Wenwu Tang
Biographic Data
| ID | 3635615 |
|---|---|
| NAME | Wenwu Tang |
| GIVEN NAMES | Wenwu |
| FAMILY NAME | Tang |
| SIGNATURE | TANG W |
| AFFILIATIONS | University of North Carolina at Charlotte |
| ORCID | 0000-0001-7870-177X |
| VERIFIED | Yes |
| TOTAL WORKS | 18 |
| TOTAL CITATIONS | 18 |
| AUTHOR COUNT | 18 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2008 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 3 |
A web-based spatial decision support system of Covid-19 wastewater surveillance on a university campus
Explicit Incorporation of Spatial Autocorrelation in 3D Deep Learning for Geospatial Object Detection
Three-dimensional (3D) geospatial object detection has become essential for 3D geospatial studies driven by explosive growth in 3D data. It is extremely labor- and cost-intensive, though, as it often requires manual detection. Deep learning has been recently used to automate object detection within 3D context. Yet, addressing spatial dependency in 3D data and how it might inform deep learning for 3D geospatial object detection remains a significa…
Simulating urban expansion using cellular automata model with spatiotemporally explicit representation of urban demand
Mixed landform with high-rise buildings
Introduction to Big Data Computing for Geospatial Applications
The convergence of big data and geospatial computing has brought challenges and opportunities to GIScience with regards to geospatial data management, processing, analysis, modeling, and visualization. This special issue highlights recent advancements in integrating new computing approaches, spatial methods, and data management strategies to tackle geospatial big data challenges and meanwhile demonstrates the opportunities for using big data for …
Patch-based cellular automata model of urban growth simulation
Agent-Based Land Change Modeling of a Large Watershed
Land use and land cover change has been recognized to have significant environmental impacts in a watershed, such as regulation of water quality. However, the identification of potential regions that are sensitive to land change activities for the protection of water quality poses a grand challenge particularly in a large watershed. These potential regions are o en associated with critical thresholds in terms of, for example, water quality. In th…
An adaptive agent-based optimization model for spatial planning
GPU Computing
Graphics processing units (GPUs) are coprocessors built using a many‐core architecture to accelerate general‐purpose computation in general, and spatial analysis and modeling in particular. The use of programmable GPUs for parallel spatial analysis and modeling has received much recent attention, and GPUs are available in a variety of alternative computing devices, from smartphones to high‐performance clusters. Leveraging GPUs for accelerating sp…
Land Use and Land Cover Change in the Qinghai Lake Region of the Tibetan Plateau and Its Impact on Ecosystem Services
Exploration of land use and land cover change (LULCC) and its impacts on ecosystem services in Tibetan plateau is valuable for landscape and environmental conservation. In this study, we conduct spatial analysis on empirical land use and land cover data in the Qinghai Lake region for 1990, 2000, and 2010 and simulate land cover patterns for 2020. We then evaluate the impacts of LULCC on ecosystem service value (ESV), and analyze the sensitivity o…
Property rights of urban underground space in China
Spatially Explicit Landscape-Level Ecological Risks Induced by Land Use and Land Cover Change in a National Ecologically Representative Region in China
Land use and land cover change is driven by multiple influential factors from environmental and social dimensions in a land system. Land use practices of human decision-makers modify the landscape of the land system, possibly leading to landscape fragmentation, biodiversity loss, or environmental pollution-severe environmental or ecological impacts. While landscape-level ecological risk assessment supports the evaluation of these impacts, investi…
Global Sensitivity Analysis of a Large Agent-Based Model of Spatial Opinion Exchange
Sensitivity analysis is an important step in agent-based modeling of complex adaptive spatial systems to evaluate the contribution of influential variables to model response. Sensitivity analysis of agent-based models is computationally demanding, however, and this analysis tends to be intractable for large agent-based modeling. This computational challenge greatly limits our ability to investigate complex spatial dynamics using large agent-based…
Futures
We present a multilevel modeling framework for simulating the emergence of landscape spatial structure in urbanizing regions using a combination of field-based and object-based representations of land change. The FUTure Urban-Regional Environment Simulation (FUTURES) produces regional projections of landscape patterns using coupled submodels that integrate nonstationary drivers of land change: per capita demand, site suitability, and the spatial …
Parallel agent-based simulation of individual-level spatial interactions within a multicore computing environment
