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Yun Chen  - - - 
Top co-authors See all
Peter Fox

77 shared publications

Tetherless World Constellation, Rensselaer Polytechnic Institute, 110 Eighth Street, Troy, NY 12180

Quan Bai

75 shared publications

School of Engineering, Computer & Mathematical Sciences, Auckland University of Technology, Auckland, New Zealand

Paulo A. De Souza

38 shared publications

CSIRO Digital Productivity Flagship, Hobart, Tasmania 7004, Australia

Shiqiang Zhang

37 shared publications

Shaanxi Key Laboratory of Earth Surface System and Environmental Carrying Capacity; Northwest University; Xi'an China

Lei Gao

33 shared publications

CSIRO Land and Water Flagship and Agriculture Flagship, Waite Campus, Urrbrae, South Australia, Australia

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Publication Record
Distribution of Articles published per year 
(2009 - 2019)
Total number of journals
published in
 
10
 
Publications See all
Article 0 Reads 0 Citations Emergency Evacuation Simulation and Management Optimization in Urban Residential Communities Hao Chu, Jia Yu, Jiahong Wen, Min Yi, Yun Chen Published: 02 February 2019
Sustainability, doi: 10.3390/su11030795
DOI See at publisher website ABS Show/hide abstract
Timely and secure evacuation of residents in communities is of great importance during unexpected disasters or emergency events. This study proposes a framework of evacuation simulation for optimizing emergency management in urban residential communities. Compared to traditional methods, the advantage of our framework lies in three aspects: (1) The method highlights easy-crowded areas in both indoor and outdoor evacuations. (2) Family behaviors are considered and implemented in evacuations. (3) Detailed measures on management optimization are spatially mapped based on a multi-level analysis and the comparison of evacuation simulation results in different scenarios. A case study in Changhongfang residential community, Xuhui District, Shanghai, China, was conducted to demonstrate the method feasibility. Simulation results have exposed potential evacuation problems in the community. A series of detailed recommended measures have been generated. These measures can help to create better emergency management for the community.
Article 1 Read 2 Citations Spatial Downscaling of Suomi NPP–VIIRS Image for Lake Mapping Chang Huang, Yun Chen, Shiqiang Zhang, Linyi Li, Kaifang Shi... Published: 30 October 2017
Water, doi: 10.3390/w9110834
DOI See at publisher website ABS Show/hide abstract
Capturing the dynamics of a lake-water area using remotely sensed images has always been an essential task. Most of the fine spatial resolution data are unsuitable for this purpose because of their low temporal resolution and limited scene coverage. A Visible Infrared Imaging Radiometer Suite on board the Suomi National Polar-orbiting Partnership (Suomi NPP–VIIRS) is a newly-available and appropriate sensor for monitoring large lakes due to its frequent revisits and wide swath (more than 3000 km). However, it provides visible and infrared images at relatively coarse spatial resolutions, which would sometimes hamper the accurate mapping of lake shorelines. This study, therefore, proposes a two-step downscaling method that combines spectral unmixing and subpixel mapping to produce a finer resolution lake map from NPP–VIIRS imagery, which is then applied to delineate the shorelines of five plateau lakes in Yunnan Province, as well as the shoreline dynamics of Poyang Lake at three separate times. A newly published global water dynamic dataset is employed in this study to improve the downscaling method. Results suggest that the proposed method can generate a finer resolution lake map that exhibits more details of the shoreline than hard classification. The downscaling results of the Suomi NPP–VIIRS generally achieve higher than 75% accuracy, while the downscaling results of a Landsat-simulated fraction map could have accuracy higher than 85%. This reveals that errors and uncertainties exist in both procedures, but mainly come from the spectral unmixing procedure which retrieves water fractions from NPP–VIIRS data.
Conference 5 Reads 0 Citations Mapping Lake-water area at sub-pixel scale using Suomi NPP-VIIRS imagery Chang Huang, Yun Chen, Shiqiang Zhang Published: 22 November 2016
The 1st International Electronic Conference on Water Sciences, doi: 10.3390/ecws-1-f001
DOI See at publisher website
Article 0 Reads 0 Citations Assessment of Reclamation Treatments of Abandoned Farmland in an Arid Region of China Haichang Yang, Fenghua Zhang, Yun Chen, Tingbao Xu, Zhibo Ch... Published: 16 November 2016
Sustainability, doi: 10.3390/su8111183
DOI See at publisher website ABS Show/hide abstract
