Yongze Song

Curtin University

A reasonable and adequate understanding of spatial association between geographical variables is the basis of spatial statistical inference and geocomputation, such as spatial prediction. Most of the current models for exploring spatial association of variables are constructed using data at sample locations. In this study, approaches for exploring...

Non-pharmaceutical interventions (NPIs) and vaccination are two fundamental approaches for mitigating the coronavirus disease 2019 (COVID-19) pandemic. However, the real-world impact of NPIs versus vaccination, or a combination of both, on COVID-19 remains uncertain. To address this, we built a Bayesian inference model to assess the changing effect...

Understanding geographical characteristics of distribution patterns and spatial association is essential for spatial statistical inference such as factor exploration and spatial prediction. The geographical similarity principle was recently developed to explain the association between geographical variables. It describes the comprehensive degree of...

Spatial heterogeneity refers to uneven distributions of geographical variables. Spatial interpolation methods that utilize spatial heterogeneity are sensitive to the way in which spatial heterogeneity is characterized. This study developed a Generalized Heterogeneity Model (GHM) for characterizing local and stratified heterogeneity within variables...

The explanation of spatial errors in geospatial modelling has long been a challenge. This study introduces an index that captures the complexity of local spatial distribution, which can partially provide insight into spatial errors. While previous studies have explored the complexity of geographical data from various perspectives , there is limited...

The Blue Nile River is an indispensable source of livelihood for over 90 million people in Ethiopia, Sudan, and Egypt. Recently, Ethiopia has constructed the Grand Ethiopian Renaissance Dam (GERD), the largest in Africa, which could potentially alter the geomorphology of the river regime, and impact downstream countries. This study offers the first...

Access to urban greenspace is a fundamental requirement in providing critical ecosystem services, improving health and well-being across all ages, fostering social cohesion, and addressing prevalent health disparities in an increasingly urbanised society. Access refers to the availability of urban greenspace, while accessibility indicates the ease...

The carbon isotope composition (δ13CLeaf) of C3 plant leaves provides valuable information on the carbon-water cycle of vegetation and their responses to climate change within terrestrial ecosystems. However, global applications of δ13CLeaf are hindered by a lack of global long-term spatial maps (isoscapes) that capture vegetation δ13CLeaf variatio...

The Yangtze River Basin (YRB), home to around 400 million people, boasts of abundant water resources and significant spatial heterogeneity. Revealing the driving factors of water storage changes in YRB is essential for effective water resource management and sustainable development. In this study, we assess the drivers of total water storage (TWS)...

Resilience has a critical role to promote human well-being in turbulent environments. However, extensive interventions and stimulus measures not only achieve resilience goals with numerous unacceptable consequences, but also highlight the narrow definition of resilience. The study proposes the concept of resilience effectiveness to constrain the un...

Identifying the factors influencing wetland variations is crucial for understanding the relationship of climate change with wetland conservation and management. The wetland distribution is associated with multiple variables, and the interactions among these variables are complex. In this study, we aim to explore an interpretable and quantitative an...

In recent years, with the rapid advancement of China’s urbanization, the contradiction between urban development and the ecological environment has become increasingly prominent, and the urban ecological system now faces severe challenges. In this study, we proposed an ecological index-based approach to monitor and evaluate the ecological environme...

Sustainable development in impoverished areas is still a global challenge owing to trade-offs between development and conservation. There are large poverty-stricken areas (PSAs) in China, which overlap highly with ecologically sensitive areas. China has made great efforts to alleviate poverty over the years. The coordinated relationship between the...

Urban greening (UG) affects local climate by altering surface energy balance, while long-term UG cooling potential, patterns, and contribution to curbing urban warming remain unclear. Here we designed an novel statistical model with universal applicability to evaluate the cooling potential of UG (CPUG) and created the first CPUG map for China. By e...

The carbon and water cycle patterns of frozen soil ecosystems in regions, such as the Qinghai-Tibet Plateau (QTP), which have fragile and sensitive ecologies, are possibly affected by climate change. However, these patterns along the gradients of varying degrees of freezing remain poorly understood. In this study, we examine the spatio-temporal pat...

