and social impacts.

Exposing the urban continuum:implications and crosscomparison from an interdisciplinary perspective

There is an increasing availability of geospatial data describing patterns of human settlement and population such as various global remote-sensing based built-up land layers,fine-grained census-based population estimates,and publicly available cadastral and building footprint data.This development constitutes new integrative modeling opportunities to characterize the continuum of urban,peri-urban,and rural settlements and populations.However,little research has been done regarding the agreement between such data products in measuring human presence which is measured by different proxy variables(i.e.presence of built-up structures derived from different remote sensors,census-derived population counts,or cadastral land parcels).In this work,we quantitatively evaluate and cross-compare the ability of such data to model the urban continuum,using a unique,integrated validation database of cadastral and building footprint data,U.S.census data,and three different versions of the Global Human Settlement Layer(GHSL)derived from remotely sensed data.We identify advantages and shortcomings of these data types across different geographic settings in the U.S.,which will inform future data users on implications of data accuracy and suitability for a given application,even in data-poor regions of the world.