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Weiming Cheng   Dr.  Institute, Department or Faculty Head 
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Weiming Cheng published an article in January 2019.
Top co-authors See all
Xinqi Zheng

40 shared publications

School of Information Engineering, China University of Geosciences, Beijing 100083, China

Wei Luo

27 shared publications

Department of Geography, Northern Illinois University, DeKalb, IL 60115, USA

Yi-Chi Zhang

26 shared publications

Assistant Professor, Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China

Manchun Li

22 shared publications

Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, Nanjing University, Nanjing 210023, China

Shangmin Zhao

20 shared publications

Department of Surveying and Mapping, College of Mining Engineering, Taiyuan University of Technology, Taiyuan 030024, China

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23
 
Publications See all
Article 0 Reads 0 Citations Model Simulation and Prediction of Decadal Mountain Permafrost Distribution Based on Remote Sensing Data in the Qilian M... Shangmin Zhao, Shifang Zhang, Weiming Cheng, Chenghu Zhou Published: 18 January 2019
Remote Sensing, doi: 10.3390/rs11020183
DOI See at publisher website ABS Show/hide abstract
Based on the results of remote sensing data interpretation, this paper aims to simulate and predict the mountain permafrost distribution changes affected by the mean decadal air temperature (MDAT), from the 1990s to the 2040s, in the Qilian Mountains. A bench-mark map is visually interpreted to acquire a mountain permafrost distribution from the 1990s, based on remote sensing images. Through comparison and estimation, a logistical regression model (LRM) is constructed using the bench-mark map, topographic and land coverage factors and MDAT data from the 1990s. MDAT data from the 2010s to the 2040s are predicted according to survey data from meteorological stations. Using the LRM, MDAT data and the factors, the probabilities (p) of decadal mountain permafrost distribution from the 1990s to the 2040s are simulated and predicted. According to the p value, the permafrost distribution statuses are classified as ‘permafrost probable’ (p > 0.7), ‘permafrost possible’ (0.7 ≥ p ≥ 0.3) and ‘permafrost improbable’ (p < 0.3). From the 1990s to the 2040s, the ‘permafrost probable’ type mainly degrades to that of ‘permafrost possible’, with the total area degenerating from 73.5 × 103 km2 to 66.5 × 103 km2. The ‘permafrost possible’ type mainly degrades to that of ‘permafrost impossible’, with a degradation area of 6.5 × 103 km2, which accounts for 21.3% of the total area. Meanwhile, the accuracy of the simulation results can reach about 90%, which was determined by the validation of the simulation results for the 1990s, 2000s and 2010s based on remote sensing data interpretation results. This research provides a way of understanding the mountain permafrost distribution changes affected by the rising air temperature rising over a long time, and can be used in studies of other mountains with similar topographic and climatic conditions.
Article 0 Reads 0 Citations Spatio-temporal distribution and transformation of cropland in geomorphologic regions of China during 1990–2015 Xiaoyu Gao, Weiming Cheng, Nan Wang, Qiangyi Liu, Ting Ma, Y... Published: 08 January 2019
Journal of Geographical Sciences, doi: 10.1007/s11442-019-1591-4
DOI See at publisher website
PREPRINT-CONTENT 0 Reads 0 Citations Hydrologic application comparison among typical open global DEM data based on remote sensing images Shangmin Zhao, Shifang Zhang, Weiming Cheng Published: 29 July 2018
PeerJ PrePrints, doi: 10.7287/peerj.preprints.27065
DOI See at publisher website ABS Show/hide abstract
As the data source in digital topographic analysis, digital elevation model (DEM) data plays an important role in many fields, and hydrologic application is an important one among them. The successive release of open global DEM datasets provides multi choices for these applications, but also brings puzzles in DEM data selection. Taking Fenhe River Basin of China as the study area, this research compared the hydrologic networks extracted by typical global DEM data using matching difference (MD), correctness (C) and figure of merit (FM) indexes. Firstly, four DEM-derived hydrologic networks (DHNs) were acquired through topographic analysis using four typical global DEM datasets, including Shuttle Radar Terrain Mission (SRTM) data with 1 arc second resolution (SRTM1), SRTM data with 3 arc second resolution (SRTM3), ASTER global DEM data in the second version (GDEM-v2) and ALOS world 3D-30m (AW3D30) data. Then, the reference hydrologic network (RHN) was interpreted based on remote sensing images. Finally, the DHNs were evaluated and compared by referencing the RHN using different indexes. Research results show: (1) four DHNs have similar distribution in mountain regions but much different performance in flat regions; (2) all the indexes (including MD, C and FM) indicate that about the quality of the DHNs, the best is the AW3D30 data, then the SRTM1 data, the next is the SRTM3 data, and the GDEM-v2 data has the worst quality; (3) through analyzing the MD distribution in different slope classes for the four global DEM datasets, the MD mainly distributes in flat region, and then sloping region, but seldom in steep region. Overall, AW3D30 has the best quality, a little better than SRTM1 and much better than SRTM3 and GDEM-v2; SRTM3 and GDEM-v2 data have much worse quality, and GDEM-v2 data is the worst in the four global DEM datasets. Considering that the AW3D30 data is originated from the DEM dataset with 5m resolution, it may exerts more effect in future digital topographic analysis.
