Yao Yao

Yao Yao
China University of Geosciences · School of Geography and Information Engineering

PhD
UrbanComp Team: https://www.urbancomp.net

About

101
Publications
41,783
Reads
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2,476
Citations
Introduction
Dr Yao Yao (姚尧) is currently a full professor at the China University of Geosciences (CUG). He also works as a senior algorithm expert at Alibaba Group (China’s biggest online shopping platform) 's data centre. His main research interests comprise geospatial big data mining and computational urban science. He has published more than 70 journal papers (including 8 ESI highly cited papers) since 2016.
Additional affiliations
March 2018 - present
China University of Geosciences
Position
  • Professor (Associate)
Description
  • Geospatial big data analysis, urban planning and high performance computation
August 2017 - present
Alibaba Group
Position
  • Engineer
Description
  • Geospatial big data analysis and location-base services (LBS)
September 2014 - January 2017
Sun Yat-Sen University
Position
  • Research Assistant
Description
  • 2014.8 - 2015.1 GNSS | 2015.2 - 2015.7 Remote sensing processing | 2015.9 - 2016.1 Spatial analysis | 2016.2 - 2016.7 Data structure (C++) | 2016.9 - 2017.1 Spatial analysis | 2017.3 - 2017.7 Data structure (C++).
Education
August 2014 - August 2017
Sun Yat-Sen University
Field of study
  • Geoscience
September 2009 - July 2011
Wuhan University
Field of study
  • Remote sening, image understanding
September 2004 - July 2008
Wuhan University
Field of study
  • Geodesy and Geomatics

Publications

Publications (101)
Article
Though global-coverage urban perception datasets have been recently created using machine learning, their efficacy in accurately assessing local urban perceptions for other countries and regions remains a problem. Here we describe a human-machine adversarial scoring framework using a methodology that incorporates deep learning and iterative feedbac...
Article
Empirical data are limited to decipher where people live and work in large cities; however, neighborhood information, such as street view image, is rich and abundant. We construct a ResNet-50-based social detection model to explore the potential relationship between street view images and job-housing attributes. The method extracts street view imag...
Article
The distribution of human perceptions in urban area was obtained. • This study first focuses on the spatial homogeneity of human perceptions. • A method is proposed to discover the homogeneous geographic domain of human perceptions. • This study explored the role of urban function in shaping human perceptions. Human perception of place refers to re...
Article
Currently, raster-based landscape indices (LIs) that measures the landscape pattern of raster-format land-use data, can be easily computed by relevant software (e.g., Fragstats). Unfortunately, open-access software for vector-based LIs often implement a small variety of metrics, which cannot meet the growing demand of the GIS and landscape design r...
Article
Full-text available
Background Residential green and blue spaces may be therapeutic for the mental health. However, solid evidence on the linkage between exposure to green and blue spaces and mental health among the elderly in non-Western countries is scarce and limited to exposure metrics based on remote sensing images (i.e., land cover and vegetation indices). Such...
Article
Understanding urban functions help with government planning and resource allocation to promote economic development. Few studies have reflected the influence of population movement and migration on urban functions overtime on a large scale. This study adopted the time-series social media data and points of interest to analyse urban functions' distr...
Article
Health inequalities are globally widespread due to regional socioeconomic inequalities. Myocardial infarction (MI) is a leading health problem causing deaths worldwide. Yet medical services for it are often inequitably distributed by region. Moreover, studies concerning MI's potential spatial risk factors generally suffer from difficulties in focus...
Article
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Many studies have disentangled the perceived benefits of vegetation on subjective well-being (SWB). Yet, scant attention has been paid to the joint effect of vegetation and building density on SWB. This study explores the relationship between streetscape vegetation (SV), building density and SWB in Beijing, China. Our analysis relies on rich measur...
Article
Awareness is increasing that greenspace is beneficial for people’s heart health. While a plethora of studies have focused on the relationship between neighbourhood greenspace and cardiovascular diseases in the general population, scant attention has been given to ischaemic heart disease (IHD) emergency department visits for middle-aged and older ad...
Article
The spatial structure of geochemical patterns is influenced by various geological processes, one of which may be mineralization. Thus, analysis of spatial geochemical patterns facilitates understanding of regional metallogenic mechanisms and recognition of geochemical anomalies related to mineralization. Convolutional neural networks (CNNs) used in...
