A5003206195- Land Use and Ecosystem Services
- Remote Sensing and Land Use
- Urban Heat Island Mitigation
- Urban Green Space and Health
- Impact of Light on Environment and Health
- Remote Sensing in Agriculture
- Remote-Sensing Image Classification
- Urban Design and Spatial Analysis
- Geochemistry and Geologic Mapping
- Flood Risk Assessment and Management
- Climate variability and models
- Urban Transport and Accessibility
- Graph Labeling and Dimension Problems
- Soil erosion and sediment transport
- Human Mobility and Location-Based Analysis
- Housing Market and Economics
- Building Energy and Comfort Optimization
- Noise Effects and Management
Tsinghua University
2016-2025
Lanzhou Jiaotong University
2015
Abstract Urban boundaries, an essential property of cities, are widely used in many urban studies. However, extracting boundaries from satellite images is still a great challenge, especially at global scale and fine resolution. In this study, we developed automatic delineation framework to generate multi-temporal dataset (GUB) using 30 m artificial impervious area (GAIA) data. First, delineated initial boundary by filling inner non-urban areas each city. A kernel density estimation approach...
High-resolution urban land use maps have important applications in planning and management, but the availability of these is low countries such as China. To address this issue, we developed a protocol to identify functions over large areas using satellite images open social data. We first derived parcels from road networks contained Open Street Map (OSM) used basic mapping unit. then 10 features Points Interest (POI) data two indices obtained Landsat 8 Operational Land Imager (OLI) classify...
Light pollution, a phenomenon in which artificial nighttime light (NTL) changes the form of brightness and darkness natural areas such as protected (PAs), has become global concern due to its threat biodiversity. With ongoing urbanization climate change, pollution status PAs deserves attention for mitigation adaptation. In this study, we developed framework evaluate PAs, using NTL time series data. First, classified (30,624) into three categories: non-polluted (5974), continuously polluted...
Timely and accurate wetland information is necessary for resource management. Recent advances in machine learning remote sensing have facilitated cost-effective monitoring of wetlands. However, reliable methods fine-grained rapid mapping are still lacking. To address the issue, a sample set with 20 categories China was collected based on sampling strategy that combines automatic generation visual interpretation. Simultaneously, novel multi-stage method classification proposed, which...
Urban land use mapping is critical to understanding human activities in space. The first national result of essential urban categories China (EULUC-China) was released 2019. However, the overall accuracies some plain cities such as Beijing, Chengdu, and Zhengzhou were lower than 50% because many parcel-based units are large with mixed uses. To address this shortcoming, we proposed an area interest (AOI)-based approach, choosing Beijing our study area. process includes two major steps. First,...
Abstract. The information of global spatially explicit urban extents under scenarios is important to mitigate future environmental risks caused by urbanization and climate change. Although dynamics extent were commonly modeled with conversion from non-urban using cellular-automata (CA)-based models, gradual changes impervious surface area (ISA) at the pixel level limitedly explored in previous studies. In this paper, we developed a dataset fractional 1 km resolution 2020 2100 (5-year...
High-quality training and validation samples are critical components of land-cover land-use mapping tasks in remote sensing. For large area it is much more difficult to build such sample sets due the huge amount work involved collection image processing. As satellite data become available, a new trend emerges that takes advantage images acquired beyond greenest season. This has created need for constructing can be used classifying multiple seasons. On other hand, seasonal information also...
Cellular automata (CA)-based models have been extensively used in urban expansion modeling because of their simplicity, flexibility and intuitiveness. Previous studies on CA-based growth mainly focused the process spatial allocation increased lands; however, temporal contexts during simulation not properly explored. In this study, we examined influence initial seeds (i.e. extent maps), transition rules, demands areas) Beijing, China, over a long period 1984–2013. Comparison annual model...
Timely cropland information is crucial for ensuring food security and promoting sustainable development. Traditional field survey methods are time-consuming costly, making it difficult to support rapid monitoring of large-scale changes. Furthermore, most existing studies focus on evaluation from a single aspect such as quantity or quality, thus cannot comprehensively reveal spatiotemporal characteristics cropland. In this study, method evaluating the quality using multi-source remote...
Urban cellular automata (CA) models propagate and accumulate errors during the modeling process due to model structure or stochastic processes involved. It is feasible assimilate real-time observations into an urban CA reduce uncertainties. However, assimilation performance sensitive spatio-temporal units in algorithm, that is, spatial block size window length (temporal interval). In this study, we coupled model, ensemble Kalman filter (EnKF) a Logistic-CA simulate dynamic Beijing over...
Abstract. The information of global spatially explicit urban extents under scenarios is important to mitigate future environmental risks caused by urbanization and climate change. Although dynamics extent were commonly modelled with conversion from non-urban using cellular automata (CA) based models, gradual changes impervious surface area (ISA) at the pixel level limitedly explored in previous studies. In this paper, we developed a dataset fractional 1 km resolution 2020 2100 (5-year...