Floating islands in Lake Victoria, the world’s second-largest fresh water lake, disrupt transportation, fisheries, irrigation, and water quality. Despite their impact, the dynamics of these islands remain unexplored. This study investigates island dynamics within the Nalubaale, Kiira, and Bujagali dams in Uganda, exploring the causes of their forma...

The global interest in moving towards a sustainable future has grown exponentially at all levels. The United Nations' Sustainable Development Goals (SDGs), adopted by world leaders in 2015, provide an integrated framework to track progress toward sustainability (UN, 2019). Textual data, such as public statements posted on websites, organization rep...

Geocomputation and geospatial artificial intelligence (GeoAI) have essential roles in advancing geographic information science (GIS) and Earth observation to a new stage. GeoAI has enhanced traditional geospatial analysis and mapping, altering the methods for understanding and managing complex human–natural systems. However, there are still challen...

Understanding disease treatment-seeking behaviors is a fundamental issue for national and regional healthcare management. However, treatment-seeking behaviors are complex and affected by various factors, including disease incidence, healthcare resources, and population accessibility to hospitals. Geospatial analysis is a practical approach to inves...

Industrial regions and relevant infrastructures are known to contribute to air pollutant emissions; thus, a detailed investigation of the air pollutant concentrations of a region based on specific land uses, with spatial reasoning, can support smart regional planning. However, the current knowledge about the spatial patterns that indicate the relat...

The power-law scaling theory has been widely applied in urban studies. Industrial development is tied to cities. However, current research on scaling pace development of industrial features in cities, and industrial features’ association with urban indicators in cities are limited. This study develops power-law scaling regression and robust geograp...

Transport infrastructure is a fundamental component of the whole infrastructure system and socio-economic development. However, it is still a challenge to identify factors affecting large-scale infrastructure due to the lack of high-quality data and inconsistent methods. To address this issue, this study developed a comparison of data-and knowledge...

Human-environment interactions (HEI) are dynamic processes involving a wide range of research areas. The complicated interaction processes, with land cover change as an intermediate process, have been investigated for decades. Urban construction, as a type of human activity, is an important part of the HEI. Earth observation (EO) techniques offer d...

Spatial stratified heterogeneity (SSH) refers to the geographical phenomena in which the geographical attributes within-strata are more similar than the between-strata, which is ubiquitous in the real world and offers information implying the causation of nature. Stratification, a primary approach to SSH, generates strata using a priori knowledge o...

Science of Remote Sensing Special Issue Call for Papers https://www.journals.elsevier.com/science-of-remote-sensing/forthcoming-special-issues/wildfire-remote-sensing

iScience (Cell Press multidisciplinary journal, JCR Q1, Impact Factor 6.107) Call for Papers: https://www.cell.com/iscience/special-issues/call-for-papers/geoai-shaping-earth-and-cities Guest Editors: Dr. Yongze Song (Curtin University), Dr. Filip Biljecki (National University of Singapore), Dr. Gustau Camps-Valls (Universitat de Valencia), and Dr...

Understanding the time required for meteorological drought to propagate to hydrological drought is crucial for producing early warnings of future hydrological droughts. However, most previous studies of this topic have used observed runoff (or streamflow), which usually has been disturbed by human activities, and accordingly, the calculated drought...

The use of fossil fuels has been a major contributor to global climate change. To mitigate the negative impact of fossil fuels, renewable energy (RE) has been increasingly promoted. This study aims to investigate factors impacting the adoption of RE in the residential sector, using the U.S. as a case study. Residential RE consumption rate data in 5...

Geographical detector (GD) is a method to measure spatial associations using a power of determinant (PD) value that compares the variance of data within spatial zones and in the whole study area. Recent studies have implemented GD in diverse fields, such as environmental and socio-economic issues. Spatial data discretization is an essential stage f...

There is global interest in spectroscopy and the development of large and diverse soil spectral libraries (SSL) to model soil organic carbon (SOC) and monitor, report, and verify (MRV) its changes. The reason is that increasing SOC can improve food production and mitigate climate change. However, 'global' modelling of SOC with such diverse and hype...