Article
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Resource-based urban agglomerations often encounter greater challenges in the sustainable development of human settlements. The aim of this study is to propose an approach to the coordinated development of competitiveness by analyzing the interaction of human settlements competitiveness (HSC) in resource-based urban agglomerations. Through the comp...
Article
We present a novel approach for estimating the proportional distributions of function types (i.e. functional distributions) in an urban area through learning semantics preserved embeddings of points-of-interest (POIs). Specifically, we represent POIs as low-dimensional vectors to capture (1) the spatial co-occurrence patterns of POIs and (2) the se...
Article
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Soil moisture is a fundamental ecological component for climate and hydrological studies. However, the distribution patterns of soil moisture are spatially heterogenous and influenced by multiple environmental factors. The knowledge is still limited in assessing the large-scale spatial heterogeneity of soil moisture in in situ data modelling, in si...
Article
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Accurate identification of urban land-use patterns is essential to rational optimization of urban structure. By combining the external physical characteristics of city parcels obtained from remote sensing images and the socioeconomic attributes revealed by social sensing data, land use can be better classified. However, most of the existing social...
Article
Active travel to school is considered one of the channels for improving schoolchildren's daily physical activity level. The built environment is increasingly recognized as a factor likely to influence travel behavior. However, previous studies have primarily captured the macro-level built environment, usually assumed to be linearly associated with...
Preprint
Full-text available
Human activity analysis based on sensor data plays a significant role in behavior sensing, human-machine interaction, health care, and so on. The current research focused on recognizing human activity and posture at the activity pattern level, neglecting the effective fusion of multi-sensor data and assessing different movement styles at the indivi...
Article
The worldwide coronavirus disease (COVID-19) pandemic has seriously affected the physical health and mental wellbeing (i.e mental stress and suicide intention) of numerous urban inhabitants across the globe. While many studies have elucidated urban parkland enhances and mental wellbeing, the potential for parkland to mitigate mental health burden i...
Article
Abstract: Promoting adolescents’ daily active travel to school (ATS) may be critical for their health and wellbeing. Based on survey data of 473 adolescents and street view images, we employed generalized structural equation models to examine 1) the relationship between objective and perceived streetscape characteristics and adolescents’ ATS and 2)...
Article
The spatial distribution of buildings is one of the key factors influencing the local environment within a city. The quantitative measurement of building distribution can provide critical information for exploring local climate patterns in urban areas. Previous studies mainly focused on the two-dimensional spatial distribution of buildings and igno...
Article
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The severe outbreak of coronavirus disease 2019 ( COVID-19 ) demonstrates the importance of disease risk assessment. The existing risk assessment methods are limited by the real time and accuracy of data. Most of them take the administrative statistical unit as the analysis scale, which has modifiable areal unit problem (MAUP). First, based on a ra...
Chapter
Full-text available
Researches on the urban development and urban planning have an urgent need for building geographic data. Traditional methods of extracting buildings from high-resolution remote sensing images need multi-view images, and have a high cost but a low degree of automation. Thus, these methods are not applied in many fields at large-scale. This study cou...
Article
Unprecedented urbanization in China has directly resulted in residential vacancies, which has seriously stunted sustainable development, a part of China's new-type urbanization plan. Understanding the various types and mixes of residential vacancies is critical for the advancement of our knowledge of speculative urbanism and for devising vacancy-mi...
Article
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Although previous studies have assessed the relationships between visual space indicators and urban residents' psychological perceptions, systematic research on the relationship between the urban visual space and residents' psychological perceptions is still rare. The purpose of this study is to explore the correlation between the urban visual spac...
Article
The spatial structural features and compositional relationships of multivariate geochemicals are influenced by complex geological processes (e.g., diagenesis and mineralization), and can help identify geochemical anomalies and provide key references for mineral resource exploration. However, previous machine-learning-based models often treat spatia...
Article
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Rapid urbanization has tremendously changed the global landscape with profound impacts on our society. Nighttime light (NTL) data can provide valuable information about human activities and socioeconomic conditions, thus has become an effective proxy to measure urban development. By using NTL-derived urban measures from 1992 to 2018, we analyzed th...
