Yao Yao

China University of Geosciences · School of Geography and Information Engineering

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...

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...

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...

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...

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...

The practice of crime risk mapping, enabled by the utilization of geospatial big data such as street view images, has received significant research attention. However, in situations where available data is scarce, mapping models may suffer from underfitting and generate inaccurate spatial pattern estimations of crime risk. The covert nature of pick...

Rapid land-use change detection (LUCD) is pivotal for refined urban planning and management. In this paper, we investigate LUCD through learning embeddings of points of interest (POIs) from multiple temporalities. There are several prominent challenges: (1) the co-occurrence problem of multi-temporal POIs, (2) the heterogeneity of POI categorizatio...

A site selection framework for urban power substation at micro-scale using spatial optimization strategy and geospatial big data

Predicting the next location of human mobility and its semantic information can support recommendations for location-based services and trajectory mining, such as human mobility pattern recognition and sequential anomaly detection. Previous studies have ignored the implicit correlation between location and spatiotemporal information thereby limitin...

The world is facing more energy crises due to extreme weather and the rapidly growing demand for electricity. Siting new substations and optimizing the location of existing ones are necessary to address the energy crisis. The current site selection lacks consideration of spatial and temporal heterogeneity in urban power demand, which results in unr...

Access to subway stations is important for daily commuting, but scant attention has been given to green space exposure at subway station areas in people's residential neighbourhoods and workplace areas. This paper focuses on the association between street-level green space exposure around subway stations at residential and work locations and people...

Environmental inequalities generated by transit—oriented development (TOD) are of planning and policy relevance in developing countries. Existing literature has pointed out that TOD has the effect of ‘place making’, which means the newly developed transit systems may be able to change the environment and amenities of a certain area. While previous...

Background: Adolescents' daily active travel (AT) has positive health effects. However, previous studies had paid little attention on the differences between the streetscape characteristics-AT relationship on the weekdays and weekends, and most of them only focused on the environmental exposure around home and schools. Methods: This study used data...

Forecasting cities' carbon emissions is an essential support for peak carbon emissions. Previous studies have mainly focused on estimating carbon emissions at large regional scales. Higher spatial resolution mapping of carbon emissions and simulation of future scenarios are important to support locally appropriate policy guidance to reduce carbon e...

Social distancing policies and other restrictive measures have demonstrated efficacy in curbing the spread of the COVID-19 pandemic. However, these interventions have concurrently led to short- and long-term alterations in social connectedness. Comprehending the transformation in intracity social interactions is imperative for facilitating post-pan...

Urban logistics is vital to the development and operation of cities, and its optimization is highly beneficial to economic growth. The increasing customer needs and the complexity of urban systems are two challenges for current logistics optimization. However, little research considers both, failing to balance efficiency and cost. In this study, we...

Poverty threatens human development especially for developing countries, so ending poverty has become one of the most important United Nations Sustainable Development Goals (SDGs). This study aims to explore China's progress in poverty reduction from 2016 to 2019 through time-series multi-source geospatial data and a deep learning model. The povert...

Accurate and efficient assessment of large-scale urban renewal potential is an indispensable prerequisite for managing and facilitating projects. However, few studies consider the built environment when assessing urban renewal potential because it is difficult to measure. Street view images can show the physical setting of a place for humans to per...

we employed generalized structural equation models to examine 1) the relationships between objective and perceived streetscape characteristics and adolescents' active school travel and 2) the mediating roles of perceived safety, walkability, and air pollution. Results showed that street safety, vitality, greenery, and vehicle volume were positively...

Social segregation hinders the development of cities and has become a hot topic in urban research. Existing studies have focused on the difference in the distribution of crowd activities to measure segregation but have ignored the impact of the urban environment on crowd gathering and segregation. To study the impact and understand social segregati...

Awareness is growing that the uneven provision of street urban green space (UGS) may lead to environmental injustice. Most previous studies have focused on the overhead perspective of street UGS provision. However, only a few studies have evaluated the disparities in visible street UGS provision. While a plethora of studies have focused on a single...

Social media data are increasingly used to examine associations between environmental exposures and mental wellbeing. In particular, studies highlight that exposure to natural outdoor environments (NOEs) is associated with fewer negative emotions. Also, people in socioeconomically disadvantaged neighbourhoods tend to benefit more from NOEs than the...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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)...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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-...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...