Small data samples are still a critical challenge for spatial predictions. Land use regression (LUR) is a widely used model for spatial predictions with observations at a limited number of locations. Studies have demonstrated that LUR models can overcome the limitation exhibited by other spatial prediction models which usually require greater spati...

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...

Increasing quantity and quality of roads are pathways to sustainable road infrastructure development. Understanding quantity-quality relations of road sustainability is critically required for strategic decision making. However, few knowledge are available about assessing quantity-quality relations of road sustainability from a perspective of spati...

Governments worldwide have rapidly deployed non-pharmaceutical interventions (NPIs) to mitigate the COVID-19 pandemic. However, the effect of these individual NPI measures across space and time has yet to be sufficiently assessed, especially with the increase of policy fatigue and the urge for NPI relaxation in the vaccination era. Using the decay...

Given the important role of green environments playing in healthy cities, the inequality in urban greenspace exposure has aroused growing attentions. However, few comparative studies are available to quantify this phenomenon for cities with different population sizes across a country, especially for those in the developing world. Besides, commonly...

Non-pharmaceutical interventions (NPIs) and vaccination are two fundamental approaches to mitigate the coronavirus disease 2019 (Covid-19) pandemic. Vaccination strategies are generally less costly and socially/economically disruptive than NPI strategies, such as business closures, social distancing, and face mask mandates, as evidenced by highly v...

Strategic maintenance is essential for sustainable road infrastructure development. Accurate estimation of road maintenance effects can support the assessment of maintenance strategies and reasonable allocation of budgets and resources. Road deterioration is affected by sophisticated factors, but accurate investigation of the integrated deteriorati...

Soil properties, such as organic carbon, pH and clay content, are critical indicators of ecosystem function. Visible–near infrared (vis–NIR) reflectance spectroscopy has been widely used to cost-efficiently estimate such soil properties. Multivariate modelling, such as partial least squares regression (PLSR), and machine learning are the most commo...

Background Air pollution has been related to incidence of type 2 diabetes (T2D). We assessed the joint association of various air pollutants with the risk of T2D and examined potential modification by obesity status and genetic susceptibility on the relationship. Methods and findings A total of 449,006 participants from UK Biobank free of T2D at b...

Remote sensing and geospatial techniques are being used to provide large-scale and regional solutions for achieving the sustainable development goals (SDGs) of the United Nations, including sustainable infrastructure development. Road transportation infrastructure has a significant contribution to the economy, but it also increases environmental pr...

Link: https://www.journals.elsevier.com/international-journal-of-applied-earth-observation-and-geoinformation/call-for-papers/call-for-papers-on-special-issue-recent-advances-in-geocomputation-and-geoai-for-mapping

Geographical variables are usually not independent of each other. Hence, it is necessary to investigate the effect of interactions among explanatory variables on a response variable to characterize spatially enhanced or weakened relationships among all variables. The geographical detector (GD) model identifies zones for each explanatory variable, d...

Infrastructure is a fundamental sector for sustainable development and Earth observation has great potentials for sustainable infrastructure development (SID). However, implementations of the timely, large–scale and multi–source Earth observation are still limited in satisfying the huge global requirements of SID. This study presents a systematical...

Worldwide governments have rapidly deployed non-pharmaceutical interventions (NPIs) to mitigate the COVID-19 pandemic, together with the large-scale rollout of vaccines since late 2020. However, the effect of these individual NPI and vaccination measures across space and time has not been sufficiently explored. By the decay ratio in the suppression...

Worldwide governments have rapidly deployed non-pharmaceutical interventions (NPIs) to mitigate the COVID-19 pandemic, together with the large-scale rollout of vaccines since late 2020. However, the effect of these individual NPI and vaccination measures across space and time has not been sufficiently explored. By the decay ratio in the suppression...

Models of spatial stratified heterogeneity can be used to identify associations of geographical attributesthrough the comparison between regional variances and the global variance of data (Wang et al. 2010, Wanget al. 2016). The geographical detector (GD) is a widely used model to estimate power of determinants (PD)regarding the theory of spatial s...