Article
Spatiotemporal data fusion is a cost-effective way to produce remote sensing images with high spatial and temporal resolutions using multisource images. Using spectral unmixing analysis and spatial interpolation, the flexible spatiotemporal data fusion (FSDAF) algorithm is suitable for heterogeneous landscapes and capable of capturing abrupt land-c...
Article
Sensing urban greenness from street view data offers a new and alternative way of measuring the association between greenness exposure and subjective wellbeing in developing countries where traditional census data are poor. This paper focuses on the association between life satisfaction and street-level visible greenness exposure at residential and...
Article
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According to the point of interest (POI) data of cultural facilities in 2019, we firstly used a combination measurement of standard deviational ellipse analysis, nearest neighbor index and nuclear density estimation to measure the spatial agglomeration characteristics of cultural facilities in Xi’an. Then we analyzed the influential factors of this...
Preprint
Full-text available
Vector-based cellular automata (CA) based on real land-parcel has become an important trend in current urban development simulation studies. Compared with raster-based and parcel-based CA models, vector CA models are difficult to be widely used because of their complex data structures and technical difficulties. The UrbanVCA, a brand-new vector CA-...
Article
Open space and urban land are interactively attractive in the simulation. • Simulated OS is evaluated with walking accessibility and population coverage rate. • Different mean sizes and time-lags of OS are considered in the simulation. • OS-CA is an effective tool for assessing the policies for creating new OS. Open spaces (OSs) in urban areas play...
Article
Awareness is mounting that urban greenspace is beneficial for residents’ health. While a plethora of studies have focused on greenspace quantity, scant attention has been paid to greenspace quality. Existing methods for assessing greenspace quality is either highly labor-intensive and/or prohibitively time-consuming. This study develops a new machi...
Article
Full-text available
Urban perception is a hot topic in current urban study and plays a positive role in urban planning and design. At present, there are two methods to calculate urban perception. 1) Using a model to learn image features directly automatically; 2) Coupling machine learning and feature extraction based on expert knowledge (e.g. object proportion) method...
Article
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Due to a lack of data and practical models, few studies have extracted tailings pond margins in large areas. In addition, there is no public dataset of tailings ponds available for relevant research. This study proposed a new deep learning-based framework for extracting tailings pond margins from high spatial resolution (HSR) remote sensing images...
Article
Interactions among cities are playing an increasingly significant role in driving urban expansion in urban agglomerations. Many studies have combined the gravitational field model (GFM) with the cellular automata (CA) model to analyze the impact of urban spatial interaction on urban agglomerations. However, previous studies have used threshold-base...
Article
Recent decades have witnessed rapid urban expansion in China and an associated reduction in people’s access to natural outdoor environments (NOE), but whether access to NOE increases people’s subjective well-being (SWB) remains inconclusive in the high-density urban setting. This study aims to examine the association of access to NOE (green and blu...
Article
In China, the illegal adoption of missing persons and especially of missing children is a major public safety issue that affects social and family stability. Recent work has established a trafficking information network developed from a volunteer-managed database of missing persons that identifies and locates node cities and critical paths of illeg...
Article
Cellular Automata (CA) are widely used to model the dynamics within complex land use and land cover (LULC) systems. Past CA model research has focused on improving the technical modeling procedures, and only a few studies have sought to improve our understanding of the nonlinear relationships that underlie LULC change. Many CA models lack the abili...
Article
Mixed land use has been widely used as a planning tool to improve the functionality of cities. However, depicting mixed land use is rather difficult due to its complexities. Previous studies have decomposed urban land areas using either remote sensing images or geospatial big data. Few studies have combined these two data sources because of the lac...
Article
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Big data and artificial intelligence (AI) have provided new methods and opportunities for many applications in geology. Nevertheless, big data and AI-based geoscience applications are still in their infancy, and the methods and objectives are still scattered, lacking a unified theoretical and application framework. This study reviews the applicatio...
Preprint
Full-text available
Cellular Automata (CA) are widely used to model the dynamics within complex land use and land cover (LULC) systems. Past CA model research has focused on improving the technical modeling procedures, and only a few studies have sought to improve our understanding of the nonlinear relationships that underlie LULC change. Many CA models lack the abili...
