Design innovation of mesoscale robotic swarms:applications to cooperative urban sensing and mapping

Development of mesoscale robots is gaining interest in security and surveillance domains due to their stealth and portable nature in achieving tasks.Their design and development require a host of hardware,controls,and behavioral innovations to yield fast,energy-efficient,distributed,adaptive,robust,and scalable systems.We extensively describe one such design and development process by:(1)the genealogy of our embedded platforms;(2)the key system architecture and functional layout;(3)the developed and implemented design principles for mesoscale robotic systems;(4)the various key algorithms developed for effective collective operations of mesoscale robotic swarms,with applications to urban sensing and mapping.This study includes our perception of the embedded hardware requirements for reliable operations of mesoscale robotic swarms and our description of the key innovations made in magnetic sensing,indoor localization,central pattern generator control,and distributed autonomy.Although some elements of the design process of such a complex robotic system are inevitably ad-hoc,we focus on the system-of-systems design process and the component design integration.This system-of-systems process provides a basis for developing future systems in the field,and the designs represent the state-of-the-art development that may be benchmarked against and adapted to other applications.

Monitoring urban land cover and vegetation change by multi-temporal remote sensing information

In order to analyze changes in human settlement in Xuzhou city during the past 20 years, changes in land cover and vegetation were investigated based on multi-temporal remote sensing Landsat TM images. We developed a hierarchical classifier system that uses different feature inputs for specific classes and conducted a classification post-processing approach to improve its accuracy. From our statistical analysis of changes in urban land cover from 1987 to 2007, we conclude that built-up land areas have obviously increased, while farmland has seen in a continuous loss due to urban growth and human activities. A NDVI difference approach was used to extract information on changes in vegetation. A false change information elimination approach was developed based on prior knowledge and statistical analysis. The areas of vegetation cover have been in continuous decline over the past 20 years, although some measures have been adopted to protect and maintain urban vegetation. Given the stability of underground coal exploitation since 1990s, urban growth has become the major driving force in vegetation loss, which is different from the vegetation change driven by coal exploitation mainly before 1990.

Evaluation of Three-dimensional Urban Expansion: A Case Study of Yangzhou City, Jiangsu Province, China

With rapid urban development in China in the last two decades, the three-dimensional(3D) characteristic has been the main feature of urban morphology. However, the vast majority of researches of urban growth have focused on the planar area(two-dimensional(2D)) expansion. Few studies have been conducted from a 3D perspective. In this paper, the 3D urban expansion of the Yangzhou City, Jiangsu Province, China from 2003 to 2012 was evaluated based on Geographical Information System(GIS) tools and high-resolution remote sensing images. Four indices, namely weighted average height of buildings, volume of buildings, 3D expansion intensity and 3D fractal dimension are used to quantify the 3D urban expansion. The weighted average height of buildings and the volume of buildings are used to illustrate the temporal change of the 3D urban morphology, while the other two indices are used to calculate the expansion intensity and the fractal dimension of the 3D urban morphology. The results show that the spatial distribution of the high-rise buildings in Yangzhou has significantly spread and the utilization of the 3D space of Yangzhou has become more efficient and intensive. The methods proposed in this paper laid a foundation for a wide range of study of 3D urban morphology changes.

Spatial Differences of Coastal Urban Expansion in China from 1970s to 2013

As the ′economic engines′ of China,coastal cities have developed and expanded considerably since the 1970 s.In this study,information on the urban expansion process of Chinese coastal cities from the 1970 s to 2013 was retrieved.Through the analysis of stage characteristics,spatial expansion modes,influences on land use,centroid shifts,and spatial morphological evolutions,the spatial differences of coastal urban expansion were revealed.Results indicate that 1) the expansion stages of southern coastal cities are more complex than those of northern coastal cities,and the expansion ranges and speeds of the former are far higher than those of the latter;2) the spatial expansion of southern coastal cities mostly adopt a single mode,whereas northern coastal cities mostly adopt a mixed mode;3) significant spatial differences in the occupations of different land sources exist between the south and the north along the coastline;4) the centroid of coastal cities tends to migrate toward the coastline,and the centroid shift distances of southern coastal cities are clearly higher than those of northern coastal cities;and 5) the spatial morphology of southern coastal cities tends to be compact,whereas that of northern coastal cities tends to be loose.Policies have a powerful significance in terms of guiding urban expansion and its spatial differences in coastal cities.Urban expansion in coastal cities will encounter new opportunities and challenges under the guidance of new types of urbanization strategies.