PREPRINT 0 Reads 0 Citations Hydrologic application comparison among typical open global DEM data based on remote sensing images Shangmin Zhao, Shifang Zhang, Weiming Cheng Published: 29 July 2018
PeerJ PrePrints, doi: 10.7287/peerj.preprints.27065v1
DOI See at publisher website ABS Show/hide abstract
As the data source in digital topographic analysis, digital elevation model (DEM) data plays an important role in many fields, and hydrologic application is an important one among them. The successive release of open global DEM datasets provides multi choices for these applications, but also brings puzzles in DEM data selection. Taking Fenhe River Basin of China as the study area, this research compared the hydrologic networks extracted by typical global DEM data using matching difference (MD), correctness (C) and figure of merit (FM) indexes. Firstly, four DEM-derived hydrologic networks (DHNs) were acquired through topographic analysis using four typical global DEM datasets, including Shuttle Radar Terrain Mission (SRTM) data with 1 arc second resolution (SRTM1), SRTM data with 3 arc second resolution (SRTM3), ASTER global DEM data in the second version (GDEM-v2) and ALOS world 3D-30m (AW3D30) data. Then, the reference hydrologic network (RHN) was interpreted based on remote sensing images. Finally, the DHNs were evaluated and compared by referencing the RHN using different indexes. Research results show: (1) four DHNs have similar distribution in mountain regions but much different performance in flat regions; (2) all the indexes (including MD, C and FM) indicate that about the quality of the DHNs, the best is the AW3D30 data, then the SRTM1 data, the next is the SRTM3 data, and the GDEM-v2 data has the worst quality; (3) through analyzing the MD distribution in different slope classes for the four global DEM datasets, the MD mainly distributes in flat region, and then sloping region, but seldom in steep region. Overall, AW3D30 has the best quality, a little better than SRTM1 and much better than SRTM3 and GDEM-v2; SRTM3 and GDEM-v2 data have much worse quality, and GDEM-v2 data is the worst in the four global DEM datasets. Considering that the AW3D30 data is originated from the DEM dataset with 5m resolution, it may exerts more effect in future digital topographic analysis.
Article 0 Reads 6 Citations Assessing Spatiotemporal Characteristics of Urbanization Dynamics in Southeast Asia Using Time Series of DMSP/OLS Nightt... Min Zhao, Weiming Cheng, Chenghu Zhou, Manchun Li, Kun Huang... Published: 08 January 2018
Remote Sensing, doi: 10.3390/rs10010047
DOI See at publisher website ABS Show/hide abstract
Intraregional spatial variations of satellite-derived anthropogenic nighttime light signals are gradually applied to identify different lighting areas with various socioeconomic activity and urbanization levels when characterizing urbanization dynamics. However, most previous partitioning approaches are carried out at local scales, easily leading to multi-standards of the extracted results from local areas, and this inevitably hinders the comparative analysis on the urbanization dynamics of the large region. Therefore, a partitioning approach considering the characteristics of nighttime light signals at both local and regional scales is necessary for studying spatiotemporal characteristics of urbanization dynamics across the large region using nighttime light imagery. Based on the quadratic relationships between the pixel-level nighttime light brightness and the corresponding spatial gradient for individual cities, we here proposed an improved partitioning approach to quickly identify different types of nighttime lighting areas for the entire region of Southeast Asia. Using the calibrated Defense Meteorological Satellite Program/Operational Line-scan System (DMSP/OLS) data with greater comparability, continuity, and intra-urban variability, the annual nighttime light imagery spanning years 1992–2013 were divided into four types of nighttime lighting areas: low, medium, high, and extremely high, associated with different intensity of anthropogenic activity. The results suggest that Southeast Asia has experienced a rapid and diverse urbanization process from 1992 to 2013. Areas with moderate or low anthropogenic activity show a faster growth rate for the spatial expansion than the developed areas with intense anthropogenic activity. Transitions between different nighttime lighting types potentially depict the trajectory of urban development, the darker areas are gradually transitioning to areas with higher lighting, indicating conspicuous trends of gradually intensified anthropogenic activity from central areas to periphery areas, and from megacities to small cities. Additionally, satellite-derived nighttime lighting areas are in good agreement with the radar-derived human settlements, with dense human settlements in extremely high and high nighttime lighting areas, while sparse human settlements in low nighttime lighting areas.
Article 0 Reads 0 Citations Using MLR to model the vertical error distribution of ASTER GDEM V2 data based on ICESat/GLA14 data in the Loess Plateau... Shangmin Zhao, Weiming Cheng, Chenghu Zhou, Haijiang Liu, Qi... Published: 01 November 2017
Zeitschrift für Geomorphologie, Supplementary Issues, doi: 10.1127/zfg_suppl/2016/0325
DOI See at publisher website
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