Reclamation of abandoned farmland is crucial to a sustainable agriculture in arid regions. This study aims to evaluate the impact of different reclamation treatments on abandoned salinized farmland. We investigated four artificial reclamation treatments, continuous cotton (CC), continuous alfalfa (CA), tree-wheat intercropping (TW) and trees (TS), which were conducted in 2011–2012 in the Manasi River Basin of Xinjiang Province, China. Soil nutrient, microorganism and enzyme activity were examined in comparison with natural succession (CK) in an integrated analysis on soil fertility improvement and soil salinization control with these reclamations. Results indicate that the four artificial reclamation treatments are more effective approaches than natural restoration to reclaim abandoned farmland. TW and CA significantly increased soil nutrient content compared to CK. CC reduced soil salinity to the lowest level among all treatments. TW significantly enhanced soil enzyme activity. All four artificial reclamations increased soil microbial populations and soil microbial biomass carbon. TW and CA had the greatest overall optimal effects among the four treatments in terms of the ecological outcomes. If both economic benefits and ecological effects are considered, TW would be the best reclamation mode. The findings from this study will assist in selecting a feasible method for reclamation of abandoned farmland for sustainable agriculture in arid regions.
Article 0 Reads 10 Citations Urban Expansion and Agricultural Land Loss in China: A Multiscale Perspective Kaifang Shi, Yun Chen, Bailang Yu, Tingbao Xu, Linyi Li, Cha... Published: 11 August 2016
Sustainability, doi: 10.3390/su8080790
DOI See at publisher website ABS Show/hide abstract
China’s rapid urbanization has contributed to a massive agricultural land loss that could threaten its food security. Timely and accurate mapping of urban expansion and urbanization-related agricultural land loss can provide viable measures to be taken for urban planning and agricultural land protection. In this study, urban expansion in China from 2001 to 2013 was mapped using the nighttime stable light (NSL), normalized difference vegetation index (NDVI), and water body data. Urbanization-related agricultural land loss during this time period was then evaluated at national, regional, and metropolitan scales by integrating multiple sources of geographic data. The results revealed that China’s total urban area increased from 31,076 km2 in 2001 to 80,887 km2 in 2013, with an average annual growth rate of 13.36%. This widespread urban expansion consumed 33,080 km2 of agricultural land during this period. At a regional scale, the eastern region lost 18,542 km2 or 1.2% of its total agricultural land area. At a metropolitan scale, the Shanghai–Nanjing–Hangzhou (SNH) and Pearl River Delta (PRD) areas underwent high levels of agricultural land loss with a decrease of 6.12% (4728 km2) and 6.05% (2702 km2) of their total agricultural land areas, respectively. Special attention should be paid to the PRD, with a decline of 13.30% (1843 km2) of its cropland. Effective policies and strategies should be implemented to mitigate urbanization-related agricultural land loss in the context of China’s rapid urbanization.
Article 1 Read 9 Citations Surface Water Mapping from Suomi NPP-VIIRS Imagery at 30 m Resolution via Blending with Landsat Data Chang Huang, Yun Chen, Shiqiang Zhang, Linyi Li, Kaifang Shi... Published: 29 July 2016
Remote Sensing, doi: 10.3390/rs8080631
DOI See at publisher website ABS Show/hide abstract
Monitoring the dynamics of surface water using remotely sensed data generally requires both high spatial and high temporal resolutions. One effective and popular approach for achieving this is image fusion. This study adopts a widely accepted fusion model, the Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (ESTARFM), for blending the newly available coarse-resolution Suomi NPP-VIIRS data with Landsat data in order to derive water maps at 30 m resolution. The Pan-sharpening technique was applied to preprocessing NPP-VIIRS data to achieve a higher-resolution before blending. The modified Normalized Difference Water Index (mNDWI) was employed for mapping surface water area. Two fusion alternatives, blend-then-index (BI) or index-then-blend (IB), were comparatively analyzed against a Landsat derived water map. A case study of mapping Poyang Lake in China, where water distribution pattern is complex and the water body changes frequently and drastically, was conducted. It has been revealed that the IB method derives more accurate results with less computation time than the BI method. The BI method generally underestimates water distribution, especially when the water area expands radically. The study has demonstrated the feasibility of blending NPP-VIIRS with Landsat for achieving surface water mapping at both high spatial and high temporal resolutions. It suggests that IB is superior to BI for water mapping in terms of efficiency and accuracy. The finding of this study also has important reference values for other blending works, such as image blending for vegetation cover monitoring.
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