Spatio-temporal-spectral observation model for urban remote sensing

Taking cities as objects being observed,urban remote sensing is an important branch of remote sensing.Given the complexity of the urban scenes,urban remote sensing observation requires data with a high temporal resolution,high spatial resolution,and high spectral resolution.To the best of our knowledge,however,no satellite owns all the above character-istics.Thus,it is necessary to coordinate data from existing remote sensing satellites to meet the needs of urban observation.In this study,we abstracted the urban remote sensing observation process and proposed an urban spatio-temporal-spectral observation model,filling the gap of no existing urban remote sensing framework.In this study,we present four applications to elaborate on the specific applications of the proposed model:1)a spatiotemporal fusion model for synthesizing ideal data,2)a spatio-spectral observation model for urban vegetation biomass estimation,3)a temporal-spectral observation model for urban flood mapping,and 4)a spatio-temporal-spectral model for impervious surface extraction.We believe that the proposed model,although in a conceptual stage,can largely benefit urban observation by providing a new data fusion paradigm.

Spatio-temporal-spectral-angular observation model that integrates observations from UAV and mobile mapping vehicle for better urban mapping

In a complex urban scene,observation from a single sensor unavoidably leads to voids in observations,failing to describe urban objects in a comprehensive manner.In this paper,we propose a spatio-temporal-spectral-angular observation model to integrate observations from UAV and mobile mapping vehicle platform,realizing a joint,coordinated observation operation from both air and ground.We develop a multi-source remote sensing data acquisition system to effectively acquire multi-angle data of complex urban scenes.Multi-source data fusion solves the missing data problem caused by occlusion and achieves accurate,rapid,and complete collection of holographic spatial and temporal information in complex urban scenes.We carried out an experiment on Baisha Town,Chongqing,China and obtained multi-sensor,multi-angle data from UAV and mobile mapping vehicle.We first extracted the point cloud from UAV and then integrated the UAV and mobile mapping vehicle point cloud.The inte-grated results combined both the characteristics of UAV and mobile mapping vehicle point cloud,confirming the practicability of the proposed joint data acquisition platform and the effectiveness of spatio-temporal-spectral-angular observation model.Compared with the observation from UAV or mobile mapping vehicle alone,the integrated system provides an effective data acquisition solution toward comprehensive urban monitoring.

Building Extraction from High Resolution SAR Imagery in Urban Areas

In this paper, the textural characteristics of the buildings were quantified by using two texture descriptors, namely, Square Root Pair Difference （SRPD） and Gi ＊. Then, a novel method, based on SRPD and Gi ＊, to extract building areas in ur- ban areas from very high resolution SAR images is presented. The results showed that this method has the ability to differentiate buildings from the complicated features in urban areas, which can be employed for land mapping and provides support for relief operations.

Social media as passive geo-participation in transportation planning-how effective are topic modeling&sentiment analysis in comparison with citizen surveys?

We live in an era of rapid urbanization as many cities are experiencing an unprecedented rate of population growth and congestion.Public transport is playing an increasingly important role in urban mobility with a need to move people and goods efficiently around the city.With such pressures on existing public transportation systems,this paper investigates the opportunities to use social media to more effectively engage with citizens and customers using such services.This research forms a case study of the use of passively collected forms of big data in cities-focusing on Sydney,Australia.Firstly,it examines social media data(Tweets)related to public transport performance.Secondly,it joins this to longitudinal big data-delay information continuously broadcast by the network over a year,thus forming hundreds of millions of data artifacts.Topics,tones,and sentiment are modeled using machine learning and Natural Language Processing(NLP)techniques.These resulting data,and models,are compared to opinions derived from a citizen survey among users.The validity of such data and models versus the intentions of users,in the context of systems that monitor and improve transport performance,are discussed.As such,key recommendations for developing Smart Cities were formed in an applied research context based on these data and techniques.

Snowdrift effect on snow deposition：Insights from a comparison of a snow pit profile and meteorological observations in east Antarctica

A high-frequency and precise ultrasonic sounder was used to monitor precipitated/deposited and drift snow events over a 3-year period(17 January 2005 to 4 January 2008) at the Eagle automatic weather station site,inland Antarctica.Ion species and oxygen isotope ratios were also generated from a snow pit below the sensor.These accumulation and snowdrift events were used to examine the synchronism with seasonal variations of δ^(18)O and ion species,providing an opportunity to assess the snowdrift effect in typical Antarctic inland conditions.There were up to 1-year differences for this 3-year-long snow pit between the traditional dating method and ultrasonic records.This difference implies that in areas with low accumulation or high wind,the snowdrift effect can induce abnormal disturbances on snow deposition.The snowdrift effect should be seriously taken into account for high-resolution dating of ice cores and estimation of surface mass balance,especially when the morphology of most Antarctic inland areas is similar to that of the Eagle site.