Climatic impact on re-established ecosystems at reclaimed mined lands may have changed. However, little knowledge is available about the difference in vegetation–climate relationships between reclaimed and unmined lands. In this study, ecological responses to climatic variability on reclaimed and neighbouring unmined lands were estimated using remo...

Platform decommissioning decision making is a major issue as many of the existing offshore oil and gas platforms (OOGPs) require to be decommissioned. The cost and environmental impact are two main criteria for OOGP decommissioning. This paper reviews OOGP decommissioning factors and the current estimation methodologies of decommissioning cost and...

Soil moisture (SM) is a fundamental environmental variable for characterizing climate, land surface and atmosphere. In recent years, several SM products have been developed based on remote sensing (RS), land surface model (LSM) or land data assimilation system (LDAS). However, little knowledge is available in understanding spatial patterns of the u...

Aims : Little is known about the relation between the long-term joint exposure to various ambient air pollutants and the incidence of heart failure (HF). We aimed to assess the joint association of various air pollutants with HF risk and examine the modification effect of the genetic susceptibility. Methods and results : This study included 432...

Road infrastructure performance is closely associated with passengers and freight transportation systems and socio-economic development. The performance of road infrastructure is commonly measured by sensor-monitored indicators, and the ability of monitored indicators in revealing actual performance is generally determined by decision makers and ro...

Road infrastructure is an important source of carbon emissions. To estimate the carbon emissions of roads, life cycle assessment (LCA) methods are widely used. Due to budget constraints, road maintenance and rehabilitation (M&R) is preferred by road agencies over new construction. However, existing LCA studies on roads have limited considerations o...

Road network conditions and road quality are directly linked with the performance of an entire infrastructure system. As sensor monitoring of road deteriorations has rapidly increased, road infrastructure performance can now be assessed using multiple measures. However, more effective and accurate quantitative analysis methods are increasingly requ...

Spatial heterogeneity represents a general characteristic of the inequitable distributions of spatial issues. The spatial stratified heterogeneity analysis investigates the heterogeneity among various strata of explanatory variables by comparing the spatial variance within strata and that between strata. The geographical detector model is a widely...

Although efficient hyperspectral image (HSI) denoising relies on complete and accurate description and modeling the spatial-spectral signal in HSI, the current approaches do not fully account for key characteristics of HSI, i.e., the mixed spectra effect, the spatial nonstationarity effect, and noise variance heterogeneity effect. To address this i...

Due to the instantaneous field-of-view (IFOV) of the sensor and diversity of land cover types, some pixels, usually named mixed pixels, contain more than one land cover type. Soft classification can predict the portion of each land cover type in mixed pixels in the absence of spatial distribution. The spatial distribution information in mixed pixel...

A new subpixel mapping (SPM) method based on a super-resolution convolutional neural network (SRCNN) is proposed to generate subpixel land cover maps for hyperspectral images. The SRCNN is used to restore the image spatial resolution from a coarse input image, which is equivalent to interpolation. First, an efficient subpixel convolutional neural n...

High-quality and long time-series soil moisture (SM) data are increasingly required for the Qinghai-Tibet Plateau (QTP) to more accurately and effectively assess climate change. In this study, to evaluate the accuracy and effectiveness of SM data, five passive microwave remotely sensed SM products are collected over the QTP, including those from th...

China has been the largest contributor to global carbon emissions since 2008, with its building and construction industry considered as one of the most significant sources. However, few studies have been conducted on analyzing the influencing factors of the carbon emissions following a life cycle perspective. This study aims to evaluate the carbon...

Geostatistical methods have been widely used for spatial prediction and the assessment of traffic issues. Most previous studies use point-based interpolation, but they ignore the critical information of the road segment itself. This can lead to inaccurate predictions, which will negatively affect decision making of road agencies. To address this pr...

Road infrastructure is important to the well-being and economic health of all nations. The performance of road pavement infrastructure is sophisticated and affected by numerous factors and varies greatly across different roads. Large scale spatial analysis for assessing road infrastructure performance is increasingly required for road management, t...

Urban forms reflect spatial structures of cities, which have been consciously and dramatically changing in China. Fast urbanisation may lead to similar urban forms due to similar habits and strategies of city planning. However, whether urban forms in China are identical or significantly different has not been empirically investigated. In this paper...