The computational approach of agent-based models (ABMs) supports the representation of interactions among spatially situated individuals as a decentralized process giving rise to space–time complexity in geographic systems. To cope with the computational complexity of these models, this article proposes a parallel approach that leverages the power of multicore systems, as these architectures have quickly become ubiquitous in high-performance and …
Agent‐based Modeling of Animal Movement
Animal movement is a complex spatiotemporal phenomenon that has intrigued researchers from many disciplines. Interactions among animals, and between animals and the environments that they traverse, play an important role in the development of the complex ecological and social systems in which they are embedded. Agent‐based models have been increasingly applied as a computational approach to the study of animal movement across landscapes. In this …
The Explicit Representation of Context in Agent-Based Models of Complex Adaptive Spatial Systems
The dynamic behavior of complex adaptive spatial systems is driven by interactions that occur among system components. The proper representation of individual–individual and individual–environment interaction in agent-based simulations of such systems is, therefore, of paramount importance to model design. In this article we develop and implement a context-driven, agent-based modeling approach that supports the explicit representation of situatio…
Simulating Complex Adaptive Geographic Systems
The objective of this paper is to present a spatially explicit agent-based simulation framework with a supporting software package to explore complex adaptive geographic systems. This framework is particularly suitable for modeling entities that are contextually aware, knowledge driven, and adaptive because it represents them as geographically aware intelligent agents. Fundamental advances in the explicit representation of contextual information,…
Futures
We present a multilevel modeling framework for simulating the emergence of landscape spatial structure in urbanizing regions using a combination of field-based and object-based representations of land change. The FUTure Urban-Regional Environment Simulation (FUTURES) produces regional projections of landscape patterns using coupled submodels that integrate nonstationary drivers of land change: per capita demand, site suitability, and the spatial …
Property rights of urban underground space in China
Simulating Complex Adaptive Geographic Systems
The objective of this paper is to present a spatially explicit agent-based simulation framework with a supporting software package to explore complex adaptive geographic systems. This framework is particularly suitable for modeling entities that are contextually aware, knowledge driven, and adaptive because it represents them as geographically aware intelligent agents. Fundamental advances in the explicit representation of contextual information,…
Global Sensitivity Analysis of a Large Agent-Based Model of Spatial Opinion Exchange
Sensitivity analysis is an important step in agent-based modeling of complex adaptive spatial systems to evaluate the contribution of influential variables to model response. Sensitivity analysis of agent-based models is computationally demanding, however, and this analysis tends to be intractable for large agent-based modeling. This computational challenge greatly limits our ability to investigate complex spatial dynamics using large agent-based…
Mixed landform with high-rise buildings
Simulating Complex Adaptive Geographic Systems
The objective of this paper is to present a spatially explicit agent-based simulation framework with a supporting software package to explore complex adaptive geographic systems. This framework is particularly suitable for modeling entities that are contextually aware, knowledge driven, and adaptive because it represents them as geographically aware intelligent agents. Fundamental advances in the explicit representation of contextual information,…
Agent‐based Modeling of Animal Movement
Animal movement is a complex spatiotemporal phenomenon that has intrigued researchers from many disciplines. Interactions among animals, and between animals and the environments that they traverse, play an important role in the development of the complex ecological and social systems in which they are embedded. Agent‐based models have been increasingly applied as a computational approach to the study of animal movement across landscapes. In this …
The Explicit Representation of Context in Agent-Based Models of Complex Adaptive Spatial Systems
The dynamic behavior of complex adaptive spatial systems is driven by interactions that occur among system components. The proper representation of individual–individual and individual–environment interaction in agent-based simulations of such systems is, therefore, of paramount importance to model design. In this article we develop and implement a context-driven, agent-based modeling approach that supports the explicit representation of situatio…
Parallel agent-based simulation of individual-level spatial interactions within a multicore computing environment