Article
The biased population coverage and short temporal lengths of newly emerged data sets (e.g., data sets of social media, mobile phones, and smart cards) obstruct the effective analysis of long-term dynamics of landuse patterns, particularly in small and developing cities. This study proposed a framework to delineate and analyze mixed land-use pattern...
Article
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Augmented Reality (AR) for geographic data is an important development direction of geographic information visualization. In recent years, some geographic studies have begun to use head-wear AR devices to visualize geographic data, making geographic spatial information more fully expressed. However, due to the limited computing power of head-wear A...
Article
With the unprecedented pace of urbanization in recent decades, urban vacant residences have increased dramatically. The problem of numerous vacant residences has been severely criticized. The lack of comprehensive data obstructs revealing the spatiotemporal dynamics and the contributing factors of the vacant residences at a fine scale. This study p...
Article
Full-text available
The spatial distribution pattern of jobs and housing plays a vital role in urban planning and traffic construction. However, obtaining the jobs-housing distribution at a fine scale (e.g., the perspective of individual jobs-housing attribute) presents difficulties due to a lack of social media data and useful models. With user data acquired from a l...
Article
Bicycle-transit integration is important for improving the efficiency and sustainability of public transportation systems in urban areas. Urban greenness around metro stations is an important factor affecting the use of cycling to or from metro stations. However, the evidence for the association between urban greenness and cycling behaviors is inco...
Article
The formulation of mixed urban land uses is not only intended to find the ideal scenario of land use but also regarded as a way toward sustainable urban development. We propose a geo-semantic mining approach Traj2Vec to quantify the trajectories of residents as high-dimensional semantic vectors. Then, a random forest (RF) method is used to model th...
Article
Background: Air pollution especially PM2.5 (particulate matter with a diameter of below 2.5 μm) has been recognized as a key environmental factor that affects mental health, but few studies has focused on its influence on older adults who are a vulnerable group. Objective: This study focused on the influence of PM2.5 on health-related behaviors...
Article
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The spatial distribution characteristics and activity patterns of urban populations play essential roles in studies of spatial isolation, optimizing urban resource allocation, and so on. Because of the sensitivity of population activity data and socioeconomic data, previous studies focus mostly on the macro level. They have difficulties in dividing...
Article
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The development of geospatial big data makes it possible to study traffic-congestion issues. In particular floating car data (FCD) is very suitable for it because FCD can help predict traffic-congestion bottlenecks and provide corresponding solutions to address traffic problems. Previous studies have discussed the impacts of rainfall on road speeds...
Article
Vector-based cellular automata (VCA) models have been applied in land use change simulations at fine scales. However, the neighborhood effects of the driving factors are rarely considered in the exploration of the transition suitability of cells, leading to lower simulation accuracy. This study proposes a convolutional neural network (CNN)-VCA mode...
Article
China’s rapid urbanization has led to an increasing level of exposure to air pollution and a decreasing level of exposure to vegetation among urban populations. Both trends may pose threats to psychological well-being. Previous studies on the interrelationships among greenness, air pollution and psychological well-being rely on exposure measures fr...
Article
The rapid development of information technology and location techniques not only leads to an increasing growth of massive geospatial big data but also raises the attention of using these data to complement with remote sensing images. Many efforts have been made to utilize geospatial big data to identify human activity patterns and carry out urban a...
Article
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Background: This study aims to investigate the mechanisms through which neighborhood social reciprocity influences older adults' mental health in China. Methods: This study used data from the 2011-2015 waves of the China Health and Retirement Longitudinal Study. It estimated the effects of neighborhood social reciprocity on older adults' mental...
Article
Full-text available
Background Neighbourhood environment characteristics have been found to be associated with residents’ willingness to conduct physical activity (PA). Traditional methods to assess perceived neighbourhood environment characteristics are often subjective, costly, and time-consuming, and can be applied only on a small scale. Recent developments in deep...
Article
Full-text available
The significance of urban function recognition has stimulated the need for multi-source geospatial data fusion, especially the fusion between remote sensing images and spatiotemporal big data. In previous studies, the natural correspondence across multi-source geospatial data has often been ignored in the description of one object, which would infl...