An increasing number of offshore platforms across the world will be retired and decommissioned in the coming decade. Since one stakeholder usually needs to decommission multiple offshore platforms simultaneously, topsides disassembly, including module lift operations and vessel transport schedule, should be carefully planned with necessary concerns...

The Leadership in Energy and Environmental Design for Neighborhood Development (LEED ND) rating system has been considered one of the major tools to assess the performance of green communities. However, few studies have been conducted on how the traditional focus on green building can be effectively transitioned to green communities. In order to fa...

The integration of facility management and building information modelling (BIM) is an innovative and critical undertaking process to support facility maintenance and management. Even though recent research has proposed various methods and performed an increasing number of case studies, there are still issues of communication processes to be address...

Accidents on offshore oil and gas platforms (OOGPs) usually cause serious fatalities and financial losses considering the demanding environment where such platforms are located and the complicated topsides structure that the platforms have. Conducting evacuation planning on OOGPs is challenging. Computational tools are considered as a good way to p...

Charitable foundations are a critical part of public services. However, there is a large gap between the locations and expenditures of charitable foundations and the real population needs for most nations. Three types of Chinese local charity foundations, i.e., those for poverty, education and medical assistance, are used as examples to explore the...

Quantification and assessment of nation-wide population access to health care services is a critical undertaking for improving population health and optimizing the performance of national health systems. Rural-urban unbalance of population access to health care services is widely involved in most of nations. This unbalance is also potentially affec...

Leadership in Energy and Environmental Design (LEED) is one of the most widely recognized green building rating systems. With more than 20% of the projects certified in non-United States (US) countries, LEED's global impact has been increasing and it is critically important for developers and regulatory authorities to understand LEED's performance...

The improvement of construction productivity has always been a key concern for both researchers and project managers. Several studies have analyzed construction productivity from different perspectives; however, little research has been conducted to evaluate the impact of outdoor ambient environmental factors on construction productivity, especiall...

The rational function model (RFM) is widely applied to orthorectification of aerial and satellite imagery. This article proposes a new method named Ortho-WTLS to solve the RFM in remote-sensing imagery orthorectification. Based on a weighted total least squares (WTLS) estimator, the proposed method allows one to handle coordinates of ground control...

The integration of building information modelling (BIM) and geographic information system (GIS) in construction management is a new and fast developing trend in recent years, from research to industrial practice. BIM has advantages on rich geometric and semantic information through the building life cycle, while GIS is a broad field covering geovis...

Accidents on offshore oil and gas platforms (OOGPs) usually cause serious fatalities and financial losses considering demanding environment platforms locate and complex topsides structure platforms own. Evacuation planning on platforms is usually challenging. The computational tool is a good choice to plan evacuation by emergency simulation. Howeve...

Accidents on offshore oil and gas platforms (OOGPs) usually cause serious fatalities and financial losses considering demanding environment platforms locate and complex topsides structure platforms own. Evacuation planning on platforms is usually challenging. The computational tool is a good choice to plan evacuation by emergency simulation. Howeve...

Background Offshore oil and gas platforms generally have a lifetime of 30 to 40 years, and platform decommissioning is a major issue because many of the existing offshore oil and gas platforms are reaching the end of their service life. There are many possible options for decommissioning offshore oil and gas platforms, and each decommissioning opti...

The concept of green building has gained rapid recognition recently. Developed by the U.S. Green Building Council, the Leadership in Energy and Environmental Design (LEED) is one of the most successful green building rating systems. Understanding the performance of LEED certified buildings on various LEED credits is therefore important for practiti...

Geographically weighted regression (GWR) is an important local method to explore spatial non-stationarity in data relationships. It has been repeatedly used to examine spatially varying relationships between epidemic diseases and predictors. Malaria, a serious parasitic disease around the world, shows spatial clustering in areas at risk. In this ar...

Background: Malaria is one of the most severe parasitic diseases in the world. Spatial distribution estimation of malaria and its future scenarios are important issues for malaria control and elimination. Furthermore, sophisticated nonlinear relationships for prediction between malaria incidence and potential variables have not been well construct...