The computational approach of agent-based models (ABMs) supports the representation of interactions among spatially situated individuals as a decentralized process giving rise to space–time complexity in geographic systems. To cope with the computational complexity of these models, this article proposes a parallel approach that leverages the power of multicore systems, as these architectures have quickly become ubiquitous in high-performance and …
Futures
We present a multilevel modeling framework for simulating the emergence of landscape spatial structure in urbanizing regions using a combination of field-based and object-based representations of land change. The FUTure Urban-Regional Environment Simulation (FUTURES) produces regional projections of landscape patterns using coupled submodels that integrate nonstationary drivers of land change: per capita demand, site suitability, and the spatial …
Global Sensitivity Analysis of a Large Agent-Based Model of Spatial Opinion Exchange
Sensitivity analysis is an important step in agent-based modeling of complex adaptive spatial systems to evaluate the contribution of influential variables to model response. Sensitivity analysis of agent-based models is computationally demanding, however, and this analysis tends to be intractable for large agent-based modeling. This computational challenge greatly limits our ability to investigate complex spatial dynamics using large agent-based…
Spatially Explicit Landscape-Level Ecological Risks Induced by Land Use and Land Cover Change in a National Ecologically Representative Region in China
Land use and land cover change is driven by multiple influential factors from environmental and social dimensions in a land system. Land use practices of human decision-makers modify the landscape of the land system, possibly leading to landscape fragmentation, biodiversity loss, or environmental pollution-severe environmental or ecological impacts. While landscape-level ecological risk assessment supports the evaluation of these impacts, investi…
GPU Computing
Graphics processing units (GPUs) are coprocessors built using a many‐core architecture to accelerate general‐purpose computation in general, and spatial analysis and modeling in particular. The use of programmable GPUs for parallel spatial analysis and modeling has received much recent attention, and GPUs are available in a variety of alternative computing devices, from smartphones to high‐performance clusters. Leveraging GPUs for accelerating sp…
Land Use and Land Cover Change in the Qinghai Lake Region of the Tibetan Plateau and Its Impact on Ecosystem Services
Exploration of land use and land cover change (LULCC) and its impacts on ecosystem services in Tibetan plateau is valuable for landscape and environmental conservation. In this study, we conduct spatial analysis on empirical land use and land cover data in the Qinghai Lake region for 1990, 2000, and 2010 and simulate land cover patterns for 2020. We then evaluate the impacts of LULCC on ecosystem service value (ESV), and analyze the sensitivity o…
Property rights of urban underground space in China
An adaptive agent-based optimization model for spatial planning
Introduction to Big Data Computing for Geospatial Applications
The convergence of big data and geospatial computing has brought challenges and opportunities to GIScience with regards to geospatial data management, processing, analysis, modeling, and visualization. This special issue highlights recent advancements in integrating new computing approaches, spatial methods, and data management strategies to tackle geospatial big data challenges and meanwhile demonstrates the opportunities for using big data for …
Patch-based cellular automata model of urban growth simulation
Agent-Based Land Change Modeling of a Large Watershed
Land use and land cover change has been recognized to have significant environmental impacts in a watershed, such as regulation of water quality. However, the identification of potential regions that are sensitive to land change activities for the protection of water quality poses a grand challenge particularly in a large watershed. These potential regions are o en associated with critical thresholds in terms of, for example, water quality. In th…
Simulating urban expansion using cellular automata model with spatiotemporally explicit representation of urban demand
Mixed landform with high-rise buildings
Explicit Incorporation of Spatial Autocorrelation in 3D Deep Learning for Geospatial Object Detection
Three-dimensional (3D) geospatial object detection has become essential for 3D geospatial studies driven by explosive growth in 3D data. It is extremely labor- and cost-intensive, though, as it often requires manual detection. Deep learning has been recently used to automate object detection within 3D context. Yet, addressing spatial dependency in 3D data and how it might inform deep learning for 3D geospatial object detection remains a significa…
A web-based spatial decision support system of Covid-19 wastewater surveillance on a university campus
Computer Science (15 works) · Geography (10 works) · Land Use and Ecosystem Services (10 works) · Artificial Intelligence (6 works) · Cartography (5 works) · Civil engineering (5 works) · Engineering (5 works) · Environmental Science (5 works) · Land use (5 works) · Data science (4 works)