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Yun Chen  - - - 
Top co-authors See all
Quan Bai

78 shared publications

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

Peter A. Fox

77 shared publications

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

Paulo A. De Souza

40 shared publications

Data61|CSIRO, Sandy Bay, TAS 7005, Australia;(P.M.);(A.D.)

Shiqiang Zhang

38 shared publications

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

Lei Gao

34 shared publications

CSIRO, Waite Campus, Urrbrae, SA 5064, Australia

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Publication Record
Distribution of Articles published per year 
(2009 - 2019)
Total number of journals
published in
 
11
 
Publications See all
Article 0 Reads 0 Citations Remote sensing for vegetation monitoring in carbon capture storage regions: A review Yun Chen, Juan P Guerschman, Zhibo Cheng, Longzhu Guo Published: 01 April 2019
Applied Energy, doi: 10.1016/j.apenergy.2019.02.027
DOI See at publisher website
Article 1 Read 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 2 Reads 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.
PROCEEDINGS-ARTICLE 6 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
Proceedings of The 1st International Electronic Conference on Water Sciences, doi: 10.3390/ecws-1-f001
DOI See at publisher website ABS Show/hide abstract
Capturing the variation of lake-water area using remotely sensed imagery is an essential topic in many related fields. There are a variety of remote sensing data that can serve this purpose. Generally speaking, higher spatial resolution data are able to derive better results. However, most high spatial resolution data are sometimes defective because of their low temporal resolution and limited scene coverage. Visible Infrared Imaging Radiometer Suite onboard Suomi National Polar-orbiting Partnership (Suomi NPP-VIIRS) provides a newly-available and appropriate manner for monitoring large lakes because of its frequent revisit and wide breadth. But its spatial resolution is relatively low, from 375m to 750m. This study introduces a two-step method that integrates spectral unmixing and sub-pixel mapping to map lake-water area at sub-pixel scale from NPP-VIIRS imagery. Accuracy was assessed by employing corresponding Landsat images as the reference. Five plateau lakes in Yunnan province, China, were selected as the case study areas. Results suggest that the proposed method is able to derive finer resolution lake maps that show more details of the shoreline. The accuracy was significantly improved comparing to traditional classification method. Analysis also reveals that errors and uncertainties also exist in this method. Most of them come from the spectral unmixing procedure that retrieve water fraction from NPP-VIIRS data. Therefore, in order to achieve better lake mapping result, future work should concentrate more on improving this part to produce a better water fraction map first.
Article 1 Read 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 12 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.
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